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Sample records for model significant predictors

  1. Personality as significant predictor of post-stroke anxiety.

    Science.gov (United States)

    Solgajová, Andrea; Sollár, Tomáš; Vörösová, Gabriela; Zrubcová, Dana

    2017-08-01

    Anxiety in stroke patients is very frequent. It negatively influences the whole recovery process. The study objective is to study personality traits, age, gender, and type of stroke as predictors of anxiety in stroke patients. Research presents a prospective cross-sectional descriptive study. The sample consisted of 74 hospitalized stroke patients. The data collection methods were the HADS for anxiety measurement and the Mini IPIP for evaluation of five personality factors. Hierarchical multiple regression analysis was used to study the relationship between anxiety and personality variables, gender, age, and type of stroke. We found three statistically significant predictors of anxiety in stroke patients. Neuroticism and low Agreeableness explain 50% of the variability of anxiety. Another statistically significant predictor was age; higher-level anxiety relates to lower age. Other personality traits (Extraversion, Openness to experience, and Conscientiousness), gender, and type of stroke do not appear as significant predictors of post-stroke anxiety. Anxiety in stroke patients is predicted mostly by the personality traits and young age of patients. Knowing these predictors can result in early detection and management of emotional consequences of disease, and thus influence the whole recovery process.

  2. Calculating the true level of predictors significance when carrying out the procedure of regression equation specification

    Directory of Open Access Journals (Sweden)

    Nikita A. Moiseev

    2017-01-01

    Full Text Available The paper is devoted to a new randomization method that yields unbiased adjustments of p-values for linear regression models predictors by incorporating the number of potential explanatory variables, their variance-covariance matrix and its uncertainty, based on the number of observations. This adjustment helps to control type I errors in scientific studies, significantly decreasing the number of publications that report false relations to be authentic ones. Comparative analysis with such existing methods as Bonferroni correction and Shehata and White adjustments explicitly shows their imperfections, especially in case when the number of observations and the number of potential explanatory variables are approximately equal. Also during the comparative analysis it was shown that when the variance-covariance matrix of a set of potential predictors is diagonal, i.e. the data are independent, the proposed simple correction is the best and easiest way to implement the method to obtain unbiased corrections of traditional p-values. However, in the case of the presence of strongly correlated data, a simple correction overestimates the true pvalues, which can lead to type II errors. It was also found that the corrected p-values depend on the number of observations, the number of potential explanatory variables and the sample variance-covariance matrix. For example, if there are only two potential explanatory variables competing for one position in the regression model, then if they are weakly correlated, the corrected p-value will be lower than when the number of observations is smaller and vice versa; if the data are highly correlated, the case with a larger number of observations will show a lower corrected p-value. With increasing correlation, all corrections, regardless of the number of observations, tend to the original p-value. This phenomenon is easy to explain: as correlation coefficient tends to one, two variables almost linearly depend on each

  3. Inpatient Treatment for Adolescents with Anorexia Nervosa: Clinical Significance and Predictors of Treatment Outcome.

    Science.gov (United States)

    Schlegl, Sandra; Diedrich, Alice; Neumayr, Christina; Fumi, Markus; Naab, Silke; Voderholzer, Ulrich

    2016-05-01

    This study evaluated the clinical significance as well as predictors of outcome for adolescents with severe anorexia nervosa (AN) treated in an inpatient setting. Body mass index (BMI), eating disorder (ED) symptoms [Eating Disorder Inventory-2 (EDI-2)], general psychopathology and depression were assessed in 238 patients at admission and discharge. BMI increased from 14.8 + 1.2 to 17.3 + 1.4 kg/m(2). Almost a fourth (23.6%) of the patients showed reliable changes, and 44.7% showed clinically significant changes (EDI-2). BMI change did not significantly differ between those with reliable or clinically significant change or no reliable change in EDI-2. Length of stay, depression and body dissatisfaction were negative predictors of a clinically significant change. Inpatient treatment is effective in about two thirds of adolescents with AN and should be considered when outpatient treatment fails. About one third of patients showed significant weight gain, but did not improve regarding overall ED symptomatology. Future studies should focus on treatment strategies for non-responders. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

  4. Bayesian modeling of measurement error in predictor variables

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; Glas, Cornelis A.W.

    2003-01-01

    It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between

  5. Selecting candidate predictor variables for the modelling of post ...

    African Journals Online (AJOL)

    Selecting candidate predictor variables for the modelling of post-discharge mortality from sepsis: a protocol development project. Afri. Health Sci. .... Initial list of candidate predictor variables, N=17. Clinical. Laboratory. Social/Demographic. Vital signs (HR, RR, BP, T). Hemoglobin. Age. Oxygen saturation. Blood culture. Sex.

  6. Ethnicity, Clothing Style, and Body Mass Index are Significant Predictors of Vitamin D Insufficiency in Germany.

    Science.gov (United States)

    Farahati, Jamshid; Nagarajah, James; Gilman, Elena; Mahjoob, Soha; Zohreh, Moussavi; Rosenbaum-Krumme, Sandra; Bockisch, Andreas; Zakavi, S Rasoul

    2015-02-01

    To analyze risk factors for vitamin D insufficiency in Germany with respect to ethnicity, sex, and clothing style. We analyzed the routine diagnostic work-ups of 1,231 adult (45.9 ± 17.9 years old) German (n = 1,034) and Turk residents (n = 197) referred with nonspecific symptoms to the Thyroid Centers at St. Elisabeth-Hospital in Dorsten, Germany and Bottrop, Germany to assess for metabolic diseases. All subjects underwent a routine examination that consisted of a questionnaire, lab tests for 25-hydroxyvitamin-D (25OHD), and thyroid profile. Turk females with traditional clothing (headscarf and covered legs and arms) were considered to wear "covered clothing." Logistic-regression was performed to identify factors that could predict vitamin D deficiency (clothes was lower than that in Turk females with conventional clothing (16.3 ± 12.3 vs. 27.2 ± 15.8, Pclothing versus 62.8% with conventional clothing (odds ratio [OR] = 3.6, P = .002). Ethnicity, body mass index (BMI), and clothing style were significant predictors of vitamin D deficiency and insufficiency by logistic regression (Pclothing. (2) Monitoring vitamin D in Turk residents in Germany is warranted. (3) Vitamin D supplements and access to facilities with sunlight exposure for females with covered clothing and all individuals with poor diets or limited access to sun exposure may prevent future health burden due to vitamin D insufficiency.

  7. Significantly reduced hypoxemic events in morbidly obese patients undergoing gastrointestinal endoscopy: Predictors and practice effect

    Directory of Open Access Journals (Sweden)

    Basavana Gouda Goudra

    2014-01-01

    Full Text Available Background: Providing anesthesia for gastrointestinal (GI endoscopy procedures in morbidly obese patients is a challenge for a variety of reasons. The negative impact of obesity on the respiratory system combined with a need to share the upper airway and necessity to preserve the spontaneous ventilation, together add to difficulties. Materials and Methods: This retrospective cohort study included patients with a body mass index (BMI >40 kg/m 2 that underwent out-patient GI endoscopy between September 2010 and February 2011. Patient data was analyzed for procedure, airway management technique as well as hypoxemic and cardiovascular events. Results: A total of 119 patients met the inclusion criteria. Our innovative airway management technique resulted in a lower rate of intraoperative hypoxemic events compared with any published data available. Frequency of desaturation episodes showed statistically significant relation to previous history of obstructive sleep apnea (OSA. These desaturation episodes were found to be statistically independent of increasing BMI of patients. Conclusion: Pre-operative history of OSA irrespective of associated BMI values can be potentially used as a predictor of intra-procedural desaturation. With suitable modification of anesthesia technique, it is possible to reduce the incidence of adverse respiratory events in morbidly obese patients undergoing GI endoscopy procedures, thereby avoiding the need for endotracheal intubation.

  8. Significantly reduced hypoxemic events in morbidly obese patients undergoing gastrointestinal endoscopy: Predictors and practice effect.

    Science.gov (United States)

    Goudra, Basavana Gouda; Singh, Preet Mohinder; Penugonda, Lakshmi C; Speck, Rebecca M; Sinha, Ashish C

    2014-01-01

    Providing anesthesia for gastrointestinal (GI) endoscopy procedures in morbidly obese patients is a challenge for a variety of reasons. The negative impact of obesity on the respiratory system combined with a need to share the upper airway and necessity to preserve the spontaneous ventilation, together add to difficulties. This retrospective cohort study included patients with a body mass index (BMI) >40 kg/m(2) that underwent out-patient GI endoscopy between September 2010 and February 2011. Patient data was analyzed for procedure, airway management technique as well as hypoxemic and cardiovascular events. A total of 119 patients met the inclusion criteria. Our innovative airway management technique resulted in a lower rate of intraoperative hypoxemic events compared with any published data available. Frequency of desaturation episodes showed statistically significant relation to previous history of obstructive sleep apnea (OSA). These desaturation episodes were found to be statistically independent of increasing BMI of patients. Pre-operative history of OSA irrespective of associated BMI values can be potentially used as a predictor of intra-procedural desaturation. With suitable modification of anesthesia technique, it is possible to reduce the incidence of adverse respiratory events in morbidly obese patients undergoing GI endoscopy procedures, thereby avoiding the need for endotracheal intubation.

  9. Predictor variable resolution governs modeled soil types

    Science.gov (United States)

    Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...

  10. Multiple Imputation of Predictor Variables Using Generalized Additive Models

    NARCIS (Netherlands)

    de Jong, Roel; van Buuren, Stef; Spiess, Martin

    2016-01-01

    The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

  11. Importance of predictor variables for models of chemical function

    Data.gov (United States)

    U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....

  12. ARMAX, OE and SSIF model predictors for power transmission and ...

    African Journals Online (AJOL)

    Three mathematical model structures, namely: ARMAX, OE and a SSIF are first formulated followed by the formulation of their respective model predictors for the model identification and prediction of power transmission and distribution within Akure and its environs. A total of 51,350 data samples from the Power Holding ...

  13. A New Perspective for the Calibration of Computational Predictor Models.

    Energy Technology Data Exchange (ETDEWEB)

    Crespo, Luis Guillermo

    2014-11-01

    This paper presents a framework for calibrating computational models using data from sev- eral and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncer- tainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of obser- vations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it is a description of the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain (i.e., roll-up and extrapolation).

  14. Dealing with missing predictor values when applying clinical prediction models.

    NARCIS (Netherlands)

    Janssen, K.J.; Vergouwe, Y.; Donders, A.R.T.; Harrell Jr, F.E.; Chen, Q.; Grobbee, D.E.; Moons, K.G.

    2009-01-01

    BACKGROUND: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with

  15. Preliminary Exploration of Adaptive State Predictor Based Human Operator Modeling

    Science.gov (United States)

    Trujillo, Anna C.; Gregory, Irene M.

    2012-01-01

    Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to quantify the effects of changing aircraft dynamics on an operator s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. A gradient descent estimator and a least squares estimator with exponential forgetting used these data to predict pilot stick input. The results indicate that individual pilot characteristics and vehicle dynamics did not affect the accuracy of either estimator method to estimate pilot stick input. These methods also were able to predict pilot stick input during changing aircraft dynamics and they may have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot.

  16. Modelling vocal anatomy's significant effect on speech

    NARCIS (Netherlands)

    de Boer, B.

    2010-01-01

    This paper investigates the effect of larynx position on the articulatory abilities of a humanlike vocal tract. Previous work has investigated models that were built to resemble the anatomy of existing species or fossil ancestors. This has led to conflicting conclusions about the relation between

  17. armax, oe and ssif model predictors for power transmission and ...

    African Journals Online (AJOL)

    Vincent

    prediction and tracking capabilities and that the OE model structure and its predictor structure can be used for power transmission ..... Cable Size: Larger cable size will have less voltage than smaller cable size of the same length; 3). Cable Length: shorter cables will have less voltage drop than longer cables of the same.

  18. Predictors of quality of life: A model based study

    NARCIS (Netherlands)

    Masthoff, E.D.M.; Trompenaars, F.J.; Heck, G.L. van; Michielsen, H.J.; Hodiamont, P.P.G.; Vries, I.J.M. de

    2007-01-01

    In this study, predictors of quality of life (QOL) in psychiatric outpatients (n = 410) were investigated using the psychological stress model developed by Taylor and Aspinwall (Psychosocial Stress. Perspective on Structures, Theory, Life-Course and Methods. San Diego, CA: Academic Press, 1996; pp.

  19. Predictors of quality of life: a model based study.

    NARCIS (Netherlands)

    Masthoff, E.D.M.; Trompenaars, F.J.; Heck, G.L. van; Michielsen, H.J.; Hodiamont, P.P.G.; Vries, J. de

    2007-01-01

    In this study, predictors of quality of life (QOL) in psychiatric outpatients (n = 410) were investigated using the psychological stress model developed by Taylor and Aspinwall (Psychosocial Stress. Perspective on Structures, Theory, Life-Course and Methods. San Diego, CA: Academic Press, 1996; pp.

  20. Smart predictors in the heterogeneous agent model

    Czech Academy of Sciences Publication Activity Database

    Baruník, Jozef; Vácha, Lukáš; Vošvrda, Miloslav

    2009-01-01

    Roč. 4, č. 2 (2009), s. 163-172 ISSN 1860-711X R&D Projects: GA ČR GP402/08/P207; GA ČR GA402/09/0965 Grant - others:GAUK(CZ) 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : Heterogeneous agent model * Market structure * Smart traders * Hurst exponent Subject RIV: AH - Economics

  1. Methodological development for selection of significant predictors explaining fatal road accidents.

    Science.gov (United States)

    Dadashova, Bahar; Arenas-Ramírez, Blanca; Mira-McWilliams, José; Aparicio-Izquierdo, Francisco

    2016-05-01

    Identification of the most relevant factors for explaining road accident occurrence is an important issue in road safety research, particularly for future decision-making processes in transport policy. However model selection for this particular purpose is still an ongoing research. In this paper we propose a methodological development for model selection which addresses both explanatory variable and adequate model selection issues. A variable selection procedure, TIM (two-input model) method is carried out by combining neural network design and statistical approaches. The error structure of the fitted model is assumed to follow an autoregressive process. All models are estimated using Markov Chain Monte Carlo method where the model parameters are assigned non-informative prior distributions. The final model is built using the results of the variable selection. For the application of the proposed methodology the number of fatal accidents in Spain during 2000-2011 was used. This indicator has experienced the maximum reduction internationally during the indicated years thus making it an interesting time series from a road safety policy perspective. Hence the identification of the variables that have affected this reduction is of particular interest for future decision making. The results of the variable selection process show that the selected variables are main subjects of road safety policy measures. Published by Elsevier Ltd.

  2. Self-Assessment and Appearance Evaluation in Student Group as Predictors in Relationships of Interpersonal Significance

    Directory of Open Access Journals (Sweden)

    Labunskaya V.A.

    2016-03-01

    Full Text Available The paper attempts to integrate the concept of relationships of interpersonal significance, approaches to the correlation between physical appearance and life satisfaction, as well as several concepts of interpersonal cognition, self-assessment and evaluations of other people’s physical appearance. It introduces the concept of “insignificant/significant assessor of appearance” and argues that among the factors that turn a group member into the “insignificant/significant assessor of appearance” are evaluations, self-evaluations and group evaluations of physical appearance. The research described in the paper involved 89 students aged 19—21 (M=20 years, 66 females and 23 males, members of five groups that have been studying together for three years. The methods employed in the study included: “The Evaluation/Content Interpretation of Appearance and its Correspondence with Gender/Age Constructs”, a technique developed by V.A. Labunskaya; a modification of a sociometric test that helped reveal “insignificant/significant assessors of appearance”. Also, nonparametric mathematical methods were used to carry out comparative analysis. The outcomes show that there are considerable differences between the self-assessments, evaluations of physical appearance of those group members who are “significant assessors of appearance”, and group evaluations of their appearance.

  3. Gastroschisis in a developing country: poor resuscitation is a more significant predictor of mortality than postnasal transfer time.

    Science.gov (United States)

    Stevens, P; Muller, E; Becker, P

    2016-03-01

    The time from birth to the first paediatric surgical consultation of neonates with gastroschisis is a predictor of mortality in dveloping countries. This is contrary to findings in the developed world. We set out to document this relationship within our population. Neonates with gastroschisis who were transferred to Steve Biko Academic Hospital within the study period were included. The association between mortality and demographic, clinical and biochemical variables was assessed. Significant variables after univariate analysis were subjected to multivariates regression. Sixty patients were included. The mortality rate was 65%. Mean transfer time and distance were 14.9 hours and 225km. Forty-eight per cent of the neonates were either dehydrated or in hypovolaemic shock clinically on arrival. Eight neonates arrived hypothermic. It was shown through univariate analysis that female sex, appropriate weight for gestational age, hydration status, gestation, transfer time, serum urea, base deficit and serum bicarbonate (HCO3) were significant predictors of mortality. Only female sex, appropriate weight for gestational age and serum HC03 were shown to be significant using ultivariate analysis. Our high mortality rate was not due to lengthy transfer times. The poor clinical condition of the patients on arrival at our hospital, which relates to deficiencies in the neonatal transfer system, had a direct impact on the survival of neonates with gastroschisis.

  4. Pediatricians' perceptions of vaccine effectiveness and safety are significant predictors of vaccine administration in India

    Science.gov (United States)

    Gargano, Lisa M.; Thacker, Naveen; Choudhury, Panna; Weiss, Paul S.; Russ, Rebecca M.; Pazol, Karen; Arora, Manisha; Orenstein, Walter A.; Omer, Saad B.; Hughes, James M.

    2013-01-01

    Background New vaccine introduction is important to decrease morbidity and mortality in India. The goal of this study was to identify perceptions that are associated with administration of four selected vaccines for prevention of Japanese encephalitis (JE), typhoid fever, influenza and human papillomavirus (HPV) infection. Methods A random sample of 785 pediatricians from a national list of Indian Academy of Pediatrics members was selected for a survey to assess perceptions of vaccine effectiveness and safety, and vaccine administration practices. Logistic regression was used to assess factors associated with selective or routine use. Results Pediatricians reported administering typhoid (91.6%), influenza (60.1%), HPV (46.0%) and JE (41.9%) vaccines selectively or routinely. Pediatricians who perceived the vaccine to be safe were significantly more likely to report administration of JE (OR 2.6, 95% CI 1.3 to 5.3), influenza (OR 4.3, 95% CI 2.0 to 9.6) and HPV vaccine (OR 6.2, 95% CI 3.1 to 12.7). Pediatricians who perceived the vaccine to be effective were significantly more likely to report administration of JE (OR 3.3, 95% CI 1.6 to 6.5), influenza (OR 7.7, 95% CI 2.5 to 23.1) and HPV vaccine (OR 3.2, 95% CI 1.6 to 6.4) Conclusion Understanding the role perceptions play provides an opportunity to design strategies to build support for vaccine use. PMID:24030271

  5. Neighborhood Predictors of Intimate Partner Violence: A Theory-Informed Analysis Using Hierarchical Linear Modeling.

    Science.gov (United States)

    Voith, Laura A; Brondino, Michael J

    2017-09-01

    Due to high prevalence rates and deleterious effects on individuals, families, and communities, intimate partner violence (IPV) is a significant public health problem. Because IPV occurs in the context of communities and neighborhoods, research must examine the broader environment in addition to individual-level factors to successfully facilitate behavior change. Drawing from the Social Determinants of Health framework and Social Disorganization Theory, neighborhood predictors of IPV were tested using hierarchical linear modeling. Results indicated that concentrated disadvantage and female-to-male partner violence were robust predictors of women's IPV victimization. Implications for theory, practice, and policy, and future research are discussed. © Society for Community Research and Action 2017.

  6. Predictor model for seasonal variations in skid resistance, volume 1

    Science.gov (United States)

    Henry, J. J.; Saito, K.; Blackburn, R.

    1984-04-01

    Two models, utilizing data collected in 1979 and 1980, were developed to predict variations in skid resistance due to rainfall conditions, temperature effects, and time of the year. A generalized predictor model was developed from purely statistical considerations and a mechanistic model was developed from hypothesized mechanisms. This model may be utilized to estimate the skid resistance at any time in the season from a measurement made during the same season, or to adjust skid-resistance measurement made at any time during the season to the end-of-season level. The mechanistic model requires, in addition to the above inputs, two pavement properties describing the polishing characteristics of the aggregate and an estimate of the percent normalized gradient of the skid resistance. The application of these models is summarized.

  7. Epigenetic Signature: A New Player as Predictor of Clinically Significant Prostate Cancer (PCa) in Patients on Active Surveillance (AS).

    Science.gov (United States)

    Ferro, Matteo; Ungaro, Paola; Cimmino, Amelia; Lucarelli, Giuseppe; Busetto, Gian Maria; Cantiello, Francesco; Damiano, Rocco; Terracciano, Daniela

    2017-05-27

    Widespread prostate-specific antigen (PSA) testing notably increased the number of prostate cancer (PCa) diagnoses. However, about 30% of these patients have low-risk tumors that are not lethal and remain asymptomatic during their lifetime. Overtreatment of such patients may reduce quality of life and increase healthcare costs. Active surveillance (AS) has become an accepted alternative to immediate treatment in selected men with low-risk PCa. Despite much progress in recent years toward identifying the best candidates for AS in recent years, the greatest risk remains the possibility of misclassification of the cancer or missing a high-risk cancer. This is particularly worrisome in men with a life expectancy of greater than 10-15 years. The Prostate Cancer Research International Active Surveillance (PRIAS) study showed that, in addition to age and PSA at diagnosis, both PSA density (PSA-D) and the number of positive cores at diagnosis (two compared with one) are the strongest predictors for reclassification biopsy or switching to deferred treatment. However, there is still no consensus upon guidelines for placing patients on AS. Each institution has its own protocol for AS that is based on PRIAS criteria. Many different variables have been proposed as tools to enrol patients in AS: PSA-D, the percentage of freePSA, and the extent of cancer on biopsy (number of positive cores or percentage of core involvement). More recently, the Prostate Health Index (PHI), the 4 Kallikrein (4K) score, and other patient factors, such as age, race, and family history, have been investigated as tools able to predict clinically significant PCa. Recently, some reports suggested that epigenetic mapping differs significantly between cancer patients and healthy subjects. These findings indicated as future prospect the use of epigenetic markers to identify PCa patients with low-grade disease, who are likely candidates for AS. This review explores literature data about the potential of

  8. Test of the Fishbein and Ajzen models as predictors of health care workers' glove use.

    Science.gov (United States)

    Levin, P F

    1999-08-01

    The aim of this study was to identify predictors of health care workers' glove use when there is a potential for blood exposure. The study hypothesis was that an extension of the theory of planned behavior would explain more of the variance in glove use behavior than the theory of reasoned action or theory of planned behavior. A random sample of nurses and laboratory workers (N = 527) completed a 26-item questionnaire with acceptable content validity and reliability estimates. Using structural equation modeling techniques, intention, attitude, and perceived risk were significant predictors of behavior. Perceived control and attitude were the significant determinants of intention. The theory of reasoned action was the most parsimonious model, explaining 70% of the variance in glove use behavior. The theory of planned behavior extension was a viable model to study behavior related to glove use and reducing workers' risks to bloodborne diseases.

  9. Clinical significance of fractional magnesium excretion (FEMg) as a predictor of interstitial nephropathy and its correlation with conventional parameters.

    Science.gov (United States)

    Noiri, Chie; Shimizu, Taisuke; Takayanagi, Kaori; Tayama, Yosuke; Iwashita, Takatsugu; Okazaki, Shimpei; Hatano, Minoru; Matsumura, Osamu; Kato, Hitoshi; Matsuda, Akihiko; Mitarai, Tetsuya; Hasegawa, Hajime

    2015-12-01

    Elevated urine Mg excretion and its correlation with histological damage in tubulo-interstitial nephropathy (TIN) were reported. Here we investigated the clinical significance of the fractional excretion of Mg (FEMg) for the prediction of TIN. We enrolled and assessed 94 adult patients with various renal diseases diagnosed principally by renal biopsy. Our stratified analysis based on the value of the conventional TIN parameter N-acetylglucosaminidase (NAG) excretion showed that the high-NAG index group (more than median value of NAG-to-Cr ratio, n = 47) demonstrated significantly high FEMg values (p = 0.017). A univariate analysis revealed a significant correlation between the FEMg and the NAG index (R = 0.60) but not for other parameters. A multivariate regression analysis confirmed the significance of the FEMg as an effective predictor of the NAG index. The FEMg showed a significant correlation with the estimated glomerular filtration rate (eGFR) in the patients with eGFR ≤ 30 mL/min. The correlation of FEMg with the NAG index was not observed in the primary glomerulonephritis patients but was apparent in the patients with hypertensive nephrosclerosis or interstitial nephritis. Our findings may indicate that the combination of the FEMg and the NAG index can provide a specific, sensitive assessment for TIN in patients without renal insufficiency.

  10. Predictors of stage transitions in the precaution adoption process model.

    Science.gov (United States)

    de Vet, Emely; de Nooijer, Jascha; Oenema, Anke; de Vries, Nanne K; Brug, Johannes

    2008-01-01

    To explore psychosocial correlates and predictors of stage transitions in the precaution adoption process model (PAPM) for fruit intake. A cohort completed three electronic questionnaires, at baseline (time 0), 35 days later (time 1), and another 32 days later (time 2). Secured Internet Web site. A cohort of 735 adults was formed from a random sample of an existing Internet panel. The mean age was 37.5 years, 51% were women, and 90% were of Dutch origin. Most respondents (48%) had a medium level of education. Precaution adoption process model stage, risk perception, perception of own fruit intake level, attitude, pros, cons, subjective norms, social support, modeling, self-efficacy, and fruit intake (assessed using a food frequency questionnaire). Cross-sectional differences in psychosocial variables and fruit intake across PAPM stages at baseline were analyzed using analysis of variance with Tukey multiple comparisons tests. Predictors of PAPM stage transitions between time 0 and time 1 and between time 1 and time 2 were analyzed using logistic regression analysis. Factors related to attitude and social influences may be important if one is to decide to act, whereas strong self-efficacy may also be required for acting on the decision to act. Although the results should be replicated in a larger and more representative sample, the PAPM seems a good framework for studying fruit intake.

  11. Interval Predictor Models for Data with Measurement Uncertainty

    Science.gov (United States)

    Lacerda, Marcio J.; Crespo, Luis G.

    2017-01-01

    An interval predictor model (IPM) is a computational model that predicts the range of an output variable given input-output data. This paper proposes strategies for constructing IPMs based on semidefinite programming and sum of squares (SOS). The models are optimal in the sense that they yield an interval valued function of minimal spread containing all the observations. Two different scenarios are considered. The first one is applicable to situations where the data is measured precisely whereas the second one is applicable to data subject to known biases and measurement error. In the latter case, the IPMs are designed to fully contain regions in the input-output space where the data is expected to fall. Moreover, we propose a strategy for reducing the computational cost associated with generating IPMs as well as means to simulate them. Numerical examples illustrate the usage and performance of the proposed formulations.

  12. High predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

    Science.gov (United States)

    Lombardo, Luigi; Castro-Camilo, Daniela; Mai, Martin; Jie, Dou; Huser, Raphaël

    2017-04-01

    Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented output. In this contribution, we generate a SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyze the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05 which were then used as predictors for landslide susceptibility. In addition, we combined shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to reduce the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to identify the geomorphic features that primarily control the SU-based susceptibility within the test area while producing high predictive performances. Level 4 validation procedures were implemented to assess uncertainty and quality of the models through a set of 500 randomly generated replicates.

  13. Perioperative Blood Transfusion as a Significant Predictor of Biochemical Recurrence and Survival after Radical Prostatectomy in Patients with Prostate Cancer.

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    Jung Kwon Kim

    Full Text Available There have been conflicting reports regarding the association of perioperative blood transfusion (PBT with oncologic outcomes including recurrence rates and survival outcomes in prostate cancer. We aimed to evaluate whether perioperative blood transfusion (PBT affects biochemical recurrence-free survival (BRFS, cancer-specific survival (CSS, and overall survival (OS following radical prostatectomy (RP for patients with prostate cancer.A total of 2,713 patients who underwent RP for clinically localized prostate cancer between 1993 and 2014 were retrospectively analyzed. We performed a comparative analysis based on receipt of transfusion (PBT group vs. no-PBT group and transfusion type (autologous PBT vs. allogeneic PBT. Univariate and multivariate Cox-proportional hazard regression analysis were performed to evaluate variables associated with BRFS, CSS, and OS. The Kaplan-Meier method was used to calculate survival estimates for BRFS, CSS, and OS, and log-rank test was used to conduct comparisons between the groups.The number of patients who received PBT was 440 (16.5%. Among these patients, 350 (79.5% received allogeneic transfusion and the other 90 (20.5% received autologous transfusion. In a multivariate analysis, allogeneic PBT was found to be statistically significant predictors of BRFS, CSS, and OS; conversely, autologous PBT was not. The Kaplan-Meier survival analysis showed significantly decreased 5-year BRFS (79.2% vs. 70.1%, log-rank, p = 0.001, CSS (98.5% vs. 96.7%, log-rank, p = 0.012, and OS (95.5% vs. 90.6%, log-rank, p < 0.001 in the allogeneic PBT group compared to the no-allogeneic PBT group. In the autologous PBT group, however, none of these were statistically significant compared to the no-autologous PBT group.We found that allogeneic PBT was significantly associated with decreased BRFS, CSS, and OS. This provides further support for the immunomodulation hypothesis for allogeneic PBT.

  14. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

    KAUST Repository

    Camilo, Daniela Castro

    2017-08-30

    Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.

  15. Interstitial glucose level is a significant predictor of energy intake in free-living women with healthy body weight.

    Science.gov (United States)

    Pittas, Anastassios G; Hariharan, Radhika; Stark, Paul C; Hajduk, Cheryl L; Greenberg, Andrew S; Roberts, Susan B

    2005-05-01

    The relative contribution of circulating glucose to meal-to-meal variability in energy intake is not known. In 8 free-living young (median age 26.5 y) women with healthy body weight (median BMI 22.2 kg/m(2)), we measured glucose in the interstitial space by an automated monitoring procedure (continuous glucose monitoring system, CGMS) for up to 3 consecutive days (mean 706 glucose readings per subject). We examined the association between interstitial glucose (which lags blood glucose by approximately 10 min), self-reported hunger, satiety, desire for a meal, and nutrient intakes. Participants reported consuming a typical Western diet (59% carbohydrate, 27% fat, 14% protein). Median (interquartile range) interstitial glucose was 5.2 mmol/L (4.7-5.8). Using repeated-measures techniques in univariate analyses, desire for a meal (r = 0.45, P energy intake. In multivariate regression analyses, desire for a meal (P energy intake, whereas absolute mean glucose measured in the period 15 to 0 min before eating was marginally significant (P = 0.08). In conclusion, absolute glucose level is a significant predictor of energy intake in nonobese women. However, desire for a meal and hunger are quantitatively more important, emphasizing the importance of both glucose signals and nonglucose (internal or environmental) factors in within-subject variability in energy intake. In addition, the CGMS may have utility in understanding the role of circulating glucose in energy regulation in free-living subjects under a wide range of different nutritional conditions.

  16. Bayesian Test of Significance for Conditional Independence: The Multinomial Model

    Directory of Open Access Journals (Sweden)

    Pablo de Morais Andrade

    2014-03-01

    Full Text Available Conditional independence tests have received special attention lately in machine learning and computational intelligence related literature as an important indicator of the relationship among the variables used by their models. In the field of probabilistic graphical models, which includes Bayesian network models, conditional independence tests are especially important for the task of learning the probabilistic graphical model structure from data. In this paper, we propose the full Bayesian significance test for tests of conditional independence for discrete datasets. The full Bayesian significance test is a powerful Bayesian test for precise hypothesis, as an alternative to the frequentist’s significance tests (characterized by the calculation of the p-value.

  17. BMI, HOMA-IR, and Fasting Blood Glucose Are Significant Predictors of Peripheral Nerve Dysfunction in Adult Overweight and Obese Nondiabetic Nepalese Individuals: A Study from Central Nepal.

    Science.gov (United States)

    Thapa, Lekhjung; Rana, P V S

    2016-01-01

    Objective. Nondiabetic obese individuals have subclinical involvement of peripheral nerves. We report the factors predicting peripheral nerve function in overweight and obese nondiabetic Nepalese individuals. Methodology. In this cross-sectional study, we included 50 adult overweight and obese nondiabetic volunteers without features of peripheral neuropathy and 50 healthy volunteers to determine the normative nerve conduction data. In cases of abnormal function, the study population was classified on the basis of the number of nerves involved, namely, "HOMA-IR) was the significant predictor (P = 0.019, 96% CI = 1.420-49.322) of sensory nerve dysfunction. Body mass index (BMI) was the significant predictor (P = 0.034, 95% CI = 1.018-1.577) in case of ≥2 mixed nerves' involvement. Conclusion. FBG, HOMA-IR, and BMI were significant predictors of peripheral nerve dysfunction in overweight and obese Nepalese individuals.

  18. Genomic predictors for recurrence patterns of hepatocellular carcinoma: model derivation and validation.

    Directory of Open Access Journals (Sweden)

    Ji Hoon Kim

    2014-12-01

    Full Text Available BACKGROUND: Typically observed at 2 y after surgical resection, late recurrence is a major challenge in the management of hepatocellular carcinoma (HCC. We aimed to develop a genomic predictor that can identify patients at high risk for late recurrence and assess its clinical implications. METHODS AND FINDINGS: Systematic analysis of gene expression data from human liver undergoing hepatic injury and regeneration revealed a 233-gene signature that was significantly associated with late recurrence of HCC. Using this signature, we developed a prognostic predictor that can identify patients at high risk of late recurrence, and tested and validated the robustness of the predictor in patients (n = 396 who underwent surgery between 1990 and 2011 at four centers (210 recurrences during a median of 3.7 y of follow-up. In multivariate analysis, this signature was the strongest risk factor for late recurrence (hazard ratio, 2.2; 95% confidence interval, 1.3-3.7; p = 0.002. In contrast, our previously developed tumor-derived 65-gene risk score was significantly associated with early recurrence (p = 0.005 but not with late recurrence (p = 0.7. In multivariate analysis, the 65-gene risk score was the strongest risk factor for very early recurrence (<1 y after surgical resection (hazard ratio, 1.7; 95% confidence interval, 1.1-2.6; p = 0.01. The potential significance of STAT3 activation in late recurrence was predicted by gene network analysis and validated later. We also developed and validated 4- and 20-gene predictors from the full 233-gene predictor. The main limitation of the study is that most of the patients in our study were hepatitis B virus-positive. Further investigations are needed to test our prediction models in patients with different etiologies of HCC, such as hepatitis C virus. CONCLUSIONS: Two independently developed predictors reflected well the differences between early and late recurrence of HCC at the molecular level and provided new

  19. Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

    Science.gov (United States)

    Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

    2014-01-01

    Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

  20. Joint Bayesian variable and graph selection for regression models with network-structured predictors

    Science.gov (United States)

    Peterson, C. B.; Stingo, F. C.; Vannucci, M.

    2015-01-01

    In this work, we develop a Bayesian approach to perform selection of predictors that are linked within a network. We achieve this by combining a sparse regression model relating the predictors to a response variable with a graphical model describing conditional dependencies among the predictors. The proposed method is well-suited for genomic applications since it allows the identification of pathways of functionally related genes or proteins which impact an outcome of interest. In contrast to previous approaches for network-guided variable selection, we infer the network among predictors using a Gaussian graphical model and do not assume that network information is available a priori. We demonstrate that our method outperforms existing methods in identifying network-structured predictors in simulation settings, and illustrate our proposed model with an application to inference of proteins relevant to glioblastoma survival. PMID:26514925

  1. Bayesian modeling of measurement error in predictor variables using item response theory

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; Glas, Cornelis A.W.

    2000-01-01

    This paper focuses on handling measurement error in predictor variables using item response theory (IRT). Measurement error is of great important in assessment of theoretical constructs, such as intelligence or the school climate. Measurement error is modeled by treating the predictors as unobserved

  2. Random generalized linear model: a highly accurate and interpretable ensemble predictor.

    Science.gov (United States)

    Song, Lin; Langfelder, Peter; Horvath, Steve

    2013-01-16

    Ensemble predictors such as the random forest are known to have superior accuracy but their black-box predictions are difficult to interpret. In contrast, a generalized linear model (GLM) is very interpretable especially when forward feature selection is used to construct the model. However, forward feature selection tends to overfit the data and leads to low predictive accuracy. Therefore, it remains an important research goal to combine the advantages of ensemble predictors (high accuracy) with the advantages of forward regression modeling (interpretability). To address this goal several articles have explored GLM based ensemble predictors. Since limited evaluations suggested that these ensemble predictors were less accurate than alternative predictors, they have found little attention in the literature. Comprehensive evaluations involving hundreds of genomic data sets, the UCI machine learning benchmark data, and simulations are used to give GLM based ensemble predictors a new and careful look. A novel bootstrap aggregated (bagged) GLM predictor that incorporates several elements of randomness and instability (random subspace method, optional interaction terms, forward variable selection) often outperforms a host of alternative prediction methods including random forests and penalized regression models (ridge regression, elastic net, lasso). This random generalized linear model (RGLM) predictor provides variable importance measures that can be used to define a "thinned" ensemble predictor (involving few features) that retains excellent predictive accuracy. RGLM is a state of the art predictor that shares the advantages of a random forest (excellent predictive accuracy, feature importance measures, out-of-bag estimates of accuracy) with those of a forward selected generalized linear model (interpretability). These methods are implemented in the freely available R software package randomGLM.

  3. Preoperative glycemic control status as a significant predictor of biochemical recurrence in prostate cancer patients after radical prostatectomy.

    Science.gov (United States)

    Lee, Hakmin; Kuk, Harim; Byun, Seok-Soo; Lee, Sang Eun; Hong, Sung Kyu

    2015-01-01

    The effect of diabetes mellitus (DM) on prostate cancer (PCa) outcome remains controversial. Thus, we investigated the association of DM history, glycemic control, and metformin use with oncologic outcomes after radical prostatectomy (RP). We reviewed the records of 746 contemporary patients who had hemoglobin A1c (HbA1c) measured within the 6 months preceding RP. The associations between clinical variables and risk of adverse pathological features and biochemical recurrence (BCR) were tested using a multivariate logistic regression and multiple Cox-proportional hazards model, respectively. BCR was defined as prostatic specific antigen (PSA) > 0.2 ng/mL in 2 consecutive tests. There were no significant differences in the rates of adverse pathologic features and BCR-free survival between patients with (n = 209) and without (n = 537) a history of DM diagnosis (all p > 0.05). In multivariate analyses, high HbA1c level (≥ 6.5%) was significantly related with high pathologic Gleason score (≥ 4+3; odds ratio [OR] 1.704, p = 0.019) and BCR-free survival (OR 1.853, p = 0.007). Metformin use was not associated with BCR-free survival (OR 0.662, p = 0.125). Poor glycemic control was significantly associated with BCR after RP. Meanwhile, metformin use was not associated with biochemical outcome after RP. Further investigation would be needed to identify exact mechanism underlying the impact of glycemic control on PCa treatment outcome.

  4. Predictor characteristics necessary for building a clinically useful risk prediction model: a simulation study

    Directory of Open Access Journals (Sweden)

    Laura Schummers

    2016-09-01

    Full Text Available Abstract Background Compelled by the intuitive appeal of predicting each individual patient’s risk of an outcome, there is a growing interest in risk prediction models. While the statistical methods used to build prediction models are increasingly well understood, the literature offers little insight to researchers seeking to gauge a priori whether a prediction model is likely to perform well for their particular research question. The objective of this study was to inform the development of new risk prediction models by evaluating model performance under a wide range of predictor characteristics. Methods Data from all births to overweight or obese women in British Columbia, Canada from 2004 to 2012 (n = 75,225 were used to build a risk prediction model for preeclampsia. The data were then augmented with simulated predictors of the outcome with pre-set prevalence values and univariable odds ratios. We built 120 risk prediction models that included known demographic and clinical predictors, and one, three, or five of the simulated variables. Finally, we evaluated standard model performance criteria (discrimination, risk stratification capacity, calibration, and Nagelkerke’s r2 for each model. Results Findings from our models built with simulated predictors demonstrated the predictor characteristics required for a risk prediction model to adequately discriminate cases from non-cases and to adequately classify patients into clinically distinct risk groups. Several predictor characteristics can yield well performing risk prediction models; however, these characteristics are not typical of predictor-outcome relationships in many population-based or clinical data sets. Novel predictors must be both strongly associated with the outcome and prevalent in the population to be useful for clinical prediction modeling (e.g., one predictor with prevalence ≥20 % and odds ratio ≥8, or 3 predictors with prevalence ≥10 % and odds ratios ≥4. Area

  5. Relapse of childhood acute lymphoblastic leukemia and outcomes at a reference center in Latin America: organomegaly at diagnosis is a significant clinical predictor.

    Science.gov (United States)

    Jaime-Pérez, José Carlos; Pinzón-Uresti, Mónica Andrea; Jiménez-Castillo, Raúl Alberto; Colunga-Pedraza, Julia Esther; González-Llano, Óscar; Gómez-Almaguer, David

    2018-01-01

    Relapse is the major cause of treatment failure in acute lymphoblastic leukemia (ALL) of childhood; it is more frequent among high-risk patients from low-middle income than from high-income countries. The frequency, sites and outcome of relapsed ALL in children of northeast Mexico over a decade was documented. A retrospective analysis of 246 children belonging to a low-income group death were estimated by the Cox regression model. Very early relapse was defined as that occurring in 36 months from diagnosis, respectively. Eighty-seven (35.4%) children relapsed. Five-year OS was 82.6% in children without relapse vs. 42% for relapsed patients. Bone marrow (BM) was the most frequent site of relapse (51.72%). Isolated central nervous system (CNS) relapses occurred in 29.9%. Five-year OS was 11.2% for BM and 15.5% for early relapse. HR of relapse for organomegaly was 3.683, 2.247 for an initial white blood cell count >50 000 × 10 9 /l and 1.169 for positive minimal residual disease status. A high rate of very early, CNS, and BM relapse with a considerably low 5-year OS requiring reassessment of therapy was documented. Organomegaly at diagnosis was a highly significant clinical predictor for relapse.

  6. Underlying Predictors of Tobacco Smoking among Iranian Teenagers: Generalized Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Fariba Khayyati

    2016-09-01

    Full Text Available Background: To define underlying predictors of tobacco smoking among Iranian Teenagers in a generalized structural equation model. Materials and Methods: In this cross-sectional study, a Generalized Structural Equation Model based on planned behavioral theory was used to explain the relationship among different factors such as demographic factors, subjective norms, and the intention to tobacco and, in turn, intention with tobacco use. The sample consisted of 4,422 high school students, based on census, in East Azerbaijan province, Iran. The questioner was designed adapting to the objectives of study. It was used global youth tobacco survey to design the queries of tobacco use. Results: The model had a good fit on data. Adjusting for age and gender, there was a statistically significant relationship between the intention to consumption and the following factors: working while studying (P

  7. Regional Distribution Models with Lack of Proximate Predictors: Africanized Honeybees Expanding North

    Science.gov (United States)

    Jarnevich, Catherine S.; Esaias, Wayne E.; Ma, Peter L. A.; Morisette, Jeffery T.; Nickeson, Jaime E.; Stohlgren, Thomas J.; Holcombe, Tracy R.; Nightingale, Joanne M.; Wolfe, Robert E.; Tan, Bin

    2014-01-01

    Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species-environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

  8. Exploratory regression analysis: a tool for selecting models and determining predictor importance.

    Science.gov (United States)

    Braun, Michael T; Oswald, Frederick L

    2011-06-01

    Linear regression analysis is one of the most important tools in a researcher's toolbox for creating and testing predictive models. Although linear regression analysis indicates how strongly a set of predictor variables, taken together, will predict a relevant criterion (i.e., the multiple R), the analysis cannot indicate which predictors are the most important. Although there is no definitive or unambiguous method for establishing predictor variable importance, there are several accepted methods. This article reviews those methods for establishing predictor importance and provides a program (in Excel) for implementing them (available for direct download at http://dl.dropbox.com/u/2480715/ERA.xlsm?dl=1) . The program investigates all 2(p) - 1 submodels and produces several indices of predictor importance. This exploratory approach to linear regression, similar to other exploratory data analysis techniques, has the potential to yield both theoretical and practical benefits.

  9. Developmental trajectories of clinically significant attention-deficit/hyperactivity disorder (ADHD) symptoms from grade 3 through 12 in a high-risk sample: Predictors and outcomes.

    Science.gov (United States)

    Sasser, Tyler R; Kalvin, Carla B; Bierman, Karen L

    2016-02-01

    Developmental trajectories of clinically significant attention-deficit/hyperactivity (ADHD) symptoms were explored in a sample of 413 children identified as high risk because of elevated kindergarten conduct problems. Symptoms of inattention and hyperactivity-impulsivity were modeled simultaneously in a longitudinal latent class analyses, using parent reports collected in Grades 3, 6, 9, and 12. Three developmental trajectories emerged: (1) low levels of inattention and hyperactivity (low), (2) initially high but then declining symptoms (declining), and (3) continuously high symptoms that featured hyperactivity in childhood and early adolescence and inattention in adolescence (high). Multinomial logistic regressions examined child characteristics and family risk factors as predictors of ADHD trajectories. Relative to the low class, children in the high and declining classes displayed similar elevations of inattention and hyperactivity in early childhood. The high class was distinguished from the declining class by higher rates of aggression and hyperactivity at school and emotion dysregulation at home. In contrast, the declining class displayed more social isolation at home and school, relative to the low class. Families of children in both high and declining trajectory classes experienced elevated life stressors, and parents of children in the high class were also more inconsistent in their discipline practices relative to the low class. By late adolescence, children in the high class were significantly more antisocial than those in the low class, with higher rates of arrests, school dropout, and unemployment, whereas children in the declining class did not differ from those in the low trajectory class. The developmental and clinical implications of these findings are discussed. (c) 2016 APA, all rights reserved).

  10. Self-reported pigmentary phenotypes and race are significant but incomplete predictors of Fitzpatrick skin phototype in an ethnically diverse population.

    Science.gov (United States)

    He, Steven Y; McCulloch, Charles E; Boscardin, W John; Chren, Mary-Margaret; Linos, Eleni; Arron, Sarah T

    2014-10-01

    Fitzpatrick skin phototype (FSPT) is the most common method used to assess sunburn risk and is an independent predictor of skin cancer risk. Because of a conventional assumption that FSPT is predictable based on pigmentary phenotypes, physicians frequently estimate FSPT based on patient appearance. We sought to determine the degree to which self-reported race and pigmentary phenotypes are predictive of FSPT in a large, ethnically diverse population. A cross-sectional survey collected responses from 3386 individuals regarding self-reported FSPT, pigmentary phenotypes, race, age, and sex. Univariate and multivariate logistic regression analyses were performed to determine variables that significantly predict FSPT. Race, sex, skin color, eye color, and hair color are significant but weak independent predictors of FSPT (Prace and pigmentary phenotypes are inaccurate predictors of sun sensitivity as defined by FSPT. There are limitations to using patient-reported race and appearance in predicting individual sunburn risk. Copyright © 2014 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

  11. [Significance of acute-phase inflammatory reactants as an indicator of prognosis after acute myocardial infarction: which is the most useful predictor?].

    Science.gov (United States)

    Katayama, Toshiro; Nakashima, Hiroshi; Yonekura, Tsuyoshi; Honda, Yukiharu; Suzuki, Shin; Yano, Katsusuke

    2003-08-01

    To investigate the relationship between representative acute-phase inflammatory reactants [highly sensitive C-reactive protein (hsCRP), serum amyloid A protein (SAA) and interleukin-6 (IL-6)] and the severity of acute myocardial infarction and patient prognosis, and to identify the most useful predictor of the three. This study investigated 132 consecutive patients admitted within 8 hr of onset of first acute myocardial infarction and successfully reperfused with primary percutaneous coronary intervention. Acute-phase (= 24 hr from onset) blood samples were taken for evaluation of inflammatory reactants (hsCRP, SAA and IL-6), and peak creatine phosphokinase levels were measured every 4 hr after admission for 48 hr to assess myocardial infarction infarct size. Left ventriculography was performed in the chronic stage (20 +/- 9 days post-admission) to analyze left ventricular ejection fraction and regional wall motion, using Killip's classification to determine acute myocardial infarction severity. Logistic regression analysis was used to quantify the usefulness of the reactants as predictors of patient prognosis. Both hsCRP and SAA showed significant positive correlations with peak creatine phosphokinase. hsCRP and SAA showed significant inverse correlations with left ventricular ejection fraction and regional wall motion in the chronic stage. Multivariate analysis identified SAA as the best predictor of severe heart failure (Killip's classification III, IV). SAA was the best predictor of a major cardiac event (shock, cardiac death). These results suggest a strong correlation between acute-phase SAA and the clinical course of patient outcomes after acute myocardial infarction, such as cardiac function, heart failure and cardiac death. SAA may be the most useful acute-phase inflammatory reactant for predicting the prognosis after acute myocardial infarction.

  12. Cognitive predictors of children's development in mathematics achievement: A latent growth modeling approach.

    Science.gov (United States)

    Xenidou-Dervou, Iro; Van Luit, Johannes E H; Kroesbergen, Evelyn H; Friso-van den Bos, Ilona; Jonkman, Lisa M; van der Schoot, Menno; van Lieshout, Ernest C D M

    2018-04-24

    Research has identified various domain-general and domain-specific cognitive abilities as predictors of children's individual differences in mathematics achievement. However, research into the predictors of children's individual growth rates, namely between-person differences in within-person change in mathematics achievement is scarce. We assessed 334 children's domain-general and mathematics-specific early cognitive abilities and their general mathematics achievement longitudinally across four time-points within the first and second grades of primary school. As expected, a constellation of multiple cognitive abilities contributed to the children's starting level of mathematical success. Specifically, latent growth modeling revealed that WM abilities, IQ, counting skills, nonsymbolic and symbolic approximate arithmetic and comparison skills explained individual differences in the children's initial status on a curriculum-based general mathematics achievement test. Surprisingly, however, only one out of all the assessed cognitive abilities was a unique predictor of the children's individual growth rates in mathematics achievement: their performance in the symbolic approximate addition task. In this task, children were asked to estimate the sum of two large numbers and decide if this estimated sum was smaller or larger compared to a third number. Our findings demonstrate the importance of multiple domain-general and mathematics-specific cognitive skills for identifying children at risk of struggling with mathematics and highlight the significance of early approximate arithmetic skills for the development of one's mathematical success. We argue the need for more research focus on explaining children's individual growth rates in mathematics achievement. © 2018 John Wiley & Sons Ltd.

  13. Predictors of smoking among the secondary high school boy students based on the health belief model

    Directory of Open Access Journals (Sweden)

    Samira Mohammadi

    2017-01-01

    Full Text Available Background: Smoking is one of the most important risk factors for health and also health problems, such as heart diseases, especially for young people. This study aimed to investigate the effect of factors related to smoking among the secondary high school students in the city of Marivan (Kurdistan-Iran, in 2015, based on the constructs of health belief model (HBM. Methods: This cross-sectional study was conducted in 470 secondary high school students in Marivan in 2015. The samples were selected by random cluster sampling. A question with four sections was used to collect data (demographic questions, knowledge section, attitude section, and questions related to e constructs of HBM. Results: According to the results, the correlation of smoking was stronger with attitude (r = 0.269 and odds ratio = 0.89 but weaker with perceived barriers (r = 0.101. There was not a significant correlation between smoking behavior and knowledge of the harms of smoking (r = −0.005. Moreover, Cues to action was effective predictor of smoking behavior (r = 0.259. Conclusions: The findings of this study show that the prevalence of smoking in the studied sample is somewhat lower than other regions of Iran, but it should be noted that if no interventions are done to prevent smoking in this age group. The findings of the study also showed that the structure of attitudes, self-efficacy, and Cues to action are the strongest predictors of smoking among students. Albeit, attitude was strongest predictor of smoking that shows the prevalence of smoking can be reduced by focusing in this part. Considering the mean age of participants (16/2 ± 0.25 years, that shows the riskiest period for smoking is 16 years and authorities can make change in policies of cigarette selling only for over 18 years.

  14. Predictors of Smoking among the Secondary High School Boy Students Based on the Health Belief Model.

    Science.gov (United States)

    Mohammadi, Samira; Ghajari, Haydeh; Valizade, Rohollah; Ghaderi, Naseh; Yousefi, Fayegh; Taymoori, Parvaneh; Nouri, Bejan

    2017-01-01

    Smoking is one of the most important risk factors for health and also health problems, such as heart diseases, especially for young people. This study aimed to investigate the effect of factors related to smoking among the secondary high school students in the city of Marivan (Kurdistan-Iran), in 2015, based on the constructs of health belief model (HBM). This cross-sectional study was conducted in 470 secondary high school students in Marivan in 2015. The samples were selected by random cluster sampling. A question with four sections was used to collect data (demographic questions, knowledge section, attitude section, and questions related to e constructs of HBM). According to the results, the correlation of smoking was stronger with attitude ( r = 0.269 and odds ratio = 0.89) but weaker with perceived barriers ( r = 0.101). There was not a significant correlation between smoking behavior and knowledge of the harms of smoking ( r = -0.005). Moreover, Cues to action was effective predictor of smoking behavior ( r = 0.259). The findings of this study show that the prevalence of smoking in the studied sample is somewhat lower than other regions of Iran, but it should be noted that if no interventions are done to prevent smoking in this age group. The findings of the study also showed that the structure of attitudes, self-efficacy, and Cues to action are the strongest predictors of smoking among students. Albeit, attitude was strongest predictor of smoking that shows the prevalence of smoking can be reduced by focusing in this part. Considering the mean age of participants (16/2 ± 0.25 years), that shows the riskiest period for smoking is 16 years and authorities can make change in policies of cigarette selling only for over 18 years.

  15. A comparison of acoustic and observed sediment classifications as predictor variables for modelling biotope distributions in Galway Bay, Ireland

    Science.gov (United States)

    O'Carroll, Jack P. J.; Kennedy, Robert; Ren, Lei; Nash, Stephen; Hartnett, Michael; Brown, Colin

    2017-10-01

    The INFOMAR (Integrated Mapping For the Sustainable Development of Ireland's Marine Resource) initiative has acoustically mapped and classified a significant proportion of Ireland's Exclusive Economic Zone (EEZ), and is likely to be an important tool in Ireland's efforts to meet the criteria of the MSFD. In this study, open source and relic data were used in combination with new grab survey data to model EUNIS level 4 biotope distributions in Galway Bay, Ireland. The correct prediction rates of two artificial neural networks (ANNs) were compared to assess the effectiveness of acoustic sediment classifications versus sediments that were visually classified by an expert in the field as predictor variables. To test for autocorrelation between predictor variables the RELATE routine with Spearman rank correlation method was used. Optimal models were derived by iteratively removing predictor variables and comparing the correct prediction rates of each model. The models with the highest correct prediction rates were chosen as optimal. The optimal models each used a combination of salinity (binary; 0 = polyhaline and 1 = euhaline), proximity to reef (binary; 0 = within 50 m and 1 = outside 50 m), depth (continuous; metres) and a sediment descriptor (acoustic or observed) as predictor variables. As the status of benthic habitats is required to be assessed under the MSFD the Ecological Status (ES) of the subtidal sediments of Galway Bay was also assessed using the Infaunal Quality Index. The ANN that used observed sediment classes as predictor variables could correctly predict the distribution of biotopes 67% of the time, compared to 63% for the ANN using acoustic sediment classes. Acoustic sediment ANN predictions were affected by local sediment heterogeneity, and the lack of a mixed sediment class. The all-round poor performance of ANNs is likely to be a result of the temporally variable and sparsely distributed data within the study area.

  16. Testosterone and religiosity as predictors of sexual attitudes and activity among adolescent males: a biosocial model.

    Science.gov (United States)

    Halpern, C T; Udry, J R; Campbell, B; Suchindran, C; Mason, G A

    1994-04-01

    A biosocial model of the effects of early adolescent testosterone levels and religiosity on adolescent males' sexual attitudes and activity over a 3-year period was examined. Using panel data for approximately 100 boys who were 12.5/13.0 years old at study entry, significant additive effects of free testosterone and frequency of attendance at religious services were demonstrated on the transition to first intercourse and other aspects of sexual behaviour and attitudes. No interactive effects of the two predictors were found. Boys with higher free testosterone levels at study entry who never or infrequently attended religious services were the most sexually active and had the most permissive attitudes. Boys with lower free testosterone who attended services once a week or more were the least active and reported the least permissive attitudes. For some behaviours, differences between free testosterone/attendance groups increased over time, resulting in substantial behavioural differences by the final round of measurement 3 years later.

  17. Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes.

    Science.gov (United States)

    Yates, Katherine L; Mellin, Camille; Caley, M Julian; Radford, Ben T; Meeuwig, Jessica J

    2016-01-01

    Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are

  18. The coronary calcium score is a more accurate predictor of significant coronary stenosis than conventional risk factors in symptomatic patients

    DEFF Research Database (Denmark)

    Nicoll, R; Wiklund, U; Zhao, Y

    2016-01-01

    AIMS: In this retrospective study we assessed the predictive value of the coronary calcium score for significant (>50%) stenosis relative to conventional risk factors. METHODS AND RESULTS: We investigated 5515 symptomatic patients from Denmark, France, Germany, Italy, Spain and the USA. All had r...

  19. The predictors of osteoporosis preventive behaviors in women based on health belief model

    Directory of Open Access Journals (Sweden)

    Ali Khani Jeihooni

    2017-06-01

    Full Text Available Osteoporosis, as a disease, is characterized by low bone mass and micro architectural deterioration of bone tissue. The aim of this study was to survey the predictors of osteoporosis preventive behaviors based on health belief model. This cross-sectional study was carried out on 401 randomly selected women referring to health centers. Data collection was based on health belief model. The employed instrument was confirmed by a panel of experts. Content validity ratio, content validity index, face validity, and exploratory factor analysis were used to determine the validity of the tool. Test-retest internal consistency was employed to determine the reliability. The mean age of women was 40.9±6.2 years. The variables of perceived susceptibility, motivation for walking behavior and variable of perceived sensitivity for nutrition behavior were predicted. The walking performance had a significant association with perceived susceptibility and motivation, the nutritional performance had a significant positive association with perceived susceptibility and self-efficacy and a negative correlation with perceived barriers. The variables under study explained 29.1% of the variance in walking behavior and 20.2% of the variance in nutrition behavior in osteoporosis prevention. This study indicated health belief model is capable to predict nutrition and walking behaviors for the prevention of osteoporosis. Hence, this model can be used as a framework for designing and implementing educational interventions for the prevention of osteoporosis in women.

  20. Predictors of Academic Performance of University Students: An Application of the Goal Efficacy Model

    Science.gov (United States)

    Klomegah, Roger Yao

    2007-01-01

    This study utilized the goal-efficacy model to examine a) the extent to which index scores of student self-efficacy, self-set goals, assigned goals, and ability (four variables in the model) could predict academic performance of university students; and b) the best predictor of academic performance. The sample comprised 103 undergraduate students…

  1. Regular smokeless tobacco use is not a reliable predictor of smoking onset when psychosocial predictors are included in the model.

    Science.gov (United States)

    O'Connor, Richard J; Flaherty, Brian P; Quinio Edwards, Beth; Kozlowski, Lynn T

    2003-08-01

    Tomar analyzed the CDC's Teenage Attitudes and Practices Survey (TAPS) and reported smokeless tobacco may act as a starter product for or gateway to cigarettes. Regular smokeless tobacco users at baseline were said to be 3.45 times more likely than never users of smokeless tobacco to become cigarette smokers after 4 years (95% CI=1.84-6.47). However, this analysis did not take into account well-known psychosocial predictors of smoking initiation. We reanalyzed TAPS to assess whether including psychosocial predictors of smoking affected the smokeless tobacco gateway effect. Experimenting with smoking, OR=2.09 (95% CI=1.51-2.90); below average school performance, OR=9.32 (95% CI=4.18-20.77); household members smoking, OR=1.49 (95% CI=1.13-1.95); frequent depressive symptoms, OR=2.19 (95% CI=1.25-3.84); fighting, OR=1.48 (95% CI=1.08-2.03); and motorcycle riding, OR=1.42 (95% CI=1.06-1.91) diminished the effect of both regular, OR=1.68 (95% CI=.83-3.41), and never regular smokeless tobacco use, OR=1.41 (95% CI=.96-2.05), to be statistically unreliable. Analyzing results from a sample of true never smokers (never a single puff) showed a similar pattern of results. Our results indicate that complex multivariate models are needed to evaluate recruitment to smoking and single factors that are important in that process. Tomar's analysis should not be used as reliable evidence that smokeless tobacco may be a starter product for cigarettes.

  2. Multiresolution wavelet-ANN model for significant wave height forecasting.

    Digital Repository Service at National Institute of Oceanography (India)

    Deka, P.C.; Mandal, S.; Prahlada, R.

    (ANN) modeling. The transformed output data are used as inputs to ANN models. Various decomposition levels have been tried for a db3 wavelet to obtain optimal results. It is found that the performance of hybrid WLNN is better than that of ANN when lead...

  3. Predictors of Discharge Disposition in Older Adults With Burns: A Study of the Burn Model Systems.

    Science.gov (United States)

    Pham, Tam N; Carrougher, Gretchen J; Martinez, Erin; Lezotte, Dennis; Rietschel, Carly; Holavanahalli, Radha; Kowalske, Karen; Esselman, Peter C

    2015-01-01

    Older patients with burn injury have a greater likelihood for discharge to nursing facilities. Recent research indicates that older patients discharged to nursing facilities are two to three times as likely to die within a 3-year period relative to those discharged to home. In light of these poor long-term outcomes, we conducted this study to identify predictors for discharge to independent vs nonindependent living status in older patients hospitalized for burns. We retrospectively reviewed all older adults (age ≥ 55 years) who were prospectively enrolled in a longitudinal multicenter study of outcomes from 1993 to 2011. Patient, injury, and treatment outcomes data were analyzed. Recognizing that transfer to inpatient rehabilitation may have impacted final hospital discharge disposition: we assessed the likelihood of inpatient rehabilitation stay, based on identified predictors of inpatient rehabilitation. We subsequently performed a logistic regression analysis on the clustered, propensity-matched cohort to assess associations of burn and injury characteristics on the primary outcome of final discharge status. A total of 591 patients aged ≥55 years were treated and discharged alive from three participating U.S. burn centers during the study period. Mean burn size was 14.8% (SD 11.2%) and mean age was 66.7 years (SD 9.3 years). Ninety-three patients had an inpatient rehabilitation stay before discharge (15.7%). Significant factors predictive of inpatient rehabilitation included a burn >20% TBSA, mechanical ventilation, older age, range of motion deficits at acute care discharge, and study site. These factors were included in the propensity model. Four hundred seventy-one patients (80%) were discharged to independent living status. By matched propensity analysis, older age was significantly associated with a higher likelihood of discharge to nonindependent living (P burn centers need to be elucidated to better understand discharge disposition status in older

  4. Inclusion of edaphic predictors for enhancement of models to determine distribution of soil-transmitted helminths: the case of Zimbabwe.

    Science.gov (United States)

    Midzi, Nicholas; Kavhu, Blessing; Manangazira, Portia; Phiri, Isaac; Mutambu, Susan L; Tshuma, Cremants; Chimbari, Moses J; Munyati, Shungu; Midzi, Stanely M; Charimari, Lincon; Ncube, Anatoria; Mutsaka-Makuvaza, Masceline J; Soko, White; Madzima, Emmanuel; Hlerema, Gibson; Mbedzi, Joel; Mhlanga, Gibson; Masocha, Mhosisi

    2018-01-19

    Reliable mapping of soil-transmitted helminth (STH) parasites requires rigorous statistical and machine learning algorithms capable of integrating the combined influence of several determinants to predict distributions. This study tested whether combining edaphic predictors with relevant environmental predictors improves model performance when predicting the distribution of STH, Ascaris lumbricoides and hookworms at a national scale in Zimbabwe. Geo-referenced parasitological data obtained from a 2010/2011 national survey indicating a confirmed presence or absence of STH among school children aged 10-15 years was used to calibrate ten species distribution models (SDMs). The performance of SDMs calibrated with a set of environmental and edaphic variables was compared to that of SDMs calibrated with environmental variables only. Model performance was evaluated using the true skill statistic and receiver operating characteristic curve. Results show a significant improvement in model performance for both A. lumbricoides and hookworms for all ten SDMs after edaphic variables were combined with environmental variables in the modelling of the geographical distribution of the two STHs at national scale. Using the top three performing models, a consensus prediction was developed to generate the first continuous maps of the potential distribution of the two STHs in Zimbabwe. The findings from this study demonstrate significant model improvement if relevant edaphic variables are included in model calibration resulting in more accurate mapping of STH. The results also provide spatially-explicit information to aid targeted control of STHs in Zimbabwe and other countries with STH burden.

  5. Adaptive State Predictor Based Human Operator Modeling on Longitudinal and Lateral Control

    Science.gov (United States)

    Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

    2015-01-01

    Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to categorize these interactions of the pilot with an adaptive controller compensating during control surface failures. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored. A gradient descent estimator (GDE), a least squares estimator with exponential forgetting (LSEEF), and a least squares estimator with bounded gain forgetting (LSEBGF) used the experiment data to predict pilot stick input. Previous results have found that the GDE and LSEEF methods are fairly accurate in predicting longitudinal stick input from commanded pitch. This paper discusses the accuracy of each of the three methods - GDE, LSEEF, and LSEBGF - to predict both pilot longitudinal and lateral stick input from the flight director's commanded pitch and bank attitudes.

  6. Using Structural Equation Modeling to Identify Predictors of Sexual Behaviors among Hispanic Men who have Sex with Men

    Science.gov (United States)

    De Santis, Joseph P; Arcia, Adriana; Vermeesch, Amber; Gattamorta, Karina A.

    2013-01-01

    Background Hispanic men who have sex with men (MSM) are at risk for HIV and other sexually transmitted infections related to high risk sexual behaviors. Little attention has been paid to the identification of predictors of sexual behaviors among this population. Objective The aim of this study was to test a model that predicts the sexual behaviors of Hispanic MSM that is based on an epidemiological framework. Methods Structural equation modeling was used to test relationships between demographic and study variables of alcohol abuse, body image, depressive symptoms, eating attitudes and behaviors, and self-esteem as predictors of sexual behaviors using a sample of 100 Hispanic MSM. Results A number of participants were at risk for alcohol abuse, body image disturbance, depression, eating disorders, and low self-esteem. Physical and social factors were not predictive of sexual behaviors. A model that included the latent variables of mental health and appearance concern adequately fit the data (X2 (10, N = 100) = 14.498, CFI = 0.966, RMSEA = 0.067, SRMR = 0.043), demonstrating that mental health is a significant predictor of sexual behaviors in this sample. Discussion The results of this study supported a model predicting sexual behaviors of Hispanic MSM. This study highlights the importance of understanding the influence of psychological/mental health on the sexual behaviors of Hispanic MSM. Interventions to decrease high risk sexual behaviors among this population must consider the impact of psychological/mental health on sexual behaviors. PMID:21501734

  7. Internet Behaviours as Predictors of Reading Proficiency of Model ...

    African Journals Online (AJOL)

    The study investigated the internet behaviours of students in selected model senior secondary schools in Ibadan metropolis and the extent to which these behaviours predicted their reading proficiency. The study adopted the descriptive research design with a sample of 500 senior secondary school (II) students randomly ...

  8. Computational models as predictors of HIV treatment outcomes for ...

    African Journals Online (AJOL)

    Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping. Objective: The evaluation as a potential treatment support tool of computational models that predict response to therapy without a genotype, ...

  9. Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors.

    Science.gov (United States)

    Talmoudi, Khouloud; Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

    2017-08-01

    Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.

  10. Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors.

    Directory of Open Access Journals (Sweden)

    Khouloud Talmoudi

    2017-08-01

    Full Text Available Transmission of zoonotic cutaneous leishmaniasis (ZCL depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015. Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM and generalized additive mixed models (GAMM were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs and the response variable (output, and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.

  11. Predictors of Health-Promoting Behaviors in Coronary Artery Bypass Surgery Patients: An Application of Pender's Health Promotion Model.

    Science.gov (United States)

    Mohsenipoua, Hossein; Majlessi, Fereshteh; Shojaeizadeh, Davood; Rahimiforooshani, Abbas; Ghafari, Rahman; Habibi, Valiollah

    2016-09-01

    Advances in coronary artery surgery have reduced patient morbidity and mortality. Nevertheless, patients still have to face physical, psychological, and social problems after discharge from hospital. The objective of this study was to determine the efficacy of Pender's health promotion model in predicting cardiac surgery patients' lifestyles in Iran. This cross-sectional study comprised 220 patients who had undergone coronary artery bypass graft (CABG) surgery in Mazandaran province (Iran) in 2015. The subjects were selected using a simple random sampling method. The data were collected via (1) the health-promoting lifestyle profile II (HPLP II) and (2) a self-designed questionnaire that included two main sections: demographic characteristics and questions based on the health-promoting model constructs. Spiritual growth (28.77 ± 5.03) and physical activity (15.79 ± 5.08) had the highest and lowest scores in the HPLP II dimensions, respectively. All the health promotion model variables were significant predictors of health-promoting behaviors and explained 69% of the variance in health-promoting behaviors. Three significant predictors were estimated using regression coefficients: behavioral feelings (β = 0.390, P health-promoting model-based self-care behaviors can help identify and predict cardiac surgery patients' lifestyles in Iran. This pattern can be used as a framework for discharge planning and the implementation of educational interventions to improve the lifestyles of CABG patients.

  12. Job strain (demands and control model) as a predictor of cardiovascular risk factors among petrochemical personnel

    Science.gov (United States)

    Habibi, Ehsanollah; Poorabdian, Siamak; Shakerian, Mahnaz

    2015-01-01

    Background: One of the practical models for the assessment of stressful working conditions due to job strain is job demand and control model, which explains how physical and psychological adverse consequences, including cardiovascular risk factors can be established due to high work demands (the amount of workload, in addition to time limitations to complete that work) and low control of the worker on his/her work (lack of decision making) in the workplace. The aim of this study was to investigate how certain cardiovascular risk factors (including body mass index [BMI], heart rate, blood pressure, cholesterol and smoking) and the job demand and job control are related to each other. Materials and Methods: This prospective cohort study was conducted on 500 workers of the petrochemical industry in south of Iran, 2009. The study population was selected using simple random statistical method. They completed job demand and control questionnaire. The cardiovascular risk factors data was extracted from the workers hygiene profiles. Chi-square (χ2) test and hypothesis test (η) were used to assess the possible relationship between different quantified variables, individual demographic and cardiovascular risk factors. Results: The results of this study revealed that a significant relationship can be found between job demand control model and cardiovascular risk factors. Chi-square test result for the heart rate showed the highest (χ2 = 145.078) relationship, the corresponding results for smoking and BMI were χ2 = 85.652 and χ2 = 30.941, respectively. Subsequently, hypothesis testing results for cholesterol and hypertension was 0.469 and 0.684, respectively. Discussion: Job strain is likely to be associated with an increased risk of cardiovascular risk factors among male staff in a petrochemical company in Iran. The parameters illustrated in the Job demands and control model can act as acceptable predictors for the probability of job stress occurrence followed by showing

  13. Predictor model for seasonal variations in skid resistance. Volume 2: Comprehensive report

    Science.gov (United States)

    Henry, J. J.; Saito, K.; Blackburn, R.

    1984-04-01

    Two models, utilizing data collected in 1979 and 1980, were developed to predict variations in skid resistance due to rainfall conditions, temperature effects, and time of the year. A generalized predictor model was developed from purely statistical considerations and a mechanistic model was developed from hypothesized mechanisms. This model may be utilized to estimate the skid resistance at any time in the season from a measurement made during the same season, or to adjust skid-resistance measurement made at any time during the season to the end-of-season level.

  14. Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model.

    Science.gov (United States)

    Islam, Mohammad Mafijul; Alam, Morshed; Tariquzaman, Md; Kabir, Mohammad Alamgir; Pervin, Rokhsona; Begum, Munni; Khan, Md Mobarak Hossain

    2013-01-08

    Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance variable namely mother's education, father's education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh.

  15. A prognostic model for development of significant liver fibrosis in HIV-hepatitis C co-infection.

    Directory of Open Access Journals (Sweden)

    Nasheed Moqueet

    Full Text Available Liver fibrosis progresses rapidly in HIV-Hepatitis C virus (HCV co-infected individuals partially due to heightened inflammation. Immune markers targeting stages of fibrogenesis could aid in prognosis of fibrosis.A case-cohort study was nested in the prospective Canadian Co-infection Cohort (n = 1119. HCV RNA positive individuals without fibrosis, end-stage liver disease or chronic Hepatitis B at baseline (n = 679 were eligible. A random subcohort (n = 236 was selected from those eligible. Pro-fibrogenic markers and Interferon Lambda (IFNL rs8099917 genotype were measured from first available sample in all fibrosis cases (APRI ≥ 1.5 during follow-up and the subcohort. We used Cox proportional hazards and compared Model 1 (selected clinical predictors only to Model 2 (Model 1 plus selected markers for predicting 3-year risk of liver fibrosis using weighted Harrell's C and Net Reclassification Improvement indices.113 individuals developed significant liver fibrosis over 1300 person-years (8.63 per 100 person-years 95% CI: 7.08, 10.60. Model 1 (age, sex, current alcohol use, HIV RNA, baseline APRI, HCV genotype was nested in model 2, which also included IFNL genotype and IL-8, sICAM-1, RANTES, hsCRP, and sCD14. The C indexes (95% CI for model 1 vs. model 2 were 0.720 (0.649, 0.791 and 0.756 (0.688, 0.825, respectively. Model 2 classified risk more appropriately (overall net reclassification improvement, p<0.05.Including IFNL genotype and inflammatory markers IL-8, sICAM-1, RANTES, hs-CRP, and sCD14 enabled better prediction of the 3-year risk of significant liver fibrosis over clinical predictors alone. Whether this modest improvement in prediction justifies their additional cost requires further cost-benefit analyses.

  16. Modeling soil organic carbon with Quantile Regression: Dissecting predictors' effects on carbon stocks

    KAUST Repository

    Lombardo, Luigi

    2017-08-13

    Soil Organic Carbon (SOC) estimation is crucial to manage both natural and anthropic ecosystems and has recently been put under the magnifying glass after the Paris agreement 2016 due to its relationship with greenhouse gas. Statistical applications have dominated the SOC stock mapping at regional scale so far. However, the community has hardly ever attempted to implement Quantile Regression (QR) to spatially predict the SOC distribution. In this contribution, we test QR to estimate SOC stock (0-30 $cm$ depth) in the agricultural areas of a highly variable semi-arid region (Sicily, Italy, around 25,000 $km2$) by using topographic and remotely sensed predictors. We also compare the results with those from available SOC stock measurement. The QR models produced robust performances and allowed to recognize dominant effects among the predictors with respect to the considered quantile. This information, currently lacking, suggests that QR can discern predictor influences on SOC stock at specific sub-domains of each predictors. In this work, the predictive map generated at the median shows lower errors than those of the Joint Research Centre and International Soil Reference, and Information Centre benchmarks. The results suggest the use of QR as a comprehensive and effective method to map SOC using legacy data in agro-ecosystems. The R code scripted in this study for QR is included.

  17. Application of the transtheoretical model to identify predictors of physical activity transition in university students

    OpenAIRE

    Kang, SooJin

    2017-01-01

    Within the physical activity domain the majority of transtheoretical model research has employed a cross sectional research design. While useful for characterizing participants within the various stages of change, it fails to capture the dynamic nature of change. The purpose of the current study was to identify predictors of naturally occurring transitional shift patterns in physical activity behavior observed over six months among 202 university students. The full set of variables from the t...

  18. High Neutrophil-to-Lymphocyte Ratio is a Significant Predictor of Cardiovascular and All-Cause Mortality in Patients Undergoing Peritoneal Dialysis

    Directory of Open Access Journals (Sweden)

    Xiangxue Lu

    2018-03-01

    Full Text Available Background/Aims: Chronic inflammation is associated with increased risk of cardiovascular death in patients with end-stage renal disease (ESRD. Although elevated neutrophil-to-lymphocyte ratio (NLR, a novel inflammatory marker, has been shown to predict cardiovascular disease and all-cause mortality in the general population, limited evidence is available for its role in ESRD. Methods: We enrolled 86 patients undergoing peritoneal dialysis (PD for a 36-month follow-up to investigate the association between the NLR and arterial stiffness markers, namely, carotid-femoral pulse wave velocity (cfPWV and carotid augmentation index (AIx, and mortality in PD patients. The primary endpoints were cardiovascular mortality and all-cause mortality. Kaplan–Meier curves were used to show the cumulative incidence of cardiovascular mortality and all-cause mortality. Results: High NLR was found to be a predictor of increased cfPWV (β = 1.150; P < 0.001 and AIx (β = 3.945; P < 0.001 in patients on PD. Patients with higher NLR had lower survival during follow-up. Kaplan–Meier curves showed that the cumulative incidences of both cardiovascular mortality and all-cause mortality were significantly higher in patients with NLR ≥ 4.5 (both P < 0.01. Conclusion: Our results suggest that high NLR is independently associated with arterial stiffness and predicts cardiovascular and all-cause mortality in PD patients.

  19. Sentinel node positive melanoma patients: prediction and prognostic significance of nonsentinel node metastases and development of a survival tree model.

    Science.gov (United States)

    Wiener, Martin; Acland, Katharine M; Shaw, Helen M; Soong, Seng-Jaw; Lin, Hui-Yi; Chen, Dung-Tsa; Scolyer, Richard A; Winstanley, Julie B; Thompson, John F

    2010-08-01

    Completion lymph node dissection (CLND) following positive sentinel node biopsy (SNB) for melanoma detects additional nonsentinel node (NSN) metastases in approximately 20% of cases. This study aimed to establish whether NSN status can be predicted, to determine its effect on survival, and to develop survival tree models for the sentinel node (SN) positive population. Sydney Melanoma Unit (SMU) patients with at least 1 positive SN, meeting inclusion criteria and treated between October 1992 and June 2005, were identified from the Unit database. Survival characteristics, potential predictors of survival, and NSN status were assessed using the Kaplan-Meier method, Cox regression model, and logistic regression analyses, respectively. Classification tree analysis was performed to identify groups with distinctly different survival characteristics. A total of 323 SN-positive melanoma patients met the inclusion criteria. On multivariate analysis, age, gender, primary tumor thickness, mitotic rate, number of positive NSNs, or total number of positive nodes were statistically significant predictors of survival. NSN metastasis, found at CLND in 19% of patients, was only predicted to a statistically significant degree by ulceration. Multivariate analyses demonstrated that survival was more closely related to number of positive NSNs than total number of positive nodes. Classification tree analysis revealed 4 prognostically distinct survival groups. Patients with NSN metastases could not be reliably identified prior to CLND. Prognosis following CLND was more closely related to number of positive NSNs than total number of positive nodes. Classification tree analysis defined distinctly different survival groups more accurately than use of single-factor analysis.

  20. Urodynamic Features and Significant Predictors of Bladder Outlet Obstruction in Patients With Lower Urinary Tract Symptoms/Benign Prostatic Hyperplasia and Small Prostate Volume.

    Science.gov (United States)

    Kang, Minyong; Kim, Myong; Choo, Min Soo; Paick, Jae-Seung; Oh, Seung-June

    2016-03-01

    To investigate the clinical and urodynamic features of patients with lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH) according to their prostate size. We analyzed 2039 LUTS/BPH patients who underwent urodynamic study between October 2004 and August 2013. We divided the patients into three groups according to their prostate size: small (≤30 mL), moderately enlarged (31-80 mL), and large prostate (≥81 mL) groups. We compared the groups regarding age, International Prostatic Symptom Score, maximal flow rate (Qmax), postvoided residual (PVR), serum prostate-specific antigen, prostate volume measured by ultrasonography, and urodynamic findings. Patients with a small prostate had better urodynamic outcomes than those with larger prostates in overall population. Although the total prostate volume significantly correlated with the bladder outlet obstruction (BOO) index (r  =  0.51), BOO patients with a small prostate had similar Qmax, higher PVR, and lower voiding efficiency, compared to those with larger prostates. Moreover, urodynamic parameters indicating bladder abnormalities, including low compliance and involuntary detrusor contraction positivity, were similar among the groups in BOO patients. A higher proportion of detrusor underactivity was also observed in the small prostate group in BOO patients. Finally, when adjusting for potential confounding variables, we identified serum prostate-specific antigen levels (odds ratio, 1.34) and Qmax (odds ratio, 0.77) as significant predictors for BOO in LUTS/BPH patients with a small prostate. BOO patients with a small prostate showed higher PVR and poor voiding efficiency, as well as similar urodynamic bladder abnormalities, compared to those with moderately enlarged and large prostates. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling

    NARCIS (Netherlands)

    Naimi, B.; Skidmore, A.K.; Groen, T.A.; Hamm, N.A.S.

    2011-01-01

    Aim To investigate the impact of positional uncertainty in species occurrences on the predictions of seven commonly used species distribution models (SDMs), and explore its interaction with spatial autocorrelation in predictors. Methods A series of artificial datasets covering 155 scenarios

  2. Using digital elevation models as an environmental predictor for soil clay contents

    DEFF Research Database (Denmark)

    Greve, Mogens Humlekrog; Bou Kheir, Rania; Greve, Mette Balslev

    2012-01-01

    The objective of this study was to evaluate the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) as an environmental predictor for soil clay content (SCC). It was based on the applicability of different DEMs, i.e., SRTM with 90-m resolution and airborne Light Detection...... and Ranging (LIDAR) (in 24- and 90-m resolution), using regression-tree analysis. Ten terrain parameters were generated from these DEMs. These terrain parameters were used along other environmental variables to statistically explain SCC content in Denmark. Results indicated that the SRTM tree model (T1: 90-m...

  3. A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy.

    Science.gov (United States)

    van Leeuwen, Pim J; Hayen, Andrew; Thompson, James E; Moses, Daniel; Shnier, Ron; Böhm, Maret; Abuodha, Magdaline; Haynes, Anne-Maree; Ting, Francis; Barentsz, Jelle; Roobol, Monique; Vass, Justin; Rasiah, Krishan; Delprado, Warick; Stricker, Phillip D

    2017-12-01

    To develop and externally validate a predictive model for detection of significant prostate cancer. Development of the model was based on a prospective cohort including 393 men who underwent multiparametric magnetic resonance imaging (mpMRI) before biopsy. External validity of the model was then examined retrospectively in 198 men from a separate institution whom underwent mpMRI followed by biopsy for abnormal prostate-specific antigen (PSA) level or digital rectal examination (DRE). A model was developed with age, PSA level, DRE, prostate volume, previous biopsy, and Prostate Imaging Reporting and Data System (PIRADS) score, as predictors for significant prostate cancer (Gleason 7 with >5% grade 4, ≥20% cores positive or ≥7 mm of cancer in any core). Probability was studied via logistic regression. Discriminatory performance was quantified by concordance statistics and internally validated with bootstrap resampling. In all, 393 men had complete data and 149 (37.9%) had significant prostate cancer. While the variable model had good accuracy in predicting significant prostate cancer, area under the curve (AUC) of 0.80, the advanced model (incorporating mpMRI) had a significantly higher AUC of 0.88 (P prostate cancer. Individualised risk assessment of significant prostate cancer using a predictive model that incorporates mpMRI PIRADS score and clinical data allows a considerable reduction in unnecessary biopsies and reduction of the risk of over-detection of insignificant prostate cancer at the cost of a very small increase in the number of significant cancers missed. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

  4. Indexed effective orifice area is a significant predictor of higher mid- and long-term mortality rates following aortic valve replacement in patients with prosthesis-patient mismatch.

    Science.gov (United States)

    Chen, Jian; Lin, Yiyun; Kang, Bo; Wang, Zhinong

    2014-02-01

    Prosthesis-patient mismatch (PPM) is defined as a too-small effective orifice area (EOA) of an inserted prosthetic relative to body size, resulting in an abnormally high postoperative gradient. It is unclear, however, whether residual stenosis after aortic valve replacement (AVR) has a negative impact on mid- and long-term survivals. We searched electronic databases, including PubMed, Embase, Medline and the Cochrane controlled trials register, through October 2012, to identify published full-text English studies on the association between PPM and mortality rates. A significant PPM was defined as an indexed EOA (iEOA)<0.85 cm2/m2, and severe PPM as an iEOA<0.65 cm2/m2. Two reviewers independently assessed the studies for inclusion and extracted data. Fourteen observational studies, involving 14 874 patients, met our final inclusion criteria. Meta-analysis demonstrated that PPM significantly increased mid-term (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.19-1.69) and long-term (OR 1.52, 95% CI 1.26-1.84) all-cause mortalities. Subgroup analysis showed that PPM was associated with higher mid- and long-term mortality rates only in younger and predominantly female populations. Risk-adjusted sensitivity analysis showed that severe PPM was associated with reduced survival (adjusted hazard ratio [HR] 1.50, 95% CI 1.24-1.80), whereas moderate PPM was not (adjusted HR 0.96, 95% CI 0.86-1.07). Regardless of severity, however, PPM had a negative effect on survival in patients with impaired ejection fraction (adjusted HR 1.26, 95% CI 1.09-1.47). PPM (iEOA<0.85 cm2/m2) after AVR tended to be associated with increased long-term all-cause mortality in younger patients, females and patients with preoperative left ventricular dysfunction. Severe PPM (iEOA<0.65 cm2/m2) was a significant predictor of reduced long-term survival in all populations undergoing AVR.

  5. Simple Decision-Analytic Functions of the AUC for Ruling Out a Risk Prediction Model and an Added Predictor.

    Science.gov (United States)

    Baker, Stuart G

    2018-02-01

    When using risk prediction models, an important consideration is weighing performance against the cost (monetary and harms) of ascertaining predictors. The minimum test tradeoff (MTT) for ruling out a model is the minimum number of all-predictor ascertainments per correct prediction to yield a positive overall expected utility. The MTT for ruling out an added predictor is the minimum number of added-predictor ascertainments per correct prediction to yield a positive overall expected utility. An approximation to the MTT for ruling out a model is 1/[P (H(AUC model )], where H(AUC) = AUC - {½ (1-AUC)} ½ , AUC is the area under the receiver operating characteristic (ROC) curve, and P is the probability of the predicted event in the target population. An approximation to the MTT for ruling out an added predictor is 1 /[P {(H(AUC Model:2 ) - H(AUC Model:1 )], where Model 2 includes an added predictor relative to Model 1. The latter approximation requires the Tangent Condition that the true positive rate at the point on the ROC curve with a slope of 1 is larger for Model 2 than Model 1. These approximations are suitable for back-of-the-envelope calculations. For example, in a study predicting the risk of invasive breast cancer, Model 2 adds to the predictors in Model 1 a set of 7 single nucleotide polymorphisms (SNPs). Based on the AUCs and the Tangent Condition, an MTT of 7200 was computed, which indicates that 7200 sets of SNPs are needed for every correct prediction of breast cancer to yield a positive overall expected utility. If ascertaining the SNPs costs $500, this MTT suggests that SNP ascertainment is not likely worthwhile for this risk prediction.

  6. Modeling Daily Rainfall Conditional on Atmospheric Predictors: An application to Western Greece

    Science.gov (United States)

    Langousis, Andreas; Kaleris, Vassilios

    2013-04-01

    Due to its intermittent and highly variable character, daily precipitation is the least well reproduced hydrologic variable by both General Circulation Models (GCMs) and Limited Area Models (LAMs). To that extent, several statistical procedures (usually referred to as downscaling schemes) have been suggested to generate synthetic rainfall time series conditional on predictor variables that are descriptive of the atmospheric circulation at the mesoscale. In addition to be more accurately simulated by GCMs and LAMs, large-scale atmospheric predictors are important indicators of the local weather. Currently used downscaling methods simulate rainfall series using either stable statistical relationships (usually referred to as transfer functions) between certain characteristics of the rainfall process and mesoscale atmospheric predictor variables, or simple stochastic schemes (e.g. properly transformed autoregressive models) with parameters that depend on the large-scale atmospheric conditions. The latter are determined by classifying large-scale circulation patterns into broad categories of weather states, using empirical or theoretically based classification schemes, and modeled by resampling from those categories; a process usually referred to as weather generation. In this work we propose a statistical framework to generate synthetic rainfall timeseries at a daily level, conditional on large scale atmospheric predictors. The latter include the mean sea level pressure (MSLP), the magnitude and direction of upper level geostrophic winds, and the 500 hPa geopotential height, relative vorticity and divergence. The suggested framework operates in continuous time, avoiding the use of transfer functions, and weather classification schemes. The suggested downscaling approach is validated using atmospheric data from the ERA-Interim archive (see http://www.ecmwf.int/research/era/do/get/index), and daily rainfall data from Western Greece, for the 14-year period from 01 October

  7. Gender and single nucleotide polymorphisms in MTHFR, BHMT, SPTLC1, CRBP2R, and SCARB1 are significant predictors of plasma homocysteine normalized by RBC folate in healthy adults.

    Science.gov (United States)

    Using linear regression models, we studied the main and two-way interaction effects of the predictor variables gender, age, BMI, and 64 folate/vitamin B-12/homocysteine/lipid/cholesterol-related single nucleotide polymorphisms (SNP) on log-transformed plasma homocysteine normalized by red blood cell...

  8. Modelo estructural predictor de la salud mental y física en mujeres A structural equation model for predictors of mental and physical health in women

    Directory of Open Access Journals (Sweden)

    Mónica Teresa González Ramírez

    2008-02-01

    Full Text Available OBJETIVO: Valorar la capacidad predictora del estrés, el apoyo social y la autoestima respecto de la salud mental y física del individuo mediante ecuaciones estructurales, integrando modelos parciales estimados anteriormente, lo que permite simplificar los efectos entre las variables. MÉTODOS: La muestra estudiada abarcó 283 mujeres con hijos. Todas las participantes residían en el municipio de General Escobedo, estado de Nuevo León, México. Las encuestas se realizaron en el segundo semestre de 2003, en los domicilios, utilizando cuestionarios de autoevaluación para valorar cada una de las variables incluidas en el modelo. Cada participante respondió a los cuestionarios en una sola sesión. Los resultados se analizaron con el programa AMOS 5.0, empleando el método de máxima verosimilitud, comúnmente utilizado en los modelos de ecuaciones estructurales. RESULTADOS: Los resultados obtenidos indican un ajuste aceptable en el modelo propuesto (ji2/gl = 3,03, GFI (índice de bondad del ajuste = 0,894, AGFI (índice de bondad del ajuste corregido = 0,848, RMSEA (error de aproximación cuadrático medio = 0,08, IFI (índice de ajuste incremental = 0,910. La varianza explicada es del 31,9% respecto del estrés, del 27,4% respecto de la salud física y del 72,1% respecto de la salud mental. CONCLUSIONES: El apoyo social y la autoestima son predictores del estrés; la edad y el estrés, predictores de la salud física; y el estrés, la autoestima y la salud física, predictores de la salud mental.OBJECTIVE: To measure the extent to which stress, social support, and self-esteem are predictors of an individual's mental and physical health. Structural equations were integrated with previously-estimated partial models, which simplify the relationships among variables. METHODS: The study sample included 283 women with children. All of the participants resided in the municipality of General Escobedo, state of Nuevo León, Mexico. The surveys were

  9. Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes.

    Science.gov (United States)

    Mikulich-Gilbertson, Susan K; Wagner, Brandie D; Grunwald, Gary K; Riggs, Paula D; Zerbe, Gary O

    2018-01-01

    Medical research is often designed to investigate changes in a collection of response variables that are measured repeatedly on the same subjects. The multivariate generalized linear mixed model (MGLMM) can be used to evaluate random coefficient associations (e.g. simple correlations, partial regression coefficients) among outcomes that may be non-normal and differently distributed by specifying a multivariate normal distribution for their random effects and then evaluating the latent relationship between them. Empirical Bayes predictors are readily available for each subject from any mixed model and are observable and hence, plotable. Here, we evaluate whether second-stage association analyses of empirical Bayes predictors from a MGLMM, provide a good approximation and visual representation of these latent association analyses using medical examples and simulations. Additionally, we compare these results with association analyses of empirical Bayes predictors generated from separate mixed models for each outcome, a procedure that could circumvent computational problems that arise when the dimension of the joint covariance matrix of random effects is large and prohibits estimation of latent associations. As has been shown in other analytic contexts, the p-values for all second-stage coefficients that were determined by naively assuming normality of empirical Bayes predictors provide a good approximation to p-values determined via permutation analysis. Analyzing outcomes that are interrelated with separate models in the first stage and then associating the resulting empirical Bayes predictors in a second stage results in different mean and covariance parameter estimates from the maximum likelihood estimates generated by a MGLMM. The potential for erroneous inference from using results from these separate models increases as the magnitude of the association among the outcomes increases. Thus if computable, scatterplots of the conditionally independent empirical Bayes

  10. Predictors of intention to smoke among junior high school students in Shanghai, China: an empirical test of the information-motivation-behavioral skills (IMB) model.

    Science.gov (United States)

    Zhu, Chendi; Cai, Yong; Ma, Jin; Li, Na; Zhu, Jingfen; He, Yaping; Redmon, Pamela; Qiao, Yun

    2013-01-01

    Adolescent smoking is a worldwide problem that is particularly severe in low- and middle-income countries. Many endogenous and environmental factors affect the intention to smoke, so a comprehensive model is needed to understand the significance and relationship of predictors. The study aimed to test the associations among information-motivation-behavioral skills (IMB) model constructs as predictors of intention to smoke in junior high school students in Shanghai, China. We conducted a cross-sectional study of 16,500 junior high school students in Shanghai, China. Data on tobacco-related information, motivation, behavioral skills, and behaviors were collected from students. Structural equation model (SEM) was used to assess the IMB model. The mean age of participants was 13.8 years old (standard deviation = 1.02; range 11-17). The experimental smoking rate among junior high school students was 6.6% and 8.7% of the participants expected that they would be smokers in 5 years. The IMB model provided acceptable fit to the data (comparative fit index = 0.984, root mean square error of approximation = 0.04). Intention to smoke was predicted by behavioral skills (β = 0.670, P motivation (β = 0.095, Pschool students. The IMB model provides a good understanding of the predictors of intention to smoke and it suggests future interventions among junior high school students should focus on improving motivation and behavioral skills.

  11. Clinical Predictors of Regression of Choroidal Melanomas after Brachytherapy: A Growth Curve Model.

    Science.gov (United States)

    Rashid, Mamunur; Heikkonen, Jorma; Singh, Arun D; Kivelä, Tero T

    2018-02-27

    To build multivariate models to assess correctly and efficiently the contribution of tumor characteristics on the rate of regression of choroidal melanomas after brachytherapy in a way that adjusts for confounding and takes into account variation in tumor regression patterns. Modeling of longitudinal observational data. Ultrasound images from 330 of 388 consecutive choroidal melanomas (87%) irradiated from 2000 through 2008 at the Helsinki University Hospital, Helsinki, Finland, a national referral center. Images were obtained with a 10-MHz B-scan during 3 years of follow-up. Change in tumor thickness and cross-sectional area were modeled using a polynomial growth-curve function in a nested mixed linear regression model considering regression pattern and tumor levels. Initial tumor dimensions, tumor-node-metastasis (TNM) stage, shape, ciliary body involvement, pigmentation, isotope, plaque size, detached muscles, and radiation parameters were considered as covariates. Covariates that independently predict tumor regression. Initial tumor thickness, largest basal diameter, ciliary body involvement, TNM stage, tumor shape group, break in Bruch's membrane, having muscles detached, and radiation dose to tumor base predicted faster regression, whether considering all tumors or those that regressed in a pattern compatible with exponential decay. Dark brown pigmentation was associated with slower regression. In multivariate modeling, initial tumor thickness remained the predominant and robust predictor of tumor regression (P future analyses efficiently without matching. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

  12. Research Pearls: The Significance of Statistics and Perils of Pooling. Part 2: Predictive Modeling.

    Science.gov (United States)

    Hohmann, Erik; Wetzler, Merrick J; D'Agostino, Ralph B

    2017-07-01

    The focus of predictive modeling or predictive analytics is to use statistical techniques to predict outcomes and/or the results of an intervention or observation for patients that are conditional on a specific set of measurements taken on the patients prior to the outcomes occurring. Statistical methods to estimate these models include using such techniques as Bayesian methods; data mining methods, such as machine learning; and classical statistical models of regression such as logistic (for binary outcomes), linear (for continuous outcomes), and survival (Cox proportional hazards) for time-to-event outcomes. A Bayesian approach incorporates a prior estimate that the outcome of interest is true, which is made prior to data collection, and then this prior probability is updated to reflect the information provided by the data. In principle, data mining uses specific algorithms to identify patterns in data sets and allows a researcher to make predictions about outcomes. Regression models describe the relations between 2 or more variables where the primary difference among methods concerns the form of the outcome variable, whether it is measured as a binary variable (i.e., success/failure), continuous measure (i.e., pain score at 6 months postop), or time to event (i.e., time to surgical revision). The outcome variable is the variable of interest, and the predictor variable(s) are used to predict outcomes. The predictor variable is also referred to as the independent variable and is assumed to be something the researcher can modify in order to see its impact on the outcome (i.e., using one of several possible surgical approaches). Survival analysis investigates the time until an event occurs. This can be an event such as failure of a medical device or death. It allows the inclusion of censored data, meaning that not all patients need to have the event (i.e., die) prior to the study's completion. Copyright © 2017 Arthroscopy Association of North America. Published by

  13. How Often Is the Misfit of Item Response Theory Models Practically Significant?

    Science.gov (United States)

    Sinharay, Sandip; Haberman, Shelby J.

    2014-01-01

    Standard 3.9 of the Standards for Educational and Psychological Testing ([, 1999]) demands evidence of model fit when item response theory (IRT) models are employed to data from tests. Hambleton and Han ([Hambleton, R. K., 2005]) and Sinharay ([Sinharay, S., 2005]) recommended the assessment of practical significance of misfit of IRT models, but…

  14. Predictors of Oral Health Behaviors in Female Students: An Application of the Health Belief Model.

    Science.gov (United States)

    Rahmati-Najarkolaei, Fatemeh; Rahnama, Parvin; Gholami Fesharaki, Mohammad; Behnood, Vahid

    2016-11-01

    Oral and dental health diseases can affect the general health of students. The aim of this study was to identify the predictors of oral and dental health behavior using the health belief model (HBM) in female students in Teheran, Iran. This was a cross-sectional study framed by the HBM, including 400 female students living in district 5 of Tehran, Iran. The sampling technique used in this study was multi-stage stratified random sampling. The data on the HBM constructs (perceived severity, perceived susceptibility, perceived benefits, perceived barriers, cues to action, and self-efficacy) and demographic characteristics were collected using a self-administered questionnaire. Descriptive statistics, bivariate correlations, and linear regression were performed to analyze the data, using the SPSS software, version 18. The results showed that there were relationships between the knowledge, perceived barriers, cues to action, and mother's education with oral health behaviors. A multivariate hierarchical regression analysis was conducted with the barrier entered at step one, knowledge at step two, and cues to action at step three. Finally, the three variables accounted for 17% of the total variance in the oral and dental health behavior. The current study provided evidence for the utility of the belief-based model in the prediction of oral health behaviors. It could be suggested that oral health behavior can be promoted by reducing the perceived barriers and enhancing the students' knowledge of oral and dental hygiene.

  15. The Significance of the Bystander Effect: Modeling, Experiments, and More Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Brenner, David J.

    2009-07-22

    Non-targeted (bystander) effects of ionizing radiation are caused by intercellular signaling; they include production of DNA damage and alterations in cell fate (i.e. apoptosis, differentiation, senescence or proliferation). Biophysical models capable of quantifying these effects may improve cancer risk estimation at radiation doses below the epidemiological detection threshold. Understanding the spatial patterns of bystander responses is important, because it provides estimates of how many bystander cells are affected per irradiated cell. In a first approach to modeling of bystander spatial effects in a three-dimensional artificial tissue, we assumed the following: (1) The bystander phenomenon results from signaling molecules (S) that rapidly propagate from irradiated cells and decrease in concentration (exponentially in the case of planar symmetry) as distance increases. (2) These signals can convert cells to a long-lived epigenetically activated state, e.g. a state of oxidative stress; cells in this state are more prone to DNA damage and behavior alterations than normal and therefore exhibit an increased response (R) for many end points (e.g. apoptosis, differentiation, micronucleation). These assumptions were implemented by a mathematical formalism and computational algorithms. The model adequately described data on bystander responses in the 3D system using a small number of adjustable parameters. Mathematical models of radiation carcinogenesis are important for understanding mechanisms and for interpreting or extrapolating risk. There are two classes of such models: (1) long-term formalisms that track pre-malignant cell numbers throughout an entire lifetime but treat initial radiation dose-response simplistically and (2) short-term formalisms that provide a detailed initial dose-response even for complicated radiation protocols, but address its modulation during the subsequent cancer latency period only indirectly. We argue that integrating short- and long

  16. Significant uncertainty in global scale hydrological modeling from precipitation data erros

    NARCIS (Netherlands)

    Sperna Weiland, F.; Vrugt, J.A.; Beek, van P.H.; Weerts, A.H.; Bierkens, M.F.P.

    2015-01-01

    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

  17. Significant uncertainty in global scale hydrological modeling from precipitation data errors

    NARCIS (Netherlands)

    Weiland, Frederiek C. Sperna; Vrugt, Jasper A.; van Beek, Rens (L. ) P. H.|info:eu-repo/dai/nl/14749799X; Weerts, Albrecht H.; Bierkens, Marc F. P.|info:eu-repo/dai/nl/125022794

    2015-01-01

    In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we

  18. Mapping the Most Significant Computer Hacking Events to a Temporal Computer Attack Model

    OpenAIRE

    Heerden , Renier ,; Pieterse , Heloise; Irwin , Barry

    2012-01-01

    Part 4: Section 3: ICT for Peace and War; International audience; This paper presents eight of the most significant computer hacking events (also known as computer attacks). These events were selected because of their unique impact, methodology, or other properties. A temporal computer attack model is presented that can be used to model computer based attacks. This model consists of the following stages: Target Identification, Reconnaissance, Attack, and Post-Attack Reconnaissance stages. The...

  19. Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling

    DEFF Research Database (Denmark)

    Giacobello, Daniele; Christensen, Mads Græsbøll; Jensen, Tobias Lindstrøm

    2014-01-01

    saturations when this is used to synthesize speech. In this paper, we introduce two new methods to obtain intrinsically stable predictors with the 1-norm minimization. The first method is based on constraining the roots of the predictor to lie within the unit circle by reducing the numerical range...... of the shift operator associated with the particular prediction problem considered. The second method uses the alternative Cauchy bound to impose a convex constraint on the predictor in the 1-norm error minimization. These methods are compared with two existing methods: the Burg method, based on the 1-norm...

  20. Comparison of different predictors of exposure for modeling impacts of metal mixtures on macroinvertebrates in stream microcosms.

    Science.gov (United States)

    Iwasaki, Yuichi; Cadmus, Pete; Clements, William H

    2013-05-15

    Knowledge about which predictors of metal exposure are best to model the impacts of metal mixtures on river macroinvertebrates remains uncertain. A new predictor based on the amount of metals binding to humic acid, which is assumed to be a proxy of non-specific biotic ligand sites, has been proposed. The amount can be calculated using Windermere Humic Aqueous Model (WHAM), which we will refer to as the WHAM-HA approach. Here, we tested the hypothesis that the predictor based on the WHAM-HA approach provided a better estimate of metal effects observed in microcosm experiments than three other measures: total metal concentrations, free metal ion concentrations, and the cumulative criterion unit (CCU) which is a measure of the ratios of measured metal concentrations relative to the U.S. Environmental Protection Agency hardness adjusted criterion values. For this evaluation, we used nine macroinvertebrate metrics of abundance and richness obtained from microcosm experiments conducted with metal mixtures (Zn alone, Zn+Cd, and Zn+Cd+Cu). For each of the four predictors, we performed multiple linear regression with variables corresponding to the three metal concentrations or CCU and selected the best model based on Akaike's information criterion corrected for small sample sizes. For all of the macroinvertebrate metrics affected by metals, the WHAM-HA approach was selected as the best among the four predictors, followed by the model with total metal concentration. In most of best models, Zn and Cu or Cu alone was responsible for reductions in invertebrate metrics, even though the highest concentrations of Cd exceeded 100 times the hardness-adjusted criterion value. Either of the models with free metal ion concentration and CCU was the third ranked model. Our results suggest that the estimated amount of metals binding to humic acid is a better predictor for the effects on macroinvertebrate richness and abundance observed in microcosm experiments than total or free ion

  1. Predictors of intention to smoke among junior high school students in Shanghai, China: an empirical test of the information-motivation-behavioral skills (IMB model.

    Directory of Open Access Journals (Sweden)

    Chendi Zhu

    Full Text Available Adolescent smoking is a worldwide problem that is particularly severe in low- and middle-income countries. Many endogenous and environmental factors affect the intention to smoke, so a comprehensive model is needed to understand the significance and relationship of predictors. The study aimed to test the associations among information-motivation-behavioral skills (IMB model constructs as predictors of intention to smoke in junior high school students in Shanghai, China.We conducted a cross-sectional study of 16,500 junior high school students in Shanghai, China. Data on tobacco-related information, motivation, behavioral skills, and behaviors were collected from students. Structural equation model (SEM was used to assess the IMB model.The mean age of participants was 13.8 years old (standard deviation = 1.02; range 11-17. The experimental smoking rate among junior high school students was 6.6% and 8.7% of the participants expected that they would be smokers in 5 years. The IMB model provided acceptable fit to the data (comparative fit index = 0.984, root mean square error of approximation = 0.04. Intention to smoke was predicted by behavioral skills (β = 0.670, P < 0.001 and motivation (β = 0.095, P<0.001 among junior high school students.The IMB model provides a good understanding of the predictors of intention to smoke and it suggests future interventions among junior high school students should focus on improving motivation and behavioral skills.

  2. Predictors of Health-Promoting Behaviors in Coronary Artery Bypass Surgery Patients: An Application of Pender’s Health Promotion Model

    Science.gov (United States)

    Mohsenipoua, Hossein; Majlessi, Fereshteh; Shojaeizadeh, Davood; Rahimiforooshani, Abbas; Ghafari, Rahman; Habibi, Valiollah

    2016-01-01

    Background Advances in coronary artery surgery have reduced patient morbidity and mortality. Nevertheless, patients still have to face physical, psychological, and social problems after discharge from hospital. Objectives The objective of this study was to determine the efficacy of Pender’s health promotion model in predicting cardiac surgery patients’ lifestyles in Iran. Methods This cross-sectional study comprised 220 patients who had undergone coronary artery bypass graft (CABG) surgery in Mazandaran province (Iran) in 2015. The subjects were selected using a simple random sampling method. The data were collected via (1) the health-promoting lifestyle profile II (HPLP II) and (2) a self-designed questionnaire that included two main sections: demographic characteristics and questions based on the health-promoting model constructs. Results Spiritual growth (28.77 ± 5.03) and physical activity (15.79 ± 5.08) had the highest and lowest scores in the HPLP II dimensions, respectively. All the health promotion model variables were significant predictors of health-promoting behaviors and explained 69% of the variance in health-promoting behaviors. Three significant predictors were estimated using regression coefficients: behavioral feelings (β = 0.390, P health-promoting model-based self-care behaviors can help identify and predict cardiac surgery patients’ lifestyles in Iran. This pattern can be used as a framework for discharge planning and the implementation of educational interventions to improve the lifestyles of CABG patients. PMID:28144467

  3. Significance of predictive models/risk calculators for HBV-related hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    DONG Jing

    2015-06-01

    Full Text Available Hepatitis B virus (HBV-related hepatocellular carcinoma (HCC is a major public health problem in Southeast Asia. In recent years, researchers from Hong Kong and Taiwan have reported predictive models or risk calculators for HBV-associated HCC by studying its natural history, which, to some extent, predicts the possibility of HCC development. Generally, risk factors of each model involve age, sex, HBV DNA level, and liver cirrhosis. This article discusses the evolution and clinical significance of currently used predictive models for HBV-associated HCC and assesses the advantages and limits of risk calculators. Updated REACH-B model and LSM-HCC model show better negative predictive values and have better performance in predicting the outcomes of patients with chronic hepatitis B (CHB. These models can be applied to stratified screening of HCC and, meanwhile, become an assessment tool for the management of CHB patients.

  4. Significance of categorization and the modeling of age related factors for radiation protection

    International Nuclear Information System (INIS)

    Matsuoka, Osamu

    1987-01-01

    It is proposed that the categorization and modelling are necessary with regard to age related factors of radionuclide metabolism for the radiation protection of the public. In order to utilize the age related information as a model for life time risk estimate of public, it is necessary to generalize and simplify it according to the categorized model patterns. Since the patterns of age related changes in various parameters of radionuclide metabolism seem to be rather simple, it is possible to categorize them into eleven types of model patterns. Among these models, five are selected as positively significant models to be considered. Examples are shown as to the fitting of representative parameters of both physiological and metabolic parameter of radionuclides into the proposed model. The range of deviation from adult standard value is also analyzed for each model. The fitting of each parameter to categorized models, and its comparative consideration provide the effective information as to the physiological basis of radionuclide metabolism. Discussions are made on the problems encountered in the application of available age related information to radiation protection of the public, i.e. distribution of categorized parameter, period of life covered, range of deviation from adult value, implication to other dosimetric and pathological models and to the final estimation. 5 refs.; 3 figs.; 4 tabs

  5. Clinical and angiographic predictors of haemodynamically significant angiographic lesions: development and validation of a risk score to predict positive fractional flow reserve.

    Science.gov (United States)

    Sareen, Nishtha; Baber, Usman; Kezbor, Safwan; Sayseng, Sonny; Aquino, Melissa; Mehran, Roxana; Sweeny, Joseph; Barman, Nitin; Kini, Annapoorna; Sharma, Samin K

    2017-04-07

    Coronary revascularisation based upon physiological evaluation of lesions improves clinical outcomes. Angiographic or visual stenosis assessment alone is insufficient in predicting haemodynamic stenosis severity by fractional flow reserve (FFR) and therefore cannot be used to guide revascularisation, particularly in the lesion subset system formulated. Of 1,023 consecutive lesions (883 patients), 314 (31%) were haemodynamically significant. Characteristics associated with FFR ≤0.8 include male gender, higher SYNTAX score, lesions ≥20 mm, stenosis >50%, bifurcation, calcification, absence of tortuosity and smaller reference diameter. A user-friendly integer score was developed with the five variables demonstrating the strongest association. On prospective validation (in 279 distinct lesions), the increasing value of the score correlated well with increasing haemodynamic significance (C-statistic 0.85). We identified several clinical and angiographic characteristics and formulated a scoring system to guide the approach to intermediate lesions. This may translate into cost savings. Larger studies with prospective validation are required to confirm our results.

  6. ARMA modeling of stochastic processes in nuclear reactor with significant detection noise

    International Nuclear Information System (INIS)

    Zavaljevski, N.

    1992-01-01

    The theoretical basis of ARMA modelling of stochastic processes in nuclear reactor was presented in a previous paper, neglecting observational noise. The identification of real reactor data indicated that in some experiments the detection noise is significant. Thus a more rigorous theoretical modelling of stochastic processes in nuclear reactor is performed. Starting from the fundamental stochastic differential equations of the Langevin type for the interaction of the detector with neutron field, a new theoretical ARMA model is developed. preliminary identification results confirm the theoretical expectations. (author)

  7. The Job Demands-Resources model as predictor of work identity and work engagement: A comparative analysis

    OpenAIRE

    Roslyn De Braine; Gert Roodt

    2011-01-01

    Orientation: Research shows that engaged employees experience high levels of energy and strong identification with their work, hence this study’s focus on work identity and dedication. Research purpose: This study explored possible differences in the Job Demands-Resources model (JD-R) as predictor of overall work engagement, dedication only and work-based identity, through comparative predictive analyses. Motivation for the study: This study may shed light on the dedication component o...

  8. Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

    Science.gov (United States)

    Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

    2014-01-01

    This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

  9. Pretreatment direct bilirubin and total cholesterol are significant predictors of overall survival in advanced non-small-cell lung cancer patients with EGFR mutations.

    Science.gov (United States)

    Zhang, Yanwei; Xu, Jianlin; Lou, Yuqing; Hu, Song; Yu, Keke; Li, Rong; Zhang, Xueyan; Jin, Bo; Han, Baohui

    2017-04-01

    This study was designed to examine the prediction of pretreatment circulating bilirubin and cholesterol for overall survival in 459 advanced non-small-cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations. Circulating total bilirubin, direct bilirubin (DB), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels were measured at baseline. The mean age (standard deviation) of all study patients was 58.7 (10.5) years, and 42.9% of them was males. Ever smokers accounted for 27.0% and lung adenocarcinoma for 90.4%. The median follow-up time and survival time were 29.5 and 34.9 months, respectively. Patients with higher DB had a 1.68-fold increased risk of death compared with patients with lower DB (hazard ratio [HR] = 1.68, 95% confidence interval [CI]: 1.22-2.30, p = 0.001), while patients with higher TC were at a 63% reduced risk of death compared with patients with lower TC (HR = 0.37, 95% CI: 0.20-0.67, p = 0.001). As for HDL-C, patients with higher levels had the risk of death reduced by 46% (HR = 0.54, 95% CI: 0.29-1.00, p = 0.049) compared with patients with lower levels. After the Bonferroni correction, only DB and TC were significantly associated with NSCLC survival. Our findings demonstrate for the first time that pretreatment DB was identified as a significant risk factor, yet TC as a protective factor, for overall survival in NSCLC patients with EGFR mutations. © 2016 UICC.

  10. The number of positive nodes and the ratio of positive to excised nodes are significant predictors of survival in women with micrometastatic node-positive breast cancer.

    Science.gov (United States)

    Truong, Pauline T; Vinh-Hung, Vincent; Cserni, Gabor; Woodward, Wendy A; Tai, Patricia; Vlastos, Georges

    2008-08-01

    To evaluate the prognostic impact of the number of positive nodes and the lymph node ratio (LNR) of positive to excised nodes on survival in women diagnosed with nodal micrometastatic breast cancer before the era of widespread sentinel lymph node biopsy. Subjects were 62,551 women identified by the Surveillance Epidemiology and End Results database, diagnosed with pT1-2pN0-1 breast cancer between 1988 and 1997. Kaplan-Meier breast cancer-specific survival (BCSS) and overall survival (OS) were compared between three cohorts: node-negative (pN0, n=57,980) nodal micrometastasis all 2mm but or= 4) and the LNR (0.25). Median follow-up was 7.3 yr. Ten-year BCSS and OS in pNmic breast cancer were significantly lower compared to pN0 disease (BCSS 82.3% versus 91.9%, p<0.001 and OS 68.1% versus 75.7%, p<0.001). BCSS and OS with pNmic disease progressively declined with increasing number of positive nodes and increasing LNR. OS with pNmic was similar to pNmac disease when matched by the number of positive nodes and by the LNR. Both pN-based and LNR-based classifications were significantly prognostic of BCSS and OS on Cox regression multivariate analysis. Nodal micrometastasis is associated with poorer survival compared to pN0 disease. Mortality hazards with nodal micrometastasis increased with increasing number of positive nodes and increasing LNR. The number of positive nodes and the LNR should be considered in risk estimates for patients with nodal micrometastatic breast cancer.

  11. Predictors of poor outcomes after significant chest trauma in multiply injured patients: a retrospective analysis from the German Trauma Registry (Trauma Register DGU®)

    Science.gov (United States)

    2014-01-01

    Background Blunt thoracic trauma is one of the critical injury mechanisms in multiply injured trauma victims. Although these patients present a plethora of potential structural damages to vital organs, it remains debated which injuries actually influence outcome and thereby should be addressed initially. Hence, the aim of this study was to identify the influence of critical structural damages on mortality. Methods All patients in the database of the TraumaRegister DGU® (TR-DGU) from 2002–2011 with AIS Chest ≥ 2, blunt trauma, age of 16 or older and an ISS ≥ 16 were analyzed. Outcome parameters were in-hospital mortality as well as ventilation time in patients surviving the initial 14 days after trauma. Results 22613 Patients were included (mean ISS 30.5 ± 12.6; 74.7% male; Mean Age 46.1 ± 197 years; mortality 17.5%; mean duration of ventilation 7.3 ± 11.5; mean ICU stay 11.7 ± 14.1 days). Only a limited number of specific injuries had a significant impact on survival. Major thoracic vessel injuries (AIS ≥5), bilateral lung contusion, bilateral flail chest, structural heart injury (AIS ≥3) significantly influence mortality in study patients. Several extrathoracic factors (age, blood transfusion, systolic blood pressure and extrathoracic severe injuries) were also predictive of increased mortality. Most injuries of the thoracic wall had no or only a moderate effect on the duration of ventilation. Injuries to the lung (laceration, contusion or pneumothoraces) had a moderate prolonging effect. Cardiac injuries and severe injuries to the thoracic vessels induced a substantially prolonged ventilation interval. Conclusions We demonstrate quantitatively the influence of specific structural damages of the chest on critical outcome parameters. While most injuries of the chest wall have no or only limited impact in the study collective, injuries to the lung overall show adverse outcome. Injuries to the heart or thoracic vessels have a

  12. Clinical Significance of Myeloid-Related Protein 8/14 as a Predictor for Biological Treatment and Disease Activity in Rheumatoid Arthritis.

    Science.gov (United States)

    Yunchun, Li; Yue, Wang; Jun, Fang Zhong; Qizhu, Su; Liumei, Ding

    2018-01-01

    To investigate the serum level of Myeloid-Related Protein 8/14 complex (MRP8/14) and to predict and monitor the response to biologic treatment in rheumatoid arthritis (RA) patients. Each patient underwent clinical examination and blood sampling for assessment of serum high-sensitivity C-reactive protein (hs-CRP) levels, erythrocyte sedimentation rate (ESR), rheumatoid factors (RF), anti-cyclic citrullinated protein antibodies (anti-CCP), and serum concentrations of MRP8/14 protein complexes (myeloid-related proteins, MRP8/14) were measured at baseline, and weeks 4 and 12 (after initiation of treatment). Serum MRP8/14 protein complex levels correlated with DAS28 and anti-CCP antibody. MRP8/14 protein complex levels decreased significantly after 12 weeks treatment with biological therapy: mono-rhTNFR-Fc active group. rhTNFR-Fc plus methotrexate (MTX) decreased MRP8/14 protein complex levels from 11839±1849 ng/ml to 5423±1130 ng/ml ( p <0.01) a reduction of 54.2% compared with 32.9% in the rhTNFR-Fc group. MRP8/14 protein complex levels were increased in active stage RA patients. MRP8/14 levels were decreased with rhTNFR-Fc treatment, suggesting serum concentrations of MRP8/14 protein complex might be a promising biomarker to predict responses to biological therapy in active RA patients at baseline and could be used to monitor responses to treatment across different mechanisms of action. © 2018 by the Association of Clinical Scientists, Inc.

  13. CAT correlates positively with respiratory rate and is a significant predictor of the impact of COPD on daily life of patients: a cross sectional study.

    Science.gov (United States)

    Becker, Cíntia; Schäfer, Janaína; Carvalho, Lisiane L; Vitiello, Isabel P; da Silva, Andréa Lg

    2014-01-01

    The pathophysiological changes of COPD tend to worsen with progression, triggering limiting symptoms and implying the decrease in the activities of daily living and quality of life. The COPD Assessment Test (CAT) is a questionnaire designed to measure the impact of COPD on the health status. The aim of this study was to evaluate the impact of the disease through the CAT in a Brazilian sample of COPD patients and to correlate symptoms at rest with the CAT score in these patients. Study of cases with COPD patients was conducted by pulmonary rehabilitation program (RP). Respiratory rate (RR) and symptoms (dyspnea by Modified Borg Scale Dyspnea Index; symptoms by CAT) were analyzed at the beginning of the RP. The study analyzed 28 COPD patients, both genders, age 65.93 ± 7.84 years and many patients ranging from severe and very severe disease. The majority of patients were rated by CAT with low impact-disease (n = 13/46, 4%);medium (n = 11/39, 3%) and the high impact-diseases were observed in a few subjects (n = 4/14.3%). The difference between all CAT scores was significant, p = 0.000. There was a positive correlation between respiratory rate and CAT scores impact-level (r = 0.585, p = 0.001). The results obtained by the Borg Scale revealed a high presence of symptoms in these COPD patients but no association with CAT. The CAT is a sensitive tool to assess the current health status of COPD patients, and in Southern Brazil it is positively correlated with respiratory rate.

  14. The identity impairment model: a longitudinal study of self-schemas as predictors of disordered eating behaviors.

    Science.gov (United States)

    Stein, Karen Farchaus; Corte, Colleen

    2008-01-01

    There is broad consensus that the eating disorders of anorexia nervosa and bulimia nervosa stem from fundamental disturbances in identity development, but theoretically based empirical support is lacking. To extend work on the identity impairment model by investigating the relationship between organizational properties of the self-concept and change in disordered eating behaviors (DEB) in an at-risk sample of college women transitioning between freshman and sophomore years. The number, valence, and organization of self-schemas; availability of a fat body weight self-schema; and DEB were measured at baseline in the freshman year and 6 and 12 months later in a community-based sample of college women engaged in subthreshold DEB (n = 77; control: n = 41). Repeated-measures analyses of variances were used to examine group differences, and hierarchical regression analyses were used to predict disordered eating behaviors. Women in the DEB group had more negative self-schemas at baseline and showed information-processing evidence of a fat self-schema compared with the controls. The groups did not differ in the number of positive self-schemas or interrelatedness. The number of negative self-schemas predicted increases in the level of DEB at 6- and 12-month follow-up, and these effects were mediated through the fat self-schema. The number of positive self-schemas predicted the fat self-schema score but was not predictive of increases in DEB. Interrelatedness of the self-concept was not a significant predictor in this model. Impairments in overall collection of identities are predictive of the availability in memory of a fat self-schema, which in turn is predictive of increases in DEB during the transition to college in a sample of women at risk for an eating disorder. Therefore, organizational properties of the self-concept may be an important focus for effective primary and secondary prevention.

  15. To cross or not to cross: modeling wildlife road crossings as a binary response variable with contextual predictors

    Science.gov (United States)

    Siers, Shane R; Reed, Robert N.; Savidge, Julie A.

    2016-01-01

    Roads are significant barriers to landscape-scale movements of individuals or populations of many wildlife taxa. The decision by an animal near a road to either cross or not cross may be influenced by characteristics of the road, environmental conditions, traits of the individual animal, and other aspects of the context within which the decision is made. We considered such factors in a mixed-effects logistic regression model describing the nightly road crossing probabilities of invasive nocturnal Brown Treesnakes (Boiga irregularis) through short-term radiotracking of 691 snakes within close proximity to 50 road segments across the island of Guam. All measures of road magnitude (traffic volume, gap width, surface type, etc.) were significantly negatively correlated with crossing probabilities. Snake body size was the only intrinsic factor associated with crossing rates, with larger snakes crossing roads more frequently. Humidity was the only environmental variable affecting crossing rate. The distance of the snake from the road at the start of nightly movement trials was the most significant predictor of crossings. The presence of snake traps with live mouse lures during a portion of the trials indicated that localized prey cues reduced the probability of a snake crossing the road away from the traps, suggesting that a snake's decision to cross roads is influenced by local foraging opportunities. Per capita road crossing rates of Brown Treesnakes were very low, and comparisons to historical records suggest that crossing rates have declined in the 60+ yr since introduction to Guam. We report a simplified model that will allow managers to predict road crossing rates based on snake, road, and contextual characteristics. Road crossing simulations based on actual snake size distributions demonstrate that populations with size distributions skewed toward larger snakes will result in a higher number of road crossings. Our method of modeling per capita road crossing

  16. Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

    Science.gov (United States)

    Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2018-04-01

    A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

  17. Significance of Various Experimental Models and Assay Techniques in Cancer Diagnosis.

    Science.gov (United States)

    Ghanghoria, Raksha; Kesharwani, Prashant; Jain, Narendra K

    2017-01-01

    The experimental models are of vital significance to provide information regarding biological as well as genetic factors that control the phenotypic characteristics of the disease and serve as the foundation for the development of rational intervention stratagem. This review highlights the importance of experimental models in the field of cancer management. The process of pathogenesis in cancer progression, invasion and metastasis can be successfully explained by employing clinically relevant laboratory models of the disease. Cancer cell lines have been used extensively to monitor the process of cancer pathogenesis process by controlling growth regulation and chemo-sensitivity for the evaluation of novel therapeutics in both in vitro and xenograft models. The experimental models have been used for the elaboration of diagnostic or therapeutic protocols, and thus employed in preclinical studies of bioactive agents relevant for cancer prevention. The outcome of this review should provide useful information in understanding and selection of various models in accordance with the stage of cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. Scoping review identifies significant number of knowledge translation theories, models and frameworks with limited use.

    Science.gov (United States)

    Strifler, Lisa; Cardoso, Roberta; McGowan, Jessie; Cogo, Elise; Nincic, Vera; Khan, Paul A; Scott, Alistair; Ghassemi, Marco; MacDonald, Heather; Lai, Yonda; Treister, Victoria; Tricco, Andrea C; Straus, Sharon E

    2018-04-13

    To conduct a scoping review of knowledge translation (KT) theories, models and frameworks that have been used to guide dissemination or implementation of evidence-based interventions targeted to prevention and/or management of cancer or other chronic diseases. We used a comprehensive multistage search process from 2000-2016, which included traditional bibliographic database searching, searching using names of theories, models and frameworks, and cited reference searching. Two reviewers independently screened the literature and abstracted data. We found 596 studies reporting on the use of 159 KT theories, models or frameworks. A majority (87%) of the identified theories, models or frameworks were used in five or fewer studies, with 60% used once. The theories, models and frameworks were most commonly used to inform planning/design, implementation and evaluation activities, and least commonly used to inform dissemination and sustainability/scalability activities. Twenty-six were used across the full implementation spectrum (from planning/design to sustainability/scalability) either within or across studies. All were used for at least individual-level behavior change, while 48% were used for organization-level, 33% for community-level and 17% for system-level change. We found a significant number of KT theories, models and frameworks with a limited evidence base describing their use. Copyright © 2018. Published by Elsevier Inc.

  19. Incorporating representation of agricultural ecosystems and management within a dynamic biosphere model: Approach, validation, and significance

    Science.gov (United States)

    Kucharik, C.

    2004-12-01

    At the scale of individual fields, crop models have long been used to examine the interactions between soils, vegetation, the atmosphere and human management, using varied levels of numerical sophistication. While previous efforts have contributed significantly towards the advancement of modeling tools, the models themselves are not typically applied across larger continental scales due to a lack of crucial data. Furthermore, many times crop models are used to study a single quantity, process, or cycle in isolation, limiting their value in considering the important tradeoffs between competing ecosystem services such as food production, water quality, and sequestered carbon. In response to the need for a more integrated agricultural modeling approach across the continental scale, an updated agricultural version of a dynamic biosphere model (IBIS) now integrates representations of land-surface physics and soil physics, canopy physiology, terrestrial carbon and nitrogen balance, crop phenology, solute transport, and farm management into a single framework. This version of the IBIS model (Agro-IBIS) uses a short 20 to 60-minute timestep to simulate the rapid exchange of energy, carbon, water, and momentum between soils, vegetative canopies, and the atmosphere. The model can be driven either by site-specific meteorological data or by gridded climate datasets. Mechanistic crop models for corn, soybean, and wheat use physiologically-based representations of leaf photosynthesis, stomatal conductance, and plant respiration. Model validation has been performed using a variety of temporal scale data collected at the following spatial scales: (1) the precision-agriculture scale (5 m), (2) the individual field experiment scale (AmeriFlux), and (3) regional and continental scales using annual USDA county-level yield data and monthly satellite (AVHRR) observations of vegetation characteristics at 0.5 degree resolution. To date, the model has been used with great success to

  20. Computation of spatial significance of mountain objects extracted from multiscale digital elevation models

    International Nuclear Information System (INIS)

    Sathyamoorthy, Dinesh

    2014-01-01

    The derivation of spatial significance is an important aspect of geospatial analysis and hence, various methods have been proposed to compute the spatial significance of entities based on spatial distances with other entities within the cluster. This paper is aimed at studying the spatial significance of mountain objects extracted from multiscale digital elevation models (DEMs). At each scale, the value of spatial significance index SSI of a mountain object is the minimum number of morphological dilation iterations required to occupy all the other mountain objects in the terrain. The mountain object with the lowest value of SSI is the spatially most significant mountain object, indicating that it has the shortest distance to the other mountain objects. It is observed that as the area of the mountain objects reduce with increasing scale, the distances between the mountain objects increase, resulting in increasing values of SSI. The results obtained indicate that the strategic location of a mountain object at the centre of the terrain is more important than its size in determining its reach to other mountain objects and thus, its spatial significance

  1. Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

    Science.gov (United States)

    Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

    2017-12-01

    Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively

  2. The significance of using satellite imagery data only in Ecological Niche Modelling of Iberian herps

    Directory of Open Access Journals (Sweden)

    Neftalí Sillero

    2012-12-01

    Full Text Available The environmental data used to calculate ecological niche models (ENM are obtained mainly from ground-based maps (e.g., climatic interpolated surfaces. These data are often not available for less developed areas, or may be at an inappropriate scale, and thus to obtain this information requires fieldwork. An alternative source of eco-geographical data comes from satellite imagery. Three sets of ENM were calculated exclusively with variables obtained (1 from optical and radar images only and (2 from climatic and altitude maps obtained by ground-based methods. These models were compared to evaluate whether satellite imagery can accurately generate ENM. These comparisons must be made in areas with well-known species distribution and with available satellite imagery and ground-based data. Thus, the study area was the south-western part of Salamanca (Spain, using amphibian and reptiles as species models. Models’ discrimination capacity was measured with ROC plots. Models’ covariation was measured with a Spatial Spearman correlation. Four modelling techniques were used (Bioclim, Mahalanobis distance, GARP and Maxent. The results of this comparison showed that there were no significant differences between models generated using remotely sensed imagery or ground-based data. However, the models built with satellite imagery data exhibited a larger diversity of values, probably related to the higher spatial resolution of the satellite imagery. Satellite imagery can produce accurate ENM, independently of the modelling technique or the dataset used. Therefore, biogeographical analysis of species distribution in remote areas can be accurately developed only with variables from satellite imagery.

  3. Time Series Analysis of Hand-Foot-Mouth Disease Hospitalization in Zhengzhou: Establishment of Forecasting Models Using Climate Variables as Predictors

    Science.gov (United States)

    Feng, Huifen; Duan, Guangcai; Zhang, Rongguang; Zhang, Weidong

    2014-01-01

    Background Large-scale outbreaks of hand-foot-mouth disease (HFMD) have occurred frequently and caused neurological sequelae in mainland China since 2008. Prediction of the activity of HFMD epidemics a few weeks ahead is useful in taking preventive measures for efficient HFMD control. Methods Samples obtained from children hospitalized with HFMD in Zhengzhou, Henan, China, were examined for the existence of pathogens with reverse-transcriptase polymerase chain reaction (RT-PCR) from 2008 to 2012. Seasonal Autoregressive Integrated Moving Average (SARIMA) models for the weekly number of HFMD, Human enterovirs 71(HEV71) and CoxsackievirusA16 (CoxA16) associated HFMD were developed and validated. Cross correlation between the number of HFMD hospitalizations and climatic variables was computed to identify significant variables to be included as external factors. Time series modeling was carried out using multivariate SARIMA models when there was significant predictor meteorological variable. Results 2932 samples from the patients hospitalized with HFMD, 748 were detected with HEV71, 527 with CoxA16 and 787 with other enterovirus (other EV) from January 2008 to June 2012. Average atmospheric temperature (T{avg}) lagged at 2 or 3 weeks were identified as significant predictors for the number of HFMD and the pathogens. SARIMA(0,1,0)(1,0,0)52 associated with T{avg} at lag 2 (T{avg}-Lag 2) weeks, SARIMA(0,1,2)(1,0,0)52 with T{avg}-Lag 2 weeks and SARIMA(0,1,1)(1,1,0)52 with T{avg}-Lag 3 weeks were developed and validated for description and predication the weekly number of HFMD, HEV71-associated HFMD, and Cox A16-associated HFMD hospitalizations. Conclusion Seasonal pattern of certain HFMD pathogens can be associated by meteorological factors. The SARIMA model including climatic variables could be used as an early and reliable monitoring system to predict annual HFMD epidemics. PMID:24498221

  4. The Job Demands-Resources model as predictor of work identity and work engagement: A comparative analysis

    Directory of Open Access Journals (Sweden)

    Roslyn De Braine

    2011-05-01

    Research purpose: This study explored possible differences in the Job Demands-Resources model (JD-R as predictor of overall work engagement, dedication only and work-based identity, through comparative predictive analyses. Motivation for the study: This study may shed light on the dedication component of work engagement. Currently no literature indicates that the JD-R model has been used to predict work-based identity. Research design: A census-based survey was conducted amongst a target population of 23134 employees that yielded a sample of 2429 (a response rate of about 10.5%. The Job Demands- Resources scale (JDRS was used to measure job demands and job resources. A work-based identity scale was developed for this study. Work engagement was studied with the Utrecht Work Engagement Scale (UWES. Factor and reliability analyses were conducted on the scales and general multiple regression models were used in the predictive analyses. Main findings: The JD-R model yielded a greater amount of variance in dedication than in work engagement. It, however, yielded the greatest amount of variance in work-based identity, with job resources being its strongest predictor. Practical/managerial implications: Identification and work engagement levels can be improved by managing job resources and demands. Contribution/value-add: This study builds on the literature of the JD-R model by showing that it can be used to predict work-based identity.

  5. Intriguing model significantly reduces boarding of psychiatric patients, need for inpatient hospitalization.

    Science.gov (United States)

    2015-01-01

    As new approaches to the care of psychiatric emergencies emerge, one solution is gaining particular traction. Under the Alameda model, which has been put into practice in Alameda County, CA, patients who are brought to regional EDs with emergency psychiatric issues are quickly transferred to a designated emergency psychiatric facility as soon as they are medically stabilized. This alleviates boarding problems in area EDs while also quickly connecting patients with specialized care. With data in hand on the model's effectiveness, developers believe the approach could alleviate boarding problems in other communities as well. The model is funded by through a billing code established by California's Medicaid program for crisis stabilization services. Currently, only 22% of the patients brought to the emergency psychiatric facility ultimately need to be hospitalized; the other 78% are able to go home or to an alternative situation. In a 30-day study of the model, involving five community hospitals in Alameda County, CA, researchers found that ED boarding times were as much as 80% lower than comparable ED averages, and that patients were stabilized at least 75% of the time, significantly reducing the need for inpatient hospitalization.

  6. Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

    Science.gov (United States)

    Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

    2016-11-01

    Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

  7. A Parallelized Pumpless Artificial Placenta System Significantly Prolonged Survival Time in a Preterm Lamb Model.

    Science.gov (United States)

    Miura, Yuichiro; Matsuda, Tadashi; Usuda, Haruo; Watanabe, Shimpei; Kitanishi, Ryuta; Saito, Masatoshi; Hanita, Takushi; Kobayashi, Yoshiyasu

    2016-05-01

    An artificial placenta (AP) is an arterio-venous extracorporeal life support system that is connected to the fetal circulation via the umbilical vasculature. Previously, we published an article describing a pumpless AP system with a small priming volume. We subsequently developed a parallelized system, hypothesizing that the reduced circuit resistance conveyed by this modification would enable healthy fetal survival time to be prolonged. We conducted experiments using a premature lamb model to test this hypothesis. As a result, the fetal survival period was significantly prolonged (60.4 ± 3.8 vs. 18.2 ± 3.2 h, P lamb fetuses to survive for a significantly longer period when compared with previous studies. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals Inc.

  8. Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

    Science.gov (United States)

    Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2018-04-01

    A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the

  9. The Significant of Model School in Pluralistic Society of the Three Southern Border Provinces of Thailand

    Directory of Open Access Journals (Sweden)

    Haji-Awang Faisol

    2016-01-01

    The result of the study show that, a significant traits of the model schools in the multi-cultural society are not merely performed well in administrative procedure, teaching and learning process, but these schools also able to reveal the real social norm and religious believe into communities’ practical life as a truly “Malay-Muslim” society. It is means that, the school able to run the integrated programs under the shade of philosophy of Islamic education paralleled the National Education aims to ensure that the productivities of the programs able to serve both sides, national education on the one hand and the Malay Muslim communities’ satisfaction on the other hand.

  10. Perceived Resources as a Predictor of Satisfaction with Food-Related Life among Chilean Elderly: An Approach with Generalized Linear Models.

    Science.gov (United States)

    Lobos, G; Schnettler, B; Grunert, K G; Adasme, C

    2017-01-01

    The main objective of this study is to show why perceived resources are a strong predictor of satisfaction with food-related life in Chilean older adults. Design, sampling and participants: A survey was conducted in rural and urban areas in 30 communes of the Maule Region with 785 participants over 60 years of age who live in their own homes. The Satisfaction with Food-related Life (SWFL) scale was used. Generalized linear models (GLM) were used for the regression analysis. The results led to different considerations: First, older adults' perceived levels of resources are a good reflection of their actual levels of resources. Second, the individuals rated the sum of the perceived resources as 'highly important' to explain older adults' satisfaction with food-related life. Third, SWFL was predicted by satisfaction with economic situation, family importance, quantity of domestic household goods and a relative health indicator. Fourth, older adults who believe they have more resources compared to others are more satisfied with their food-related life. Finally, Poisson and binomial logistic models showed that the sum of perceived resources significantly increased the prediction of SWFL. The main conclusion is that perceived personal resources are a strong predictor of SWFL in Chilean older adults.

  11. Predictors of Condom Use Behaviors Based on the Health Belief Model (HBM) among Female Sex Workers: A Cross-Sectional Study in Hubei Province, China

    Science.gov (United States)

    Zhao, Jinzhu; Song, Fujian; Ren, Shuhua; Wang, Yan; Wang, Liang; Liu, Wei; Wan, Ying; Xu, Hong; Zhou, Tao; Hu, Tian; Bazzano, Lydia; Sun, Yi

    2012-01-01

    Background HIV infection related to commercial sexual contact is a serious public health issue in China. The objectives of the present study are to explore the predictors of condom use among female sex workers (FSWs) in China and examine the relationship between Health Belief Model (HBM) constructs. Methodology/Principal Findings A cross-sectional study was conducted in two cities (Wuhan and Suizhou) in Hubei Province, China, between July 2009 and June 2010. A total of 427 FSWs were recruited through mediators from the ‘low-tier’ entertainment establishments. Data were obtained by self-administered questionnaires. Structural equation models were constructed to examine the association. We collected 363 valid questionnaires. Within the context of HBM, perceived severity of HIV mediated through perceived benefits of condom use had a weak effect on condom use (r = 0.07). Perceived benefits and perceived barriers were proximate determinants of condom use (r = 0.23 and r = −0.62, respectively). Self-efficacy had a direct effect on perceived severity, perceived benefits, and perceived barriers, which was indirectly associated with condom use behaviors (r = 0.36). Conclusions/Significance The HBM provides a useful framework for investigating predictors of condom use behaviors among FSWs. Future HIV prevention interventions should focus on increasing perceived benefits of condom use, reducing barriers to condoms use, and improving self-efficacy among FSWs. PMID:23185355

  12. Relevance and clinical significance of serum resistin level in obese T2DM rhesus monkey models.

    Science.gov (United States)

    Qi, S-D; He, Z-L; Chen, Y; Ma, J; Yu, W-H; Li, Y-Y; Yang, F-M; Wang, J-B; Chen, L-X; Zhao, Y; Lu, S-Y

    2015-09-01

    Resistin is a type of hormone-like adipocytokines, which is secreted specifically by adipocytes. It may be a key factor in the development of type 2 diabetes mellitus (T2DM) from obesity- associated insulin resistance due to results that show that it has a close relationship with insulin resistance in rodents. We utilized the rhesus monkeys as study objects to preliminarily test the association with glucose metabolism and to conduct a correlation analysis for clinical parameters and serum resistin levels in obese rhesus monkey models of T2DM. The results suggested that resistin was significantly increased in T2DM monkeys (P insulin (FPI) and glycated hemoglobin (HbA1c), Insulin resistance index (HOA-IR), but a negative correlation with islet β-cell function (HOMA-β). In the course of glucose metabolism, reverse release change of resistin and insulin in T2DM monkeys occurred, but the phenomenon that was not observed in the control group, these findings indicated that resistin negatively regulated and interfered with carbohydrate metabolism in T2DM monkey models. The character of the releasing change of resistin might be a unique process in T2DM. Therefore, all of the results could provide references for clinical diagnostic criteria for human cases of T2DM, and could have clinical significance for obese T2DM diagnosis and degree of insulin resistance. © Georg Thieme Verlag KG Stuttgart · New York.

  13. VALORA: data base system for storage significant information used in the behavior modelling in the biosphere

    International Nuclear Information System (INIS)

    Valdes R, M.; Aguero P, A.; Perez S, D.; Cancio P, D.

    2006-01-01

    The nuclear and radioactive facilities can emit to the environment effluents that contain radionuclides, which are dispersed and/or its accumulate in the atmosphere, the terrestrial surface and the surface waters. As part of the evaluations of radiological impact, it requires to be carried out qualitative and quantitative analysis. In many of the cases it doesn't have the real values of the parameters that are used in the modelling, neither it is possible to carry out their measure, for that to be able to carry out the evaluation it needs to be carried out an extensive search of that published in the literature about the possible values of each parameter, under similar conditions to the object of study, this work can be extensive. In this work the characteristics of the VALORA Database System developed with the purpose of organizing and to automate significant information that it appears in different sources (scientific or technique literature) of the parameters that are used in the modelling of the behavior of the pollutants in the environment and the values assigned to these parameters that are used in the evaluation of the radiological impact potential is described; VALORA allows the consultation and selection of the characteristic parametric data of different situations and processes that are required by the calculation pattern implemented. The software VALORA it is a component of a group of tools computer that have as objective to help to the resolution of dispersion models and transfer of pollutants. (Author)

  14. RS-WebPredictor

    DEFF Research Database (Denmark)

    Zaretzki, J.; Bergeron, C.; Huang, T.-W.

    2013-01-01

    Regioselectivity-WebPredictor (RS-WebPredictor) is a server that predicts isozyme-specific cytochrome P450 (CYP)-mediated sites of metabolism (SOMs) on drug-like molecules. Predictions may be made for the promiscuous 2C9, 2D6 and 3A4 CYP isozymes, as well as CYPs 1A2, 2A6, 2B6, 2C8, 2C19 and 2E1....... RS-WebPredictor is the first freely accessible server that predicts the regioselectivity of the last six isozymes. Server execution time is fast, taking on average 2s to encode a submitted molecule and 1s to apply a given model, allowing for high-throughput use in lead optimization projects.......Availability: RS-WebPredictor is accessible for free use at http://reccr.chem.rpi.edu/ Software/RS-WebPredictor....

  15. Developing and testing a measurement tool for assessing predictors of breakfast consumption based on a health promotion model.

    Science.gov (United States)

    Dehdari, Tahereh; Rahimi, Tahereh; Aryaeian, Naheed; Gohari, Mahmood Reza; Esfeh, Jabiz Modaresi

    2014-01-01

    To develop an instrument for measuring Health Promotion Model constructs in terms of breakfast consumption, and to identify the constructs that were predictors of breakfast consumption among Iranian female students. A questionnaire on Health Promotion Model variables was developed and potential predictors of breakfast consumption were assessed using this tool. One hundred female students, mean age 13 years (SD ± 1.2 years). Two middle schools from moderate-income areas in Qom, Iran. Health Promotion Model variables were assessed using a 58-item questionnaire. Breakfast consumption was also measured. Internal consistency (Cronbach alpha), content validity index, content validity ratio, multiple linear regression using stepwise method, and Pearson correlation. Content validity index and content validity ratio scores of the developed scale items were 0.89 and 0.93, respectively. Internal consistencies (range, .74-.91) of subscales were acceptable. Prior related behaviors, perceived barriers, self-efficacy, and competing demand and preferences were 4 constructs that could predict 63% variance of breakfast frequency per week among subjects. The instrument developed in this study may be a useful tool for researchers to explore factors affecting breakfast consumption among students. Students with a high level of self-efficacy, more prior related behavior, fewer perceived barriers, and fewer competing demands were most likely to regularly consume breakfast. Copyright © 2014 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

  16. Predictors of employees’ psychophysical health and sickness absenteeism: Modelling based on REBT framework

    Directory of Open Access Journals (Sweden)

    Popov Boris

    2016-01-01

    Full Text Available The main objective of the study was to examine whether negative experiences at work, irrational beliefs, alone and in interaction, and negative affectivity as a mediator, could predict psychosomatic complaints and frequency of sickness absenteeism. The hypothesized model showed acceptable fit to the data, suggesting that negative affectivity mediates the relationship between negative experiences and irrational beliefs on the one hand, and psychosomatic complaints on the other. The results also revealed no significant effect of interaction between negative experiences and irrational beliefs, while fatigue and physical symptoms have a significant and direct effect on the number of days of absence. It was concluded that the lack of an effect of psychological symptoms on absenteeism may indicate that employees in Serbia do not see them as a sufficient reason for sick leave. The results are discussed within frameworks of Rational-emotive behaviour therapy and strategic stress management approach.

  17. Phasic firing in vasopressin cells: understanding its functional significance through computational models.

    Directory of Open Access Journals (Sweden)

    Duncan J MacGregor

    Full Text Available Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response

  18. Models and Mechanisms of Acquired Antihormone Resistance in Breast Cancer: Significant Clinical Progress Despite Limitations

    Science.gov (United States)

    Sweeney, Elizabeth E.; McDaniel, Russell E.; Maximov, Philipp Y.; Fan, Ping; Jordan, V. Craig

    2012-01-01

    Translational research for the treatment and prevention of breast cancer depends upon the four Ms: models, molecules, and mechanisms in order to create medicines. The process, to target the estrogen receptor (ER) in estrogen-dependent breast cancer, has yielded significant advances in patient survivorship and the first approved medicines (tamoxifen and raloxifene) to reduce the incidence of any cancer in high- or low-risk women. This review focuses on the critical role of the few ER-positive cell lines (MCF-7, T47D, BT474, ZR-75) that continue to advance our understanding of the estrogen-regulated biology of breast cancer. More importantly, the model cell lines have provided an opportunity to document the development and evolution of acquired antihormone resistance. The description of this evolutionary process that occurs in micrometastatic disease during up to a decade of adjuvant therapy would not be possible in the patient. The use of the MCF-7 breast cancer cell line in particular has been instrumental in discovering a vulnerability of ER-positive breast cancer exhaustively treated with antihormone therapy. Physiologic estradiol acts as an apoptotic trigger to cause tumor regression. These unanticipated findings in the laboratory have translated to clinical advances in our knowledge of the paradoxical role of estrogen in the life and death of breast cancer. PMID:23308083

  19. Significance tests to determine the direction of effects in linear regression models.

    Science.gov (United States)

    Wiedermann, Wolfgang; Hagmann, Michael; von Eye, Alexander

    2015-02-01

    Previous studies have discussed asymmetric interpretations of the Pearson correlation coefficient and have shown that higher moments can be used to decide on the direction of dependence in the bivariate linear regression setting. The current study extends this approach by illustrating that the third moment of regression residuals may also be used to derive conclusions concerning the direction of effects. Assuming non-normally distributed variables, it is shown that the distribution of residuals of the correctly specified regression model (e.g., Y is regressed on X) is more symmetric than the distribution of residuals of the competing model (i.e., X is regressed on Y). Based on this result, 4 one-sample tests are discussed which can be used to decide which variable is more likely to be the response and which one is more likely to be the explanatory variable. A fifth significance test is proposed based on the differences of skewness estimates, which leads to a more direct test of a hypothesis that is compatible with direction of dependence. A Monte Carlo simulation study was performed to examine the behaviour of the procedures under various degrees of associations, sample sizes, and distributional properties of the underlying population. An empirical example is given which illustrates the application of the tests in practice. © 2014 The British Psychological Society.

  20. Analysis of significance of environmental factors in landslide susceptibility modeling: Case study Jemma drainage network, Ethiopia

    Directory of Open Access Journals (Sweden)

    Vít Maca

    2017-06-01

    Full Text Available Aim of the paper is to describe methodology for calculating significance of environmental factors in landslide susceptibility modeling and present result of selected one. As a study area part of a Jemma basin in Ethiopian Highland is used. This locality is highly affected by mass movement processes. In the first part all major factors and their influence are described briefly. Majority of the work focuses on research of other methodologies used in susceptibility models and design of own methodology. This method is unlike most of the methods used completely objective, therefore it is not possible to intervene in the results. In article all inputs and outputs of the method are described as well as all stages of calculations. Results are illustrated on specific examples. In study area most important factor for landslide susceptibility is slope, on the other hand least important is land cover. At the end of article landslide susceptibility map is created. Part of the article is discussion of results and possible improvements of the methodology.

  1. Multilevel linear modelling of the response-contingent learning of young children with significant developmental delays.

    Science.gov (United States)

    Raab, Melinda; Dunst, Carl J; Hamby, Deborah W

    2018-02-27

    The purpose of the study was to isolate the sources of variations in the rates of response-contingent learning among young children with multiple disabilities and significant developmental delays randomly assigned to contrasting types of early childhood intervention. Multilevel, hierarchical linear growth curve modelling was used to analyze four different measures of child response-contingent learning where repeated child learning measures were nested within individual children (Level-1), children were nested within practitioners (Level-2), and practitioners were nested within the contrasting types of intervention (Level-3). Findings showed that sources of variations in rates of child response-contingent learning were associated almost entirely with type of intervention after the variance associated with differences in practitioners nested within groups were accounted for. Rates of child learning were greater among children whose existing behaviour were used as the building blocks for promoting child competence (asset-based practices) compared to children for whom the focus of intervention was promoting child acquisition of missing skills (needs-based practices). The methods of analysis illustrate a practical approach to clustered data analysis and the presentation of results in ways that highlight sources of variations in the rates of response-contingent learning among young children with multiple developmental disabilities and significant developmental delays. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  2. Urban Growth Causes Significant increase in Extreme Rainfall - A modelling study

    Science.gov (United States)

    Pathirana, Assela

    2010-05-01

    World's urban centers are growing rapidly causing the impact of extreme rainfall events felt much more severely due to relatively well unerstood phenomena like decreased infiltration and flow resistance. However, an increasing set of evidence (e.g. heavy rainfall event observed at Nerima, central part of Tokyo metropolitan area, on 21 July 1999) suggest that the extreme rainfall, the driving force itself increases as a result of the microclimatic changes due to urban growth. Urban heat islands(UHI) due to heat anomalies of urban sprawl act as virtual mountains resulting in a local atmosphere more conducive for heavy rainfall. In this study, we employ a popular mesoscale atmoshperic model to numerically simulate the UHI induced rainfall enhancement. Initial idealized experiments conducted under trophical atmospheric conditions indicated that the changes in landuse due to significant urban growth will indeed cause more intense rainfall events. This is largely due to increased convective breakup, causing a favourable situation for convective cloud systems. Five historical heavy rainfall events that caused floods in five urban centres (Dhaka, Mumbai, Colombo, Lyon and Taipei) were selected from historical records. Numerical simulations were setup to assertain what would be the amount of rainfall if the same large-scale atmospheric situations (forcings) occured under a hypothetical situation of doubled urbanization level these events. Significant increases (upto 50%) of extreme rainfall was indicated for many of the events. Under major assumptions, these simulations were used to estimate the anticipated changes in the Intensity-Duration-Frequency (IDF). The magnitude of the 30min event with 25 year return period increased by about 20 percent. Without considering any changes in the external forcing the urban growth alone could cause very significant increase in local rainfall.

  3. Predictors of consistent condom use based on the Information-Motivation-Behavior Skill (IMB) model among senior high school students in three coastal cities in China.

    Science.gov (United States)

    Cai, Yong; Ye, Xiuxia; Shi, Rong; Xu, Gang; Shen, Lixiao; Ren, Jia; Huang, Hong

    2013-06-04

    High prevalence of risky sexual behaviors and lack of information, skills and preventive support mean that, adolescents face high risks of HIV/AIDS. This study applied the information-motivation-behavioral skills (IMB) model to examine the predictors of consistent condom use among senior high school students from three coastal cities in China and clarify the relationships between the model constructs. A cross-sectional study was conducted to assess HIV/AIDS related information, motivation, behavioral skills and preventive behaviors among senior high school students in three coastal cities in China. Structural equation modelling (SEM) was used to assess the IMB model. Of the 12313 participants, 4.5% (95% CI: 4.2-5.0) reported having had premarital sex and among them 25.0% (95% CI: 21.2-29.1) reported having used a condom in their sexual debut. Only about one-ninth of participants reported consistent condom use. The final IMB model provided acceptable fit to the data (CFI = 0.981, RMSEA = 0.014). Consistent condom use was significantly predicted by motivation (β = 0.175, P students in China. The IMB model could predict consistent condom use and suggests that future interventions should focus on improving motivation and behavioral skills.

  4. Cyclosporin A significantly improves preeclampsia signs and suppresses inflammation in a rat model.

    Science.gov (United States)

    Hu, Bihui; Yang, Jinying; Huang, Qian; Bao, Junjie; Brennecke, Shaun Patrick; Liu, Huishu

    2016-05-01

    Preeclampsia is associated with an increased inflammatory response. Immune suppression might be an effective treatment. The aim of this study was to examine whether Cyclosporin A (CsA), an immunosuppressant, improves clinical characteristics of preeclampsia and suppresses inflammation in a lipopolysaccharide (LPS) induced preeclampsia rat model. Pregnant rats were randomly divided into 4 groups: group 1 (PE) rats each received LPS via tail vein on gestational day (GD) 14; group 2 (PE+CsA5) rats were pretreated with LPS (1.0 μg/kg) on GD 14 and were then treated with CsA (5mg/kg, ip) on GDs 16, 17 and 18; group 3 (PE+CsA10) rats were pretreated with LPS (1.0 μg/kg) on GD 14 and were then treated with CsA (10mg/kg, ip) on GDs 16, 17 and 18; group 4 (pregnant control, PC) rats were treated with the vehicle (saline) used for groups 1, 2 and 3. Systolic blood pressure, urinary albumin, biometric parameters and the levels of serum cytokines were measured on day 20. CsA treatment significantly reduced LPS-induced systolic blood pressure and the mean 24-h urinary albumin excretion. Pro-inflammatory cytokines IL-6, IL-17, IFN-γ and TNF-α were increased in the LPS treatment group but were reduced in (LPS+CsA) group (Ppreeclampsia signs and attenuated inflammatory responses in the LPS induced preeclampsia rat model which suggests that immunosuppressant might be an alternative management option for preeclampsia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Kernel density surface modelling as a means to identify significant concentrations of vulnerable marine ecosystem indicators.

    Directory of Open Access Journals (Sweden)

    Ellen Kenchington

    Full Text Available The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify "significant concentrations" of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores, and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here

  6. Radiogenic heat production variability of some common lithological groups and its significance to lithospheric thermal modeling

    Science.gov (United States)

    Vilà, M.; Fernández, M.; Jiménez-Munt, I.

    2010-07-01

    Determining the temperature distribution within the lithosphere requires the knowledge of the radiogenic heat production (RHP) distribution within the crust and the lithospheric mantle. RHP of crustal rocks varies considerably at different scales as a result of the petrogenetic processes responsible for their formation and therefore RHP depends on the considered lithologies. In this work we address RHP variability of some common lithological groups from a compilation of a total of 2188 representative U, Th and K concentrations of different worldwide rock types derived from 102 published studies. To optimize the use of the generated RHP database we have classified and renamed the rock-type denominations of the original works following a petrologic classification scheme with a hierarchical structure. The RHP data of each lithological group is presented in cumulative distribution plots, and we report a table with the mean, the standard deviation, the minimum and maximum values, and the significant percentiles of these lithological groups. We discuss the reported RHP distribution for the different igneous, sedimentary and metamorphic lithological groups from a petrogenetic viewpoint and give some useful guidelines to assign RHP values to lithospheric thermal modeling.

  7. Hidden symmetry in asymmetric morphology: significance of Hjortsjo's anatomical model in liver surgery.

    Science.gov (United States)

    Shindoh, Junichi; Satou, Shoichi; Aoki, Taku; Beck, Yoshifumi; Hasegawa, Kiyoshi; Sugawara, Yasuhiko; Kokudo, Norihiro

    2012-01-01

    Several studies have recently reappraised the liver classification proposed by Hjortsjo in the 1940's and reported it as a surgically relevant theory. However, its clinical relevance and significance in liver surgery have not yet been well documented. Three-dimensional (3D) simulations of the livers of 100 healthy donors for living donor liver transplantation were reviewed. The adequacy of Hjortsjo's model was evaluated using 3D simulations and its clinical relevance was demonstrated in donor surgery. Both portal and hepatic venous branches exhibited symmetrical configuration on either side of the Rex-Cantlie line on the 3D images. In terms of the symmetry, the right paramedian sector seemed to be subdivided into two longitudinal parts, namely the "ventral" and "dorsal" parts. Volume analysis revealed that these longitudinal parts occupied relatively large areas of the liver (the ventral part, 15.7% and the dorsal part, 20.9% of the whole livers, respectively). Postoperative CT imaging confirmed marked congestion and/or impaired regeneration of these areas due to deprivation of the middle or right hepatic veins. Considering the symmetry of intrahepatic vascular distributions and clinical relevance, Hjortsjo's classification offers important viewpoint for surgeons to handle the liver based on both the portal and venous distributions.

  8. High-fat diet induces significant metabolic disorders in a mouse model of polycystic ovary syndrome.

    Science.gov (United States)

    Lai, Hao; Jia, Xiao; Yu, Qiuxiao; Zhang, Chenglu; Qiao, Jie; Guan, Youfei; Kang, Jihong

    2014-11-01

    Polycystic ovary syndrome (PCOS) is the most common female endocrinopathy associated with both reproductive and metabolic disorders. Dehydroepiandrosterone (DHEA) is currently used to induce a PCOS mouse model. High-fat diet (HFD) has been shown to cause obesity and infertility in female mice. The possible effect of an HFD on the phenotype of DHEA-induced PCOS mice is unknown. The aim of the present study was to investigate both reproductive and metabolic features of DHEA-induced PCOS mice fed a normal chow or a 60% HFD. Prepubertal C57BL/6 mice (age 25 days) on the normal chow or an HFD were injected (s.c.) daily with the vehicle sesame oil or DHEA for 20 consecutive days. At the end of the experiment, both reproductive and metabolic characteristics were assessed. Our data show that an HFD did not affect the reproductive phenotype of DHEA-treated mice. The treatment of HFD, however, caused significant metabolic alterations in DHEA-treated mice, including obesity, glucose intolerance, dyslipidemia, and pronounced liver steatosis. These findings suggest that HFD induces distinct metabolic features in DHEA-induced PCOS mice. The combined DHEA and HFD treatment may thus serve as a means of studying the mechanisms involved in metabolic derangements of this syndrome, particularly in the high prevalence of hepatic steatosis in women with PCOS. © 2014 by the Society for the Study of Reproduction, Inc.

  9. Prevalence and Predictors of Pre-Diabetes and Diabetes among Adults 18 Years or Older in Florida: A Multinomial Logistic Modeling Approach.

    Directory of Open Access Journals (Sweden)

    Ifechukwude Obiamaka Okwechime

    Full Text Available Individuals with pre-diabetes and diabetes have increased risks of developing macro-vascular complications including heart disease and stroke; which are the leading causes of death globally. The objective of this study was to estimate the prevalence of pre-diabetes and diabetes, and to investigate their predictors among adults ≥18 years in Florida.Data covering the time period January-December 2013, were obtained from Florida's Behavioral Risk Factor Surveillance System (BRFSS. Survey design of the study was declared using SVYSET statement of STATA 13.1. Descriptive analyses were performed to estimate the prevalence of pre-diabetes and diabetes. Predictors of pre-diabetes and diabetes were investigated using multinomial logistic regression model. Model goodness-of-fit was evaluated using both the multinomial goodness-of-fit test proposed by Fagerland, Hosmer, and Bofin, as well as, the Hosmer-Lemeshow's goodness of fit test.There were approximately 2,983 (7.3% and 5,189 (12.1% adults in Florida diagnosed with pre-diabetes and diabetes, respectively. Over half of the study respondents were white, married and over the age of 45 years while 36.4% reported being physically inactive, overweight (36.4% or obese (26.4%, hypertensive (34.6%, hypercholesteremic (40.3%, and 26% were arthritic. Based on the final multivariable multinomial model, only being overweight (Relative Risk Ratio [RRR] = 1.85, 95% Confidence Interval [95% CI] = 1.41, 2.42, obese (RRR = 3.41, 95% CI = 2.61, 4.45, hypertensive (RRR = 1.69, 95% CI = 1.33, 2.15, hypercholesterolemic (RRR = 1.94, 95% CI = 1.55, 2.43, and arthritic (RRR = 1.24, 95% CI = 1.00, 1.55 had significant associations with pre-diabetes. However, more predictors had significant associations with diabetes and the strengths of associations tended to be higher than for the association with pre-diabetes. For instance, the relative risk ratios for the association between diabetes and being overweight (RRR = 2.00, 95

  10. More Use of Peritoneal Dialysis Gives Significant Savings: A Systematic Review and Health Economic Decision Model.

    Science.gov (United States)

    Pike, Eva; Hamidi, Vida; Ringerike, Tove; Wisloff, Torbjorn; Klemp, Marianne

    2017-02-01

    Patients with end-stage renal disease (ESRD) are in need of renal replacement therapy as dialysis and/or transplantation. The prevalence of ESRD and, thus, the need for dialysis are constantly growing. The dialysis modalities are either peritoneal performed at home or hemodialysis (HD) performed in-center (hospital or satellite) or home. We examined effectiveness and cost-effectiveness of HD performed at different locations (hospital, satellite, and home) and peritoneal dialysis (PD) at home in the Norwegian setting. We conducted a systematic review for patients above 18 years with end-stage renal failure requiring dialysis in several databases and performed several meta-analyses of existing literature. Mortality and major complications that required were our main clinical outcomes. The quality of the evidence for each outcome was evaluated using GRADE. Cost-effectiveness was assessed by developing a probabilistic Markov model. The analysis was carried out from a societal perspective, and effects were expressed in quality-adjusted life-years. Uncertainties in the base-case parameter values were explored with a probabilistic sensitivity analysis. Scenario analyses were conducted by increasing the proportion of patients receiving PD with a corresponding reduction in HD patients in-center both for Norway and Europian Union. We assumed an annual growth rate of 4% in the number of dialysis patients, and a relative distribution between PD and HD in-center of 30% and 70%, respectively. From a societal perspective and over a 5-year time horizon, PD was the most cost-effective dialysis alternative. We found no significant difference in mortality between peritoneal and HD modalities. Our scenario analyses showed that a shift toward more patients on PD (as a first choice) with a corresponding reduction in HD in-center gave a saving over a 5-year period of 32 and 10,623 million EURO, respectively, for Norway and the European Union. PD was the most cost-effective dialysis

  11. Theoretical models regarding factors influencing switching regimes and the hydrological and erosional significance of hydrophobicity

    Science.gov (United States)

    Walsh, Rory; Urbanek, Emilia; Ferreira, Carla; Shakesby, Richard; Bento, Celia; Ferreira, Antonio

    2013-04-01

    The influence which soil hydrophobicity may have on hillslope hydrology and erosion in any location will depend on the proportion of storm events in which it is spatially contiguous. This in turn is dependent upon (a) the speed and three-dimensional pattern with which it disappears in wet weather and (b) the speed, three-dimensional pattern and degree of re-establishment of hydrophobicity in dry weather following hydrophilic or partially hydrophilic episodes. This paper draws upon results of laboratory and field investigations of changes through time in hydrophobicity, as well as recent advances in knowledge of switching mechanisms, to develop theory relating to hydrophobicity, its three-dimensional temporal dynamics and controls and its influence on overland flow and slopewash. Particular attention is given to modelling temporal change following fire. Use is made of key findings from (1) a field study of changes over a 4.2-year period January 2009 to March 2013 in hydrophobicity at two 10 m x 10 m grids (270 points, surface and 5 cm depth) on heather moorland in Central Portugal, where one grid was burned by an experimental fire in February 2009 and the other was an immediately adjacent unburned control; (2) a laboratory study of three-dimensional change in hydrophobicity with wetting (by an 8 mm simulated rainfall) and at different stages in an 80-hour drying phase of three different but initially equally hydrophobic soils, each of which comprising variants with and without artificial vertical routeways (simulated roots or linear cracks) and with or without drainage impedance at 2.5 cm depth. A series of theoretical models are presented addressing 1) factors and mechanisms influencing post-fire temporal change in hydrophobicity and (2) factors and mechanisms controlling the significance and temporal dynamics of hydrophobicity influence on overland flow and erosion (i) in unburned terrain and (ii) following fire. The field evidence from Portugal suggests a three

  12. Preoperative Cognitive Impairment As a Predictor of Postoperative Outcomes in a Collaborative Care Model.

    Science.gov (United States)

    Zietlow, Kahli; McDonald, Shelley R; Sloane, Richard; Browndyke, Jeffrey; Lagoo-Deenadayalan, Sandhya; Heflin, Mitchell T

    2018-01-13

    To compare postoperative outcomes of individuals with and without cognitive impairment enrolled in the Perioperative Optimization of Senior Health (POSH) program at Duke University, a comanagement model involving surgery, anesthesia, and geriatrics. Retrospective analysis of individuals enrolled in a quality improvement program. Tertiary academic center. Older adults undergoing surgery and referred to POSH (N = 157). Cognitive impairment was defined as a score less than 25 out of 30 (adjusted for education) on the St. Louis University Mental Status (SLUMS) Examination. Median length of stay (LOS), mean number of postoperative complications, rates of postoperative delirium (POD, %), 30-day readmissions (%), and discharge to home (%) were compared using bivariate analysis. Seventy percent of participants met criteria for cognitive impairment (mean SLUMS score 20.3 for those with cognitive impairment and 27.7 for those without). Participants with and without cognitive impairment did not significantly differ in demographic characteristics, number of medications (including anticholinergics and benzodiazepines), or burden of comorbidities. Participants with and without cognitive impairment had similar LOS (P = .99), cumulative number of complications (P = .70), and 30-day readmission (P = .20). POD was more common in those with cognitive impairment (31% vs 24%), but the difference was not significant (P = .34). Participants without cognitive impairment had higher rates of discharge to home (80.4% vs 65.1%, P = .05). Older adults with and without cognitive impairment referred to the POSH program fared similarly on most postoperative outcomes. Individuals with cognitive impairment may benefit from perioperative geriatric comanagement. Questions remain regarding the validity of available measures of cognition in the preoperative period. © 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.

  13. Comparison of Far-field Noise for Three Significantly Different Model Turbofans

    Science.gov (United States)

    Woodward, Richard P.

    2008-01-01

    Far-field noise sound power level (PWL) spectra and overall sound pressure level (OASPL) directivities were compared for three significantly different model fan stages which were tested in the NASA Glenn 9 15 Low Speed Wind Tunnel. The test fans included the Advanced Ducted Propulsor (ADP) Fan1, the baseline Source Diagnostic Test (SDT) fan, and the Quiet High Speed Fan2 (QHSF2). These fans had design rotor tangential tip speeds from 840 to 1474 ft/s and stage pressure ratios from 1.29 to 1.82. Additional parameters included rotor-stator spacing, stator sweep, and downstream support struts. Acoustic comparison points were selected on the basis of stage thrust. Acoustic results for the low tip speed/low pressure ratio fan (ADP Fan1) were thrust-adjusted to show how a geometrically-scaled version of this fan might compare at the higher design thrust levels of the other two fans. Lowest noise levels were typically observed for ADP Fan1 (which had a radial stator) and for the intermediate tip speed fan (Source Diagnostics Test, SDT, R4 rotor) with a swept stator. Projected noise levels for the ADP fan to the SDT swept stator configuration at design point conditions showed the fans to have similar noise levels. However, it is possible that the ADP fan could be 2 to 3 dB quieter with incorporation of a swept stator. Benefits of a scaled ADP fan include avoidance of multiple pure tones associated with transonic and higher blade tip speeds. Penalties of a larger size ADP fan would include increased nacelle size and drag.

  14. Talent predictors

    Directory of Open Access Journals (Sweden)

    Raquel Lorenzo

    2007-07-01

    Full Text Available The knowledge of talent predictors is the initial point for building diagnosis and encouragement procedures in this field. The meaning of word predictor is to anticipate the future, to divine. Early prediction of high performance is complex problem no resolute by the science yet. There are many discrepancies about what measure and how to do. The article analyze the art state in this problematic because the excellence is determined by the interaction between internal and environmental factors.

  15. Explaining variance and identifying predictors of children's communication via a multilevel model of single-case design research.

    Science.gov (United States)

    Ottley, Jennifer Riggie; Ferron, John M; Hanline, Mary Frances

    2016-06-01

    The purpose of this study was to explain the variability in data collected from a single-case design study and to identify predictors of communicative outcomes for children with developmental delays or disabilities (n = 4). Using SAS University Edition, we fit multilevel models with time nested within children. Children's initial levels of communication and teachers' frequency of strategy use when directed at the children predicted children's communicative outcomes. These results indicate that teachers' implementation of evidence-based communication strategies, when directed toward children with disabilities, and the interaction between their use of the strategies and children's initial levels of communication predict children's communicative outcomes. Implications for research and practice are provided.

  16. Predictors of work injury in underground mines - an application of a logistic regression model

    Energy Technology Data Exchange (ETDEWEB)

    P.S. Paul [Indian School of Mines University, Dhanbad (India). Department of Mining Engineering

    2009-05-15

    Mine accidents and injuries are complex and generally characterized by several factors starting from personal to technical, and technical to social characteristics. In this study, an attempt has been made to identify the various factors responsible for work related injuries in mines and to estimate the risk of work injury to mine workers. The prediction of work injury in mines was done by a step-by-step multivariate logistic regression modeling with an application to case study mines in India. In total, 18 variables were considered in this study. Most of the variables are not directly quantifiable. Instruments were developed to quantify them through a questionnaire type survey. Underground mine workers were randomly selected for the survey. Responses from 300 participants were used for the analysis. Four variables, age, negative affectivity, job dissatisfaction, and physical hazards bear significant discriminating power for risk of injury to the workers, comparing between cases and controls in a multivariate situation while controlling all the personal and socio-technical variables. The analysis reveals that negatively affected workers are 2.54 times more prone to injuries than the less negatively affected workers and this factor is a more important risk factor for the case-study mines. Long term planning through identification of the negative individuals, proper counseling regarding the adverse effects of negative behaviors and special training is urgently required. Care should be taken for the aged and experienced workers in terms of their job responsibility and training requirements. Management should provide a friendly atmosphere during work to increase the confidence of the injury prone miners. 44 refs., 4 tabs.

  17. The use of the health belief model to assess predictors of intent to receive the novel (2009 H1N1 influenza vaccine

    Directory of Open Access Journals (Sweden)

    Jean-Venable “Kelly” R.Goode, PharmD, BCPS, FAPhA, FCCP

    2012-01-01

    Full Text Available Objectives: 1 Assess participants’ perceptions of severity, risk, and susceptibility to the novel H1N1 influenza virus and/or vaccine, vaccine benefits and barriers, and cues to action and 2 Identify predictors of participants’ intention to receive the novel H1N1 vaccine.Design: Cross-sectional, descriptive studySetting: Local grocery store chain and university in the central Virginia areaParticipants: Convenience sample of adult college students and grocery store patronsIntervention: Participants filled out an anonymous, self-administered questionnaire based upon the Health Belief Model.Main Outcome Measures: Participants’ predictors of intention to receive the novel H1N1 vaccineResults: A total of 664 participants completed a questionnaire. The majority of participants were aged 25-64 years old (66.9%. The majority were female (69.1%, Caucasian (73.7%, and felt at risk for getting sick from the virus (70.3%. Most disagreed that they would die from the virus (68.0%. Participants received novel H1N1 vaccine recommendations from their physicians (28.2%, pharmacists (20.7%, and nurses (16.1%. The majority intended to receive the H1N1 vaccine (58.1%. Participants were significantly more likely to intend to receive the H1N1 vaccine if they had lower scores on the perceived vaccine barriers domain (OR= 0.57, CI: 0.35-0.93. Physicians’ recommendations (OR=0.26, CI: 0.11-0.62 and 2008 seasonal flu vaccination (OR=0.45, CI: 0.24-0.83 were significant predictors of intention to receive the H1N1 vaccine.Conclusions: Most participants felt at risk for getting the novel H1N1 virus and intended to receive the novel H1N1 vaccine. Educating patients about vaccine benefits and increasing healthcare professionals' vaccine recommendations may increase vaccination rates in future pandemics.

  18. Significance of predictive models/risk calculators for HBV-related hepatocellular carcinoma

    OpenAIRE

    DONG Jing

    2015-01-01

    Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) is a major public health problem in Southeast Asia. In recent years, researchers from Hong Kong and Taiwan have reported predictive models or risk calculators for HBV-associated HCC by studying its natural history, which, to some extent, predicts the possibility of HCC development. Generally, risk factors of each model involve age, sex, HBV DNA level, and liver cirrhosis. This article discusses the evolution and clinical significa...

  19. Predictors and Characteristics of Erikson's Life Cycle Model Among Men: A 32-Year Longitudinal Study

    Science.gov (United States)

    Westermeyer, Jerry F.

    2004-01-01

    To assess Erikson's life cycle model, 86 men, initially selected for health, were prospectively studied at age 21, and reassessed 32 years later at age 53. Using the Vaillant and Milofsky (1980) modification of Erikson's model, 48 men (56%) achieved generativity, an advanced developmental stage, at follow-up. Results generally support Erikson's…

  20. Significance of kinetics for sorption on inorganic colloids: modeling and experiment interpretation issues.

    Science.gov (United States)

    Painter, S; Cvetkovic, V; Pickett, D; Turner, D R

    2002-12-15

    A two-site kinetic model for solute sorption on inorganic colloids is developed. The model quantifies linear first-order sorption on two types of sites ("fast" and "slow") characterized by two pairs of rates (forward and reverse). We use the model to explore data requirements for long-term predictive calculations of colloid-facilitated transport and to evaluate laboratory kinetic sorption data of Lu et al.. Five batch sorption data sets are considered with plutonium as the tracer and montmorillonite, hematite, silica, and smectite as colloids. Using asymptotic results applicable on the time scale of limited duration experiments, a robust estimation procedure is developed for the fast-site partitioning coefficient K(C) and the slow forward rate alpha. The estimated range of K(C) is 1.1-76 L/g, and the range for alpha is 0.0017-0.02 1/h. The fast reverse rate k(r) is estimated in the range 0.012-0.1 1/h. Comparison of one-site and two-site sorption interpretations reveals the difficulty in discriminating between the two models for montmorillonite and to a lesser extent for hematite. For silica and smectite, the two-site model clearly provides a better representation of the data as compared with a single site model. Kinetic data for silica are available for different colloid concentrations (0.2 g/L and 1 g/L). For the range of experimental conditions considered, alpha appears to be independent of colloid concentration.

  1. Significance of uncertainties derived from settling tank model structure and parameters on predicting WWTP performance - A global sensitivity analysis study

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2011-01-01

    Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based....... The outcome of this study contributes to a better understanding of uncertainty in WWTPs, and explicitly demonstrates the significance of secondary settling processes that are crucial elements of model prediction under dry and wet-weather loading conditions....

  2. An Ecological-Transactional Model of Significant Risk Factors for Child Psychopathology in Outer Mongolia

    Science.gov (United States)

    Kohrt, Holbrook E.; Kohrt, Brandon A.; Waldman, Irwin; Saltzman, Kasey; Carrion, Victor G.

    2004-01-01

    The present study examined significant risk factors, including child maltreatment, for child psychopathology in a cross-cultural setting. Ninety-nine Mongolian boys, ages 3-10 years, were assessed. Primary caregivers (PCG) completed structured interviews including the Emory Combined Rating Scale (ECRS) and the Mood and Feelings Questionnaire…

  3. The Effectiveness of a Cohort Model as a Predictor of Grade Point Average and Graduation Status of Pre-Health Sciences Students in a Public Community College

    Science.gov (United States)

    Brandon, Elvis Nash

    2017-01-01

    There is a college completion crisis in the United States. In today's competitive job market, health sciences students cannot afford to fail in their educational attainment. The purpose of this study was to determine if participation in the cohort model is a predictor of the success of public community college pre-health sciences students.…

  4. Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Felix F. Gonzalez-Navarro

    2016-10-01

    Full Text Available Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization.

  5. A significant advantage for trapped field magnet applications—A failure of the critical state model

    Science.gov (United States)

    Weinstein, Roy; Parks, Drew; Sawh, Ravi-Persad; Carpenter, Keith; Davey, Kent

    2015-10-01

    Ongoing research has increased achievable field in trapped field magnets (TFMs) to multi-Tesla levels. This has greatly increased the attractiveness of TFMs for applications. However, it also increases the already very difficult problem of in situ activation and reactivation of the TFMs. The pulsed zero-field-cool (ZFC) method of activation is used in most applications because it can be accomplished with much lower power and more modest equipment than field-cool activation. The critical state model (CSM) has been a reliable theoretical tool for experimental analysis and engineering design of TFMs and their applications for over a half-century. The activating field, BA, required to fully magnetize a TFM to its maximum trappable field, BT,max, using pulsed-ZFC is predicted by CSM to be R ≡ BA/BT,max ≥ 2.0. We report here experiments on R as a function of Jc, which find a monotonic decrease of R to 1.0 as Jc increases. The reduction to R = 1.0 reduces the power needed to magnetize TFMs by about an order of magnitude. This is a critical advantage for TFM applications. The results also indicate the limits of applicability of CSM, and shed light on the physics omitted from the model. The experimental results rule out heating effects and pinning center geometry as causes of the decrease in R. A possible physical cause is proposed.

  6. On the selection of significant variables in a model for the deteriorating process of facades

    Science.gov (United States)

    Serrat, C.; Gibert, V.; Casas, J. R.; Rapinski, J.

    2017-10-01

    In previous works the authors of this paper have introduced a predictive system that uses survival analysis techniques for the study of time-to-failure in the facades of a building stock. The approach is population based, in order to obtain information on the evolution of the stock across time, and to help the manager in the decision making process on global maintenance strategies. For the decision making it is crutial to determine those covariates -like materials, morphology and characteristics of the facade, orientation or environmental conditions- that play a significative role in the progression of different failures. The proposed platform also incorporates an open source GIS plugin that includes survival and test moduli that allow the investigator to model the time until a lesion taking into account the variables collected during the inspection process. The aim of this paper is double: a) to shortly introduce the predictive system, as well as the inspection and the analysis methodologies and b) to introduce and illustrate the modeling strategy for the deteriorating process of an urban front. The illustration will be focused on the city of L’Hospitalet de Llobregat (Barcelona, Spain) in which more than 14,000 facades have been inspected and analyzed.

  7. A mediation model linking dispatcher leadership and work ownership with safety climate as predictors of truck driver safety performance.

    Science.gov (United States)

    Zohar, Dov; Huang, Yueng-hsiang; Lee, Jin; Robertson, Michelle

    2014-01-01

    The study was designed to test the effect of safety climate on safety behavior among lone employees whose work environment promotes individual rather than consensual or shared climate perceptions. The paper presents a mediation path model linking psychological (individual-level) safety climate antecedents and consequences as predictors of driving safety of long-haul truck drivers. Climate antecedents included dispatcher (distant) leadership and driver work ownership, two contextual attributes of lone work, whereas its proximal consequence included driving safety. Using a prospective design, safety outcomes, consisting of hard-braking frequency (i.e. traffic near-miss events) were collected six months after survey completion, using GPS-based truck deceleration data. Results supported the hypothesized model, indicating that distant leadership style and work ownership promote psychological safety climate perceptions, with subsequent prediction of hard-braking events mediated by driving safety. Theoretical and practical implications for studying safety climate among lone workers in general and professional drivers in particular are discussed. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Anxiety after completion of treatment for early-stage breast cancer: a systematic review to identify candidate predictors and evaluate multivariable model development.

    Science.gov (United States)

    Harris, Jenny; Cornelius, Victoria; Ream, Emma; Cheevers, Katy; Armes, Jo

    2017-07-01

    The purpose of this review was to identify potential candidate predictors of anxiety in women with early-stage breast cancer (BC) after adjuvant treatments and evaluate methodological development of existing multivariable models to inform the future development of a predictive risk stratification model (PRSM). Databases (MEDLINE, Web of Science, CINAHL, CENTRAL and PsycINFO) were searched from inception to November 2015. Eligible studies were prospective, recruited women with stage 0-3 BC, used a validated anxiety outcome ≥3 months post-treatment completion and used multivariable prediction models. Internationally accepted quality standards were used to assess predictive risk of bias and strength of evidence. Seven studies were identified: five were observational cohorts and two secondary analyses of RCTs. Variability of measurement and selective reporting precluded meta-analysis. Twenty-one candidate predictors were identified in total. Younger age and previous mental health problems were identified as risk factors in ≥3 studies. Clinical variables (e.g. treatment, tumour grade) were not identified as predictors in any studies. No studies adhered to all quality standards. Pre-existing vulnerability to mental health problems and younger age increased the risk of anxiety after completion of treatment for BC survivors, but there was no evidence that chemotherapy was a predictor. Multiple predictors were identified but many lacked reproducibility or were not measured across studies, and inadequate reporting did not allow full evaluation of the multivariable models. The use of quality standards in the development of PRSM within supportive cancer care would improve model quality and performance, thereby allowing professionals to better target support for patients.

  9. Use of Standard Deviations as Predictors in Models Using Large-Scale International Data Sets

    Science.gov (United States)

    Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad

    2017-01-01

    Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

  10. Global climate change model natural climate variation: Paleoclimate data base, probabilities and astronomic predictors

    Energy Technology Data Exchange (ETDEWEB)

    Kukla, G.; Gavin, J. [Columbia Univ., Palisades, NY (United States). Lamont-Doherty Geological Observatory

    1994-05-01

    This report was prepared at the Lamont-Doherty Geological Observatory of Columbia University at Palisades, New York, under subcontract to Pacific Northwest Laboratory it is a part of a larger project of global climate studies which supports site characterization work required for the selection of a potential high-level nuclear waste repository and forms part of the Performance Assessment Scientific Support (PASS) Program at PNL. The work under the PASS Program is currently focusing on the proposed site at Yucca Mountain, Nevada, and is under the overall direction of the Yucca Mountain Project Office US Department of Energy, Las Vegas, Nevada. The final results of the PNL project will provide input to global atmospheric models designed to test specific climate scenarios which will be used in the site specific modeling work of others. The primary purpose of the data bases compiled and of the astronomic predictive models is to aid in the estimation of the probabilities of future climate states. The results will be used by two other teams working on the global climate study under contract to PNL. They are located at and the University of Maine in Orono, Maine, and the Applied Research Corporation in College Station, Texas. This report presents the results of the third year`s work on the global climate change models and the data bases describing past climates.

  11. A differential-geometric approach to generalized linear models with grouped predictors

    NARCIS (Netherlands)

    Augugliaro, Luigi; Mineo, Angelo M.; Wit, Ernst C.

    We propose an extension of the differential-geometric least angle regression method to perform sparse group inference in a generalized linear model. An efficient algorithm is proposed to compute the solution curve. The proposed group differential-geometric least angle regression method has important

  12. Dispositional and Environmental Predictors of the Development of Internalizing Problems in Childhood: Testing a Multilevel Model.

    Science.gov (United States)

    Hastings, Paul D; Helm, Jonathan; Mills, Rosemary S L; Serbin, Lisa A; Stack, Dale M; Schwartzman, Alex E

    2015-07-01

    This investigation evaluated a multilevel model of dispositional and environmental factors contributing to the development of internalizing problems from preschool-age to school-age. In a sample of 375 families (185 daughters, 190 sons) drawn from three independent samples, preschoolers' behavioral inhibition, cortisol and gender were examined as moderators of the links between mothers' negative parenting behavior, negative emotional characteristics, and socioeconomic status when children were 3.95 years, and their internalizing problems when they were 8.34 years. Children's dispositional characteristics moderated all associations between these environmental factors and mother-reported internalizing problems in patterns that were consistent with either diathesis-stress or differential-susceptibility models of individual-environment interaction, and with gender models of developmental psychopathology. Greater inhibition and lower socioeconomic status were directly predictive of more teacher reported internalizing problems. These findings highlight the importance of using multilevel models within a bioecological framework to understand the complex pathways through which internalizing difficulties develop.

  13. Computational models as predictors of HIV treatment outcomes for the Phidisa cohort in South Africa

    NARCIS (Netherlands)

    Revell, Andrew; Khabo, Paul; Ledwaba, Lotty; Emery, Sean; Wang, Dechao; Wood, Robin; Morrow, Carl; Tempelman, Hugo; Hamers, Raph L.; Reiss, Peter; van Sighem, Ard; Pozniak, Anton; Montaner, Julio; Lane, H. Clifford; Larder, Brendan

    2016-01-01

    Background: Selecting the optimal combination of HIV drugs for an individual in resourcelimited settings is challenging because of the limited availability of drugs and genotyping. Objective: The evaluation as a potential treatment support tool of computational models that predict response to

  14. The significance of parks to physical activity and public health: a conceptual model.

    Science.gov (United States)

    Bedimo-Rung, Ariane L; Mowen, Andrew J; Cohen, Deborah A

    2005-02-01

    Park-based physical activity is a promising means to satisfy current physical activity requirements. However, there is little research concerning what park environmental and policy characteristics might enhance physical activity levels. This study proposes a conceptual model to guide thinking and suggest hypotheses. This framework describes the relationships between park benefits, park use, and physical activity, and the antecedents/correlates of park use. In this classification scheme, the discussion focuses on park environmental characteristics that could be related to physical activity, including park features, condition, access, aesthetics, safety, and policies. Data for these categories should be collected within specific geographic areas in or around the park, including activity areas, supporting areas, the overall park, and the surrounding neighborhood. Future research should focus on how to operationalize specific measures and methodologies for collecting data, as well as measuring associations between individual physical activity levels and specific park characteristics. Collaboration among many disciplines is needed.

  15. Breast cancer-associated metastasis is significantly increased in a model of autoimmune arthritis

    Science.gov (United States)

    Das Roy, Lopamudra; Pathangey, Latha B; Tinder, Teresa L; Schettini, Jorge L; Gruber, Helen E; Mukherjee, Pinku

    2009-01-01

    Introduction Sites of chronic inflammation are often associated with the establishment and growth of various malignancies including breast cancer. A common inflammatory condition in humans is autoimmune arthritis (AA) that causes inflammation and deformity of the joints. Other systemic effects associated with arthritis include increased cellular infiltration and inflammation of the lungs. Several studies have reported statistically significant risk ratios between AA and breast cancer. Despite this knowledge, available for a decade, it has never been questioned if the site of chronic inflammation linked to AA creates a milieu that attracts tumor cells to home and grow in the inflamed bones and lungs which are frequent sites of breast cancer metastasis. Methods To determine if chronic inflammation induced by autoimmune arthritis contributes to increased breast cancer-associated metastasis, we generated mammary gland tumors in SKG mice that were genetically prone to develop AA. Two breast cancer cell lines, one highly metastatic (4T1) and the other non-metastatic (TUBO) were used to generate the tumors in the mammary fat pad. Lung and bone metastasis and the associated inflammatory milieu were evaluated in the arthritic versus the non-arthritic mice. Results We report a three-fold increase in lung metastasis and a significant increase in the incidence of bone metastasis in the pro-arthritic and arthritic mice compared to non-arthritic control mice. We also report that the metastatic breast cancer cells augment the severity of arthritis resulting in a vicious cycle that increases both bone destruction and metastasis. Enhanced neutrophilic and granulocytic infiltration in lungs and bone of the pro-arthritic and arthritic mice and subsequent increase in circulating levels of proinflammatory cytokines, such as macrophage colony stimulating factor (M-CSF), interleukin-17 (IL-17), interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), and tumor necrosis factor

  16. Breast-cancer-associated metastasis is significantly increased in a model of autoimmune arthritis.

    Science.gov (United States)

    Das Roy, Lopamudra; Pathangey, Latha B; Tinder, Teresa L; Schettini, Jorge L; Gruber, Helen E; Mukherjee, Pinku

    2009-01-01

    Sites of chronic inflammation are often associated with the establishment and growth of various malignancies including breast cancer. A common inflammatory condition in humans is autoimmune arthritis (AA) that causes inflammation and deformity of the joints. Other systemic effects associated with arthritis include increased cellular infiltration and inflammation of the lungs. Several studies have reported statistically significant risk ratios between AA and breast cancer. Despite this knowledge, available for a decade, it has never been questioned if the site of chronic inflammation linked to AA creates a milieu that attracts tumor cells to home and grow in the inflamed bones and lungs which are frequent sites of breast cancer metastasis. To determine if chronic inflammation induced by autoimmune arthritis contributes to increased breast cancer-associated metastasis, we generated mammary gland tumors in SKG mice that were genetically prone to develop AA. Two breast cancer cell lines, one highly metastatic (4T1) and the other non-metastatic (TUBO) were used to generate the tumors in the mammary fat pad. Lung and bone metastasis and the associated inflammatory milieu were evaluated in the arthritic versus the non-arthritic mice. We report a three-fold increase in lung metastasis and a significant increase in the incidence of bone metastasis in the pro-arthritic and arthritic mice compared to non-arthritic control mice. We also report that the metastatic breast cancer cells augment the severity of arthritis resulting in a vicious cycle that increases both bone destruction and metastasis. Enhanced neutrophilic and granulocytic infiltration in lungs and bone of the pro-arthritic and arthritic mice and subsequent increase in circulating levels of proinflammatory cytokines, such as macrophage colony stimulating factor (M-CSF), interleukin-17 (IL-17), interleukin-6 (IL-6), vascular endothelial growth factor (VEGF), and tumor necrosis factor-alpha (TNF-alpha) may contribute

  17. Social support and personal models of diabetes as predictors of self- care and well-being

    DEFF Research Database (Denmark)

    Skinner, T. Chas; John, Mary; Hampson, Sarah E.

    2000-01-01

    Objectives: To examine whether peer support and illness representation mediate the link between family support, self-management and well-being. Method: Fifty-two adolescents (12-18 years old) with Type I diabetes were recruited and followed over 6 months, completing assessments of self- management...... model beliefs. In particular, beliefs about the effectiveness of the diabetes treatment regimen to control diabetes was predictive of better dietary self-care. Conclusions: Both friends and family are important to support adolescents as they live with and manage their diabetes. Personal models......, well-being, and social support. Results: Perceived impact of diabetes and supportive family and friends were prospectively predictive of participants' well-being measures. Although support from family and friends was predictive of better dietary self-care, this relationship was mediated by personal...

  18. Pre-treatment growth and IGF-I deficiency as main predictors of response to growth hormone therapy in neural models

    Directory of Open Access Journals (Sweden)

    Urszula Smyczyn´ska

    2018-01-01

    Full Text Available Mathematical models have been applied in prediction of growth hormone treatment effectiveness in children since the end of 1990s. Usually they were multiple linear regression models; however, there are also examples derived by empirical non-linear methods. Proposed solution consists in application of machine learning technique – artificial neural networks – to analyse this problem. This new methodology, contrary to previous ones, allows detection of both linear and non-linear dependencies without assuming their character a priori. The aims of this work included: development of models predicting separately growth during 1st year of treatment and final height as well as identification of important predictors and in-depth analysis of their influence on treatment’s effectiveness. The models were derived on the basis of clinical data of 272 patients treated for at least 1 year, 133 of whom have already attained final height. Starting from models containing 17 and 20 potential predictors, respectively for 1st year and final height model, we were able to reduce their number to 9 and 10. Basing on the final models, IGF-I concentration and earlier growth were indicated as belonging to most important predictors of response to GH therapy, while results of GH secretion tests were automatically excluded as insignificant. Moreover, majority of the dependencies were observed to be non-linear, thus using neural networks seems to be reasonable approach despite it being more complex than previously applied methods.

  19. Thermophysical modeling of asteroids from WISE thermal infrared data - Significance of the shape model and the pole orientation uncertainties

    Science.gov (United States)

    Hanuš, J.; Delbo', M.; Ďurech, J.; Alí-Lagoa, V.

    2015-08-01

    In the analysis of thermal infrared data of asteroids by means of thermophysical models (TPMs) it is a common practice to neglect the uncertainty of the shape model and the rotational state, which are taken as an input for the model. Here, we present a novel method of investigating the importance of the shape model and the pole orientation uncertainties in the thermophysical modeling - the varied shape TPM (VS-TPM). Our method uses optical photometric data to generate various shape models that map the uncertainty in the shape and the rotational state. The TPM procedure is then run for all these shape models. We apply the implementation of the classical TPM as well as our VS-TPM to the convex shape models of several asteroids together with their thermal infrared data acquired by the NASA's Wide-field Infrared Survey Explorer (WISE) and compare the results. These show that the uncertainties of the shape model and the pole orientation can be very important (e.g., for the determination of the thermal inertia) and should be considered in the thermophysical analyses. We present thermophysical properties for six asteroids - (624) Hektor, (771) Libera, (1036) Ganymed, (1472) Muonio, (1627) Ivar, and (2606) Odessa.

  20. Insects on pig carcasses as a model for predictor of death interval in forensic medicine

    OpenAIRE

    Sunny Wangko; Erwin G. Kristanto; Sonny J.R. Kalangi; Johannes Huijbregts; Dantje T. Sembel

    2015-01-01

    Background: Forensic entomology has not been acknowledged in Indonesia so far. Indonesian carrion insects are very rarely reported. The aim of this study was to obtain the types of insects on pig carcasses that could be used for the estimation of post-mortem interval.Methods: Four domestic pigs sacrificed with different methods were used as a model. The carcasses were observed twice daily (around 9 a.m and 4 p.m) during 15 days to assess the stages of decomposition and to collect insects, bot...

  1. Myriocin significantly increases the mortality of a non-mammalian model host during Candida pathogenesis.

    Directory of Open Access Journals (Sweden)

    Nadja Rodrigues de Melo

    Full Text Available Candida albicans is a major human pathogen whose treatment is challenging due to antifungal drug toxicity, drug resistance and paucity of antifungal agents available. Myrocin (MYR inhibits sphingosine synthesis, a precursor of sphingolipids, an important cell membrane and signaling molecule component. MYR also has dual immune suppressive and antifungal properties, potentially modulating mammalian immunity and simultaneously reducing fungal infection risk. Wax moth (Galleria mellonella larvae, alternatives to mice, were used to establish if MYR suppressed insect immunity and increased survival of C. albicans-infected insects. MYR effects were studied in vivo and in vitro, and compared alone and combined with those of approved antifungal drugs, fluconazole (FLC and amphotericin B (AMPH. Insect immune defenses failed to inhibit C. albicans with high mortalities. In insects pretreated with the drug followed by C. albicans inoculation, MYR+C. albicans significantly increased mortality to 93% from 67% with C. albicans alone 48 h post-infection whilst AMPH+C. albicans and FLC+C. albicans only showed 26% and 0% mortalities, respectively. MYR combinations with other antifungal drugs in vivo also enhanced larval mortalities, contrasting the synergistic antifungal effect of the MYR+AMPH combination in vitro. MYR treatment influenced immunity and stress management gene expression during C. albicans pathogenesis, modulating transcripts putatively associated with signal transduction/regulation of cytokines, I-kappaB kinase/NF-kappaB cascade, G-protein coupled receptor and inflammation. In contrast, all stress management gene expression was down-regulated in FLC and AMPH pretreated C. albicans-infected insects. Results are discussed with their implications for clinical use of MYR to treat sphingolipid-associated disorders.

  2. Myriocin Significantly Increases the Mortality of a Non-Mammalian Model Host during Candida Pathogenesis

    Science.gov (United States)

    de Melo, Nadja Rodrigues; Abdrahman, Ahmed; Greig, Carolyn; Mukherjee, Krishnendu; Thornton, Catherine; Ratcliffe, Norman A.; Vilcinskas, Andreas; Butt, Tariq M.

    2013-01-01

    Candida albicans is a major human pathogen whose treatment is challenging due to antifungal drug toxicity, drug resistance and paucity of antifungal agents available. Myrocin (MYR) inhibits sphingosine synthesis, a precursor of sphingolipids, an important cell membrane and signaling molecule component. MYR also has dual immune suppressive and antifungal properties, potentially modulating mammalian immunity and simultaneously reducing fungal infection risk. Wax moth (Galleria mellonella) larvae, alternatives to mice, were used to establish if MYR suppressed insect immunity and increased survival of C. albicans-infected insects. MYR effects were studied in vivo and in vitro, and compared alone and combined with those of approved antifungal drugs, fluconazole (FLC) and amphotericin B (AMPH). Insect immune defenses failed to inhibit C. albicans with high mortalities. In insects pretreated with the drug followed by C. albicans inoculation, MYR+C. albicans significantly increased mortality to 93% from 67% with C. albicans alone 48 h post-infection whilst AMPH+C. albicans and FLC+C. albicans only showed 26% and 0% mortalities, respectively. MYR combinations with other antifungal drugs in vivo also enhanced larval mortalities, contrasting the synergistic antifungal effect of the MYR+AMPH combination in vitro. MYR treatment influenced immunity and stress management gene expression during C. albicans pathogenesis, modulating transcripts putatively associated with signal transduction/regulation of cytokines, I-kappaB kinase/NF-kappaB cascade, G-protein coupled receptor and inflammation. In contrast, all stress management gene expression was down-regulated in FLC and AMPH pretreated C. albicans -infected insects. Results are discussed with their implications for clinical use of MYR to treat sphingolipid-associated disorders. PMID:24260135

  3. Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2014-01-01

    Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks...... (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D......) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution...

  4. Model Pemesanan Bahan Baku menggunakan Peramalan Time Series dengan CB Predictor

    Directory of Open Access Journals (Sweden)

    Tri Pujadi

    2014-12-01

    Full Text Available A company that manufactures finished goods often faces a shortage of raw materials, due to the determination of the quantity of raw material ordering improper because it is done by intuition and the lack of raw material inventory reserves. This resulted in costs because inefficient production processes are inhibited or had to perform an emergency procurement of raw materials to meet customer orders. The company seeks to use the method in determining the order quantity of raw material, comprising the steps of (1 collecting historical data of raw material use, step (2 forecasting needs raw materials, step (3 calculating the order quantity forecasting based on the data by comparing the deterministic method and probabilistic methods. Calculating safety stock for each raw material is done so as to cope with the situation outside of normal conditions, such a surge in orders. In its design, the system will be developed using the Unified Modeling Language modeling language (UML on the basis of the concept of object-oriented analysis and design (Object Oriented Analysis and Design. With the proposed implementation of the information system, the company can estimate the need for raw materials more quickly and accurately, and can determine the order quantity that is tailored to the needs. So that the costs associated with ordering and storage of raw materials can be minimized.

  5. Predictors of quality of life in Portuguese obese patients: a structural equation modeling application.

    Science.gov (United States)

    Vilhena, Estela; Pais-Ribeiro, José; Silva, Isabel; Cardoso, Helena; Mendonça, Denisa

    2014-01-01

    Living with obesity is an experience that may affect multiple aspects of an individual's life. Obesity is considered a relevant public health problem in modern societies. To determine the comparative efficacy of different treatments and to assess their impact on patients' everyday life, it is important to identify factors that are relevant to the quality of life of obese patients. The present study aims to evaluate, in Portuguese obese patients, the simultaneous impact of several psychosocial factors on quality of life. This study also explores the mediating role of stigma in the relationship between positive/negative affect and quality of life. A sample of 215 obese patients selected from the main hospitals in Portugal completed self-report questionnaires to assess sociodemographic, clinical, psychosocial, and quality of life variables. Data were analysed using structural equation modeling. The model fitted the data reasonably well, CFI = 0.9, RMSEA = 0.06. More enthusiastic and more active patients had a better quality of life. Those who reflect lower perception of stigma had a better physical and mental health. Partial mediation effects of stigma between positive affect and mental health and between negative affect and physical health were found. The stigma is pervasive and causes consequences for psychological and physical health.

  6. Predictors of Quality of Life in Portuguese Obese Patients: A Structural Equation Modeling Application

    Directory of Open Access Journals (Sweden)

    Estela Vilhena

    2014-01-01

    Full Text Available Living with obesity is an experience that may affect multiple aspects of an individual’s life. Obesity is considered a relevant public health problem in modern societies. To determine the comparative efficacy of different treatments and to assess their impact on patients’ everyday life, it is important to identify factors that are relevant to the quality of life of obese patients. The present study aims to evaluate, in Portuguese obese patients, the simultaneous impact of several psychosocial factors on quality of life. This study also explores the mediating role of stigma in the relationship between positive/negative affect and quality of life. A sample of 215 obese patients selected from the main hospitals in Portugal completed self-report questionnaires to assess sociodemographic, clinical, psychosocial, and quality of life variables. Data were analysed using structural equation modeling. The model fitted the data reasonably well, CFI = 0.9, RMSEA = 0.06. More enthusiastic and more active patients had a better quality of life. Those who reflect lower perception of stigma had a better physical and mental health. Partial mediation effects of stigma between positive affect and mental health and between negative affect and physical health were found. The stigma is pervasive and causes consequences for psychological and physical health.

  7. Predictors of Drinking Water Boiling and Bottled Water Consumption in Rural China: A Hierarchical Modeling Approach.

    Science.gov (United States)

    Cohen, Alasdair; Zhang, Qi; Luo, Qing; Tao, Yong; Colford, John M; Ray, Isha

    2017-06-20

    Approximately two billion people drink unsafe water. Boiling is the most commonly used household water treatment (HWT) method globally and in China. HWT can make water safer, but sustained adoption is rare and bottled water consumption is growing. To successfully promote HWT, an understanding of associated socioeconomic factors is critical. We collected survey data and water samples from 450 rural households in Guangxi Province, China. Covariates were grouped into blocks to hierarchically construct modified Poisson models and estimate risk ratios (RR) associated with boiling methods, bottled water, and untreated water. Female-headed households were most likely to boil (RR = 1.36, p boiled. Our findings show that boiling is not an undifferentiated practice, but one with different methods of varying effectiveness, environmental impact, and adoption across socioeconomic strata. Our results can inform programs to promote safer and more efficient boiling using electric kettles, and suggest that if rural China's economy continues to grow then bottled water use will increase.

  8. Social support and personal models of diabetes as predictors of self- care and well-being

    DEFF Research Database (Denmark)

    Skinner, T. Chas; John, Mary; Hampson, Sarah E.

    2000-01-01

    , well-being, and social support. Results: Perceived impact of diabetes and supportive family and friends were prospectively predictive of participants' well-being measures. Although support from family and friends was predictive of better dietary self-care, this relationship was mediated by personal...... of diabetes are important determinants of both dietary self-care and well-being. In addition, personal models may serve to mediate the relationship between social support and dietary behavior.......Objectives: To examine whether peer support and illness representation mediate the link between family support, self-management and well-being. Method: Fifty-two adolescents (12-18 years old) with Type I diabetes were recruited and followed over 6 months, completing assessments of self- management...

  9. Predictors of biochemical failure in patients undergoing prostate whole-gland salvage cryotherapy: a novel risk stratification model.

    Science.gov (United States)

    Spiess, Philippe E; Levy, David A; Mouraviev, Vladimir; Pisters, Louis L; Jones, J Stephen

    2013-08-01

    What's known on the subject? and what does the study add?: Previous studies have identified the most important prognostic factors of the likely outcomes of salvage prostate whole-gland ablation, including initial clinical stage, biopsy Gleason score, and PSA (total and doubling time). There is potential for further optimization of candidate selection for salvage cryoablation with curative intent and nadir PSA achieved after whole-gland cryotherapy may provide additional prognostic value. The study shows that the most important prognostic factors of biochemical progression-free survival for patients who have undergone whole-gland salvage prostate cryotherapy are nadir PSA achieved after therapy and pre-therapy biopsy Gleason score. Based on these two prognostic variables, we have identified risk stratification groups (low, intermediate and high) which help predict the expected outcomes of salvage whole-gland prostate cryotherapy in a given patient. This risk stratification constitutes a useful clinical tool in defining which patients maybe best suited for this local salvage treatment method. To assess the prognostic variables predicting the risk of biochemical progression-free survival (bPFS) after salvage prostate whole-gland cryotherapy using the Phoenix definition of bPFS. A total of 132 patients underwent prostate whole-gland salvage cryotherapy with curative intent. No patient underwent neoadjuvant/adjuvant hormonal ablative therapy, and all had extended post-salvage prostate-specific antigen (PSA) follow-up data. Cox univariate and multivariate logistic regression analyses of potential predictors of bPFS were conducted. Kaplan-Meier analyses of bPFS was also performed. At a mean (range) follow-up of 4.3 (0.9-12.7) years, the median (range) post-cryotherapy nadir PSA achieved was 0.17 (0-33.9) ng/mL. On multivariate analysis, predictors of bPFS were nadir PSA post-cryotherapy and pre-salvage biopsy Gleason score (P 2.5 ng/mL or biopsy Gleason score ≥ 7, with

  10. A comparison of predictive models for the onset of significant void at low pressures in forced-convection subcooled boiling

    International Nuclear Information System (INIS)

    Lee, S. C.; Bankoff, S. G.

    1998-01-01

    The predictive models for the Onset of Significant Void (OSV) in forced-convection subcooled boiling are reviewed and compared with extensive data. Three analytical models and seven empirical correlations are considered in this paper. These models and correlations are put onto a common basis and are compared, again on a common basis, with a variety of data. The evaluation of their range of validity and applicability under various operating conditions are discussed. The results show that the correlations of Saha-Zuber (1974) seems to be the best model to predict OSV in vertical subcooled boiling flow

  11. Insects on pig carcasses as a model for predictor of death interval in forensic medicine

    Directory of Open Access Journals (Sweden)

    Sunny Wangko

    2015-07-01

    Full Text Available Background: Forensic entomology has not been acknowledged in Indonesia so far. Indonesian carrion insects are very rarely reported. The aim of this study was to obtain the types of insects on pig carcasses that could be used for the estimation of post-mortem interval.Methods: Four domestic pigs sacrificed with different methods were used as a model. The carcasses were observed twice daily (around 9 a.m and 4 p.m during 15 days to assess the stages of decomposition and to collect insects, both in mature and immature stages. The immature insects were reared and the mature insects were indentified in the Laboratory of Pests and Plant Diseases, University of Sam Ratulangi, Manado. Chrysomya megacephala and C. rufifacies were identified both morphologically and with deoxyribose-nucleic acid (DNA techniques.Results: Five stages of decomposition (fresh, bloated, active decay, post-decay, and skeletonization were observed. A total of 11 Diptera and 8 Coleoptera species were found during a 15-days succession study. Chrysomya megacephala, C. rufifacies and Hermetia illucens colonized in all carcasses.Conclusion: Insects found on four different pig carcasses consisted mainly of widespread Diptera and Coleoptera. Chrysomya megacephala, C. rufifacies and Hermetia illucens seemed to be primary candidates for the estimation of the post-mortem interval.

  12. Predictors of diabetes outcomes in Mexico: testing the Hispanic health protection model.

    Science.gov (United States)

    Latham, Christine L; Calvillo, Evelyn

    2013-07-01

    Given the high morbidity and mortality rate of Hispanic immigrants to the United States, a study of the Hispanic Health Protection Model (HHPM) was replicated with 109 residents in Mexico who were newly diagnosed with diabetes. People with diabetes from rural clinics in Tlaxcala underwent a three-phase interview process with laboratory and weight follow-up over 4 to 6 months following a confirmed diagnosis of diabetes. This predictive, correlational study replicated the HHPM and the previous U.S. findings, including relationships between lifestyle profile, health beliefs, professional and social support, self-efficacy, diabetes knowledge, quality of life (self-satisfaction and impact of diabetes), and changes in HbA1c and body mass index. The study found that participants frequently followed good lifestyle practices while continuing to adhere to culturally based treatment and attribution beliefs. There were moderate perceptions of diabetes self-care efficacy, low ratings of support, very poor understanding of diabetes, continued obesity, acceptable quality of life ratings, and near-normal HbA1c levels.

  13. Clinical and microperimetric predictors of reading speed in low vision patients: a structural equation modeling approach.

    Science.gov (United States)

    Giacomelli, Giovanni; Virgili, Gianni; Giansanti, Fabrizio; Sato, Giovanni; Cappello, Ezio; Cruciani, Filippo; Varano, Monica; Menchini, Ugo

    2013-06-27

    To investigate the simultaneous association of several psychophysical measures with reading ability in patients with mild and moderate low vision attending rehabilitation services. Standard measurements of reading ability (Minnesota Reading [MNREAD] charts), visual acuity (Early Treatment of Diabetic Retinopathy Study [ETDRS] charts), contrast sensitivity (Pelli-Robson charts), reading contrast threshold (Reading Explorer [REX] charts), retinal sensitivity, and fixation stability and localization (Micro Perimeter 1 [MP1] fundus perimetry) were obtained in 160 low vision patients with better eye visual acuity ranging from 0.3 to 1.0 logarithm of the minimum angle of resolution and affected by either age-related macular degeneration or diabetic retinopathy. All variables were moderately associated with reading performance measures (MNREAD reading speed and reading acuity and REX reading contrast threshold), as well as among each other. In a structural equation model, REX reading contrast threshold was highly associated with MNREAD reading speed (standardized coefficient, 0.63) and moderately associated with reading acuity (standardized coefficient, -0.30). REX test also mediated the effects of Pelli-Robson contrast sensitivity (standardized coefficient, 0.44), MP1 fixation eccentricity (standardized coefficient, -0.19), and the mean retinal sensitivity (standardized coefficient, 0.23) on reading performance. The MP1 fixation stability was associated with both MNREAD reading acuity (standardized coefficient, -0.24) and MNREAD reading speed (standardized coefficient, 0.23), while ETDRS visual acuity only affected reading acuity (standardized coefficient, 0.44). Fixation instability and contrast sensitivity loss are key factors limiting reading performance of patients with mild or moderate low vision. REX charts directly assess the impact of text contrast on letter recognition and text navigation and may be a useful aid in reading rehabilitation.

  14. Personality-related factors as predictors of help-seeking for depression: a population-based study applying the Behavioral Model of Health Services Use.

    Science.gov (United States)

    Schomerus, Georg; Appel, Katja; Meffert, Peter J; Luppa, Melanie; Andersen, Ronald M; Grabe, Hans J; Baumeister, Sebastian E

    2013-11-01

    Although the prevalence of mental disorders and the demand for mental health services are increasing, little is known about the impact of personality-related factors on help-seeking among depressive individuals. We, therefore, investigated the relationship between the "Big Five" personality traits, resilience, alexithymia, childhood neglect or abuse, and help-seeking among depressive individuals. We used data from 354 persons with a diagnosis of major depression from the population-based cohort study of health in Pomerania within the theoretical framework of the Andersen Behavioral Model of Health Services Use. Using stepwise regression techniques, we found that older age, higher education, more perceived social support, presence of childhood abuse, higher levels of conscientiousness, lower levels of resilience, and more severe depression were associated with help-seeking for depression. In contrast, gender, extraversion, openness, agreeableness, neuroticism, and alexithymia did not significantly predict help-seeking. In addition, no evidence for gender-specific effects was observed. Personality-related predisposing factors are important predictors of help-seeking. The influence of resilience on help-seeking among depressed individuals merits further exploration.

  15. Hydrothermal Fe cycling and deep ocean organic carbon scavenging: Model-based evidence for significant POC supply to seafloor sediments

    Digital Repository Service at National Institute of Oceanography (India)

    German, C.R.; Legendre, L.L.; Sander, S.G.;; Niquil, N.; Luther-III, G.W.; LokaBharathi, P.A.; Han, X.; LeBris, N.

    by more than ~10% over background values, what the model does indicate is that scavenging of carbon in association with Fe-rich hydrothermal plume particles should play a significant role in the delivery of particulate organic carbon to deep ocean...

  16. ToPs: Ensemble Learning With Trees of Predictors

    Science.gov (United States)

    Yoon, Jinsung; Zame, William R.; van der Schaar, Mihaela

    2018-04-01

    We present a new approach to ensemble learning. Our approach constructs a tree of subsets of the feature space and associates a predictor (predictive model) - determined by training one of a given family of base learners on an endogenously determined training set - to each node of the tree; we call the resulting object a tree of predictors. The (locally) optimal tree of predictors is derived recursively; each step involves jointly optimizing the split of the terminal nodes of the previous tree and the choice of learner and training set (hence predictor) for each set in the split. The feature vector of a new instance determines a unique path through the optimal tree of predictors; the final prediction aggregates the predictions of the predictors along this path. We derive loss bounds for the final predictor in terms of the Rademacher complexity of the base learners. We report the results of a number of experiments on a variety of datasets, showing that our approach provides statistically significant improvements over state-of-the-art machine learning algorithms, including various ensemble learning methods. Our approach works because it allows us to endogenously create more complex learners - when needed - and endogenously match both the learner and the training set to the characteristics of the dataset while still avoiding over-fitting.

  17. Use pattern and predictors of use of highly caffeinated energy drinks among South Korean adolescents: a study using the Health Belief Model.

    Science.gov (United States)

    Ha, Dongmun; Song, Inmyung; Jang, Gyeongil; Lee, Eui-Kyung; Shin, Ju-Young

    2017-09-24

    Concerns about the use of highly caffeinated energy drinks among Korean adolescents remains. We compared adolescents' perceptions regarding the use of drinks to their behaviours and factors. A structured questionnaire based on the Health Belief Model was administered to 850 freshmen and sophomores at three high schools in Bucheon, South Korea. Benefits were defined as beneficial effects from the use of highly caffeinated energy drinks (eg, awakening from sleepiness) and harms as adverse effects of the drinks (eg, cardiac palpitation). Likelihood of action represents the likelihood of taking actions that are perceived to be more beneficial after comparison of the benefits and harms of caffeine use. Descriptive analysis was used to quantify the relationship between their beliefs about highly caffeinated energy drinks and their use. We conducted hierarchical logistic regression to compute ORs and 95% CIs for: (1) demographic factors, (2) health threat, (3) likelihood of action and (4) cues to act. Altogether, 833 students responded to the questionnaire (effective response rate=98.0%). About 63.0% reported use of highly caffeinated energy drinks and 35.2% had used them as needed and habitually. The more susceptible the respondents perceived themselves to be to the risk of using these drinks, the less likely they were to use them (OR: 0.73, 95% CI 0.50 to 1.06). The more severe the perception of a health threat, the less that perception was associated with use (OR: 0.44, 95% CI 0.29 to 0.67). Likelihood of action was the strongest predictor of use, explaining 12.5% in use. Benefits and harms (OR: 4.43, 95% CI 2.77 to 7.09; OR: 1.86, 95% CI 1.16 to 2.99) also were significant predictors. Enhancing adolescents' perceptions of benefits and harms regarding using highly caffeinated energy drinks could be an effective way to influence the use of these drinks. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All

  18. Time to recurrence is a significant predictor of cancer-specific survival after recurrence in patients with recurrent renal cell carcinoma--results from a comprehensive multi-centre database (CORONA/SATURN-Project).

    Science.gov (United States)

    Brookman-May, Sabine D; May, Matthias; Shariat, Shahrokh F; Novara, Giacomo; Zigeuner, Richard; Cindolo, Luca; De Cobelli, Ottavio; De Nunzio, Cosimo; Pahernik, Sascha; Wirth, Manfred P; Longo, Nicola; Simonato, Alchiede; Serni, Sergio; Siracusano, Salvatore; Volpe, Alessandro; Morgia, Giuseppe; Bertini, Roberto; Dalpiaz, Orietta; Stief, Christian; Ficarra, Vincenzo

    2013-11-01

    To assess the prognostic impact of time to recurrence (TTR) on cancer-specific survival (CSS) after recurrence in patients with renal cell carcinoma (RCC) undergoing radical nephrectomy or nephron-sparing surgery. To analyse differences in clinical and histopathological criteria between patients with early and late recurrence. Of 13,107 patients with RCC from an international multicentre database, 1712 patients developed recurrence in the follow-up (FU), at a median (interquartile range) of 50.1 (25-106) months. In all, 1402 patients had recurrence at ≤5 years (Group A) and 310 patients beyond this time (Group B). Differences in clinical and histopathological variables between patients with early and late recurrence were analysed. The influence of TTR and further variables on CSS after recurrence was assessed by Cox regression analysis. Male gender, advanced age, tumour diameter and stage, Fuhrman grade 3-4, lymphovascular invasion (LVI), and pN + stage were significantly more frequent in patients with early recurrence, who had a significantly reduced 3-year CSS of 30% compared with patients in Group B (41%; P = 0.001). Age, gender, tumour histology, pT stage, and continuous TTR (hazard ratio 0.99, P = 0.006; monthly interval) independently predicted CSS. By inclusion of dichotomised TTR in the multivariable model, a significant influence of this variable on CSS was present until 48 months after surgery, but not beyond this time. Advanced age, male gender, larger tumour diameters, LVI, Fuhrman grade 3-4, pN + stage, and advanced tumour stages are associated with early recurrence. Up to 4 years from surgery, a shorter TTR independently predicts a reduced CSS after recurrence. © 2013 The Authors. BJU International © 2013 BJU International.

  19. Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis.

    Science.gov (United States)

    Eekhout, Iris; van de Wiel, Mark A; Heymans, Martijn W

    2017-08-22

    Multiple imputation is a recommended method to handle missing data. For significance testing after multiple imputation, Rubin's Rules (RR) are easily applied to pool parameter estimates. In a logistic regression model, to consider whether a categorical covariate with more than two levels significantly contributes to the model, different methods are available. For example pooling chi-square tests with multiple degrees of freedom, pooling likelihood ratio test statistics, and pooling based on the covariance matrix of the regression model. These methods are more complex than RR and are not available in all mainstream statistical software packages. In addition, they do not always obtain optimal power levels. We argue that the median of the p-values from the overall significance tests from the analyses on the imputed datasets can be used as an alternative pooling rule for categorical variables. The aim of the current study is to compare different methods to test a categorical variable for significance after multiple imputation on applicability and power. In a large simulation study, we demonstrated the control of the type I error and power levels of different pooling methods for categorical variables. This simulation study showed that for non-significant categorical covariates the type I error is controlled and the statistical power of the median pooling rule was at least equal to current multiple parameter tests. An empirical data example showed similar results. It can therefore be concluded that using the median of the p-values from the imputed data analyses is an attractive and easy to use alternative method for significance testing of categorical variables.

  20. Prediction error variance and expected response to selection, when selection is based on the best predictor - for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

    DEFF Research Database (Denmark)

    Andersen, Anders Holst; Korsgaard, Inge Riis; Jensen, Just

    2002-01-01

    In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed...

  1. Expression and clinical significance of rhubarb on serum amylase and TNF-alpha of rat model of acute pancreatitis.

    Science.gov (United States)

    Zhang, W F; Li, Z T; Fang, J J; Wang, G B; Yu, Y; Liu, Z Q; Wu, Y N; Zheng, S S; Cai, L

    2017-01-01

    The aim of this study was to evaluate the therapeutic effect of rhubarb extract on acute pancreatitis. Ninety-six healthy Sprague Dawley rats, weighing 301±5.12 g were randomly divided into 4 groups: sham surgery (group A), acute pancreatitis model (group B), acute pancreatitis with normal saline (group C), and acute pancreatitis model with rhubarb (group D). The levels of serum amylase (AMY) and TNF-α were measured at 1st, 6th, 12th and 24th hour after modeling, and the pancreatic tissue were used to observe the pathologic changes. Compared to the sham group, the serum AMY and serum tumor necrosis factor (TNF-α) levels were significantly increased in the other groups (p acute pancreatitis. The rhubarb reduced the serum AMY and TNF-α level in rats with acute pancreatitis and reduced the pathological changes of pancreas and other tissues.

  2. PD-0332991, a CDK4/6 Inhibitor, Significantly Prolongs Survival in a Genetically Engineered Mouse Model of Brainstem Glioma

    Science.gov (United States)

    Barton, Kelly L.; Misuraca, Katherine; Cordero, Francisco; Dobrikova, Elena; Min, Hooney D.; Gromeier, Matthias; Kirsch, David G.; Becher, Oren J.

    2013-01-01

    Diffuse intrinsic pontine glioma (DIPG) is an incurable tumor that arises in the brainstem of children. To date there is not a single approved drug to effectively treat these tumors and thus novel therapies are desperately needed. Recent studies suggest that a significant fraction of these tumors contain alterations in cell cycle regulatory genes including amplification of the D-type cyclins and CDK4/6, and less commonly, loss of Ink4a-ARF leading to aberrant cell proliferation. In this study, we evaluated the therapeutic approach of targeting the cyclin-CDK-Retinoblastoma (Rb) pathway in a genetically engineered PDGF-B-driven brainstem glioma (BSG) mouse model. We found that PD-0332991 (PD), a CDK4/6 inhibitor, induces cell-cycle arrest in our PDGF-B; Ink4a-ARF deficient model both in vitro and in vivo. By contrast, the PDGF-B; p53 deficient model was mostly resistant to treatment with PD. We noted that a 7-day treatment course with PD significantly prolonged survival by 12% in the PDGF-B; Ink4a-ARF deficient BSG model. Furthermore, a single dose of 10 Gy radiation therapy (RT) followed by 7 days of treatment with PD increased the survival by 19% in comparison to RT alone. These findings provide the rationale for evaluating PD in children with Ink4a-ARF deficient gliomas. PMID:24098593

  3. PD-0332991, a CDK4/6 inhibitor, significantly prolongs survival in a genetically engineered mouse model of brainstem glioma.

    Directory of Open Access Journals (Sweden)

    Kelly L Barton

    Full Text Available Diffuse intrinsic pontine glioma (DIPG is an incurable tumor that arises in the brainstem of children. To date there is not a single approved drug to effectively treat these tumors and thus novel therapies are desperately needed. Recent studies suggest that a significant fraction of these tumors contain alterations in cell cycle regulatory genes including amplification of the D-type cyclins and CDK4/6, and less commonly, loss of Ink4a-ARF leading to aberrant cell proliferation. In this study, we evaluated the therapeutic approach of targeting the cyclin-CDK-Retinoblastoma (Rb pathway in a genetically engineered PDGF-B-driven brainstem glioma (BSG mouse model. We found that PD-0332991 (PD, a CDK4/6 inhibitor, induces cell-cycle arrest in our PDGF-B; Ink4a-ARF deficient model both in vitro and in vivo. By contrast, the PDGF-B; p53 deficient model was mostly resistant to treatment with PD. We noted that a 7-day treatment course with PD significantly prolonged survival by 12% in the PDGF-B; Ink4a-ARF deficient BSG model. Furthermore, a single dose of 10 Gy radiation therapy (RT followed by 7 days of treatment with PD increased the survival by 19% in comparison to RT alone. These findings provide the rationale for evaluating PD in children with Ink4a-ARF deficient gliomas.

  4. Significance of hypoxia for tumor response to radiation: Mathematical modeling and analysis of local control and clonogenic assay data

    International Nuclear Information System (INIS)

    Buffa, Francesca Meteora

    2002-01-01

    Various hypotheses for radiation local tumor control probability (ltcp) were modeled, and assessed against local tumor control (LTC) and clonogenic assay (CA) data. For head-and-neck tumors receiving low-LET external-beam irradiation, the best model was a Poisson ltcp accounting for cell repopulation, hypoxia, and tumor volume dependence of radiosensitivity (α). This confirmed that hypoxia is limiting LTC of these tumors, with the magnitude depending upon tumor volume. However, LTC of cervical carcinoma receiving external-beam irradiation and brachytherapy was well described by a model not accounting for hypoxia. Furthermore, when the survival fraction at 2 Gy (SF 2 ) and colony forming efficiency (CFE) measured for individual patients were incorporated into this model, very good correlation with LTC was seen (p=0.0004). After multivariate analysis, this model was the best independent prognostic factor for LTC and patient survival. Furthermore, no difference in prediction was seen when a model based on birth-and-death stochastic theory was used. Two forms of hypoxia are known to be present in tumors: diffusion-limited, chronic hypoxia (CH), and acute, transient hypoxia (TH). A modeling study on WiDr multicellular spheroids showed that the CH effect on LTC is significantly lower than expected from CA. This could arise from energy charge depletion accompanying CH, reducing the number of proliferating clonogenic cells that can repair radiation damage, and thus mitigating the radioresistance of CH cells. This suggests that TH, rather than CH, may be the limiting factor for in vivo LTC. Finally, by computing ltcp using Monte Carlo calculated dose distributions, it was shown that Monte Carlo statistical noise can cause an underestimation of ltcp, with the magnitude depending upon the model hypotheses

  5. DIFFERENCES IN WATER VAPOR RADIATIVE TRANSFER AMONG 1D MODELS CAN SIGNIFICANTLY AFFECT THE INNER EDGE OF THE HABITABLE ZONE

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jun; Wang, Yuwei [Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing (China); Leconte, Jérémy; Forget, François [Laboratoire de Météorologie Dynamique, Institut Pierre Simon Laplace, CNRS, Paris (France); Wolf, Eric T. [Laboratory for Atmospheric and Space Physics, University of Colorado in Boulder, CO (United States); Goldblatt, Colin [School of Earth and Ocean Sciences, University of Victoria, Victoria, BC (Canada); Feldl, Nicole [Division of Geological and Planetary Sciences, California Institute of Technology, CA (United States); Merlis, Timothy [Department of Atmospheric and Oceanic Sciences at McGill University, Montréal (Canada); Koll, Daniel D. B.; Ding, Feng; Abbot, Dorian S., E-mail: junyang@pku.edu.cn, E-mail: abbot@uchicago.edu [Department of the Geophysical Sciences, University of Chicago, Chicago, IL (United States)

    2016-08-01

    An accurate estimate of the inner edge of the habitable zone is critical for determining which exoplanets are potentially habitable and for designing future telescopes to observe them. Here, we explore differences in estimating the inner edge among seven one-dimensional radiative transfer models: two line-by-line codes (SMART and LBLRTM) as well as five band codes (CAM3, CAM4-Wolf, LMDG, SBDART, and AM2) that are currently being used in global climate models. We compare radiative fluxes and spectra in clear-sky conditions around G and M stars, with fixed moist adiabatic profiles for surface temperatures from 250 to 360 K. We find that divergences among the models arise mainly from large uncertainties in water vapor absorption in the window region (10 μ m) and in the region between 0.2 and 1.5 μ m. Differences in outgoing longwave radiation increase with surface temperature and reach 10–20 W m{sup 2}; differences in shortwave reach up to 60 W m{sup 2}, especially at the surface and in the troposphere, and are larger for an M-dwarf spectrum than a solar spectrum. Differences between the two line-by-line models are significant, although smaller than among the band models. Our results imply that the uncertainty in estimating the insolation threshold of the inner edge (the runaway greenhouse limit) due only to clear-sky radiative transfer is ≈10% of modern Earth’s solar constant (i.e., ≈34 W m{sup 2} in global mean) among band models and ≈3% between the two line-by-line models. These comparisons show that future work is needed that focuses on improving water vapor absorption coefficients in both shortwave and longwave, as well as on increasing the resolution of stellar spectra in broadband models.

  6. A methodologic framework for modeling and assessing biomarkers of environmental enteropathy as predictors of growth in infants: an example from a Peruvian birth cohort.

    Science.gov (United States)

    Colston, Josh M; Peñataro Yori, Pablo; Colantuoni, Elizabeth; Moulton, Lawrence H; Ambikapathi, Ramya; Lee, Gwenyth; Rengifo Trigoso, Dixner; Siguas Salas, Mery; Kosek, Margaret N

    2017-07-01

    Background: Environmental enteropathy (EE) impairs the gut's absorptive capacity and immune function and causes decelerations in statural growth that manifest gradually over time. Objective: To illustrate an approach for assessing emerging biomarkers of EE, we separately assessed the associations between 3 such markers and subsequent nutritional status. Design: Stool samples were routinely collected between January 2010 and November 2014 from a cohort of 303 Peruvian infants and analyzed for concentrations of the biomarkers α-1-antitrypsin (AAT), myeloperoxidase, and neopterin. For each marker, a mixed-effects linear regression model was fitted for length-for-age z scores (LAZs) obtained from anthropometric assessments that incorporated covariate predictors, polynomial terms for age, and product interaction terms to test associations over varying lag lengths. The biomarkers' contribution to the models was assessed with the use of the likelihood ratio test and partial R 2 statistics. Results: Test statistics for the combined inclusion of the 4-model terms that involved the biomarker were highly statistically significant for AAT (28.71; P < 0.0001) and myeloperoxidase (62.79; P < 0.0001) over a 3-mo lag and moderately so for neopterin (13.97; P = 0.0074). AAT and myeloperoxidase seemed to interact strongly with age, with the magnitude and direction of the effect varying considerably over the first 3 y of life. The largest proportion of the variance explained by any biomarker (2.8%) and the largest difference in LAZ predicted between the 5th and 95th percentile (0.25) was by myeloperoxidase over a 2-mo lag. Conclusions: Of the 3 fecal biomarkers studied, 2 that related to intestinal function-AAT and myeloperoxidase-were associated with small but highly statistically significant differences in future statural growth trajectories in infants in this cohort, lending further evidence to the EE hypothesis that increased gut permeability and inflammation adversely affects

  7. Is satisfaction a direct predictor of nursing turnover? Modelling the relationship between satisfaction, expressed intention and behaviour in a longitudinal cohort study

    Directory of Open Access Journals (Sweden)

    Griffiths Peter

    2008-10-01

    Full Text Available Abstract Background The theory of planned behaviour states that attitudinal variables (e.g. job satisfaction only have an indirect effect on retention whereas intentions have a direct effect. This study uses secondary data from a longitudinal cohort of newly qualified nurses to test for the direct and indirect effects of job satisfaction (client care, staffing, development, relationships, education, work-life interface, resources, pay and intentions to nurse on working as a nurse during the 3 years after qualification. Methods A national sample (England of newly qualified (1997/98 nurses (n = 3669 were surveyed at 6 months, 18 months and 3 years. ANOVA and MANOVA were used for comparison of mean job satisfaction scores between groups; intentions to nurse (very likely, likely vs. unlikely, very unlikely and unable to say at this stage; working (or not working as a nurse at each time-point. Indirect and direct effects were tested using structural equation and logistic regression models. Results Intentions expressed at 6 months to nurse at 18 months were associated with higher scores on pay and relationships, and intentions at 3 years were associated with higher scores on care, development, relationships, work-life interface, resources, pay respectively. Intentions expressed at 18 months to nurse at 3 years were associated with higher scores on development, relationships, education and work-life interface. Associations with actual nursing were fewer. Those working as a nurse had higher satisfaction scores for development (18 months and relationships (3 years. Regression models found significant associations between the pay and staffing factors and intentions expressed at 6 months to nurse at 18 months, and between pay and intentions to nurse at 3 years. Many of the associations between intentions and working as a nurse were significant. Development was the only job satisfaction factor significantly associated with working as a nurse and just at 18

  8. Electricity curtailment behaviors in Greek households: Different behaviors, different predictors

    International Nuclear Information System (INIS)

    Botetzagias, Iosif; Malesios, Chrisovaladis; Poulou, Dimitra

    2014-01-01

    Highlights: • We study the self-reported energy (electricity) curtailment behaviors of Greek households (N=285). • We find that the curtailment behaviors are distinct and should be studied/analyzed separately. • ‘Age’, ‘Gender’ and ‘Perceived Behavioral Control’ are statistically significant predictors of most behaviors. • The demographic/structural and the psychological predictors contribute significantly explain the variance of the behaviors. • The cluster of moral predictors does not contribute statistically significantly to the explained variance. - Abstract: This paper argues that electricity ‘curtailment’ behaviors (i.e. frequent and/or low cost or free energy saving behaviors) in households are distinct from one another and they thus should be analyzed and promoted. We test this claim with data from telephone interviews with Greek households in the capital city of Athens (N=285), analyzing the impact of a number of demographical/structural, psychological (based on the Theory of Planned Behavior) and moral (based on norms’ activation) predictors though hierarchical binary logistic regression modeling. We find that that each electricity curtailment behavior depends on a different mix of predictors with ‘Age’, ‘Gender’ and ‘Perceived Behavioral Control’ being statistically significant for most behaviors. Overall, the psychological and the demographical/structural clusters of variables substantially contribute to the explained variance of electricity curtailment behaviors. The moral cluster's contribution is not statistically significant since moral concerns are largely interwoven in the psychological constructs

  9. Predictors of readmission after outpatient plastic surgery.

    Science.gov (United States)

    Mioton, Lauren M; Buck, Donald W; Rambachan, Aksharananda; Ver Halen, Jon; Dumanian, Gregory A; Kim, John Y S

    2014-01-01

    Hospital readmissions have become a topic of focus for quality care measures and cost-reduction efforts. However, no comparative multi-institutional data on plastic surgery outpatient readmission rates currently exist. The authors endeavored to investigate hospital readmission rates and predictors of readmission following outpatient plastic surgery. The 2011 National Surgical Quality Improvement Program database was reviewed for all outpatient procedures. Unplanned readmission rates were calculated for all 10 tracked surgical specialties (i.e., general, thoracic, vascular, cardiac, orthopedics, otolaryngology, plastics, gynecology, urology, and neurosurgery). Multivariate logistic regression models were used to determine predictors of readmission for plastic surgery. A total of 7005 outpatient plastic surgery procedures were isolated. Outpatient plastic surgery had a low associated readmission rate (1.94 percent) compared with other specialties. Seventy-five patients were readmitted with a complication. Multivariate regression analysis revealed obesity (body mass index ≥ 30), wound infection within 30 days of the index surgery, and American Society of Anesthesiologists class 3 or 4 physical status as significant predictors for unplanned readmission. Unplanned readmission after outpatient plastic surgery is infrequent and compares favorably to rates of readmission among other specialties. Obesity, wound infection within 30 days of the index operation, and American Society of Anesthesiologists class 3 or 4 physical status are independent predictors of readmission. As procedures continue to transition into outpatient settings and the drive to improve patient care persists, these findings will serve to optimize outpatient surgery use.

  10. Predictors of intuitive eating in adolescent girls.

    Science.gov (United States)

    Andrew, Rachel; Tiggemann, Marika; Clark, Levina

    2015-02-01

    To examine proposed predictors of intuitive eating, including social appearance comparison, and to test a modified acceptance model of intuitive eating in adolescent girls. Participants were 400 adolescent girls aged 12-16 years who completed measures of body acceptance by others, self-objectification, social appearance comparison, body appreciation, and intuitive eating. Correlations showed that all proposed predictors were related to intuitive eating in the expected direction. In particular, social appearance comparison was negatively related to body appreciation and intuitive eating. After controlling for other predictors, social appearance comparison was shown to explain unique variance in intuitive eating. Using structural equation modeling, an integrated modified acceptance model of intuitive eating yielded an overall good fit to the data. Mediation analyses showed that there was a significant indirect effect of body acceptance by others on both body appreciation and intuitive eating through social appearance comparison and self-objectification. The findings extend the acceptance model of intuitive eating to adolescent girls but also identify social comparison as an important mechanism in this process. Practically, the findings highlight several areas that may be targeted to foster adaptive eating patterns in girls. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  11. An automated nowcasting model of significant instability events in the flight terminal area of Rio de Janeiro, Brazil

    Science.gov (United States)

    Borges França, Gutemberg; Valdonel de Almeida, Manoel; Rosette, Alessana C.

    2016-05-01

    This paper presents a novel model, based on neural network techniques, to produce short-term and local-specific forecasts of significant instability for flights in the terminal area of Galeão Airport, Rio de Janeiro, Brazil. Twelve years of data were used for neural network training/validation and test. Data are originally from four sources: (1) hourly meteorological observations from surface meteorological stations at five airports distributed around the study area; (2) atmospheric profiles collected twice a day at the meteorological station at Galeão Airport; (3) rain rate data collected from a network of 29 rain gauges in the study area; and (4) lightning data regularly collected by national detection networks. An investigation was undertaken regarding the capability of a neural network to produce early warning signs - or as a nowcasting tool - for significant instability events in the study area. The automated nowcasting model was tested using results from five categorical statistics, indicated in parentheses in forecasts of the first, second, and third hours, respectively, namely proportion correct (0.99, 0.97, and 0.94), BIAS (1.10, 1.42, and 2.31), the probability of detection (0.79, 0.78, and 0.67), false-alarm ratio (0.28, 0.45, and 0.73), and threat score (0.61, 0.47, and 0.25). Possible sources of error related to the test procedure are presented and discussed. The test showed that the proposed model (or neural network) can grab the physical content inside the data set, and its performance is quite encouraging for the first and second hours to nowcast significant instability events in the study area.

  12. Two-part survival models applied to administrative data for determining rate of and predictors for maternal-child transmission of HIV.

    Science.gov (United States)

    Hauck, W W; McKee, L J; Turner, B J

    1997-08-15

    In analysing maternal-child HIV transmission from Medicaid claims data, we must deal with follow-up that is sometimes so short that we cannot claim that an apparently uninfected infant is actually uninfected as opposed to not yet exhibiting HIV-associated symptoms. To overcome this, we have been using analyses of 'time-to-diagnosis' of HIV infection to estimate transmission rates and predictors of transmission. Such analyses mix the event of transmission with that of our ability to diagnose HIV infection from coded claims data. We would like to separate these two pieces. Also, due to incomplete follow-up, Kaplan-Meier analyses will underestimate transmission rates. In econometrics and biostatistics there are two-part (mixture) models that can serve the goal of separating transmission from the process of diagnosing HIV infection in the newborn. Farewell describes a model that combines a logistic regression for the yes/no event (in our case, HIV transmission) and a Weibull regression model for the survival analysis portion (in our case, time-to-diagnosis). We use this approach to fit models that have potentially separate covariates for transmission and for time-to-diagnosis. The results allow us to identify predictors of transmission and estimate transmission rates with reduced concern for adequacy of follow-up.

  13. Evaluating the significance of paleophylogeographic species distribution models in reconstructing quaternary range-shifts of nearctic chelonians.

    Directory of Open Access Journals (Sweden)

    Dennis Rödder

    Full Text Available The climatic cycles of the Quaternary, during which global mean annual temperatures have regularly changed by 5-10°C, provide a special opportunity for studying the rate, magnitude, and effects of geographic responses to changing climates. During the Quaternary, high- and mid-latitude species were extirpated from regions that were covered by ice or otherwise became unsuitable, persisting in refugial retreats where the environment was compatible with their tolerances. In this study we combine modern geographic range data, phylogeny, Pleistocene paleoclimatic models, and isotopic records of changes in global mean annual temperature, to produce a temporally continuous model of geographic changes in potential habitat for 59 species of North American turtles over the past 320 Ka (three full glacial-interglacial cycles. These paleophylogeographic models indicate the areas where past climates were compatible with the modern ranges of the species and serve as hypotheses for how their geographic ranges would have changed in response to Quaternary climate cycles. We test these hypotheses against physiological, genetic, taxonomic and fossil evidence, and we then use them to measure the effects of Quaternary climate cycles on species distributions. Patterns of range expansion, contraction, and fragmentation in the models are strongly congruent with (i phylogeographic differentiation; (ii morphological variation; (iii physiological tolerances; and (iv intraspecific genetic variability. Modern species with significant interspecific differentiation have geographic ranges that strongly fluctuated and repeatedly fragmented throughout the Quaternary. Modern species with low genetic diversity have geographic distributions that were highly variable and at times exceedingly small in the past. Our results reveal the potential for paleophylogeographic models to (i reconstruct past geographic range modifications, (ii identify geographic processes that result in

  14. How Significant is the Slope of the Sea-side Boundary for Modelling Seawater Intrusion in Coastal Aquifers?

    Science.gov (United States)

    Walther, Marc; Graf, Thomas; Kolditz, Olaf; Lield, Rudolf; Post, Vincent

    2017-04-01

    A large number of people live in coastal areas using the available water resources, which in (semi-)arid regions are often taken from groundwater resources as the only sufficient source. Compared to surface water, these usually provide a safe water supply due to the remediation and retention capabilities of the subsurface, their high yield, and potentially longer term stability. With a water withdrawal from a coastal aquifer, coastal water management, however, has to ensure that seawater intrusion is retained in order to keep the water salinity at an acceptable level for all water users (e.g. agriculture, industry, households). Besides monitoring of water levels and saline intrusion, it has become a common practice to use numerical modeling for evaluating the coastal water resources and projecting future scenarios. When applying a model, it is necessary for the simplifications implied during the conceptualization of the setup to include the relevant processes (here variable-density flow and mass transport) and sensitive parameters (for a steady state commonly hydraulic conductivity, density ratio, dispersivity). Additionally, the model's boundary conditions are essential to the simulation results. In order to reduce the number of elements, and thus, the computational burden, one simplification that is made in most regional scale saltwater intrusion applications, is to represent the sea-side boundary with a vertical geometry, contrary to the natural conditions, that usually show a very shallow decent of the interface between the aquifer and the open seawater. We use the scientific open-source modeling toolbox OpenGeoSys [1] to quantify the influence of this simplification on the saline intrusion, submarine groundwater discharge, and groundwater residence times. Using an ensemble of different shelf shapes for a steady state setup, we identified a significant dependency of saline intrusion length on the geometric parameters of the sea-side boundary. Results show that

  15. Genome-wide significant localization for working and spatial memory: Identifying genes for psychosis using models of cognition.

    Science.gov (United States)

    Knowles, Emma E M; Carless, Melanie A; de Almeida, Marcio A A; Curran, Joanne E; McKay, D Reese; Sprooten, Emma; Dyer, Thomas D; Göring, Harald H; Olvera, Rene; Fox, Peter; Almasy, Laura; Duggirala, Ravi; Kent, Jack W; Blangero, John; Glahn, David C

    2014-01-01

    It is well established that risk for developing psychosis is largely mediated by the influence of genes, but identifying precisely which genes underlie that risk has been problematic. Focusing on endophenotypes, rather than illness risk, is one solution to this problem. Impaired cognition is a well-established endophenotype of psychosis. Here we aimed to characterize the genetic architecture of cognition using phenotypically detailed models as opposed to relying on general IQ or individual neuropsychological measures. In so doing we hoped to identify genes that mediate cognitive ability, which might also contribute to psychosis risk. Hierarchical factor models of genetically clustered cognitive traits were subjected to linkage analysis followed by QTL region-specific association analyses in a sample of 1,269 Mexican American individuals from extended pedigrees. We identified four genome wide significant QTLs, two for working and two for spatial memory, and a number of plausible and interesting candidate genes. The creation of detailed models of cognition seemingly enhanced the power to detect genetic effects on cognition and provided a number of possible candidate genes for psychosis. © 2013 Wiley Periodicals, Inc.

  16. Predictors of Wellness and American Indians

    Science.gov (United States)

    Hodge, Felicia S.; Nandy, Karabi

    2012-01-01

    Wellness is an important American Indian (AI) concept, understood as being in balance with one’s body, mind, and environment. Wellness predictors are reported in this paper within the context of health. A cross-sectional randomized household survey of 457 AI adults at 13 rural health care sites in California was conducted. Measures included wellness perceptions, barriers, health status/health conditions, spirituality, cultural connectivity, high-risk behaviors and abuse history. Statistical analysis obtained the best predictive model for wellness. Predictors of wellness were general health status perception, participation in AI cultural practices and suicide ideation. Significant differences in wellness status were observed depending on experience of adverse events in childhood and adulthood (neglect, physical abuse, and sexual abuse). Cultural connectivity (speaking tribal language, participating in AI practices, and feeling connected to community) was also associated with perceptions of wellness. Recommendations are for culturally-appropriate education and interventions emphasizing community and cultural connectivity for improving wellness status. PMID:21841279

  17. Assessing the effect of quantitative and qualitative predictors on gastric cancer individuals survival using hierarchical artificial neural network models.

    Science.gov (United States)

    Amiri, Zohreh; Mohammad, Kazem; Mahmoudi, Mahmood; Parsaeian, Mahbubeh; Zeraati, Hojjat

    2013-01-01

    There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models. This study was designed and conducted to examine the application of these models in order to determine the survival of gastric cancer patients, in comparison to the Cox proportional hazards model. We studied the postoperative survival of 330 gastric cancer patients who suffered surgery at a surgical unit of the Iran Cancer Institute over a five-year period. Covariates of age, gender, history of substance abuse, cancer site, type of pathology, presence of metastasis, stage, and number of complementary treatments were entered in the models, and survival probabilities were calculated at 6, 12, 18, 24, 36, 48, and 60 months using the Cox proportional hazards and neural network models. We estimated coefficients of the Cox model and the weights in the neural network (with 3, 5, and 7 nodes in the hidden layer) in the training group, and used them to derive predictions in the study group. Predictions with these two methods were compared with those of the Kaplan-Meier product limit estimator as the gold standard. Comparisons were performed with the Friedman and Kruskal-Wallis tests. Survival probabilities at different times were determined using the Cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the Kaplan-Meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between Cox and Kaplan-Meier (P neural network, and the neural network and the standard (Kaplan-Meier), as well as better accuracy for the neural network (with 3 nodes in the hidden layer

  18. Predictors of maternal responsiveness.

    Science.gov (United States)

    Drake, Emily E; Humenick, Sharron S; Amankwaa, Linda; Younger, Janet; Roux, Gayle

    2007-01-01

    To explore maternal responsiveness in the first 2 to 4 months after delivery and to evaluate potential predictors of maternal responsiveness, including infant feeding, maternal characteristics, and demographic factors such as age, socioeconomic status, and educational level. A cross-sectional survey design was used to assess the variables of maternal responsiveness, feeding patterns, and maternal characteristics in a convenience sample of 177 mothers in the first 2 to 4 months after delivery. The 60-item self-report instrument included scales to measure maternal responsiveness, self-esteem, and satisfaction with life as well as infant feeding questions and sociodemographic items. An online data-collection strategy was used, resulting in participants from 41 U.S. states. Multiple regression analysis showed that satisfaction with life, self-esteem, and number of children, but not breastfeeding, explained a significant portion of the variance in self-reported maternal responsiveness scores. In this analysis, sociodemographic variables such as age, education, income, and work status showed little or no relationship to maternal responsiveness scores. This study provides additional information about patterns of maternal behavior in the transition to motherhood and some of the variables that influence that transition. Satisfaction with life was a new predictor of maternal responsiveness. However, with only 15% of the variance explained by the predictors in this study, a large portion of the variance in maternal responsiveness remains unexplained. Further research in this area is needed.

  19. Optical polarization tractography revealed significant fiber disarray in skeletal muscles of a mouse model for Duchenne muscular dystrophy.

    Science.gov (United States)

    Wang, Y; Zhang, K; Wasala, N B; Duan, D; Yao, G

    2015-02-01

    Optical polarization tractography (OPT) was recently developed to visualize tissue fiber architecture with cellular-level resolution and accuracy. In this study, we explored the feasibility of using OPT to study muscle disease in the mdx4cv mouse model of Duchenne muscular dystrophy. The freshly dissected tibialis anterior muscles of mdx4cv and normal mice were imaged. A "fiber disarray index" (FDI) was developed to quantify the myofiber disorganization. In necrotic muscle regions of the mdx4cv mice, the FDI was significantly elevated and can be used to segment the 3D necrotic regions for assessing the overall muscle damage. These results demonstrated the OPT's capability for imaging microscopic fiber alternations in muscle research.

  20. Mental Health Changes and Its Predictors in Adolescents using the Path Analytic Model: A 7-Year Observational Study.

    Directory of Open Access Journals (Sweden)

    Ali Reza Soltanian

    2014-03-01

    Full Text Available This 7-year observational study examines the hours of TV-watching, phone conversation with friends, using the internet, and physical activity as predictors of mental health among adolescents in south of Iran.At the baseline (in 2005, the participants were 2584 high school students in the 9th to 11th grade. At the baseline, 30% of the available participants (n = 775 were selected in the follow-up (2012 using convenience sampling method. This study used the path analysis to examine the predictors of mental health and to obtain direct, indirect and total effects of the independent variables.At the baseline (2005, female gender, internet use, maternal education, physical activity and father's education were associated with mental health (p<0.05. Baseline mental health, internet use and physical activity predicted mental health of the participants in the follow up (p<0.05.The findings of the study revealed that better mental health in later life is associated with better mental health at baseline, male gender, higher physical activity and phone communication with friends, and less use of the internet and TV.

  1. Bacteriophage treatment significantly reduces viable Clostridium difficile and prevents toxin production in an in vitro model system.

    Science.gov (United States)

    Meader, Emma; Mayer, Melinda J; Gasson, Michael J; Steverding, Dietmar; Carding, Simon R; Narbad, Arjan

    2010-12-01

    Clostridium difficile is primarily a nosocomial pathogen, causing thousands of cases of antibiotic-associated diarrhoea in the UK each year. In this study, we used a batch fermentation model of a C. difficile colonised system to evaluate the potential of a prophylactic and a remedial bacteriophage treatment regime to control the pathogen. It is shown that the prophylaxis regime was effective at preventing the growth of C. difficile (p = viable C. difficile cells (p = <0.0001), but still resulted in a lower level of toxin production relative to the control. The numbers of commensal bacteria including total aerobes and anaerobes, Bifidobacterium sp., Bacteroides sp., Lactobacillus sp., total Clostridium sp., and Enterobacteriaceae were not significantly decreased by this therapy, whereas significant detrimental effects were observed with metronidazole treatment. Our study indicates that phage therapy has potential to be used for the control of C. difficile; it highlights the main benefits of this approach, and some future challenges. Copyright © 2010 Elsevier Ltd. All rights reserved.

  2. DISENTANGLING INTERPOLATION AND EXTRAPOLATION UNCERTAINTIES IN SPECIES DISTRIBUTION MODELS: A NOVEL VISUALIZATION TECHNIQUE FOR THE SPATIAL VARIATION OF PREDICTOR VARIABLE COLINEARITY

    Directory of Open Access Journals (Sweden)

    Dennis Rödder

    2012-08-01

    Full Text Available Abstract. - Species distribution models (SDMs are increasingly used in many scientific fields, with most studies requiring the application of the SDM to predict the likelihood of occurrence and/or environmental suitability in locations and time periods outside the range of the data set used to fit the model. Uncertainty in the quality of SDM predictions caused by errors of interpolation and extrapolation has been acknowledged for a long time, but the explicit consideration of the magnitude of such errors is, as yet, uncommon. Among other issues, the spatial variation in the colinearity of the environmental predictor variables used in the development of SDMs may cause misleading predictions when applying SDMs to novel locations and time periods. In this paper, we provide a framework for the spatially explicit identification of areas prone to errors caused by changes in the inter-correlation structure (i.e. their colinearity of environmental predictors used for SDM development. The proposed method is compatible with all SDM algorithms currently employed, and expands the available toolbox for assessing the uncertainties raising from SDM predictions. We provide an implementation of the analysis as a script for the R statistical platform in an online appendix.

  3. Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers

    Directory of Open Access Journals (Sweden)

    Pierluigi eZoccolotti

    2014-11-01

    Full Text Available This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN. Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37% to 52% of the explained variance when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69% and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colours as stimuli (both in the RAN task and in the discrete naming task obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs distal causes to predict reading fluency is

  4. Material stiffness parameters as potential predictors of presence of left ventricle myocardial infarction: 3D echo-based computational modeling study.

    Science.gov (United States)

    Fan, Longling; Yao, Jing; Yang, Chun; Wu, Zheyang; Xu, Di; Tang, Dalin

    2016-04-05

    Ventricle material properties are difficult to obtain under in vivo conditions and are not readily available in the current literature. It is also desirable to have an initial determination if a patient had an infarction based on echo data before more expensive examinations are recommended. A noninvasive echo-based modeling approach and a predictive method were introduced to determine left ventricle material parameters and differentiate patients with recent myocardial infarction (MI) from those without. Echo data were obtained from 10 patients, 5 with MI (Infarct Group) and 5 without (Non-Infarcted Group). Echo-based patient-specific computational left ventricle (LV) models were constructed to quantify LV material properties. All patients were treated equally in the modeling process without using MI information. Systolic and diastolic material parameter values in the Mooney-Rivlin models were adjusted to match echo volume data. The equivalent Young's modulus (YM) values were obtained for each material stress-strain curve by linear fitting for easy comparison. Predictive logistic regression analysis was used to identify the best parameters for infract prediction. The LV end-systole material stiffness (ES-YMf) was the best single predictor among the 12 individual parameters with an area under the receiver operating characteristic (ROC) curve of 0.9841. LV wall thickness (WT), material stiffness in fiber direction at end-systole (ES-YMf) and material stiffness variation (∆YMf) had positive correlations with LV ejection fraction with correlation coefficients r = 0.8125, 0.9495 and 0.9619, respectively. The best combination of parameters WT + ∆YMf was the best over-all predictor with an area under the ROC curve of 0.9951. Computational modeling and material stiffness parameters may be used as a potential tool to suggest if a patient had infarction based on echo data. Large-scale clinical studies are needed to validate these preliminary findings.

  5. GeoSciML v3.0 - a significant upgrade of the CGI-IUGS geoscience data model

    Science.gov (United States)

    Raymond, O.; Duclaux, G.; Boisvert, E.; Cipolloni, C.; Cox, S.; Laxton, J.; Letourneau, F.; Richard, S.; Ritchie, A.; Sen, M.; Serrano, J.-J.; Simons, B.; Vuollo, J.

    2012-04-01

    GeoSciML version 3.0 (http://www.geosciml.org), released in late 2011, is the latest version of the CGI-IUGS* Interoperability Working Group geoscience data interchange standard. The new version is a significant upgrade and refactoring of GeoSciML v2 which was released in 2008. GeoSciML v3 has already been adopted by several major international interoperability initiatives, including OneGeology, the EU INSPIRE program, and the US Geoscience Information Network, as their standard data exchange format for geoscience data. GeoSciML v3 makes use of recently upgraded versions of several Open Geospatial Consortium (OGC) and ISO data transfer standards, including GML v3.2, SWE Common v2.0, and Observations and Measurements v2 (ISO 19156). The GeoSciML v3 data model has been refactored from a single large application schema with many packages, into a number of smaller, but related, application schema modules with individual namespaces. This refactoring allows the use and future development of modules of GeoSciML (eg; GeologicUnit, GeologicStructure, GeologicAge, Borehole) in smaller, more manageable units. As a result of this refactoring and the integration with new OGC and ISO standards, GeoSciML v3 is not backwardly compatible with previous GeoSciML versions. The scope of GeoSciML has been extended in version 3.0 to include new models for geomorphological data (a Geomorphology application schema), and for geological specimens, geochronological interpretations, and metadata for geochemical and geochronological analyses (a LaboratoryAnalysis-Specimen application schema). In addition, there is better support for borehole data, and the PhysicalProperties model now supports a wider range of petrophysical measurements. The previously used CGI_Value data type has been superseded in favour of externally governed data types provided by OGC's SWE Common v2 and GML v3.2 data standards. The GeoSciML v3 release includes worked examples of best practice in delivering geochemical

  6. Significance of myoglobin as an oxygen store and oxygen transporter in the intermittently perfused human heart: a model study.

    Science.gov (United States)

    Endeward, Volker; Gros, Gerolf; Jürgens, Klaus D

    2010-07-01

    The mechanisms by which the left ventricular wall escapes anoxia during the systolic phase of low blood perfusion are investigated, especially the role of myoglobin (Mb), which can (i) store oxygen and (ii) facilitate intracellular oxygen transport. The quantitative role of these two Mb functions is studied in the maximally working human heart. Because discrimination between Mb functions has not been achieved experimentally, we use a Krogh cylinder model here. At a heart rate of 200 beats/min and a 1:1 ratio of diastole/systole, the systole lasts for 150 ms. The basic model assumption is that, with mobile Mb, the oxygen stored in the end-diastolic left ventricle wall exactly meets the demand during the 150 ms of systolic cessation of blood flow. The coronary blood flow necessary to achieve this agrees with literature data. By considering Mb immobile or setting its concentration to zero, respectively, we find that, depending on Mb concentration, Mb-facilitated O(2) transport maintains O(2) supply to the left ventricle wall during 22-34 of the 150 ms, while Mb storage function accounts for a further 12-17 ms. When Mb is completely absent, anoxia begins to develop after 116-99 ms. While Mb plays no significant role during diastole, it supplies O(2) to the left ventricular wall for < or = 50 ms of the 150 ms systole, whereas capillary haemoglobin is responsible for approximately 80 ms. Slight increases in haemoglobin concentration, blood flow, or capillary density can compensate the absence of Mb, a finding which agrees well with the observations using Mb knockout mice.

  7. Intelligent system for statistically significant expertise knowledge on the basis of the model of self-organizing nonequilibrium dissipative system

    Directory of Open Access Journals (Sweden)

    E. A. Tatokchin

    2017-01-01

    Full Text Available Development of the modern educational technologies caused by broad introduction of comput-er testing and development of distant forms of education does necessary revision of methods of an examination of pupils. In work it was shown, need transition to mathematical criteria, exami-nations of knowledge which are deprived of subjectivity. In article the review of the problems arising at realization of this task and are offered approaches for its decision. The greatest atten-tion is paid to discussion of a problem of objective transformation of rated estimates of the ex-pert on to the scale estimates of the student. In general, the discussion this question is was con-cluded that the solution to this problem lies in the creation of specialized intellectual systems. The basis for constructing intelligent system laid the mathematical model of self-organizing nonequilibrium dissipative system, which is a group of students. This article assumes that the dissipative system is provided by the constant influx of new test items of the expert and non-equilibrium – individual psychological characteristics of students in the group. As a result, the system must self-organize themselves into stable patterns. This patern will allow for, relying on large amounts of data, get a statistically significant assessment of student. To justify the pro-posed approach in the work presents the data of the statistical analysis of the results of testing a large sample of students (> 90. Conclusions from this statistical analysis allowed to develop intelligent system statistically significant examination of student performance. It is based on data clustering algorithm (k-mean for the three key parameters. It is shown that this approach allows you to create of the dynamics and objective expertise evaluation.

  8. Perceived parental rearing behaviours, responsibility attitudes and life events as predictors of obsessive compulsive symptomatology: test of a cognitive model.

    Science.gov (United States)

    Haciomeroglu, Bikem; Karanci, A Nuray

    2014-11-01

    It is important to investigate the role of cognitive, developmental and environmental factors in the development and maintenance of Obsessive Compulsive Symptomatology (OCS). The main objective of this study was to examine the vulnerability factors of OCS in a non-clinical sample. On the basis of Salkovskis' cognitive model of OCD, the study aimed to investigate the role of perceived parental rearing behaviours, responsibility attitudes, and life events in predicting OCS. Furthermore, the mediator role of responsibility attitudes in the relationship between perceived parental rearing behaviours and OCS was examined. Finally, the specificity of these variables to OCS was evaluated by examining the relationship of the same variables with depression and trait anxiety. A total of 300 university students (M = 19.55±1.79) were administered the Padua Inventory-Washington State University Revision, Responsibility Attitudes Scale, s-EMBU (My memories of upbringing), Life Events Inventory for University Students, Beck Depression Inventory, and State-Trait Anxiety Inventory-Trait Form. Regression analysis revealed that perceived mother overprotection, responsibility attitudes and life events significantly predicted OCS. Furthermore, responsibility attitudes mediated the relationship between perceived mother overprotection and OCS. The predictive role of perceived mother overprotection and the mediator role responsibility attitudes were OCS specific. The findings of the present study supported that perceived mother over-protection as a developmental vulnerability factor significantly contributed to the explanation of a cognitive vulnerability factor (namely responsibility attitudes), and perceived maternal overprotection had its predictive role for OCS through responsibility attitudes.

  9. Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

    Science.gov (United States)

    Coupé, Christophe

    2018-01-01

    As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we

  10. Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

    Directory of Open Access Journals (Sweden)

    Christophe Coupé

    2018-04-01

    Full Text Available As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM, which address grouping of observations, and generalized linear mixed-effects models (GLMM, which offer a family of distributions for the dependent variable. Generalized additive models (GAM are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS. We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships

  11. Predictors of empathy in health science students.

    Science.gov (United States)

    Brown, Ted; Boyle, Malcolm; Williams, Brett; Molloy, Andrew; Palermo, Claire; McKenna, Lisa; Molloy, Liz

    2011-01-01

    The significance of both empathy and effective communication as key components in the provision of health care services is widely acknowledged. It is important, therefore, to promote those communication styles which facilitate an empathetic understanding among health science students. To explores whether listening and communication styles are predictive of empathy among health science students. A cross-sectional study of 860 undergraduate health science students (response rate, 59%) using paper-based versions of the Jefferson Scale of Physician Empathy-Health Professional Version, Listening Styles Profile, Communicator Styles Measure, and a brief demographic questionnaire. Two stepwise linear regression analyses were completed using the empathy construct as the dependent/criterion variable and listening and communication styles as the two sets of independent/predictor variables. As there was a statistically significant difference in empathy between males and females, gender was controlled for in both regression models. In first model, the People and Time listening styles were found to be predictive of empathy, accounting for 20.3% of the total variance. In the second model, both the Friendly and Relaxed communication styles were predictive of empathy, accounting for 9.7% of the total variance. The findings indicate that People and Time listening styles and the Friendly and Relaxed communication styles were significant predictors of empathy in health science students. The findings suggest that promoting effective communication among health science students may improve their ability to empathize.

  12. A non-traditional model of the metabolic syndrome: the adaptive significance of insulin resistance in fasting-adapted seals

    Directory of Open Access Journals (Sweden)

    Dorian S Houser

    2013-11-01

    Full Text Available Insulin resistance in modern society is perceived as a pathological consequence of excess energy consumption and reduced physical activity. Its presence in relation to the development of cardiovascular risk factors has been termed the metabolic syndrome, which produces increased mortality and morbidity and which is rapidly increasing in human populations. Ironically, insulin resistance likely evolved to assist animals during food shortages by increasing the availability of endogenous lipid for catabolism while protecting protein from use in gluconeogenesis and eventual oxidation. Some species that incorporate fasting as a predictable component of their life history demonstrate physiological traits similar to the metabolic syndrome during prolonged fasts. One such species is the northern elephant seal (Mirounga angustirostris, which fasts from food and water for periods of up to three months. During this time, ~90% of the seals metabolic demands are met through fat oxidation and circulating non-esterified fatty acids are high (0.7-3.2 mM. All life history stages of elephant seal studied to date demonstrate insulin resistance and fasting hyperglycemia as well as variations in hormones and adipocytokines that reflect the metabolic syndrome to some degree. Elephant seals demonstrate some intriguing adaptations with the potential for medical advancement; for example, ketosis is negligible despite significant and prolonged fatty acid oxidation and investigation of this feature might provide insight into the treatment of diabetic ketoacidosis. The parallels to the metabolic syndrome are likely reflected to varying degrees in other marine mammals, most of which evolved on diets high in lipid and protein content but essentially devoid of carbohydrate. Utilization of these natural models of insulin resistance may further our understanding of the pathophysiology of the metabolic syndrome in humans and better assist the development of preventative measures

  13. A non-traditional model of the metabolic syndrome: the adaptive significance of insulin resistance in fasting-adapted seals.

    Science.gov (United States)

    Houser, Dorian S; Champagne, Cory D; Crocker, Daniel E

    2013-11-01

    Insulin resistance in modern society is perceived as a pathological consequence of excess energy consumption and reduced physical activity. Its presence in relation to the development of cardiovascular risk factors has been termed the metabolic syndrome, which produces increased mortality and morbidity and which is rapidly increasing in human populations. Ironically, insulin resistance likely evolved to assist animals during food shortages by increasing the availability of endogenous lipid for catabolism while protecting protein from use in gluconeogenesis and eventual oxidation. Some species that incorporate fasting as a predictable component of their life history demonstrate physiological traits similar to the metabolic syndrome during prolonged fasts. One such species is the northern elephant seal (Mirounga angustirostris), which fasts from food and water for periods of up to 4 months. During this time, ∼90% of the seals metabolic demands are met through fat oxidation and circulating non-esterified fatty acids are high (0.7-3.2 mM). All life history stages of elephant seal studied to date demonstrate insulin resistance and fasting hyperglycemia as well as variations in hormones and adipocytokines that reflect the metabolic syndrome to some degree. Elephant seals demonstrate some intriguing adaptations with the potential for medical advancement; for example, ketosis is negligible despite significant and prolonged fatty acid oxidation and investigation of this feature might provide insight into the treatment of diabetic ketoacidosis. The parallels to the metabolic syndrome are likely reflected to varying degrees in other marine mammals, most of which evolved on diets high in lipid and protein content but essentially devoid of carbohydrate. Utilization of these natural models of insulin resistance may further our understanding of the pathophysiology of the metabolic syndrome in humans and better assist the development of preventative measures and therapies.

  14. Biological Age Predictors

    Directory of Open Access Journals (Sweden)

    Juulia Jylhävä

    2017-07-01

    Full Text Available The search for reliable indicators of biological age, rather than chronological age, has been ongoing for over three decades, and until recently, largely without success. Advances in the fields of molecular biology have increased the variety of potential candidate biomarkers that may be considered as biological age predictors. In this review, we summarize current state-of-the-art findings considering six potential types of biological age predictors: epigenetic clocks, telomere length, transcriptomic predictors, proteomic predictors, metabolomics-based predictors, and composite biomarker predictors. Promising developments consider multiple combinations of these various types of predictors, which may shed light on the aging process and provide further understanding of what contributes to healthy aging. Thus far, the most promising, new biological age predictor is the epigenetic clock; however its true value as a biomarker of aging requires longitudinal confirmation.

  15. Solutions for Determining the Significance Region Using the Johnson-Neyman Type Procedure in Generalized Linear (Mixed) Models

    Science.gov (United States)

    Lazar, Ann A.; Zerbe, Gary O.

    2011-01-01

    Researchers often compare the relationship between an outcome and covariate for two or more groups by evaluating whether the fitted regression curves differ significantly. When they do, researchers need to determine the "significance region," or the values of the covariate where the curves significantly differ. In analysis of covariance (ANCOVA),…

  16. Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

    International Nuclear Information System (INIS)

    Fourie, Zacharias; Damstra, Janalt; Schepers, Rutger H.; Gerrits, Peter O.; Ren Yijin

    2012-01-01

    Aims: To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. Materials and methods: Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D surface models were created of the mandible using two different segmentation protocols. The one series of 3D models was segmented by a commercial software company, while the other series was done by an experienced 3D clinician. The heads were then macerated following a standard process. A high resolution laser surface scanner was used to make a 3D model of the macerated mandibles, which acted as the reference 3D model or “gold standard”. The 3D models generated from the two rendering protocols were compared with the “gold standard” using a point-based rigid registration algorithm to superimpose the three 3D models. The linear difference at 25 anatomic and cephalometric landmarks between the laser surface scan and the 3D models generate from the two rendering protocols was measured repeatedly in two sessions with one week interval. Results: The agreement between the repeated measurement was excellent (ICC = 0.923–1.000). The mean deviation from the gold standard by the 3D models generated from the CS group was 0.330 mm ± 0.427, while the mean deviation from the Clinician's rendering was 0.763 mm ± 0.392. The surface models segmented by both CS and DS protocols tend to be larger than those of the reference models. In the DS group, the biggest mean differences with the LSS models were found at the points ConLatR (CI: 0.83–1.23), ConMedR (CI: −3.16 to 2.25), CoLatL (CI: −0.68 to 2.23), Spine (CI: 1.19–2.28), ConAntL (CI: 0.84–1.69), ConSupR (CI: −1.12 to 1.47) and RetMolR (CI: 0.84–1.80). Conclusion: The Commercially segmented models resembled the reality more closely than the Doctor's segmented models. If 3D models are needed for surgical drilling

  17. A test of the vulnerability model : Temperament and temperament change as predictors of future mental disorders - The TRAILS study

    NARCIS (Netherlands)

    Laceulle, Odilia M.; Ormel, Johan; Vollebergh, Wilma A M; Van Aken, Marcel A G; Nederhof, Esther

    2014-01-01

    Background This study aimed to test the vulnerability model of the relationship between temperament and mental disorders using a large sample of adolescents from the TRacking Adolescents Individual Lives' Survey (TRAILS). The vulnerability model argues that particular temperaments can place

  18. Predictors of Transience among Homeless Emerging Adults

    Science.gov (United States)

    Ferguson, Kristin M.; Bender, Kimberly; Thompson, Sanna J.

    2014-01-01

    This study identified predictors of transience among homeless emerging adults in three cities. A total of 601 homeless emerging adults from Los Angeles, Austin, and Denver were recruited using purposive sampling. Ordinary least squares regression results revealed that significant predictors of greater transience include White ethnicity, high…

  19. On the significance of the noise model for the performance of a linear MPC in closed-loop operation

    DEFF Research Database (Denmark)

    Hagdrup, Morten; Boiroux, Dimitri; Mahmoudi, Zeinab

    2016-01-01

    models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation...

  20. Understanding the limits of animal models as predictors of human biology: lessons learned from the sbv IMPROVER Species Translation Challenge.

    Science.gov (United States)

    Rhrissorrakrai, Kahn; Belcastro, Vincenzo; Bilal, Erhan; Norel, Raquel; Poussin, Carine; Mathis, Carole; Dulize, Rémi H J; Ivanov, Nikolai V; Alexopoulos, Leonidas; Rice, J Jeremy; Peitsch, Manuel C; Stolovitzky, Gustavo; Meyer, Pablo; Hoeng, Julia

    2015-02-15

    Inferring how humans respond to external cues such as drugs, chemicals, viruses or hormones is an essential question in biomedicine. Very often, however, this question cannot be addressed because it is not possible to perform experiments in humans. A reasonable alternative consists of generating responses in animal models and 'translating' those results to humans. The limitations of such translation, however, are far from clear, and systematic assessments of its actual potential are urgently needed. sbv IMPROVER (systems biology verification for Industrial Methodology for PROcess VErification in Research) was designed as a series of challenges to address translatability between humans and rodents. This collaborative crowd-sourcing initiative invited scientists from around the world to apply their own computational methodologies on a multilayer systems biology dataset composed of phosphoproteomics, transcriptomics and cytokine data derived from normal human and rat bronchial epithelial cells exposed in parallel to 52 different stimuli under identical conditions. Our aim was to understand the limits of species-to-species translatability at different levels of biological organization: signaling, transcriptional and release of secreted factors (such as cytokines). Participating teams submitted 49 different solutions across the sub-challenges, two-thirds of which were statistically significantly better than random. Additionally, similar computational methods were found to range widely in their performance within the same challenge, and no single method emerged as a clear winner across all sub-challenges. Finally, computational methods were able to effectively translate some specific stimuli and biological processes in the lung epithelial system, such as DNA synthesis, cytoskeleton and extracellular matrix, translation, immune/inflammation and growth factor/proliferation pathways, better than the expected response similarity between species. pmeyerr@us.ibm.com or Julia

  1. Predictors of reducing sexual and reproductive risk behaviors based on the information-motivation-behavioral skills (IMB model among unmarried rural-to-urban female migrants in Shanghai, China.

    Directory of Open Access Journals (Sweden)

    Yong Cai

    Full Text Available BACKGROUND: Due to the increase of premarital sex and the lack of reproductive health services, unmarried rural-to-urban female migrants experience more risks of sex and reproductive health (SRH. This study was designed to describe SRH related knowledge, attitude and risk behaviors among unmarried rural-to-urban female migrants and examine the predictors of reducing sexual and reproductive risk behaviors based on information-motivation-behavioral skills (IMB model and to describe the relationships between the constructs. METHODS: We conducted a cross-sectional study to assess SRH related information, motivation, behavioral skills and preventive behaviors among unmarried rural-to-urban female migrants in Shanghai, one of the largest importers of migrant laborers in China. Structural equation modeling (SEM was used to assess the IMB model. RESULTS: A total of 944 subjects completed their questionnaires. The mean age was 21.2 years old (SD = 2.3; range 16 to 28. Over one-fourth of participants reported having had premarital sex (N = 261, 27.6% and among whom 15.3% reported having had the experience of unintended pregnancy, 14.6% with the experience of abortion. The final IMB model provided acceptable fit to the data (CFI = 0.99, RMSEA = 0.034. Reducing sexual and reproductive risk behaviors was significantly predicted by SRH related information (β = 0.681, P<0.001 and behavioral skills(β = 0.239, P<0.001. Motivation (β = 0.479, P<0.001 was the significant indirect predictor of reducing sexual and reproductive risk behaviors mediated through behavioral skills. CONCLUSIONS: The results highlight the importance and necessity of conducting reproductive health promotion among unmarried rural-to-urban female migrants in China. The IMB model could be used to predict reducing sexual and reproductive risk behaviors and it suggests future interventions should focus on improving SRH related information and behavioral skills.

  2. Body image flexibility: A predictor and moderator of outcome in transdiagnostic outpatient eating disorder treatment.

    Science.gov (United States)

    Pellizzer, Mia L; Waller, Glenn; Wade, Tracey D

    2018-04-01

    Predictors of attrition and predictors and moderators of outcome were explored in a transdiagnostic sample of patients who received ten-session cognitive behavioral therapy (CBT-T) for nonunderweight eating disorders. Body image flexibility, a protective positive body image construct, was hypothesized to be a significant moderator. Data from two case series were combined to form a sample of 78 participants who received CBT-T. Baseline measures of body image, negative affect, personality, and motivation (readiness to change and self-efficacy) were included as potential predictors. Global eating disorder psychopathology at each assessment point (baseline, mid- and post-treatment, 1- and 3-month follow-up) was the outcome variable. Predictors of attrition were assessed using logistic regression, and multilevel modeling was applied for predictors and moderators of outcome. Body image flexibility emerged as the strongest predictor and moderator of global eating disorder psychopathology, followed by body image avoidance. Body checking, negative affect, personality beliefs, and self-efficacy were significant predictors of global eating disorder psychopathology. Higher body image flexibility predicted lower global eating disorder psychopathology at every assessment point. Further research is required to replicate findings and explore the benefit of focusing on positive body image in treatment. © 2018 Wiley Periodicals, Inc.

  3. Quality Circles: Determination of Significant Factors for Success an a General Model for Implementing a Quality Circle Process.

    Science.gov (United States)

    1981-06-01

    Quality Cir- cles?" First Annual IAQC Transactions, 1979, pp 59-65. 11. Beckhard , Richard . 0rganization Development: Strategies and Models. Reading...improve task accomplishment /57. Beckhard /T17 identifies three models that are commonly used in attempting to deal with a client’s problems. The...Jananese Challerfe. Addison-Wesley Publishing Co., Reading, Massachusetts, 1981. 84. Pascale, Richard T., Anthony G. Athos. The Art of Japaese

  4. Psychosocial predictors of breast self-examination behavior among female students: an application of the health belief model using logistic regression.

    Science.gov (United States)

    Didarloo, Alireza; Nabilou, Bahram; Khalkhali, Hamid Reza

    2017-11-03

    Breast cancer is a life-threatening condition affecting women around the world. The early detection of breast lumps using a breast self-examination (BSE) is important for the prevention and control of this disease. The aim of this study was to examine BSE behavior and its predictive factors among female university students using the Health Belief Model (HBM). This investigation was a cross-sectional survey carried out with 334 female students at Urmia University of Medical Sciences in the northwest of Iran. To collect the necessary data, researchers applied a valid and reliable three-part questionnaire. The data were analyzed using descriptive statistics and a chi-square test, in addition to multivariate logistic regression statistics in SPSS software version 16.0 (SPSS Inc., Chicago, IL, USA). The results indicated that 82 of the 334 participants (24.6%) reported practicing BSEs. Multivariate logistic regression analyses showed that high perceived severity [OR = 2.38, 95% CI = (1.02-5.54)], high perceived benefits [OR = 1.94, 95% CI = (1.09-3.46)], and high perceived self-efficacy [OR = 13.15, 95% CI = (3.64-47.51)] were better predictors of BSE behavior (P < 0.05) than low perceived severity, benefits, and self-efficacy. The findings also showed that a high level of knowledge compared to a low level of knowledge [OR = 5.51, 95% CI = (1.79-16.86)] and academic undergraduate and graduate degrees compared to doctoral degrees [OR = 2.90, 95% CI = (1.42-5.92)] of the participants were predictors of BSE performance (P < 0.05). The study revealed that the HBM constructs are able to predict BSE behavior. Among these constructs, self-efficacy was the most important predictor of the behavior. Interventions based on the constructs of perceived self-efficacy, benefits, and severity are recommended for increasing women's regular screening for breast cancer.

  5. Baseline Muscle Mass Is a Poor Predictor of Functional Overload-Induced Gain in the Mouse Model.

    Science.gov (United States)

    Kilikevicius, Audrius; Bunger, Lutz; Lionikas, Arimantas

    2016-01-01

    Genetic background contributes substantially to individual variability in muscle mass. Muscle hypertrophy in response to resistance training can also vary extensively. However, it is less clear if muscle mass at baseline is predictive of the hypertrophic response. The aim of this study was to examine the effect of genetic background on variability in muscle mass at baseline and in the adaptive response of the mouse fast- and slow-twitch muscles to overload. Males of eight laboratory mouse strains: C57BL/6J (B6, n = 17), BALB/cByJ ( n = 7), DBA/2J (D2, n = 12), B6.A-( rs3676616-D10Utsw1 )/Kjn (B6.A, n = 9), C57BL/6J-Chr10 A/J /NaJ (B6.A10, n = 8), BEH+/+ ( n = 11), BEH ( n = 12), and DUHi ( n = 12), were studied. Compensatory growth of soleus and plantaris muscles was triggered by a 4-week overload induced by synergist unilateral ablation. Muscle weight in the control leg (baseline) varied from 5.2 ± 07 mg soleus and 11.4 ± 1.3 mg plantaris in D2 mice to 18.0 ± 1.7 mg soleus in DUHi and 43.7 ± 2.6 mg plantaris in BEH ( p muscles). In addition, soleus in the B6.A10 strain was ~40% larger ( p muscle weight, however, the extent of gain was strain-dependent for both soleus ( p muscle, the BEH strain emerged as the least responsive, with a 1.3-fold increase, compared to a 1.7-fold gain in the most responsive D2 strain, and there was no difference in the gain between the B6.A10 and B6 strains. The BEH strain appeared the least responsive in the gain of plantaris as well, 1.3-fold, compared to ~1.5-fold gain in the remaining strains. We conclude that variation in muscle mass at baseline is not a reliable predictor of that in the overload-induced gain. This suggests that a different set of genes influence variability in muscle mass acquired in the process of normal development, growth, and maintenance, and in the process of adaptive growth of the muscle challenged by overload.

  6. Baseline muscle mass is a poor predictor of functional overload-induced gain in the mouse model

    Directory of Open Access Journals (Sweden)

    Audrius Kilikevicius

    2016-11-01

    Full Text Available Genetic background contributes substantially to individual variability in muscle mass. Muscle hypertrophy in response to resistance training can also vary extensively. However, it is less clear if muscle mass at baseline is predictive of the hypertrophic response.The aim of this study was to examine the effect of genetic background on variability in muscle mass at baseline and in the adaptive response of the mouse fast- and slow-twitch muscles to overload. Males of eight laboratory mouse strains: C57BL/6J (B6, n=17, BALB/cByJ (n=7, DBA/2J (D2, n=12, B6.A-(rs3676616-D10Utsw1/Kjn (B6.A, n=9, C57BL/6J-Chr10A/J/NaJ (B6.A10, n=8, BEH+/+ (n=11, BEH (n=12 and DUHi (n=12, were studied. Compensatory growth of soleus and plantaris muscles was triggered by a 4-week overload induced by synergist unilateral ablation. Muscle weight in the control leg (baseline varied from 5.2±07 mg soleus and 11.4±1.3 mg plantaris in D2 mice to 18.0±1.7 mg soleus in DUHi and 43.7±2.6 mg plantaris in BEH (p<0.001 for both muscles. In addition, soleus in the B6.A10 strain was ~40% larger (p<0.001 compared to the B6. Functional overload increased muscle weight, however, the extent of gain was strain-dependent for both soleus (p<0.01 and plantaris (p<0.02 even after accounting for the baseline differences. For the soleus muscle, the BEH strain emerged as the least responsive, with a 1.3-fold increase, compared to a 1.7-fold gain in the most responsive D2 strain, and there was no difference in the gain between the B6.A10 and B6 strains. The BEH strain appeared the least responsive in the gain of plantaris as well, 1.3-fold, compared to ~1.5-fold gain in the remaining strains. We conclude that variation in muscle mass at baseline is not a reliable predictor of that in the overload-induced gain. This suggests that a different set of genes influence variability in muscle mass acquired in the process of normal development, growth and maintenance, and in the process of adaptive

  7. Using ComBase Predictor and Pathogen Modeling Program as support tools in outbreak investigation: an example from Denmark

    DEFF Research Database (Denmark)

    Møller, Cleide; Hansen, Tina Beck; Andersen, Jens Kirk

    2009-01-01

    of salt to the batter. A deterministic model was constructed in Microsoft Excel using information on the production of the implicated sausage. This model predicted the level of Y. enterocolitica to increase 2.3, 4.2 and 7.8 log-units during fermentation, drying and storage, respectively. At the point...

  8. Regulatory and personality predictors of the reliability of professional actions

    Directory of Open Access Journals (Sweden)

    Morosanova V.I.

    2017-12-01

    Full Text Available Background. The present research is carried out in the context of the conscious self-regulation of professional activity. Objective. It investigates the regulatory and personality predictors of reliability in rescue operations under stressful conditions. Design. The research sample includes 87 rescuers (72 men and 15 women aged from 25 to 50 years. Respondents were asked to complete the Morosanova’s Self-Regulation Profile Questionnaire – SRPQM, the Eysenck Personality Profile - Short (EPP-S, and the expert questionnaire “Professional Reliability of Rescue Operation” designed for this particular study. Results. On the basis of a correlation analysis, the structural model of the predictors of action reliability was constructed using the maximum likelihood method. Consistency indices showed a good agreement between the model and empirical data. The model contains three latent factors: “Self-regulation”, “Neuroticism” and “Reliability of actions”. As the model displays, the “Self-regulation” factor is a significant predictor of professional action reliability. There are two indicator variables for the factor “Self-regulation”: the self-regulation reliability considered as its stability in the stressful situations, and the rescuers’ levels of development of professionally critical regulatory features - modeling of conditions significant for the achievement of goals and the programming of actions. The study results also show that personality dispositions (by Eysenck have only indirect influence on action reliability. As the structural model reveals, the conscious self-regulation is a mediator in the relationship of neuroticism traits and action reliability. Conclusion. The conscious self-regulation is a significant predictor of professional action reliability under stressful conditions. It is also the mediator of the effects of personality dispositions on the reliability of action.

  9. Improving winter leaf area index estimation in evergreen coniferous forests and its significance in carbon and water fluxes modeling

    Science.gov (United States)

    Wang, R.; Chen, J. M.; Luo, X.

    2016-12-01

    Modeling of carbon and water fluxes at the continental and global scales requires remotely sensed LAI as inputs. For evergreen coniferous forests (ENF), severely underestimated winter LAI has been one of the issues for mostly available remote sensing products, which could cause negative bias in the modeling of Gross Primary Productivity (GPP) and evapotranspiration (ET). Unlike deciduous trees which shed all the leaves in winter, conifers retains part of their needles and the proportion of the retained needles depends on the needle longevity. In this work, the Boreal Ecosystem Productivity Simulator (BEPS) was used to model GPP and ET at eight FLUXNET Canada ENF sites. Two sets of LAI were used as the model inputs: the 250m 10-day University of Toronto (U of T) LAI product Version 2 and the corrected LAI based on the U of T LAI product and the needle longevity of the corresponding tree species at individual sites. Validating model daily GPP (gC/m2) against site measurements, the mean RMSE over eight sites decreases from 1.85 to 1.15, and the bias changes from -0.99 to -0.19. For daily ET (mm), mean RMSE decreases from 0.63 to 0.33, and the bias changes from -0.31 to -0.16. Most of the improvements occur in the beginning and at the end of the growing season when there is large correction of LAI and meanwhile temperature is still suitable for photosynthesis and transpiration. For the dormant season, the improvement in ET simulation mostly comes from the increased interception of precipitation brought by the elevated LAI during that time. The results indicate that model performance can be improved by the application the corrected LAI. Improving the winter RS LAI can make a large impact on land surface carbon and energy budget.

  10. Investigation of the chromosome regions with significant affinity for the nuclear envelope in fruit fly--a model based approach.

    Directory of Open Access Journals (Sweden)

    Nicholas Allen Kinney

    Full Text Available Three dimensional nuclear architecture is important for genome function, but is still poorly understood. In particular, little is known about the role of the "boundary conditions"--points of attachment between chromosomes and the nuclear envelope. We describe a method for modeling the 3D organization of the interphase nucleus, and its application to analysis of chromosome-nuclear envelope (Chr-NE attachments of polytene (giant chromosomes in Drosophila melanogaster salivary glands. The model represents chromosomes as self-avoiding polymer chains confined within the nucleus; parameters of the model are taken directly from experiment, no fitting parameters are introduced. Methods are developed to objectively quantify chromosome territories and intertwining, which are discussed in the context of corresponding experimental observations. In particular, a mathematically rigorous definition of a territory based on convex hull is proposed. The self-avoiding polymer model is used to re-analyze previous experimental data; the analysis suggests 33 additional Chr-NE attachments in addition to the 15 already explored Chr-NE attachments. Most of these new Chr-NE attachments correspond to intercalary heterochromatin--gene poor, dark staining, late replicating regions of the genome; however, three correspond to euchromatin--gene rich, light staining, early replicating regions of the genome. The analysis also suggests 5 regions of anti-contact, characterized by aversion for the NE, only two of these correspond to euchromatin. This composition of chromatin suggests that heterochromatin may not be necessary or sufficient for the formation of a Chr-NE attachment. To the extent that the proposed model represents reality, the confinement of the polytene chromosomes in a spherical nucleus alone does not favor the positioning of specific chromosome regions at the NE as seen in experiment; consequently, the 15 experimentally known Chr-NE attachment positions do not

  11. Predicting bottlenose dolphin distribution along Liguria coast (northwestern Mediterranean Sea) through different modeling techniques and indirect predictors.

    Science.gov (United States)

    Marini, C; Fossa, F; Paoli, C; Bellingeri, M; Gnone, G; Vassallo, P

    2015-03-01

    Habitat modeling is an important tool to investigate the quality of the habitat for a species within a certain area, to predict species distribution and to understand the ecological processes behind it. Many species have been investigated by means of habitat modeling techniques mainly to address effective management and protection policies and cetaceans play an important role in this context. The bottlenose dolphin (Tursiops truncatus) has been investigated with habitat modeling techniques since 1997. The objectives of this work were to predict the distribution of bottlenose dolphin in a coastal area through the use of static morphological features and to compare the prediction performances of three different modeling techniques: Generalized Linear Model (GLM), Generalized Additive Model (GAM) and Random Forest (RF). Four static variables were tested: depth, bottom slope, distance from 100 m bathymetric contour and distance from coast. RF revealed itself both the most accurate and the most precise modeling technique with very high distribution probabilities predicted in presence cells (90.4% of mean predicted probabilities) and with 66.7% of presence cells with a predicted probability comprised between 90% and 100%. The bottlenose distribution obtained with RF allowed the identification of specific areas with particularly high presence probability along the coastal zone; the recognition of these core areas may be the starting point to develop effective management practices to improve T. truncatus protection. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Exogenous and Endogenous Learning Resources in the Actiotope Model of Giftedness and Its Significance for Gifted Education

    Science.gov (United States)

    Ziegler, Albert; Chandler, Kimberley L.; Vialle, Wilma; Stoeger, Heidrun

    2017-01-01

    Based on the Actiotope Model of Giftedness, this article introduces a learning-resource-oriented approach for gifted education. It provides a comprehensive categorization of learning resources, including five exogenous learning resources termed "educational capital" and five endogenous learning resources termed "learning…

  13. Segmentation process significantly influences the accuracy of 3D surface models derived from cone beam computed tomography

    NARCIS (Netherlands)

    Fourie, Zacharias; Damstra, Janalt; Schepers, Rutger H; Gerrits, Pieter; Ren, Yijin

    AIMS: To assess the accuracy of surface models derived from 3D cone beam computed tomography (CBCT) with two different segmentation protocols. MATERIALS AND METHODS: Seven fresh-frozen cadaver heads were used. There was no conflict of interests in this study. CBCT scans were made of the heads and 3D

  14. Predictors of male microchimerism

    DEFF Research Database (Denmark)

    Kamper-Jørgensen, Mads; Mortensen, Laust Hvas; Andersen, Anne-Marie Nybo

    2012-01-01

    confounding and reverse causation. To address the issue of confounding, we conducted an analysis of predictors of male microchimerism in 272 female participants of the Danish Diet, Cancer and Health cohort. Buffy coat DNA was tested for Y chromosome presence as a marker of male microchimerism. First, we used...... logistic regression and thereafter random forest modeling to evaluate the ability of a range of reproductive, lifestyle, hospital or clinic visit history, and other variables to predict whether women tested positive for male microchimerism. We found some indication that current use of contraceptive pills...... and hormone replacement therapy reduced the odds of testing positive for male microchimerism. However, prediction of male microchimerism presence was poor based on the available variables. Studies of the possible role of male microchimerism in maternal health and disease are therefore unlikely to be heavily...

  15. A conceptual model of individual competency components as one of the predictors of success in mergers and acquisitions

    Directory of Open Access Journals (Sweden)

    Darko Kovač

    2008-12-01

    Full Text Available The increasing challenge of how to balance “soft” human factors with “hard” financial factors in mergers and acquisitions (M&A to be successful is not new. However, the real challenge lies in the question of how, and with which yardstick, to measure and compare the human factor in both the acquiring and the acquired companies in all phases of M&A. In this study, a model for measuring and comparing the human factor with competencies is presented. The model enables the measuring of soft factors with quantitative criteria. A tripartite individual competency components construct is conceived: cognitive, affective and conative, to which the personal value system is added. The model discussed is based on empirical findings and the cases of two companies and literature. The model enables companies to compare differences in competencies and thus to plan activities how to overcome those differences and achieve a higher success rate in M&A.

  16. Empowering Yoruba Women in Nigeria to Prevent HIV/AIDS: The Relative Significance of Behavioural and Social Determinant Models

    Directory of Open Access Journals (Sweden)

    Oluwatosin Ige Alo

    2013-10-01

    Full Text Available This article uncovers the relevance to practice of behavioural and social determinant models of HIV prevention among Yoruba women in Nigeria. Exploring what factors influence health behaviour in heterosexual relationships, the key question raised was whether the women’s experiences support the assumptions and prescriptions for action of these two dominant public health models. Eight focus group discussions and 39 in-depth interviews were conducted, which involved 121 women and men who were chosen purposefully and through self-nomination technique. This study revealed that the women were very much constrained by social environments in negotiating safe sex, despite having at least a basic knowledge of HIV prevention. Limiting factors included the fear of relationship breakup, economic dependence, violence, and the difficulties in justifying why they feel the need to insist on condom use, especially since initiating condom use is antithetical to trust. Furthermore, evidence suggested that improved access to income and education might be vital but it does not automatically constitute a direct means of empowering women to prevent HIV infection. The limitations of both behavioural and social determinants perspectives thus suggests the need for a combination prevention model, which focuses on how social, behavioural and biomedical factors overlap in shaping health outcomes.

  17. Flexible parametric survival models built on age-specific antimüllerian hormone percentiles are better predictors of menopause.

    Science.gov (United States)

    Ramezani Tehrani, Fahimeh; Mansournia, Mohammad Ali; Solaymani-Dodaran, Masoud; Steyerberg, Ewout; Azizi, Fereidoun

    2016-06-01

    This study aimed to improve existing prediction models for age at menopause. We identified all reproductive aged women with regular menstrual cycles who met our eligibility criteria (n = 1,015) in the Tehran Lipid and Glucose Study-an ongoing population-based cohort study initiated in 1998. Participants were examined every 3 years and their reproductive histories were recorded. Blood levels of antimüllerian hormone (AMH) were measured at the time of recruitment. Age at menopause was estimated based on serum concentrations of AMH using flexible parametric survival models. The optimum model was selected according to Akaike Information Criteria and the realness of the range of predicted median menopause age. We followed study participants for a median of 9.8 years during which 277 women reached menopause and found that a spline-based proportional odds model including age-specific AMH percentiles as the covariate performed well in terms of statistical criteria and provided the most clinically relevant and realistic predictions. The range of predicted median age at menopause for this model was 47.1 to 55.9 years. For those who reached menopause, the median of the absolute mean difference between actual and predicted age at menopause was 1.9 years (interquartile range 2.9). The model including the age-specific AMH percentiles as the covariate and using proportional odds as its covariate metrics meets all the statistical criteria for the best model and provides the most clinically relevant and realistic predictions for age at menopause for reproductive-aged women.

  18. Using ComBase Predictor and Pathogen Modeling Program as support tools in outbreak investigation: an example from Denmark

    DEFF Research Database (Denmark)

    Møller, Cleide; Hansen, Tina Beck; Andersen, Jens Kirk

    2009-01-01

    of salt to the batter. A deterministic model was constructed in Microsoft Excel using information on the production of the implicated sausage. This model predicted the level of Y. enterocolitica to increase 2.3, 4.2 and 7.8 log-units during fermentation, drying and storage, respectively. At the point...... of release of the sausage for sale, 1 Y. enterocolitica could have increased to 106 and the sausage could, therefore, not be ruled out as the source of Y. enterocolitica found in two of the outbreak cases....

  19. Technique for ranking potential predictor layers for use in remote sensing analysis

    Science.gov (United States)

    Andrew Lister; Mike Hoppus; Rachel Riemann

    2004-01-01

    Spatial modeling using GIS-based predictor layers often requires that extraneous predictors be culled before conducting analysis. In some cases, using extraneous predictor layers might improve model accuracy but at the expense of increasing complexity and interpretability. In other cases, using extraneous layers can dilute the relationship between predictors and target...

  20. Anthropogenic fugitive, combustion and industrial dust is a significant, underrepresented fine particulate matter source in global atmospheric models

    Science.gov (United States)

    Philip, Sajeev; Martin, Randall V.; Snider, Graydon; Weagle, Crystal L.; van Donkelaar, Aaron; Brauer, Michael; Henze, Daven K.; Klimont, Zbigniew; Venkataraman, Chandra; Guttikunda, Sarath K.; Zhang, Qiang

    2017-04-01

    Global measurements of the elemental composition of fine particulate matter across several urban locations by the Surface Particulate Matter Network reveal an enhanced fraction of anthropogenic dust compared to natural dust sources, especially over Asia. We develop a global simulation of anthropogenic fugitive, combustion, and industrial dust which, to our knowledge, is partially missing or strongly underrepresented in global models. We estimate 2-16 μg m-3 increase in fine particulate mass concentration across East and South Asia by including anthropogenic fugitive, combustion, and industrial dust emissions. A simulation including anthropogenic fugitive, combustion, and industrial dust emissions increases the correlation from 0.06 to 0.66 of simulated fine dust in comparison with Surface Particulate Matter Network measurements at 13 globally dispersed locations, and reduces the low bias by 10% in total fine particulate mass in comparison with global in situ observations. Global population-weighted PM2.5 increases by 2.9 μg m-3 (10%). Our assessment ascertains the urgent need of including this underrepresented fine anthropogenic dust source into global bottom-up emission inventories and global models.

  1. Health Promotion Efforts as Predictors of Physical Activity in Schools: An Application of the Diffusion of Innovations Model

    Science.gov (United States)

    Glowacki, Elizabeth M.; Centeio, Erin E.; Van Dongen, Daniel J.; Carson, Russell L.; Castelli, Darla M.

    2016-01-01

    Background: Implementing a comprehensive school physical activity program (CSPAP) effectively addresses public health issues by providing opportunities for physical activity (PA). Grounded in the Diffusion of Innovations model, the purpose of this study was to identify how health promotion efforts facilitate opportunities for PA. Methods: Physical…

  2. [Different explanatory models for addictive behavior in Turkish and German youths in Germany: significance for prevention and treatment].

    Science.gov (United States)

    Penka, S; Krieg, S; Hunner, Ch; Heinz, A

    2003-07-01

    Due to cultural and social barriers, immigrants seldom frequent centers for information, counseling, and treatment of addictive disorders. We examine cultural differences in the explanatory models of addictive behavior among Turkish and German youths in Germany with statistical devices that map the concepts associated with problems of addiction. Relevant differences were found between the disorder concepts of Turkish and German youth. German but not Turkish youths classified eating disorders among severe addictive disorders and associated them with embarrassment and shame. Concerning substance abuse, German but not Turkish youths clearly differentiated between illegal drug abuse and the abuse of alcohol and nicotine. Nearly half of all Turkish youths rejected central medical concepts such as "physical dependence" or "reduced control of substance intake" as completely inadequate to characterize problems of addictive behavior. Preventive information programs must consider these differences and use concepts that are accepted and clearly associated with addictive behavior by immigrant populations.

  3. Exposure to family violence and attachment styles as predictors of dating violence perpetration among men and women: a mediational model.

    Science.gov (United States)

    Lee, Mary; Reese-Weber, Marla; Kahn, Jeffrey H

    2014-01-01

    This study examined a multiple mediator model explaining how sibling perpetration and one's attachment style mediate the relation between parent-to-child victimization and dating violence perpetration. A sample of undergraduate students (n = 392 women, n = 89 men) completed measures of the aforementioned variables on an Internet survey. For men, path analyses found no mediation; parent-to-child victimization had a direct association with dating violence perpetration, no association was found between sibling perpetration and dating violence perpetration, and attachment anxiety, but not attachment avoidance, was positively associated with dating violence perpetration for men. For women, the hypothesized mediation model was supported; parent-to-child victimization had a direct association with dating violence perpetration, and sibling perpetration and attachment anxiety served as mediating variables. Attachment avoidance was not associated with dating violence perpetration for women. Implications for future research and clinical practice are discussed.

  4. Cloud Computing Security Model with Combination of Data Encryption Standard Algorithm (DES) and Least Significant Bit (LSB)

    Science.gov (United States)

    Basri, M.; Mawengkang, H.; Zamzami, E. M.

    2018-03-01

    Limitations of storage sources is one option to switch to cloud storage. Confidentiality and security of data stored on the cloud is very important. To keep up the confidentiality and security of such data can be done one of them by using cryptography techniques. Data Encryption Standard (DES) is one of the block cipher algorithms used as standard symmetric encryption algorithm. This DES will produce 8 blocks of ciphers combined into one ciphertext, but the ciphertext are weak against brute force attacks. Therefore, the last 8 block cipher will be converted into 8 random images using Least Significant Bit (LSB) algorithm which later draws the result of cipher of DES algorithm to be merged into one.

  5. Predictors of hepatitis B cure using gene therapy to deliver DNA cleavage enzymes: a mathematical modeling approach.

    Directory of Open Access Journals (Sweden)

    Joshua T Schiffer

    Full Text Available Most chronic viral infections are managed with small molecule therapies that inhibit replication but are not curative because non-replicating viral forms can persist despite decades of suppressive treatment. There are therefore numerous strategies in development to eradicate all non-replicating viruses from the body. We are currently engineering DNA cleavage enzymes that specifically target hepatitis B virus covalently closed circular DNA (HBV cccDNA, the episomal form of the virus that persists despite potent antiviral therapies. DNA cleavage enzymes, including homing endonucleases or meganucleases, zinc-finger nucleases (ZFNs, TAL effector nucleases (TALENs, and CRISPR-associated system 9 (Cas9 proteins, can disrupt specific regions of viral DNA. Because DNA repair is error prone, the virus can be neutralized after repeated cleavage events when a target sequence becomes mutated. DNA cleavage enzymes will be delivered as genes within viral vectors that enter hepatocytes. Here we develop mathematical models that describe the delivery and intracellular activity of DNA cleavage enzymes. Model simulations predict that high vector to target cell ratio, limited removal of delivery vectors by humoral immunity, and avid binding between enzyme and its DNA target will promote the highest level of cccDNA disruption. Development of de novo resistance to cleavage enzymes may occur if DNA cleavage and error prone repair does not render the viral episome replication incompetent: our model predicts that concurrent delivery of multiple enzymes which target different vital cccDNA regions, or sequential delivery of different enzymes, are both potentially useful strategies for avoiding multi-enzyme resistance. The underlying dynamics of cccDNA persistence are unlikely to impact the probability of cure provided that antiviral therapy is given concurrently during eradication trials. We conclude by describing experiments that can be used to validate the model, which

  6. Predictors of hepatitis B cure using gene therapy to deliver DNA cleavage enzymes: a mathematical modeling approach.

    Science.gov (United States)

    Schiffer, Joshua T; Swan, Dave A; Stone, Daniel; Jerome, Keith R

    2013-01-01

    Most chronic viral infections are managed with small molecule therapies that inhibit replication but are not curative because non-replicating viral forms can persist despite decades of suppressive treatment. There are therefore numerous strategies in development to eradicate all non-replicating viruses from the body. We are currently engineering DNA cleavage enzymes that specifically target hepatitis B virus covalently closed circular DNA (HBV cccDNA), the episomal form of the virus that persists despite potent antiviral therapies. DNA cleavage enzymes, including homing endonucleases or meganucleases, zinc-finger nucleases (ZFNs), TAL effector nucleases (TALENs), and CRISPR-associated system 9 (Cas9) proteins, can disrupt specific regions of viral DNA. Because DNA repair is error prone, the virus can be neutralized after repeated cleavage events when a target sequence becomes mutated. DNA cleavage enzymes will be delivered as genes within viral vectors that enter hepatocytes. Here we develop mathematical models that describe the delivery and intracellular activity of DNA cleavage enzymes. Model simulations predict that high vector to target cell ratio, limited removal of delivery vectors by humoral immunity, and avid binding between enzyme and its DNA target will promote the highest level of cccDNA disruption. Development of de novo resistance to cleavage enzymes may occur if DNA cleavage and error prone repair does not render the viral episome replication incompetent: our model predicts that concurrent delivery of multiple enzymes which target different vital cccDNA regions, or sequential delivery of different enzymes, are both potentially useful strategies for avoiding multi-enzyme resistance. The underlying dynamics of cccDNA persistence are unlikely to impact the probability of cure provided that antiviral therapy is given concurrently during eradication trials. We conclude by describing experiments that can be used to validate the model, which will in turn

  7. Mouse p53-Deficient Cancer Models as Platforms for Obtaining Genomic Predictors of Human Cancer Clinical Outcomes

    Science.gov (United States)

    Dueñas, Marta; Santos, Mirentxu; Aranda, Juan F.; Bielza, Concha; Martínez-Cruz, Ana B.; Lorz, Corina; Taron, Miquel; Ciruelos, Eva M.; Rodríguez-Peralto, José L.; Martín, Miguel; Larrañaga, Pedro; Dahabreh, Jubrail; Stathopoulos, George P.; Rosell, Rafael; Paramio, Jesús M.; García-Escudero, Ramón

    2012-01-01

    Mutations in the TP53 gene are very common in human cancers, and are associated with poor clinical outcome. Transgenic mouse models lacking the Trp53 gene or that express mutant Trp53 transgenes produce tumours with malignant features in many organs. We previously showed the transcriptome of a p53-deficient mouse skin carcinoma model to be similar to those of human cancers with TP53 mutations and associated with poor clinical outcomes. This report shows that much of the 682-gene signature of this murine skin carcinoma transcriptome is also present in breast and lung cancer mouse models in which p53 is inhibited. Further, we report validated gene-expression-based tests for predicting the clinical outcome of human breast and lung adenocarcinoma. It was found that human patients with cancer could be stratified based on the similarity of their transcriptome with the mouse skin carcinoma 682-gene signature. The results also provide new targets for the treatment of p53-defective tumours. PMID:22880004

  8. Predictors of Burnout Among Nurses in Taiwan.

    Science.gov (United States)

    Lee, Huan-Fang; Yen, Miaofen; Fetzer, Susan; Chien, Tsair Wei

    2015-08-01

    Nurse burnout is a crucial issue for health care professionals and impacts nurse turnover and nursing shortages. Individual and situational factors are related to nurse burnout with predictors of burnout differing among cultures and health care systems. The predictors of nurse burnout in Asia, particularly Taiwan, are unknown. The purpose of this study was to investigate the predictors of burnout among a national sample of nurses in Taiwan. A secondary data analysis of a nationwide database investigated the predictors of burnout among 1,846 nurses in Taiwan. Hierarchical regression analysis determined the relationship between predictors and burnout. Predictors of Taiwanese nurse burnout were age, physical/psychological symptoms, job satisfaction, work engagement, and work environment. The most significant predictors were physical/psychological symptoms and work engagement. The variables explained 35, 39, and 18 % of the emotional exhaustion, personal accomplishment, and depersonalization variance for 54 % of the total variance of burnout. Individual characteristics and nurse self-awareness, especially work, engagement can impact Taiwanese nurses' burnout. Nurse burnout predictors provide administrators with information to develop strategies including education programs and support services to reduce nurse burnout.

  9. Social network predictors of latrine ownership.

    Science.gov (United States)

    Shakya, Holly B; Christakis, Nicholas A; Fowler, James H

    2015-01-01

    Poor sanitation, including the lack of clean functioning toilets, is a major factor contributing to morbidity and mortality from infectious diseases in the developing world. We examine correlates of latrine ownership in rural India with a focus on social network predictors. Participants from 75 villages provided the names of their social contacts as well as their own relevant demographic and household characteristics. Using these measures, we test whether the latrine ownership of an individual's social contacts is a significant predictor of individual latrine ownership. We also investigate whether network centrality significantly predicts latrine ownership, and if so, whether it moderates the relationship between the latrine ownership of the individual and that of her social contacts. Our results show that, controlling for the standard predictors of latrine ownership such as caste, education, and income, individuals are more likely to own latrines if their social contacts own latrines. Interaction models suggest that this relationship is stronger among those of the same caste, the same education, and those with stronger social ties. We also find that more central individuals are more likely to own latrines, but the correlation in latrine ownership between social contacts is strongest among individuals on the periphery of the network. Although more data is needed to determine how much the clustering of latrine ownership may be caused by social influence, the results here suggest that interventions designed to promote latrine ownership should consider focusing on those at the periphery of the network. The reason is that they are 1) less likely to own latrines and 2) more likely to exhibit the same behavior as their social contacts, possibly as a result of the spread of latrine adoption from one person to another. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state–space models

    Science.gov (United States)

    Polansky, Leo; Kilian, Werner; Wittemyer, George

    2015-01-01

    Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State–space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water. Behavioural change point (BCP) analyses demonstrated that these goal-oriented movements were initiated on average 4.59 km, and up to 49.97 km, from the visited waterhole, with the closest waterhole accessed 90% of the time. Distances of decision points increased when switching to different waterholes, during the dry season, or for female groups relative to males, while selection of the closest waterhole decreased when switching. Overall, our analyses indicated detailed spatial knowledge over large scales, enabling elephants to minimize travel distance through highly directional movement when accessing water. We discuss the likely cognitive and socioecological mechanisms driving these spatially precise movements that are most consistent with our findings. By applying modern analytic techniques to high-resolution movement data, this study illustrates emerging approaches for studying how cognition structures animal movement behaviour in different ecological and social contexts. PMID:25808888

  11. On the significance of contaminant plume-scale and dose-response models in defining hydrogeological characterization needs

    Science.gov (United States)

    de Barros, F.; Rubin, Y.; Maxwell, R.; Bai, H.

    2007-12-01

    Defining rational and effective hydrogeological data acquisition strategies is of crucial importance since financial resources available for such efforts are always limited. Usually such strategies are developed with the goal of reducing uncertainty, but less often they are developed in the context of the impacts of uncertainty. This paper presents an approach for determining site characterization needs based on human health risk factors. The main challenge is in striking a balance between improved definition of hydrogeological, behavioral and physiological parameters. Striking this balance can provide clear guidance on setting priorities for data acquisition and for better estimating adverse health effects in humans. This paper addresses this challenge through theoretical developments and numerical testing. We will report on a wide range of factors that affect the site characterization needs including contaminant plume's dimensions, travel distances and other length scales that characterize the transport problem, as well as health risk models. We introduce a new graphical tool that allows one to investigate the relative impact of hydrogeological and physiological parameters in risk. Results show that the impact of uncertainty reduction in the risk-related parameters decreases with increasing distances from the contaminant source. Also, results indicate that human health risk becomes less sensitive to hydrogeological measurements when dealing with ergodic plumes. This indicates that under ergodic conditions, uncertainty reduction in human health risk may benefit from better understanding of the physiological component as opposed to a detailed hydrogeological characterization

  12. Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state-space models.

    Science.gov (United States)

    Polansky, Leo; Kilian, Werner; Wittemyer, George

    2015-04-22

    Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State-space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water. Behavioural change point (BCP) analyses demonstrated that these goal-oriented movements were initiated on average 4.59 km, and up to 49.97 km, from the visited waterhole, with the closest waterhole accessed 90% of the time. Distances of decision points increased when switching to different waterholes, during the dry season, or for female groups relative to males, while selection of the closest waterhole decreased when switching. Overall, our analyses indicated detailed spatial knowledge over large scales, enabling elephants to minimize travel distance through highly directional movement when accessing water. We discuss the likely cognitive and socioecological mechanisms driving these spatially precise movements that are most consistent with our findings. By applying modern analytic techniques to high-resolution movement data, this study illustrates emerging approaches for studying how cognition structures animal movement behaviour in different ecological and social contexts. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  13. Different Techniques of Respiratory Support Do Not Significantly Affect Gas Exchange during Cardiopulmonary Resuscitation in a Newborn Piglet Model.

    Science.gov (United States)

    Mendler, Marc R; Maurer, Miriam; Hassan, Mohammad A; Huang, Li; Waitz, Markus; Mayer, Benjamin; Hummler, Helmut D

    2015-01-01

    There are no evidence-based recommendations on the use of different techniques of respiratory support and chest compressions (CC) during neonatal cardiopulmonary resuscitation (CPR). We studied the short-term effects of different ventilatory support strategies along with CC representing clinical practice on gas exchange [arterial oxygen saturation (SaO2), arterial partial pressure of oxygen (PaO2) and arterial partial pressure of carbon dioxide (PaCO2)], hemodynamics and cerebral oxygenation. We hypothesized that in newborn piglets with cardiac arrest, use of a T-piece resuscitator (TPR) providing positive end-expiratory pressure (PEEP) improves gas exchange as measured by SaO2 during CPR as compared to using a self-inflating bag (SIB) without PEEP. Furthermore, we explored the effects of a mechanical ventilator without synchrony to CC. Thirty newborn piglets with asystole were randomized into three groups and resuscitated for 20 min [fraction of inspired oxygen (FiO2) = 0.21 for 10 min and 1.0 thereafter]. Group 1 received ventilation using a TPR [peak inspiratory pressure (PIP)/PEEP of 20/5 cm H2O, rate 30/min] with inflations interposed between CC (3:1 ratio). Group 2 received ventilation using a SIB (PIP of 20 cm H2O without PEEP, rate 30/min) with inflations interposed between CC (3:1 ratio). Group 3 received ventilation using a mechanical ventilator (PIP/PEEP of 20/5 cm H2O, rate 30/min). CC were applied with a rate of 120/min without synchrony to inflations. We found no significant differences in SaO2 between the three groups. However, there was a trend toward a higher SaO2 [TPR: 28.0% (22.3-40.0); SIB: 23.7% (13.4-52.3); ventilator: 44.1% (39.2-54.3); median (interquartile range)] and a lower PaCO2 [TPR: 95.6 mm Hg (82.1-113.6); SIB: 100.8 mm Hg (83.0-108.0); ventilator: 74.1 mm Hg (68.5-83.1); median (interquartile range)] in the mechanical ventilator group. We found no significant effect on gas exchange using different respiratory support strategies

  14. Predictors of FIFA 11+ Implementation Intention in Female Adolescent Soccer: An Application of the Health Action Process Approach (HAPA Model

    Directory of Open Access Journals (Sweden)

    Carly D. McKay

    2016-07-01

    Full Text Available The Fédération Internationale de Football (FIFA 11+ warm-up program is efficacious at preventing lower limb injury in youth soccer; however, there has been poor adoption of the program in the community. The purpose of this study was to determine the utility of the Health Action Process Approach (HAPA behavior change model in predicting intention to use the FIFA 11+ in a sample of 12 youth soccer teams (coaches n = 10; 12–16 year old female players n = 200. A bespoke cross-sectional questionnaire measured pre-season risk perceptions, outcome expectancies, task self-efficacy, facilitators, barriers, and FIFA 11+ implementation intention. Most coaches (90.0% and players (80.0% expected the program to reduce injury risk but reported limited intention to use it. Player data demonstrated an acceptable fit to the hypothesized model (standardized root mean square residual (SRMR = 0.08; root mean square of error of approximation (RMSEA = 0.06 (0.047–0.080; comparative fit index (CFI = 0.93; Tucker Lewis index (TLI = 0.91 Task self-efficacy (β = 0.53, p ≤ 0.01 and outcome expectancies (β = 0.13 p ≤ 0.05 were positively associated with intention, but risk perceptions were not (β = −0.02. The findings suggest that the HAPA model is appropriate for use in this context, and highlight the need to target task self-efficacy and outcome expectancies in FIFA 11+ implementation strategies.

  15. Poverty as a Predictor of 4-Year-Olds’ Executive Function: New Perspectives on Models of Differential Susceptibility

    Science.gov (United States)

    Raver, C. Cybele; Blair, Clancy; Willoughby, Michael

    2017-01-01

    In a predominantly low-income, population-based longitudinal sample of 1,259 children followed from birth, results suggest that chronic exposure to poverty and the strains of financial hardship were each uniquely predictive of young children’s performance on measures of executive functioning. Results suggest that temperament-based vulnerability serves as a statistical moderator of the link between poverty-related risk and children’s executive functioning. Implications for models of ecology and biology in shaping the development of children’s self-regulation are discussed. PMID:22563675

  16. The Significance of Quality Assurance within Model Intercomparison Projects at the World Data Centre for Climate (WDCC)

    Science.gov (United States)

    Toussaint, F.; Hoeck, H.; Stockhause, M.; Lautenschlager, M.

    2014-12-01

    The classical goals of a quality assessment system in the data life cycle are (1) to encourage data creators to improve their quality assessment procedures to reach the next quality level and (2) enable data consumers to decide, whether a dataset has a quality that is sufficient for usage in the target application, i.e. to appraise the data usability for their own purpose.As the data volumes of projects and the interdisciplinarity of data usage grow, the need for homogeneous structure and standardised notation of data and metadata increases. This third aspect is especially valid for the data repositories, as they manage data through machine agents. So checks for homogeneity and consistency in early parts of the workflow become essential to cope with today's data volumes.Selected parts of the workflow in the model intercomparison project CMIP5 and the archival of the data for the interdiscipliary user community of the IPCC-DDC AR5 and the associated quality checks are reviewed. We compare data and metadata checks and relate different types of checks to their positions in the data life cycle.The project's data citation approach is included in the discussion, with focus on temporal aspects of the time necessary to comply with the project's requirements for formal data citations and the demand for the availability of such data citations.In order to make different quality assessments of projects comparable, WDCC developed a generic Quality Assessment System. Based on the self-assessment approach of a maturity matrix, an objective and uniform quality level system for all data at WDCC is derived which consists of five maturity quality levels.

  17. Greater expectations: using hierarchical linear modeling to examine expectancy for treatment outcome as a predictor of treatment response.

    Science.gov (United States)

    Price, Matthew; Anderson, Page; Henrich, Christopher C; Rothbaum, Barbara Olasov

    2008-12-01

    A client's expectation that therapy will be beneficial has long been considered an important factor contributing to therapeutic outcomes, but recent empirical work examining this hypothesis has primarily yielded null findings. The present study examined the contribution of expectancies for treatment outcome to actual treatment outcome from the start of therapy through 12-month follow-up in a clinical sample of individuals (n=72) treated for fear of flying with either in vivo exposure or virtual reality exposure therapy. Using a piecewise hierarchical linear model, outcome expectancy predicted treatment gains made during therapy but not during follow-up. Compared to lower levels, higher expectations for treatment outcome yielded stronger rates of symptom reduction from the beginning to the end of treatment on 2 standardized self-report questionnaires on fear of flying. The analytic approach of the current study is one potential reason that findings contrast with prior literature. The advantages of using hierarchical linear modeling to assess interindividual differences in longitudinal data are discussed.

  18. Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children

    Science.gov (United States)

    Onicescu, Georgiana; Lawson, Andrew B.; McDermott, Suzanne; Aelion, C. Marjorie; Cai, Bo

    2014-01-01

    In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months. PMID:24888618

  19. Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children.

    Science.gov (United States)

    Onicescu, Georgiana; Lawson, Andrew B; McDermott, Suzanne; Aelion, C Marjorie; Cai, Bo

    2014-09-01

    In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months.

  20. Macrophytes may not contribute significantly to removal of nutrients, pharmaceuticals, and antibiotic resistance in model surface constructed wetlands.

    Science.gov (United States)

    Cardinal, Pascal; Anderson, Julie C; Carlson, Jules C; Low, Jennifer E; Challis, Jonathan K; Beattie, Sarah A; Bartel, Caitlin N; Elliott, Ashley D; Montero, Oscar F; Lokesh, Sheetal; Favreau, Alex; Kozlova, Tatiana A; Knapp, Charles W; Hanson, Mark L; Wong, Charles S

    2014-06-01

    Outdoor shallow wetland mesocosms, designed to simulate surface constructed wetlands to improve lagoon wastewater treatment, were used to assess the role of macrophytes in the dissipation of wastewater nutrients, selected pharmaceuticals, and antibiotic resistance genes (ARGs). Specifically, mesocosms were established with or without populations of Typha spp. (cattails), Myriophyllum sibiricum (northern water milfoil), and Utricularia vulgaris (bladderwort). Following macrophyte establishment, mesocosms were seeded with ARG-bearing organisms from a local wastewater lagoon, and treated with a single pulse of artificial municipal wastewater with or without carbamazepine, clofibric acid, fluoxetine, and naproxen (each at 7.6μg/L), as well as sulfamethoxazole and sulfapyridine (each at 150μg/L). Rates of pharmaceutical dissipation over 28d ranged from 0.073 to 3.0d(-1), corresponding to half-lives of 0.23 to 9.4d. Based on calculated rate constants, observed dissipation rates were consistent with photodegradation driving clofibric acid, naproxen, sulfamethoxazole, and sulfapyridine removal, and with sorption also contributing to carbamazepine and fluoxetine loss. Of the seven gene determinants assayed, only two genes for both beta-lactam resistance (blaCTX and blaTEM) and sulfonamide resistance (sulI and sulII) were found in sufficient quantity for monitoring. Genes disappeared relatively rapidly from the water column, with half-lives ranging from 2.1 to 99d. In contrast, detected gene levels did not change in the sediment, with the exception of sulI, which increased after 28d in pharmaceutical-treated systems. These shallow wetland mesocosms were able to dissipate wastewater contaminants rapidly. However, no significant enhancement in removal of nutrients or pharmaceuticals was observed in mesocosms with extensive aquatic plant communities. This was likely due to three factors: first, use of naïve systems with an unchallenged capacity for nutrient assimilation and

  1. Caspase-3 may be employed as an early predictor for fracture‑induced osteonecrosis of the femoral head in a canine model.

    Science.gov (United States)

    Gao, You-Shui; Guo, Shang-Chun; Ding, Hao; Zhang, Chang-Qing

    2012-09-01

    The aim of the current study was to investigate the local expression of caspase-3 following femoral neck fractures in a canine model and to investigate its effect on the occurrence of fracture-induced osteonecrosis of the femoral head (ONFH). Eight dogs had surgically-induced femoral neck fractures on the left side which remained untreated. Radiological and histological examinations were employed to detect morphological changes of the femoral head. Immunohistochemical staining of caspase-3 was used to evaluate cell apoptosis, which may play an important role in ONFH. The results were compared to the normal side for statistical analysis. As a result, all eight dogs had ONFH, with non-union in five and malunion in three on radiological examination. Histologically, the untreated femoral heads developed osteonecrosis with an accumulation of bone marrow cell debris, empty lacunae and/or ghost nuclei in the lacunae, and an increase in the number of fat cells. Immunohistochemical staining of caspase-3 indicated that it was upregulated in fracture-induced ONFH two weeks postoperatively, which showed a statistical difference when compared to the normal side. In conclusion, the local expression of caspase-3 was upregulated in fracture-induced ONFH, suggesting that cell apoptosis is crucial in traumatic ONFH. Caspase-3 may therefore be employed as an effective and early predictor for fracture-induced ONFH.

  2. Predictors of bovine TB risk behaviour amongst meat handlers in Nigeria: a cross-sectional study guided by the health belief model.

    Science.gov (United States)

    Hambolu, Dupe; Freeman, Jenny; Taddese, Henock B

    2013-01-01

    Bovine Tuberculosis (bTB) is still a serious public health threat in developing countries. The aim of this study is to determine the social and cognitive factors predicting one of the risk behaviours amongst meat handlers in Nigeria, namely, eating Fuku Elegusi. This is the practice of eating the visibly infected parts of the lung in-order to convince customers to buy meat. The study is guided by the health belief model (HBM). This is a cross-sectional study of 349 randomly selected meat handlers in Oko-Oba Abattoir, in Lagos State. Descriptive statistics and multiple logistic regression analysis were employed to determine perceptions and prevalence of risk behaviours and to identify predictors of eating Fuku Elegusi. Just over a quarter (28.1%) of the study participants knew that eating Fuku Elegusi could be a source of bTB in humans. The prevalence of eating Fuku Elegusi was found to be 22%. Across all knowledge indicators related to bTB, those who don't eat Fuku Elegusi exhibited better knowledge. Strong predictors of eating Fuku Elegusi were: being male (OR: 2.39, 95% CI: 1.10 to 5.19; p = 0.03), not knowing that eating Fuku Elegusi exposes to bTB (OR: 3.72, 95% CI: 1.69 to 8.22; p = 0.001), and the perception that one cannot sell meat without tasting it (perceived barrier) (OR: 1.35, 95% CI: 1.13 to 1.60; p = 0.001). Lower risk of eating Fuku Elegusi was predicted by perceived susceptibility to bTB due to another risk behaviour, namely, not washing hands after handling meat (OR: 0.78, 95% CI: 0.64 to 0.96; p-value = 0.021). Television and radio were the most acceptable media for TB prevention messages (78.5% and 75.6% respectively). Meat handlers in developing countries bear high risk to bTB owing to prevailing social and cognition determinants. Findings were largely consistent with the propositions of HBM.

  3. Predictors of bovine TB risk behaviour amongst meat handlers in Nigeria: a cross-sectional study guided by the health belief model.

    Directory of Open Access Journals (Sweden)

    Dupe Hambolu

    Full Text Available Bovine Tuberculosis (bTB is still a serious public health threat in developing countries. The aim of this study is to determine the social and cognitive factors predicting one of the risk behaviours amongst meat handlers in Nigeria, namely, eating Fuku Elegusi. This is the practice of eating the visibly infected parts of the lung in-order to convince customers to buy meat. The study is guided by the health belief model (HBM.This is a cross-sectional study of 349 randomly selected meat handlers in Oko-Oba Abattoir, in Lagos State. Descriptive statistics and multiple logistic regression analysis were employed to determine perceptions and prevalence of risk behaviours and to identify predictors of eating Fuku Elegusi.Just over a quarter (28.1% of the study participants knew that eating Fuku Elegusi could be a source of bTB in humans. The prevalence of eating Fuku Elegusi was found to be 22%. Across all knowledge indicators related to bTB, those who don't eat Fuku Elegusi exhibited better knowledge. Strong predictors of eating Fuku Elegusi were: being male (OR: 2.39, 95% CI: 1.10 to 5.19; p = 0.03, not knowing that eating Fuku Elegusi exposes to bTB (OR: 3.72, 95% CI: 1.69 to 8.22; p = 0.001, and the perception that one cannot sell meat without tasting it (perceived barrier (OR: 1.35, 95% CI: 1.13 to 1.60; p = 0.001. Lower risk of eating Fuku Elegusi was predicted by perceived susceptibility to bTB due to another risk behaviour, namely, not washing hands after handling meat (OR: 0.78, 95% CI: 0.64 to 0.96; p-value = 0.021. Television and radio were the most acceptable media for TB prevention messages (78.5% and 75.6% respectively.Meat handlers in developing countries bear high risk to bTB owing to prevailing social and cognition determinants. Findings were largely consistent with the propositions of HBM.

  4. Acute hypothalamic suppression significantly affects trabecular bone but not cortical bone following recovery and ovariectomy surgery in a rat model

    Directory of Open Access Journals (Sweden)

    Vanessa R. Yingling

    2016-01-01

    RH-a group compared to C, a similar deficit in BV/TV was also measured following recovery and post-OVX. The trabecular number and thickness were lower in the GnRH-a group compared to control.Conclusion. These data suggest that following a transient delay in pubertal onset, trabecular bone volume was significantly lower and no restoration of bone volume occurred following recovery or post-OVX surgery. However, cortical bone strength was maintained through architectural adaptations in the cortical bone envelope. An increase in the polar moment of inertia offset increased bone resorption. The current data are the first to suppress trabecular bone during growth, and then add an OVX protocol at maturity. Trabecular bone and cortical bone differed in their response to hypothalamic suppression during development; trabecular bone was more sensitive to the negative effects of hypothalamic suppression.

  5. Predictors of the nicotine reinforcement threshold, compensation, and elasticity of demand in a rodent model of nicotine reduction policy*

    Science.gov (United States)

    Grebenstein, Patricia E.; Burroughs, Danielle; Roiko, Samuel A.; Pentel, Paul R.; LeSage, Mark G.

    2015-01-01

    Background The FDA is considering reducing the nicotine content in tobacco products as a population-based strategy to reduce tobacco addiction. Research is needed to determine the threshold level of nicotine needed to maintain smoking and the extent of compensatory smoking that could occur during nicotine reduction. Sources of variability in these measures across sub-populations also need to be identified so that policies can take into account the risks and benefits of nicotine reduction in vulnerable populations. Methods The present study examined these issues in a rodent nicotine self- administration model of nicotine reduction policy to characterize individual differences in nicotine reinforcement thresholds, degree of compensation, and elasticity of demand during progressive reduction of the unit nicotine dose. The ability of individual differences in baseline nicotine intake and nicotine pharmacokinetics to predict responses to dose reduction was also examined. Results Considerable variability in the reinforcement threshold, compensation, and elasticity of demand was evident. High baseline nicotine intake was not correlated with the reinforcement threshold, but predicted less compensation and less elastic demand. Higher nicotine clearance predicted low reinforcement thresholds, greater compensation, and less elastic demand. Less elastic demand also predicted lower reinforcement thresholds. Conclusions These findings suggest that baseline nicotine intake, nicotine clearance, and the essential value of nicotine (i.e. elasticity of demand) moderate the effects of progressive nicotine reduction in rats and warrant further study in humans. They also suggest that smokers with fast nicotine metabolism may be more vulnerable to the risks of nicotine reduction. PMID:25891231

  6. The Homeostasis Model Assessment-adiponectin (HOMA-AD) is the most sensitive predictor of insulin resistance in obese children.

    Science.gov (United States)

    Makni, Emna; Moalla, Wassim; Lac, Gérard; Aouichaoui, Chirine; Cannon, Daniel; Elloumi, Mohamed; Tabka, Zouhair

    2012-02-01

    The aim of this study was to examine the efficacy of three indices i.e. adiponectin/leptin ratio, HOMA-IR and HOMA-AD in assessing insulin resistance among obese children. One hundred and twenty-two obese children (57 girls, 65 boys): mean age 13.7±1.3 years, BMI 30.1±4.5kg/m(2), eight tanner stage I, 48 tanner stage II-III, 66 tanner stage IV-V, participated in this study. They were classified into four groups according to sex and the presence of metabolic syndrome characteristics: with metabolic syndrome (MS; 21 girls and 36 boys) and controls without metabolic syndrome (CON, 36 girls and 29 boys). The correlations between these three indices of insulin resistance and the MS criteria were analyzed using linear and multiple regressions and receiver operating characteristics (ROC) curves analysis. The majority of anthropometric and biological parameters as well as adiponectin/leptin ratio, HOMA-IR and HOMA-AD were significantly different between MS and CON in both sexes. Both HOMA-AD and HOMA-IR were significantly correlated with the majority of metabolic syndrome components than was the adiponectin/leptin ratio in MS of both sexes. In boys and girls with and without MS, multiple regression analyses highlighted that both HOMA-AD and adiponectin/leptin ratio (r=-0.99 and r=-0.54 for MS girls and boys respectively, 0.05HOMA-AD and HOMA-IR (r=0.66 and r=0.31 for MS girls and boys respectively, 0.05HOMA-IR. Additionally, the area under the ROC curves for predicting insulin resistance were 0.69 (CI 95%, 0.60-0.77), 0.68 (CI 95%, 0.59-0.76) and 0.71 (CI 95%, 0.62-0.79) for adiponectin/leptin ratio, HOMA-IR and HOMA-AD, respectively. The current study strengthens the validity of the HOMA-AD as an adequate tool for determining insulin resistance among obese children with MS. Copyright © 2012. Published by Elsevier Masson SAS.

  7. Serum metabolomics identifies citrulline as a predictor of adverse outcomes in an equine model of gut-derived sepsis.

    Science.gov (United States)

    Steelman, Samantha M; Johnson, Philip; Jackson, Amy; Schulze, James; Chowdhary, Bhanu P

    2014-05-15

    Acute laminitis is an inflammatory disease of the equine foot that often occurs secondarily to sepsis or systemic inflammation associated with gastrointestinal disease. It has been suggested that laminitis is similar to multiple organ dysfunction syndrome in humans, although in horses the weight-bearing laminar epithelium of the foot appears to be the tissue most sensitive to insult and the first "organ" to fail. Metabolomics performed on serum samples collected before (Con) and after (Lmn) experimental induction of gastrointestinal-associated sepsis in six horses detected 1,177 metabolites of both mammalian and bacterial origin in equine serum. Network and correlation analyses suggested a dysregulation of fatty acid metabolism in the Lmn group, as well as an accumulation of organic acids such as lactate. Furthermore, concentrations of the amino acid citrulline were decreased in Lmn samples from all study animals, suggesting that citrulline might be useful as a biomarker to identify critically ill animals that are at risk of developing laminitis. We therefore established normal ranges of plasma citrulline concentrations in a separate group of horses (n = 36) and tested the ability of citrulline to predict adverse outcomes (laminitis or death) in critically ill horses (n = 23). Plasma citrulline was significantly lower in critically ill horses that went on to experience adverse outcomes (n = 6). Further study is required to accurately determine a diagnostic cutoff, but the present data are suggestive of the predictive value of citrulline as a biomarker for laminar failure in equine sepsis. Copyright © 2014 the American Physiological Society.

  8. Intra-articular (IA) ropivacaine microparticle suspensions reduce pain, inflammation, cytokine, and substance p levels significantly more than oral or IA celecoxib in a rat model of arthritis.

    Science.gov (United States)

    Rabinow, Barrett; Werling, Jane; Bendele, Alison; Gass, Jerome; Bogseth, Roy; Balla, Kelly; Valaitis, Paul; Hutchcraft, Audrey; Graham, Sabine

    2015-02-01

    Current therapeutic treatment options for osteoarthritis entail significant safety concerns. A novel ropivacaine crystalline microsuspension for bolus intra-articular (IA) delivery was thus developed and studied in a peptidoglycan polysaccharide (PGPS)-induced ankle swelling rat model. Compared with celecoxib controls, both oral and IA, ropivacaine IA treatment resulted in a significant reduction of pain upon successive PGPS reactivation, as demonstrated in two different pain models, gait analysis and incapacitance testing. The reduction in pain was attended by a significant reduction in histological inflammation, which in turn was accompanied by significant reductions in the cytokines IL-18 and IL-1β. This may have been due to inhibition of substance P, which was also significantly reduced. Pharmacokinetic analysis indicated that the analgesic effects outlasted measurable ropivacaine levels in either blood or tissue. The results are discussed in the context of pharmacologic mechanisms both of local anesthetics as well as inflammatory arthritis.

  9. Predictors of workplace violence among female sex workers in Tijuana, Mexico.

    Science.gov (United States)

    Katsulis, Yasmina; Durfee, Alesha; Lopez, Vera; Robillard, Alyssa

    2015-05-01

    For sex workers, differences in rates of exposure to workplace violence are likely influenced by a variety of risk factors, including where one works and under what circumstances. Economic stressors, such as housing insecurity, may also increase the likelihood of exposure. Bivariate analyses demonstrate statistically significant associations between workplace violence and selected predictor variables, including age, drug use, exchanging sex for goods, soliciting clients outdoors, and experiencing housing insecurity. Multivariate regression analysis shows that after controlling for each of these variables in one model, only soliciting clients outdoors and housing insecurity emerge as statistically significant predictors for workplace violence. © The Author(s) 2014.

  10. Childhood cardiovascular risk factors, a predictor of late adolescent overweight

    Directory of Open Access Journals (Sweden)

    Saeed Kalantari

    2016-01-01

    Conclusion: Increased CVD risk factors are predictors of future overweight in childhood and adolescent and increased weight is linked significantly with dyslipidemia and hypertension in this age group.

  11. Predictors of functional capacity in colorectal cancer patients.

    Science.gov (United States)

    Tomruk, Murat; Karadibak, Didem; Yavuzşen, Tuğba; Akman, Tülay

    2015-09-01

    The aim of this study is to determine the predictors of functional capacity and explore the relationship between functional capacity, performance status, fatigue, quality of life, anxiety, and depression in colorectal cancer (CRC) patients. Forty-two patients diagnosed as stage II-III CRC according to tumor, node, metastasis (TNM) classification were included the study. Functional capacity, performance status, fatigue, quality of life, anxiety, and depression of CRC patients were assessed using six-minute walk distance (6MWD) in the six-minute walk test (6MWT), Eastern Cooperative Oncology Group Performance Status (ECOG-PS), Brief Fatigue Inventory (BFI), Functional Assessment of Cancer Therapy-Colorectal (FACT-C), and Hospital Anxiety and Depression Scale (HADS), respectively. A multiple linear regression model was used to identify independent predictors of functional capacity. The six-minute walk distance (6MWD) was intermediately and negatively correlated with ECOG-PS score (p = 0.001, r = -0.415), BFI-impact of fatigue on daily functioning score (p = 0.013, r = -0.379), and age (p = 0.040, r = -0.319). An intermediate and positive correlation was found between 6MWD and FACT-C score (p = 0.016, r = 0.369). The multiple regression analysis revealed that only ECOG-PS score was significant and independent predictor of the 6MWD, accounted for 34.8 % of the variance. Performance status was found to be the only significant predictor of functional capacity in this study. Assessing performance status may have an essential role in order to predict functional capacity in CRC patients. Future studies that include a larger sample size would more clearly elucidate the predictors and relationships of functional capacity.

  12. Carbon monoxide production from five volatile anesthetics in dry sodalime in a patient model: halothane and sevoflurane do produce carbon monoxide; temperature is a poor predictor of carbon monoxide production

    Directory of Open Access Journals (Sweden)

    Perez Roberto SGM

    2005-06-01

    Full Text Available Abstract Background Desflurane and enflurane have been reported to produce substantial amounts of carbon monoxide (CO in desiccated sodalime. Isoflurane is said to produce less CO and sevoflurane and halothane should produce no CO at all. The purpose of this study is to measure the maximum amounts of CO production for all modern volatile anesthetics, with completely dry sodalime. We also tried to establish a relationship between CO production and temperature increase inside the sodalime. Methods A patient model was simulated using a circle anesthesia system connected to an artificial lung. Completely desiccated sodalime (950 grams was used in this system. A low flow anesthesia (500 ml/min was maintained using nitrous oxide with desflurane, enflurane, isoflurane, halothane or sevoflurane. For immediate quantification of CO production a portable gas chromatograph was used. Temperature was measured within the sodalime container. Results Peak concentrations of CO were very high with desflurane and enflurane (14262 and 10654 ppm respectively. It was lower with isoflurane (2512 ppm. We also measured small concentrations of CO for sevoflurane and halothane. No significant temperature increases were detected with high CO productions. Conclusion All modern volatile anesthetics produce CO in desiccated sodalime. Sodalime temperature increase is a poor predictor of CO production.

  13. Big Five Personality Traits as the Predictor of Teachers' Organizational Psychological Capital

    Science.gov (United States)

    Bozgeyikli, Hasan

    2017-01-01

    The method of the research was defined as the descriptive survey model since it was aimed to test whether the personality traits of teachers are a significant predictor of their psychological capital levels in this study. 416 teachers (60.3% female, 39.7% male) who were teaching in the schools of Ministry of National Education in Istanbul and were…

  14. Recidivism among Juvenile Offenders following Release from Residential Placements: Multivariate Predictors and Gender Differences

    Science.gov (United States)

    Minor, Kevin I.; Wells, James B.; Angel, Earl

    2008-01-01

    Using a sample of 580 juvenile offenders released from out-of-home placements, this study regressed 18-month recidivism on 33 possible predictors. Over 52 percent of juveniles had new adjudications. Only gender, age, victimization history, and presence of special education needs significantly predicted recidivism. When separate models were…

  15. School Climate as a Predictor of Incivility and Bullying among Public School Employees: A Multilevel Analysis

    Science.gov (United States)

    Powell, Joshua E.; Powell, Anna L.; Petrosko, Joseph M.

    2015-01-01

    We surveyed public school educators on the workplace incivility and workplace bullying they experienced and obtained their ratings of the organizational climate of the school. We used multilevel modeling to determine the effects of individual-level and school-level predictors. Ratings of school climate were significantly related to incivility and…

  16. Family and Cultural Predictors of Depression among Samoan American Middle and High School Students

    Science.gov (United States)

    Yeh, Christine J.; Borrero, Noah E.; Tito, Patsy

    2013-01-01

    This study investigated family intergenerational conflict and collective self-esteem as predictors of depression in a sample of 128 Samoan middle and high school students. Simultaneous regression analyses revealed that each independent variable significantly contributed to an overall model that accounted for 13% of the variance in depression.…

  17. Self-efficacy beliefs as predictors of loneliness and psychological distress in older adults

    NARCIS (Netherlands)

    Fry, P.S; Debats, D.L.H.M.

    2002-01-01

    Sociodemographic variables, social support, and physical health have been used previously in a few predictor models of loneliness and psychological distress in late life. The present study, however, was designed to test the hypothesis that self-efficacy beliefs of elderly persons are significantly

  18. End-to-end models for marine ecosystems: Are we on the precipice of a significant advance or just putting lipstick on a pig?

    Directory of Open Access Journals (Sweden)

    Kenneth A. Rose

    2012-02-01

    Full Text Available There has been a rapid rise in the development of end-to-end models for marine ecosystems over the past decade. Some reasons for this rise include need for predicting effects of climate change on biota and dissatisfaction with existing models. While the benefits of a well-implemented end-to-end model are straightforward, there are many challenges. In the short term, my view is that the major role of end-to-end models is to push the modelling community forward, and to identify critical data so that these data can be collected now and thus be available for the next generation of end-to-end models. I think we should emulate physicists and build theoretically-oriented models first, and then collect the data. In the long-term, end-to-end models will increase their skill, data collection will catch up, and end-to-end models will move towards site-specific applications with forecasting and management capabilities. One pathway into the future is individual efforts, over-promise, and repackaging of poorly performing component submodels (“lipstick on a pig”. The other pathway is a community-based collaborative effort, with appropriate caution and thoughtfulness, so that the needed improvements are achieved (“significant advance”. The promise of end-to-end modelling is great. We should act now to avoid missing a great opportunity.

  19. Morphometric Predictors of Morbidity after Pancreatectomy.

    Science.gov (United States)

    Jaap, Kathryn; Hunsinger, Marie; Dove, James; McGinty, Katrina; Stefanowicz, Edward; Fera, Jillian; Wild, Jeffrey; Shabahang, Mohsen; Blansfield, Joseph

    2016-12-01

    Pancreatic surgery has historically been associated with high morbidity and mortality. One model that could predict outcomes is the assessment of preoperative morphometrics. The objective of this study was to compare different clinical and morphometric features of patients undergoing pancreatectomy to predict morbidity. This is a retrospective chart review of patients undergoing pancreatectomy from December 2004 to October 2013. Morphometric parameters on preoperative CT scans were measured and patients were grouped to examine their association with postoperative morbidity. A total of 180 patients were included in this study (90 males and 90 females). At the time of diagnosis, patients had an average age of 66.7 years (range = 24-90), and median body mass index of 27.4 kg/m2 (range = 16-58 kg/m2). Sixty-one patients (33.9%) experienced surgical complications. Of the individual morphometric variables examined, sarcopenia was the best predictor of length of stay and surgical complications. On multivariate analysis, there was a strong statistically significant correlation of sarcopenia with surgical complications (odds ratio = 3.524, P = 0.0049). No other morphometric variables predicted morbidity. Sarcopenia is a useful predictor for postoperative morbidity after pancreatectomy. The results of this study suggest that noninvasive preoperative testing can be used to quantify postoperative complications after pancreatic surgery.

  20. Longitudinal Predictors of Institutionalization in Old Age.

    Science.gov (United States)

    Hajek, André; Brettschneider, Christian; Lange, Carolin; Posselt, Tina; Wiese, Birgitt; Steinmann, Susanne; Weyerer, Siegfried; Werle, Jochen; Pentzek, Michael; Fuchs, Angela; Stein, Janine; Luck, Tobias; Bickel, Horst; Mösch, Edelgard; Wagner, Michael; Jessen, Frank; Maier, Wolfgang; Scherer, Martin; Riedel-Heller, Steffi G; König, Hans-Helmut

    2015-01-01

    To investigate time-dependent predictors of institutionalization in old age using a longitudinal approach. In a representative survey of the German general population aged 75 years and older predictors of institutionalization were observed every 1.5 years over six waves. Conditional fixed-effects logistic regressions (with 201 individuals and 960 observations) were performed to estimate the effects of marital status, depression, dementia, and physical impairments (mobility, hearing and visual impairments) on the risk of admission to old-age home or nursing home. By exploiting the longitudinal data structure using panel econometric models, we were able to control for unobserved heterogeneity such as genetic predisposition and personality traits. The probability of institutionalization increased significantly with occurrence of widowhood, depression, dementia, as well as walking and hearing impairments. In particular, the occurrence of widowhood (OR = 78.3), dementia (OR = 154.1) and substantial mobility impairment (OR = 36.7) were strongly associated with institutionalization. Findings underline the strong influence of loss of spouse as well as dementia on institutionalization. This is relevant as the number of old people (a) living alone and (b) suffering from dementia is expected to increase rapidly in the next decades. Consequently, it is supposed that the demand for institutionalization among the elderly will increase considerably. Practitioners as well as policy makers should be aware of these upcoming challenges.

  1. Longitudinal Predictors of Institutionalization in Old Age.

    Directory of Open Access Journals (Sweden)

    André Hajek

    Full Text Available To investigate time-dependent predictors of institutionalization in old age using a longitudinal approach.In a representative survey of the German general population aged 75 years and older predictors of institutionalization were observed every 1.5 years over six waves. Conditional fixed-effects logistic regressions (with 201 individuals and 960 observations were performed to estimate the effects of marital status, depression, dementia, and physical impairments (mobility, hearing and visual impairments on the risk of admission to old-age home or nursing home. By exploiting the longitudinal data structure using panel econometric models, we were able to control for unobserved heterogeneity such as genetic predisposition and personality traits.The probability of institutionalization increased significantly with occurrence of widowhood, depression, dementia, as well as walking and hearing impairments. In particular, the occurrence of widowhood (OR = 78.3, dementia (OR = 154.1 and substantial mobility impairment (OR = 36.7 were strongly associated with institutionalization.Findings underline the strong influence of loss of spouse as well as dementia on institutionalization. This is relevant as the number of old people (a living alone and (b suffering from dementia is expected to increase rapidly in the next decades. Consequently, it is supposed that the demand for institutionalization among the elderly will increase considerably. Practitioners as well as policy makers should be aware of these upcoming challenges.

  2. Biological Age Predictors

    OpenAIRE

    Jylh?v?, Juulia; Pedersen, Nancy L.; H?gg, Sara

    2017-01-01

    The search for reliable indicators of biological age, rather than chronological age, has been ongoing for over three decades, and until recently, largely without success. Advances in the fields of molecular biology have increased the variety of potential candidate biomarkers that may be considered as biological age predictors. In this review, we summarize current state-of-the-art findings considering six potential types of biological age predictors: epigenetic clocks, telomere length, transcr...

  3. Survey and Method for Determination of Trajectory Predictor Requirements

    Science.gov (United States)

    Rentas, Tamika L.; Green, Steven M.; Cate, Karen Tung

    2009-01-01

    A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result

  4. Parenting Style and Behavior as Longitudinal Predictors of Adolescent Alcohol Use.

    Science.gov (United States)

    Minaie, Matin Ghayour; Hui, Ka Kit; Leung, Rachel K; Toumbourou, John W; King, Ross M

    2015-09-01

    Adolescent alcohol use is a serious problem in Australia and other nations. Longitudinal data on family predictors are valuable to guide parental education efforts. The present study tested Baumrind's proposal that parenting styles are direct predictors of adolescent alcohol use. Latent class modeling was used to investigate adolescent perceptions of parenting styles and multivariate regression to examine their predictive effect on the development of adolescent alcohol use. The data set comprised 2,081 secondary school students (55.9% female) from metropolitan Melbourne, Australia, who completed three waves of annual longitudinal data starting in 2004. Baumrind's parenting styles were significant predictors in unadjusted analyses, but these effects were not maintained in multivariate models that also included parenting behavior dimensions. Family influences on the development of adolescent alcohol use appear to operate more directly through specific family management behaviors rather than through more global parenting styles.

  5. A Longitudinal Study of PTSD in the Elderly Bereaved: Prevalence and Predictors

    DEFF Research Database (Denmark)

    O'Connor, Maja

    2010-01-01

    -report questionnaires measuring traumatic stress (HTQ), coping style (CSQ), crisis support (CSS), and personality (e.g. NEO-FFI). Elderly bereaved people (N=296, Mean=73 years) participated at two, 6, 13, and 18 months post bereavement. The control group consisted of married elderly people who had experienced at least...... one significant loss (N=276, Mean=70 years). The PTSD-frequency within the sample was high (16%) compared to the control group (4%) and remained stable across time. Individually analyzed each domain was a predictor of PTSD 18 months post loss. Most predictors remained stable across time....... A hierarchical regression analysis of the four domains predicted 49% of the variance, indicating a considerable overlap between the domains. Only one predictor, early posttraumatic distress, remained significant in the hierarchical model. The results confirm that loss of a spouse in old age is traumatic for some...

  6. Why Do Students Use Mobile Technology for Social Purposes during Class? Modeling Teacher Credibility, Learner Empowerment, and Online Communication Attitude as Predictors

    Science.gov (United States)

    Ledbetter, Andrew M.; Finn, Amber N.

    2016-01-01

    Following research indicating prevalent and deleterious use of social communication technology in college classrooms, this study investigated teacher credibility, learner empowerment, and online communication attitude as predictors of such use. The sample included 379 participants who completed an online survey about a college course. Results…

  7. A Preliminary Study of Perfectionism and Loneliness as Predictors of Depressive and Anxious Symptoms in Latinas: A Top-Down Test of a Model

    Science.gov (United States)

    Chang, Edward C.; Hirsch, Jameson K.; Sanna, Lawrence J.; Jeglic, Elizabeth L.; Fabian, Cathryn G.

    2011-01-01

    In the present study, we used a top-down approach to examine perfectionism and loneliness as additive sociocognitive predictors of depressive and anxious symptoms in a sample of 121 Latina college students. Consistent with expectations, we found perfectionism and loneliness to be associated with both depressive and anxious symptoms. In addition,…

  8. Predictors of life disability in trichotillomania.

    Science.gov (United States)

    Tung, Esther S; Flessner, Christopher A; Grant, Jon E; Keuthen, Nancy J

    2015-01-01

    Limited research has investigated disability and functional impairment in trichotillomania (TTM) subjects. This study examined the relationships between hair pulling (HP) style and severity and disability while controlling for mood severity. Disability was measured in individual life areas (work, social, and family/home life) instead of as a total disability score as in previous studies. One hundred fifty three adult hair pullers completed several structured interviews and self-report instruments. HP style and severity, as well as depression, anxiety, and stress were correlated with work, social, and family/home life impairment on the Sheehan Disability Scale (SDS). Multiple regression analyses were performed to determine significant predictors of life impairment. Depressive severity was a significant predictor for all SDS life areas. In addition, interference/avoidance associated with HP was a predictor for work and social life disability. Distress from HP was a significant predictor of social and family/home life disability. Focused HP score and anxiety were significant predictors of family/home life disability. As expected, depression in hair pullers predicted disability across life domains. Avoiding work and social situations can seriously impair functioning in those life domains. Severity of distress and worry about HP may be most elevated in social situations with friends and family and thus predict impairment in those areas. Finally, since HP often occurs at home, time spent in focused hair pulling would have a greater negative impact on family and home responsibilities than social and work life. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. A comparison of model-based imputation methods for handling missing predictor values in a linear regression model: A simulation study

    Science.gov (United States)

    Hasan, Haliza; Ahmad, Sanizah; Osman, Balkish Mohd; Sapri, Shamsiah; Othman, Nadirah

    2017-08-01

    In regression analysis, missing covariate data has been a common problem. Many researchers use ad hoc methods to overcome this problem due to the ease of implementation. However, these methods require assumptions about the data that rarely hold in practice. Model-based methods such as Maximum Likelihood (ML) using the expectation maximization (EM) algorithm and Multiple Imputation (MI) are more promising when dealing with difficulties caused by missing data. Then again, inappropriate methods of missing value imputation can lead to serious bias that severely affects the parameter estimates. The main objective of this study is to provide a better understanding regarding missing data concept that can assist the researcher to select the appropriate missing data imputation methods. A simulation study was performed to assess the effects of different missing data techniques on the performance of a regression model. The covariate data were generated using an underlying multivariate normal distribution and the dependent variable was generated as a combination of explanatory variables. Missing values in covariate were simulated using a mechanism called missing at random (MAR). Four levels of missingness (10%, 20%, 30% and 40%) were imposed. ML and MI techniques available within SAS software were investigated. A linear regression analysis was fitted and the model performance measures; MSE, and R-Squared were obtained. Results of the analysis showed that MI is superior in handling missing data with highest R-Squared and lowest MSE when percent of missingness is less than 30%. Both methods are unable to handle larger than 30% level of missingness.

  10. Significance of the expression of matrix metalloproteinase-9 (MMP-9) in brain tissue of rat models of experimental intracerebral haemorrhage (ICH)

    International Nuclear Information System (INIS)

    Wu Jiami; Liu Shengda

    2005-01-01

    Objective: To study the relationship between the brain tissue expression of MMP-9 and brain water content in rat models of experimental ICH. Methods: Rat models of ICH were prepared with intracerebral (caudate nuclei) injection of autologous noncoagulated blood (50 μl). Animals were sacrificed at 6h, 12h, 24h, 48h, 72h, 120h, lw, 2w and the MMP-9 expressions at the periphery of intracerebral hematoma were examined with immunohisto chemistry. The brain water content was also determined at the same time. Control models were prepared with intracerebral sham injection of normal saline. Results: (1) In the ICH models, the number of MMP-9 positive capillaries at the periphery of hematoma began to rise at 6h (vs that of sham group, P < 0.01 ) with peak at 48h, then gradually dropped. At lwk, the number was still significantly higher than that in the sham group (P <0.01 ). However, there were no expression at 2wk. (2) The brain water content in the ICH group was significantly increased at 12h (vs sham group, P < 0.05) with peak at 72h. At lwk, the brain water content was still significantly higher in the ICH group (P <0.01 ) but at 2wk, the brain water content was about the same in both groups. (3) Animals injected with different amounts of blood (30 μl, 50 μl, 100 μl) showed increased expression of MMP-9 along with the increase of dose (P<0.01). (4) The MMP-9 expression was positively correlated with the brain water content (r=0.8291, P<0.05). Conclusion: In the rat models, MMP-9 expression was activated after ICH. The increase paralleled that of the amount of haemorrhage and brain water content. It was postulated that MMP-9 enhanced development of brain edema through degrading of the blood brain barrier component substances. (authors)

  11. The significance of the interception in a Thornthwaite-type monthly step water balance model in context of the climate change

    Science.gov (United States)

    Herceg, András; Kalicz, Péter; Kisfaludi, Balázs

    2017-04-01

    The hydrological impacts of the climate change can be dramatic. Our main purpose is the methodical improvement of a previously established Thornthwaite-type monthly step water balance model, which takes the interception item into account, and compare the results of the evapotranspiration and the soil moisture projections for the 21st century of the original and the upgraded models. Both of the models will be calibrated and validated (using remote-sensed actual evapotranspiration data, called CREMAP) and requires only temperature and precipitation time series as inputs. The projections based on 4 bias-corrected regional climate models databases (FORESEE), and the 3 investigation periods are: 2015-2045, 2045-2075, and 2070-2100. The key parameter is the water storage capacity of the soil, which can be also calibrated using the actual evapotranspiration data. The maximal rooting depth is determinable if the physical properties of the soil are available. The interception can be ranges from 5-40% of gross precipitation, which rate are differing in the various plant communities. Generally, the forests canopy intercepts considerable amounts of rainfall and evaporates back into the atmosphere during and after precipitation event. Leaf area index (LAI) is one of the most significant factor, which determine the canopies storage capacity. Here, MODIS sensor based LAI time series are applied to estimate the storage capacity. A forest covered experimental catchment is utilized for testing the models near to Sopron, Hungary. The projections will expected to demonstrate increasing actual evapotranspiration values, but decreasing trends for the 10 percentile minimum soil moisture values at the end of the 21st century in both model runs. The seasonal periodicity of evapotranspiration may demonstrates the maximums in June or July, while in case of the soil moisture it may shows minimum values in autumn. With the comparison of the two model runs, we expect lower soil water storage

  12. Predictors of Hospitalization Among Newly Admitted Skilled Nursing Facility Residents: Rethinking the Role of Functional Decline

    Directory of Open Access Journals (Sweden)

    Sun J. Kim

    2014-05-01

    Full Text Available Purpose: Hospital transfer from a skilled nursing facility (SNF is costly, and many are potentially preventable. This study examines: 1 whether functional decline is a predictor of hospital transfer, and 2 the magnitude of relationships between predictors (functional impairment and chronic medical illness and hospital transfer from SNFs. Methods: We used Minimum Data Set (MDS Version 2.0 in the state of Michigan between 2007 and 2009. In total, 196,662 new SNF admissions were observed. Multilevel generalized estimating equations and regression models were performed for each functional and clinical domain while adjusting for demographic variables and change in activities of daily living (ADL. Results: 65% of recently admitted SNF residents experienced functional decline after SNF admission, and 58% were readmitted to a hospital. Residents who needed extensive assistance or were completely dependent in their functional domains had pressure ulcers, deteriorated mood or lower cognitive performance scale scores. These residents experienced higher chances of hospital transfer. However, a deteriorated ADL played a significant role in all multivariate models, indicating that a decline in ADL is a stronger predictor of hospital transfer than other functional or clinical predictors. Conclusion: Although all functional impairments and chronic medical illness can be associated with hospital transfer, functional decline may be the most important predictor of hospital transfer in patients newly admitted to an SNF.

  13. Ethnic differences in predictors of hearing protection behavior between Black and White workers.

    Science.gov (United States)

    Hong, OiSaeng; Lusk, Sally L; Ronis, David L

    2005-01-01

    The purpose of the study is to determine whether there are ethnic differences in predictors of hearing protection behavior between Black and White workers. The Predictors of Use of Hearing Protection Model (PUHPM) derived from Pender's Health Promotion Model (Pender, 1987) was used as a conceptual model. A total of 2,119 (297 Blacks, 1,822 Whites) were included in the analysis. Internal consistency of instrument items was assessed using theta reliability estimates. Significant predictors of the use of hearing protective devices (HPDs) for Black and White workers and differences in predictors between the two groups were examined using multiple regression with interaction terms. Ethnic differences in scale or individual item scores were assessed using chi-square and t-test analyses. Different factors influenced hearing protection behavior among Black and White workers. The model was much less predictive of Blacks' hearing protection behavior than Whites' (R2 = .12 vs. .36). Since the PUHPM was not as effective in predicting hearing protection behavior for Blacks as for Whites, future studies are needed to expand the PUHPM through qualitative study and to develop culturally appropriate models to identify factors that better predict hearing protection behavior as a basis for developing effective interventions.

  14. Predictors for glucose change in hypertensive participants following short-term treatment with atenolol or hydrochlorothiazide.

    Science.gov (United States)

    Moore, Mariellen J; Gong, Yan; Hou, Wei; Hall, Karen; Schmidt, Siegfried O F; Curry, Robert Whitney; Beitelshees, Amber L; Chapman, Arlene; Turner, Stephen T; Schwartz, Gary L; Bailey, Kent; Boerwinkle, Eric; Gums, John G; Cooper-DeHoff, Rhonda M; Johnson, Julie A

    2014-11-01

    To develop and validate a predictive model for glucose change and risk for new-onset impaired fasting glucose in hypertensive participants following treatment with atenolol or hydrochlorothiazide (HCTZ). Randomized multicenter clinical trial. A total of 735 white or African-American men and women with uncomplicated hypertension. Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) is a randomized clinical trial to assess the genetic and nongenetic predictors of blood pressure response and adverse metabolic effects following treatment with atenolol or HCTZ. To develop and validate predictive models for glucose change, PEAR participants were randomly divided into a derivation cohort of 367 and a validation cohort of 368. Linear and logistic regression modeling were used to build models of drug-associated glucose change and impaired fasting glucose (IFG), respectively, in the derivation cohorts. These models were then evaluated in the validation cohorts. For glucose change after atenolol or HCTZ treatment, baseline glucose was a significant (p<0.0001) predictor, explaining 13% of the variability in glucose change after atenolol and 12% of the variability in glucose change after HCTZ. Baseline glucose was also the strongest and most consistent predictor (p<0.0001) for development of IFG after atenolol or HCTZ monotherapy. The area under the receiver operating curve was 0.77 for IFG after atenolol and 0.71 after HCTZ treatment, respectively. Baseline glucose is the primary predictor of atenolol or HCTZ-associated glucose increase and development of IFG after treatment with either drug. © 2014 Pharmacotherapy Publications, Inc.

  15. Predictors of Poor Pregnancy Outcomes Among Antenatal Care Attendees in Primary Health Care Facilities in Cross River State, Nigeria: A Multilevel Model

    OpenAIRE

    Ameh, Soter; Adeleye, Omokhoa A.; Kabiru, Caroline W.; Agan, Thomas; Duke, Roseline; Mkpanam, Nkese; Nwoha, Doris

    2016-01-01

    Objectives Pregnancy carries a high risk for millions of women and varies by urban?rural location in Nigeria, a country with the second highest maternal deaths in the world. Addressing multilevel predictors of poor pregnancy outcomes among antenatal care (ANC) attendees in primary health care (PHC) facilities could reduce the high maternal mortality rate in Nigeria. This study utilised the ?Risk Approach? strategy to (1) compare the risks of poor pregnancy outcomes among ANC attendees by urba...

  16. Estimation of torque on mechanical heart valves due to magnetic resonance imaging including an estimation of the significance of the Lenz effect using a computational model

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, Neil M. [44 Ardgowan Street, Greenock PA16 8EL (United Kingdom). E-mail: neil.robertson at physics.org; Diaz-Gomez, Manuel [Plaza Alcalde Horacio Hermoso, 2, 3-A 41013 Seville (Spain). E-mail: manolo-diaz at latinmail.com; Condon, Barrie [Department of Clinical Physics, Institute of Neurological Sciences, Glasgow G51 4TF (United Kingdom). E-mail: barrie.condon at udcf.gla.ac.uk

    2000-12-01

    Mitral and aortic valve replacement is a procedure which is common in cardiac surgery. Some of these replacement valves are mechanical and contain moving metal parts. Should the patient in whom such a valve has been implanted be involved in magnetic resonance imaging, there is a possible dangerous interaction between the moving metal parts and the static magnetic field due to the Lenz effect. Mathematical models of two relatively common forms of single-leaflet valves have been derived and the magnitude of the torque which opposes the motion of the valve leaflet has been calculated for a valve disc of solid metal. In addition, a differential model of a ring-strengthener valve type has been considered to determine the likely significance of the Lenz effect in the context of the human heart. For common magnetic field strengths at present, i.e. 1 to 2 T, the effect is not particularly significant. However, there is a marked increase in back pressure as static magnetic field strength increases. There are concerns that, since field strengths in the range 3 to 4 T are increasingly being used, the Lenz effect could become significant. At 5 to 10 T the malfunction of the mechanical heart valve could cause the heart to behave as though it is diseased. For unhealthy or old patients this could possibly prove fatal. (author)

  17. Predictors of monoterpene exposure in the Danish furniture industry.

    Science.gov (United States)

    Hagström, Katja; Jacobsen, Gitte; Sigsgaard, Torben; Schaumburg, Inger; Erlandsen, Mogens; Schlunssen, Vivi

    2012-04-01

    Individuals who work with pine in the furniture industry may be exposed to monoterpenes, the most abundant of which are α-pinene, β-pinene, and Δ(3)-carene. Monoterpenes are suspected to cause dermatitis and to harm the respiratory system. An understanding of the predictors of monoterpene exposure is therefore important in preventing these adverse effects. These predictors may include general characteristics of the work environment and specific work operations. We sought to assess the extent to which workers are exposed to monoterpenes and to identify possible predictors of monoterpene exposure in the pine furniture industry in Denmark. Passive measurements of the levels of selected monoterpenes (α-pinene, β-pinene, and Δ(3)-carene) were performed on 161 subjects from 17 pine furniture factories in Viborg County, Denmark; one sample was acquired from each worker. Additionally, wood dust samples were collected from 145 workers. Data on potential predictors of exposure were acquired over the course of the day on which the exposure measurements were recorded and could be assigned to one of four hierarchic ordered levels: worker, machine, department, and factory. In addition to univariate analyses, a mixed model was used to account for imbalances within the data and random variation with each of the hierarchically ordered levels. The geometric mean (GM) monoterpene content observed over the 161 measurements was 7.8 mg m(-3) [geometric standard deviation (GSD): 2.4]; the GM wood dust level over 145 measurements was 0.58 mg m(-3) (GSD: 1.49). None of the measured samples exceeded the occupational exposure limit for terpenes in Denmark (25 ppm, 150 mg m(-3)). In the univariate analyses, half of the predictors tested were found to be significant; the multivariate model indicated that only three of the potential predictors were significant. These were the recirculation of air in rooms used for the processing of wood (a factory level predictor), the presence of a

  18. Predictors of physical inactivity among elderly malaysians: recommendations for policy planning.

    Science.gov (United States)

    Kaur, Jasvindar; Kaur, Gurpreet; Ho, Bee Kiau; Yao, Weng Keong; Salleh, Mohmad; Lim, Kuang Hock

    2015-04-01

    Physical inactivity is the fourth leading risk factor for global mortality. Regular moderate-intensity physical activity has significant benefits for health. To determine the socioeconomic predictors of physical inactivity among elderly Malaysian population. A nationwide community-based survey was conducted among 4831 respondents aged ≥60 years with a face-to-face questionnaire. The prevalence of physical inactivity among the elderly was 88.0%, highest in respondents aged older than 80 years (95.4%), females (90.1%), other Bumiputra (92.2%), earning household income less than RM1000 (87.9%), and residing in urban locality (88.4%). In the multivariate model, the predictors of physical inactivity were only sex, ethnicity, locality, and age group (adjusted odds ratio = 1.3-3.6). The predictors of physical inactivity can identify the risk factors to develop policies that will reduce the public health burden of noncommunicable diseases. © 2014 APJPH.

  19. Predictors for early introduction of solid food among Danish mothers and infants

    DEFF Research Database (Denmark)

    Kronborg, Hanne; Foverskov, Else; Væth, Michael

    2014-01-01

    BACKGROUND: Early introduction of complementary feeding may interfere with breastfeeding and the infant's self-controlled appetite resulting in increased growth. The aim of the present study was to investigate predictors for early introduction of solid food. METHODS: In an observational study...... infants. Data were analysed using ordered logistic regression models. Outcome variable was time for introduction to solid food. RESULTS: Almost all of the included infants 4386 (97%) initiated breastfeeding. At weeks 16, 17-25, 25+, 330 infants (7%); 2923 (65%); and 1250 (28%), respectively had been...... introduced to solid food. Full breastfeeding at five weeks was the most influential predictor for later introduction of solid food (OR = 2.52 CI: 1.93-3.28). Among infant factors male gender, increased gestational age at birth, and higher birth weight were found to be statistically significant predictors...

  20. Incorporating biologic measurements (SF2, CFE) into a tumor control probability model increases their prognostic significance: a study in cervical carcinoma treated with radiation therapy

    International Nuclear Information System (INIS)

    Buffa, Francesca Meteora; Davidson, Susan E.; Hunter, Robert D.; Nahum, Alan E.; West, Catharine M.L.

    2001-01-01

    Purpose: To assess whether incorporation of measurements of surviving fraction at 2 Gy (SF 2 ) and colony-forming efficiency (CFE) into a tumor control probability (tcp) model increases their prognostic significance. Methods and Materials: Measurements of SF 2 and CFE were available from a study on carcinoma of the cervix treated with radiation alone. These measurements, as well as tumor volume, dose, and treatment time, were incorporated into a Poisson tcp model (tcp α,ρ ). Regression analysis was performed to assess the prognostic power of tcp α,ρ vs. the use of either tcp models with biologic parameters fixed to best-fit estimates (but incorporating individual dose, volume, and treatment time) or the use of SF 2 and CFE measurements alone. Results: In a univariate regression analysis of 44 patients, tcp α,ρ was a better prognostic factor for both local control and survival (p 2 alone (p=0.009 for local control, p=0.29 for survival) or CFE alone (p=0.015 for local control, p=0.38 for survival). In multivariate analysis, tcp α,ρ emerged as the most important prognostic factor for local control (p α,ρ , CFE was still a significant independent prognostic factor for local control, whereas SF 2 was not. The sensitivities of tcp α,ρ and SF 2 as predictive tests for local control were 87% and 65%, respectively. Specificities were 70% and 77%, respectively. Conclusions: A Poisson tcp model incorporating individual SF 2 , CFE, dose, tumor volume, and treatment time was found to be the best independent prognostic factor for local control and survival in cervical carcinoma patients

  1. Gemtuzumab Ozogamicin (GO Inclusion to Induction Chemotherapy Eliminates Leukemic Initiating Cells and Significantly Improves Survival in Mouse Models of Acute Myeloid Leukemia

    Directory of Open Access Journals (Sweden)

    Cathy C Zhang

    2018-01-01

    Full Text Available Gemtuzumab ozogamicin (GO is an anti-CD33 antibody-drug conjugate for the treatment of acute myeloid leukemia (AML. Although GO shows a narrow therapeutic window in early clinical studies, recent reports detailing a modified dosing regimen of GO can be safely combined with induction chemotherapy, and the combination provides significant survival benefits in AML patients. Here we tested whether the survival benefits seen with the combination arise from the enhanced reduction of chemoresidual disease and leukemic initiating cells (LICs. Herein, we use cell line and patient-derived xenograft (PDX AML models to evaluate the combination of GO with daunorubicin and cytarabine (DA induction chemotherapy on AML blast growth and animal survival. DA chemotherapy and GO as separate treatments reduced AML burden but left significant chemoresidual disease in multiple AML models. The combination of GO and DA chemotherapy eliminated nearly all AML burden and extended overall survival. In two small subsets of AML models, chemoresidual disease following DA chemotherapy displayed hallmark markers of leukemic LICs (CLL1 and CD34. In vivo, the two chemoresistant subpopulations (CLL1+/CD117− and CD34+/CD38+ showed higher ability to self-renewal than their counterpart subpopulations, respectively. CD33 was coexpressed in these functional LIC subpopulations. We demonstrate that the GO and DA induction chemotherapy combination more effectively eliminates LICs in AML PDX models than either single agent alone. These data suggest that the survival benefit seen by the combination of GO and induction chemotherapy, nonclinically and clinically, may be attributed to the enhanced reduction of LICs.

  2. The Significance of Shifts in Precipitation Patterns: Modelling the Impacts of Climate Change and Glacier Retreat on Extreme Flood Events in Denali National Park, Alaska

    Science.gov (United States)

    Crossman, Jill; Futter, Martyn N.; Whitehead, Paul G.

    2013-01-01

    In glacier-fed systems climate change may have various effects over a range of time scales, including increasing river discharge, flood frequency and magnitude. This study uses a combination of empirical monitoring and modelling to project the impacts of climate change on the glacial-fed Middle Fork Toklat River, Denali National Park, Alaska. We use a regional calibration of the model HBV to account for a paucity of long term observed flow data, validating a local application using glacial mass balance data and summer flow records. Two Global Climate Models (HADCM3 and CGCM2) and two IPCC scenarios (A2 and B2) are used to ascertain potential changes in meteorological conditions, river discharge, flood frequency and flood magnitude. Using remote sensing methods this study refines existing estimates of glacial recession rates, finding that since 2000, rates have increased from 24m per year to 68.5m per year, with associated increases in ablation zone ice loss. GCM projections indicate that over the 21st century these rates will increase still further, most extensively under the CGCM2 model, and A2 scenarios. Due to greater winter precipitation and ice and snow accumulation, glaciers release increasing meltwater quantities throughout the 21st century. Despite increases in glacial melt, results indicate that it is predominantly precipitation that affects river discharge. Three of the four IPCC scenarios project increases in flood frequency and magnitude, events which were primarily associated with changing precipitation patterns, rather than extreme temperature increases or meltwater release. Results suggest that although increasing temperatures will significantly increase glacial melt and winter baseflow, meltwater alone does not pose a significant flood hazard to the Toklat River catchment. Projected changes in precipitation are the primary concern, both through changing snow volumes available for melt, and more directly through increasing catchment runoff. PMID

  3. The significance of shifts in precipitation patterns: modelling the impacts of climate change and glacier retreat on extreme flood events in Denali National Park, Alaska.

    Science.gov (United States)

    Crossman, Jill; Futter, Martyn N; Whitehead, Paul G

    2013-01-01

    In glacier-fed systems climate change may have various effects over a range of time scales, including increasing river discharge, flood frequency and magnitude. This study uses a combination of empirical monitoring and modelling to project the impacts of climate change on the glacial-fed Middle Fork Toklat River, Denali National Park, Alaska. We use a regional calibration of the model HBV to account for a paucity of long term observed flow data, validating a local application using glacial mass balance data and summer flow records. Two Global Climate Models (HADCM3 and CGCM2) and two IPCC scenarios (A2 and B2) are used to ascertain potential changes in meteorological conditions, river discharge, flood frequency and flood magnitude. Using remote sensing methods this study refines existing estimates of glacial recession rates, finding that since 2000, rates have increased from 24 m per year to 68.5m per year, with associated increases in ablation zone ice loss. GCM projections indicate that over the 21(st) century these rates will increase still further, most extensively under the CGCM2 model, and A2 scenarios. Due to greater winter precipitation and ice and snow accumulation, glaciers release increasing meltwater quantities throughout the 21(st) century. Despite increases in glacial melt, results indicate that it is predominantly precipitation that affects river discharge. Three of the four IPCC scenarios project increases in flood frequency and magnitude, events which were primarily associated with changing precipitation patterns, rather than extreme temperature increases or meltwater release. Results suggest that although increasing temperatures will significantly increase glacial melt and winter baseflow, meltwater alone does not pose a significant flood hazard to the Toklat River catchment. Projected changes in precipitation are the primary concern, both through changing snow volumes available for melt, and more directly through increasing catchment runoff.

  4. Murine xenograft model demonstrates significant radio-sensitising effect of liposomal doxorubicin in a combination therapy for Feline Injection Site Sarcoma.

    Science.gov (United States)

    Petznek, H; Kleiter, M; Tichy, A; Fuchs-Baumgartinger, A; Hohenadl, C

    2014-10-01

    Therapy of cats suffering from feline injection site sarcomas (FISS) is still a challenging problem, as the recurrence rate after surgery is up to 70%. Four FISS-derived primary tumour cell lines and corresponding xenograft tumour mouse models were established to evaluate the efficacy of a concomitant chemo-/radiation therapy with doxorubicin. In vitro, strongly depending upon the timing of administration, pre-treatment with 0.25 µmol doxorubicin resulted in a significant enhancement of radiation-induced (3.5 Gy) tumour cell death. This result was confirmed in vivo, where only the combined chemo-/radiation therapy resulted in a significant reduction in tumour growth compared to the respective mono-therapies with either doxorubicin or radiation. These results support the use of the concomitant chemo-/radiation therapy for adjuvant treatment of FISS, particularly in advanced or recurrent disease where surgery alone is no longer feasible. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Predictors of neutrophilic airway inflammation in young smokers with asthma

    DEFF Research Database (Denmark)

    Westergaard, Christian Grabow; Munck, Christian; Helby, Jens

    2014-01-01

    and methacholine challenge. A sample from the sputum induction was taken for bacterial analysis using 16S gene PCR technique and sequencing. Results: Using one-way analysis of variance and binary and linear regression models, only age and ACQ6 score were found to be significant predictors for airway neutrophilia......Introduction: Asthma is one of the most widespread chronic diseases worldwide. In spite of numerous detrimental effects on asthma, smoking is common among asthma patients. These smoking-induced aggravations of asthma may be attributed to changes in airway inflammation, which is characterized...

  6. Predictor combination in binary decision-making situations.

    Science.gov (United States)

    McGrath, Robert E

    2008-09-01

    Professional psychologists are often confronted with the task of making binary decisions about individuals, such as predictions about future behavior or employee selection. Test users familiar with linear models and Bayes's theorem are likely to assume that the accuracy of decisions is consistently improved by combination of outcomes across valid predictors. However, neither statistical method accurately estimates the increment in accuracy that results from use of additional predictors in the typical applied setting. It was demonstrated that the best single predictor often can perform better than do multiple predictors when the predictors are combined using methods common in applied settings. This conclusion is consistent with previous findings concerning G. Gigerenzer and D. Goldstein's (1996) "take the best" heuristic. Furthermore, the information needed to ensure an increment in fit over the best single predictor is rarely available. (c) 2008 APA, all rights reserved.

  7. Surface tensions of multi-component mixed inorganic/organic aqueous systems of atmospheric significance: measurements, model predictions and importance for cloud activation predictions

    Directory of Open Access Journals (Sweden)

    D. O. Topping

    2007-01-01

    Full Text Available In order to predict the physical properties of aerosol particles, it is necessary to adequately capture the behaviour of the ubiquitous complex organic components. One of the key properties which may affect this behaviour is the contribution of the organic components to the surface tension of aqueous particles in the moist atmosphere. Whilst the qualitative effect of organic compounds on solution surface tensions has been widely reported, our quantitative understanding on mixed organic and mixed inorganic/organic systems is limited. Furthermore, it is unclear whether models that exist in the literature can reproduce the surface tension variability for binary and higher order multi-component organic and mixed inorganic/organic systems of atmospheric significance. The current study aims to resolve both issues to some extent. Surface tensions of single and multiple solute aqueous solutions were measured and compared with predictions from a number of model treatments. On comparison with binary organic systems, two predictive models found in the literature provided a range of values resulting from sensitivity to calculations of pure component surface tensions. Results indicate that a fitted model can capture the variability of the measured data very well, producing the lowest average percentage deviation for all compounds studied. The performance of the other models varies with compound and choice of model parameters. The behaviour of ternary mixed inorganic/organic systems was unreliably captured by using a predictive scheme and this was dependent on the composition of the solutes present. For more atmospherically representative higher order systems, entirely predictive schemes performed poorly. It was found that use of the binary data in a relatively simple mixing rule, or modification of an existing thermodynamic model with parameters derived from binary data, was able to accurately capture the surface tension variation with concentration. Thus

  8. [Extradyadic Sex and its Predictors in Homo- and Heterosexuals.

    Science.gov (United States)

    Haversath, Julia; Kröger, Christoph

    2014-12-01

    Infidelity appears to be a common phenomenon. Although there are initially positive consequences for the unfaithful partner, it has negative impacts on individuals, the relationship and health in the long-term. How often are extradyadic sexual contacts indicated within a German sample? Which factors predict infidelity? Via Internet (n=1 899) socio-demographic, individual (attitudes towards infidelity, religiosity), relationship (global and emotional relationship satisfaction, length of primary relationship, sexual agreements), and contextual factors (opportunities) were surveyed. The results of the regression analysis on an 80% subsample (n=1 533) were cross-validated with the remaining 20% of the data (n=366). The analysis showed that 4% of lesbian women, 34% of gay men, 29% of heterosexual women and 49% of heterosexual men reported extra-dyadic sexual contacts. Sexual orientation and restrictive attitudes towards monogamy and infidelity were found to be significant predictors. Low global relationship satisfaction, longer duration of primary relationship, non-monogamous relationships, availability of alternative sexual partners and ways to conceal infidelity increased the likelihood of extradyadic involvement. Cross-validation with 20% of the data (n=366) confirmed the stability of the regression model. Future research should examine identified predictors using representative population-based data. Predictors should be considered in therapy. © Georg Thieme Verlag KG Stuttgart · New York.

  9. Predictors of Energy Compensation during Exercise Interventions: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Marie-Ève Riou

    2015-05-01

    Full Text Available Weight loss from exercise-induced energy deficits is usually less than expected. The objective of this systematic review was to investigate predictors of energy compensation, which is defined as body energy changes (fat mass and fat-free mass over the total amount of exercise energy expenditure. A search was conducted in multiple databases without date limits. Of 4745 studies found, 61 were included in this systematic review with a total of 928 subjects. The overall mean energy compensation was 18% ± 93%. The analyses indicated that 48% of the variance of energy compensation is explained by the interaction between initial fat mass, age and duration of exercise interventions. Sex, frequency, intensity and dose of exercise energy expenditure were not significant predictors of energy compensation. The fitted model suggested that for a shorter study duration, lower energy compensation was observed in younger individuals with higher initial fat mass (FM. In contrast, higher energy compensation was noted for younger individuals with lower initial FM. From 25 weeks onward, energy compensation was no longer different for these predictors. For studies of longer duration (about 80 weeks, the energy compensation approached 84%. Lower energy compensation occurs with short-term exercise, and a much higher level of energy compensation accompanies long-term exercise interventions.

  10. Predictors of organizational commitment among staff in assisted living.

    Science.gov (United States)

    Sikorska-Simmons, Elzbieta

    2005-04-01

    This study examines the role of organizational culture, job satisfaction, and sociodemographic characteristics as predictors of organizational commitment among staff in assisted living. It is particularly important to examine organizational commitment, because of its close links to staff turnover. Data were collected from 317 staff members in 61 facilities, using self-administered questionnaires. The facilities were selected from licensed assisted living programs and were stratified into small, traditional, and new-model homes. Staff questionnaires were distributed by a researcher during 1-day visits to each facility. Organizational commitment was measured by the extent of staff identification, involvement, and loyalty to the organization. Organizational culture, job satisfaction, and education were strong predictors of commitment, together explaining 58% of the total variance in the dependent variable. Higher levels of organizational commitment were associated with more favorable staff perceptions of organizational culture and greater job satisfaction. In addition, more educated staff members tended to report higher levels of organizational commitment. Other than education, sociodemographic characteristics failed to account for a significant amount of variance in organizational commitment. Because job satisfaction and organizational culture were strong predictors of commitment, interventions aimed at increasing job satisfaction and creating an organizational culture that values and respects staff members could be most effective in producing higher levels of organizational commitment.

  11. Predictors of Service Utilization among Youth Diagnosed with Mood Disorders

    Science.gov (United States)

    Mendenhall, Amy N.

    2012-01-01

    In this study, I investigated patterns and predictors of service utilization for children with mood disorders. The Behavioral Model for Health Care Utilization was used as an organizing framework for identifying predictors of the number and quality of services utilized. Hierarchical regression was used in secondary data analyses of the…

  12. The anti-tumor effect of HDAC inhibition in a human pancreas cancer model is significantly improved by the simultaneous inhibition of cyclooxygenase 2.

    Directory of Open Access Journals (Sweden)

    Olivier Peulen

    Full Text Available Pancreatic ductal adenocarcinoma is the fourth leading cause of cancer death worldwide, with no satisfactory treatment to date. In this study, we tested whether the combined inhibition of cyclooxygenase-2 (COX-2 and class I histone deacetylase (HDAC may results in a better control of pancreatic ductal adenocarcinoma. The impact of the concomitant HDAC and COX-2 inhibition on cell growth, apoptosis and cell cycle was assessed first in vitro on human pancreas BxPC-3, PANC-1 or CFPAC-1 cells treated with chemical inhibitors (SAHA, MS-275 and celecoxib or HDAC1/2/3/7 siRNA. To test the potential antitumoral activity of this combination in vivo, we have developed and characterized, a refined chick chorioallantoic membrane tumor model that histologically and proteomically mimics human pancreatic ductal adenocarcinoma. The combination of HDAC1/3 and COX-2 inhibition significantly impaired proliferation of BxPC-3 cells in vitro and stalled entirely the BxPC-3 cells tumor growth onto the chorioallantoic membrane in vivo. The combination was more effective than either drug used alone. Consistently, we showed that both HDAC1 and HDAC3 inhibition induced the expression of COX-2 via the NF-kB pathway. Our data demonstrate, for the first time in a Pancreatic Ductal Adenocarcinoma (PDAC model, a significant action of HDAC and COX-2 inhibitors on cancer cell growth, which sets the basis for the development of potentially effective new combinatory therapies for pancreatic ductal adenocarcinoma patients.

  13. Targeted liquid chromatography quadrupole ion trap mass spectrometry analysis of tachykinin related peptides reveals significant expression differences in a rat model of neuropathic pain.

    Science.gov (United States)

    Pailleux, Floriane; Vachon, Pascal; Lemoine, Jérôme; Beaudry, Francis

    2013-08-01

    Animal models are widely used to perform basic scientific research in pain. The rodent chronic constriction injury (CCI) model is widely used to study neuropathic pain. Animals were tested prior and after CCI surgery using behavioral tests (von Frey filaments and Hargreaves test) to evaluate pain. The brain and the lumbar enlargement of the spinal cord were collected from neuropathic and normal animals. Tachykinin related peptides were analyzed by high performance liquid chromatography quadrupole ion trap mass spectrometry. Our results reveal that the β-tachykinin₅₈₋₇₁, SP and SP₃₋₁₁ up-regulation are closely related to pain behavior. The spinal β-tachykinin₅₈₋₇₁, SP and SP₃₋₁₁ concentrations were significantly up-regulated in neuropathic animals compared with normal animals (ptachykinin₅₈₋₇₁ and SP concentrations were significantly up-regulated (ptachykinin₅₈₋₇₁, SP₁₋₇ and SP₆₋₁₁ (p>0.05). The β-tachykinin₅₈₋₇₁, SP and C-terminal SP metabolites could potentially serve as biomarkers in early drug discovery. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Clinical significance of changes of serum IL-6 and TNF-α levels in rat models of hypoxic-ischemia brain injury

    International Nuclear Information System (INIS)

    Niu Tingxian; Shi Zhiyong; Luo Jianjun

    2009-01-01

    Objective: To explore the clinical significance of changes of serum interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) levels in rat models of hypoxic-ischemia (HI) brain injury. Methods: Seventy five rat HI brain injury nodels were prepared with bilateral occlusion of common carotid artery for 24rs followed 2hrs later by hypoxia (breathing 8% oxygen) for 2hrs. One fifth of the animals were sacrificed at 4h, 8h, 12h, 24h and 48h later respectively, the serum and brain homogenate concentrations of IL-6 and TNF-α were determined with RIA and brain tissues were pathologically examined. Results: The concentrations of IL-6 and TNF-α were dynamically changed within 48h in serum and brain homogenate. Peak values occurred at 24h with serum and at 12h with brain homogenate. Meanwhile, levels of both cytokines were significantly higher in the models than those in controls (P<0.01 or P<0.05). Conclusion: The concentrations of IL-6 and TNF-α were dynamically(sham operation only, 15 animals) changed and might be regarded as the clinical markers of degree of HI brain injury. (authors)

  15. Towards general models of the three-dimensional occurrence of soil water-repellency, its hydrological significance, temporal dynamics and response to climatic change

    Science.gov (United States)

    Walsh, Rory; Urbanek, Emilia; Ferreira, Carla; Ferreira, Antonio; Shakesby, Rick

    2014-05-01

    Although it is well-established that soil water-repellency exists - at least transiently - in some vegetation/land-use types within a wide range of climatic zones, it varies greatly both in its four-dimensional character and the nature and significance of its hydrological effects. Thus within landscapes, soil water-repellency varies not only in severity, but also in percentage cover, spatial pattern and connectivity; in vertical position and vertical extent; in its temporal regime; and in the presence/absence and frequency of bypass routes through any hydrophobic layer. The nature and degree of significance of any hydrological impacts of hydrophobicity are very dependent on these variations. Assessments of the likely impacts of current and future climatic change on hydrophobic (or potentially hydrophobic) environments need to take these variations in the four-dimensional nature of hydrophobicity and their controlling factors and mechanisms into account. This poster paper presents and discusses a series of conceptual models that together attempt to understand the factors and mechanisms controlling soil water-repellency and its hydrological consequences. The paper draws on a combination of: (1) results of field measurements and experiments in burned and unburned scrub, pine and eucalyptus terrain in central Portugal; (2) laboratory experiments of the influence of the presence/absence of basal impedance and cracks, root-holes and stones on the temporal dynamics of three-dimensional patterns of repellency in wetting and drying cycles; and (3) findings from a wider range of environments and locations from the published literature. Three conceptual models are considered. The first addresses the environmental factors that control and influence the occurrence and three-dimensional structure of soil water-repellency within landscapes. Within this model, the emphasis is placed on vegetation, land-use and land management (including their influence - together with climate - on

  16. Attitudes of prejudice as a predictor of cultural competence among baccalaureate nursing students.

    Science.gov (United States)

    Dunagan, Pamela B; Kimble, Laura P; Gunby, Susan Sweat; Andrews, Margaret M

    2014-06-01

    The purpose of this study was to explore the relationship between attitudes of prejudice and cultural competence among nursing students. Using a mixed-methods design, a convenience sample of students (N = 129) currently enrolled in a baccalaureate nursing program was recruited via Web networking. Data regarding attitudes of prejudice, cultural competence, prior cultural experience, and integration of cultural competence were obtained via a Web-based survey. Multiple linear regression was used to predict cultural knowledge, attitudes, and consciousness. Although all three regression models were statistically significant, the significant predictors varied within each model. Greater prejudice was a significant predictor of less culturally competent attitudes toward providing nursing care. Existing prejudice among nursing students needs to be addressed to help promote positive cultural attitudes and, ultimately, cultural competent nursing care.

  17. Increase of the Integration Degree of Wind Power Plants into the Energy System Using Wind Forecasting and Power Consumption Predictor Models by Transmission System Operator

    Directory of Open Access Journals (Sweden)

    Manusov V.Z.

    2017-12-01

    Full Text Available Wind power plants’ (WPPs high penetration into the power system leads to various inconveniences in the work of system operators. This fact is associated with the unpredictable nature of wind speed and generated power, respectively. Due to these factors, such source of electricity must be connected to the power system to avoid detrimental effects on the stability and quality of electricity. The power generated by the WPPs is not regulated by the system operator. Accurate forecasting of wind speed and power, as well as power load can solve this problem, thereby making a significant contribution to improving the power supply systems reliability. The article presents a mathematical model for the wind speed prediction, which is based on autoregression and fuzzy logic derivation of Takagi-Sugeno. The new model of wavelet transform has been developed, which makes it possible to include unnecessary noise from the model, as well as to reveal the cycling of the processes and their trend. It has been proved, that the proposed combination of methods can be used simultaneously to predict the power consumption and the wind power plant potential power at any time interval, depending on the planning horizon. The proposed models support a new scientific concept for the predictive control system of wind power stations and increase their degree integration into the electric power system.

  18. Prediction error variance and expected response to selection, when selection is based on the best predictor – for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

    Directory of Open Access Journals (Sweden)

    Jensen Just

    2002-05-01

    Full Text Available Abstract In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed or random effects. In the different models, expressions are given (when these can be found – otherwise unbiased estimates are given for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non Gaussian traits are generalisations of the well-known formulas for Gaussian traits – and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part of the model (heritability on the normally distributed level of the model or a generalised version of heritability plays a central role in these formulas.

  19. The effectiveness of the anti-CD11d treatment is reduced in rat models of spinal cord injury that produce significant levels of intraspinal hemorrhage.

    Science.gov (United States)

    Geremia, N M; Hryciw, T; Bao, F; Streijger, F; Okon, E; Lee, J H T; Weaver, L C; Dekaban, G A; Kwon, B K; Brown, A

    2017-09-01

    We have previously reported that administration of a CD11d monoclonal antibody (mAb) improves recovery in a clip-compression model of SCI. In this model the CD11d mAb reduces the infiltration of activated leukocytes into the injured spinal cord (as indicated by reduced intraspinal MPO). However not all anti-inflammatory strategies have reported beneficial results, suggesting that success of the CD11d mAb treatment may depend on the type or severity of the injury. We therefore tested the CD11d mAb treatment in a rat hemi-contusion model of cervical SCI. In contrast to its effects in the clip-compression model, the CD11d mAb treatment did not improve forelimb function nor did it significantly reduce MPO levels in the hemi-contused cord. To determine if the disparate results using the CD11d mAb were due to the biomechanical nature of the cord injury (compression SCI versus contusion SCI) or to the spinal level of the injury (12th thoracic level versus cervical) we further evaluated the CD11d mAb treatment after a T12 contusion SCI. In contrast to the T12 clip compression SCI, the CD11d mAb treatment did not improve locomotor recovery or significantly reduce MPO levels after T12 contusion SCI. Lesion analyses revealed increased levels of hemorrhage after contusion SCI compared to clip-compression SCI. SCI that is accompanied by increased intraspinal hemorrhage would be predicted to be refractory to the CD11d mAb therapy as this approach targets leukocyte diapedesis through the intact vasculature. These results suggest that the disparate results of the anti-CD11d treatment in contusion and clip-compression models of SCI are due to the different pathophysiological mechanisms that dominate these two types of spinal cord injuries. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

  20. Longitudinal Predictors of High School Completion

    Science.gov (United States)

    Barry, Melissa; Reschly, Amy L.

    2012-01-01

    This longitudinal study examined predictors of dropout assessed in elementary school. Student demographic data, achievement, attendance, and ratings of behavior from the Behavior Assessment System for Children were used to predict dropout and completion. Two models, which varied on student sex and race, predicted dropout at rates ranging from 75%…

  1. Quantitative renal perfusion measurements in a rat model of acute kidney injury at 3T: testing inter- and intramethodical significance of ASL and DCE-MRI.

    Directory of Open Access Journals (Sweden)

    Fabian Zimmer

    Full Text Available OBJECTIVES: To establish arterial spin labelling (ASL for quantitative renal perfusion measurements in a rat model at 3 Tesla and to test the diagnostic significance of ASL and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI in a model of acute kidney injury (AKI. MATERIAL AND METHODS: ASL and DCE-MRI were consecutively employed on six Lewis rats, five of which had a unilateral ischaemic AKI. All measurements in this study were performed on a 3 Tesla MR scanner using a FAIR True-FISP approach and a TWIST sequence for ASL and DCE-MRI, respectively. Perfusion maps were calculated for both methods and the cortical perfusion of healthy and diseased kidneys was inter- and intramethodically compared using a region-of-interest based analysis. RESULTS/SIGNIFICANCE: Both methods produce significantly different values for the healthy and the diseased kidneys (P<0.01. The mean difference was 147±47 ml/100 g/min and 141±46 ml/100 g/min for ASL and DCE-MRI, respectively. ASL measurements yielded a mean cortical perfusion of 416±124 ml/100 g/min for the healthy and 316±102 ml/100 g/min for the diseased kidneys. The DCE-MRI values were systematically higher and the mean cortical renal blood flow (RBF was found to be 542±85 ml/100 g/min (healthy and 407±119 ml/100 g/min (AKI. CONCLUSION: Both methods are equally able to detect abnormal perfusion in diseased (AKI kidneys. This shows that ASL is a capable alternative to DCE-MRI regarding the detection of abnormal renal blood flow. Regarding absolute perfusion values, nontrivial differences and variations remain when comparing the two methods.

  2. Predictors of clinical outcomes after periodontal treatment of aggressive periodontitis: 12-month randomized trial.

    Science.gov (United States)

    Haas, Alex Nogueira; Silva-Boghossian, Carina Maciel; Colombo, Ana Paula; Albandar, Jasim; Oppermann, Rui Vicente; Rösing, Cassiano Kuchenbecker; Susin, Cristiano

    2016-05-20

    Little is known about the factors that may be used in clinical practice to predict the therapeutic response of aggressive periodontitis patients. The aim of this study was to determine predictors of clinical outcomes after non-surgical treatment of aggressive periodontitis. A total of 24 patients (aged 13-26 years) received oral hygiene instructions, as well as subgingival scaling and root planing. Twelve subjects received systemic azithromycin at random. Clinical variables were assessed at baseline, 3, 6, 9, and 12 months. Baseline microbiological assessment was performed by checkerboard DNA-DNA hybridization. Multivariable models used generalized estimating equations. There were significant improvements in the entire sample in regard to pocket depth, clinical attachment level and bleeding on probing. Significant predictors of a reduction in mean pocket depth were: use of azithromycin, non-molar teeth, generalized disease and baseline pocket depth. Absence of plaque predicted a 0.22 mm higher attachment gain, whereas a baseline pocket depth ≥7 mm predicted a 1.36 mm higher attachment loss. Azithromycin, plaque, and baseline pocket depth were significant predictors of bleeding on probing. The concomitant presence of all three red complex species predicted a 0.78 mm higher attachment loss. It may be concluded that dental plaque, tooth type, disease extent, baseline pocket depth, and use of azithromycin were significant predictors of the clinical response to treatment for aggressive periodontitis in young individuals. Moreover, the presence of multiple periodontal pathogens may predict challenges in achieving a favorable outcome for aggressive periodontitis.

  3. Psychological Predictors of Anabolic Steroid Use: An Exploratory Study.

    Science.gov (United States)

    Schwerin, Michael J.; Corcoran, Kevin J.; LaFleur, Bonnie J.; Fisher, Leslee; Patterson, David; Olrich, Tracy

    1997-01-01

    Examined social physique anxiety, upper body esteem, social anxiety, and body dissatisfaction as possible predictors of anabolic steroid (AS) use. Results based on 185 AS-using bodybuilders and various control groups indicated that the upper body strength subscale of two measures, along with age, were significant predictors of AS use. (RJM)

  4. Predictors of Attitudes toward Seeking Counseling among International Students.

    Science.gov (United States)

    Komiya, Noboru; Eells, Gregory T.

    2001-01-01

    Investigates predictors of international students' (N=121) attitudes toward seeking counseling. Results indicate that being female, having greater openness to emotions, and having had prior counseling experience were significant predictors of more open attitudes toward seeking counseling. (Contains 27 references.) (GCP)

  5. Predictors of early versus late smoking abstinence within a 24-month disease management program.

    Science.gov (United States)

    Cox, Lisa Sanderson; Wick, Jo A; Nazir, Niaman; Cupertino, A Paula; Mussulman, Laura M; Ahluwalia, Jasjit S; Ellerbeck, Edward F

    2011-03-01

    Standard smoking cessation treatment studies have been limited to 6- to 12-month follow-up, and examination of predictors of abstinence has been restricted to this timeframe. The KanQuit study enrolled 750 rural smokers across all stages of readiness to stop smoking and provided pharmacotherapy management and/or disease management, including motivational interviewing (MI) counseling every 6 months over 2 years. This paper examines differences in predictors of abstinence following initial (6-month) and extended (24-month) intervention. Baseline variables were analyzed as potential predictors of self-reported smoking abstinence at Month 6 and at Month 24. Chi-square tests, 2-sample t tests, and multiple logistic regression analyses were used to identify predictors of abstinence among 592 participants who completed assessment at baseline and Months 6 and 24. Controlling for treatment group, the final regression models showed that male gender and lower baseline cigarettes per day predicted abstinence at both 6 and 24 months. While remaining significant, the relative advantage of being male decreased over time. Global motivation to stop smoking, controlled motivation, and self-efficacy predicted abstinence at 6 months but did not predict abstinence at Month 24. In contrast, stage of change was strongly predictive of 24-month smoking status. While the importance of some predictors of successful smoking cessation appeared to diminish over time, initial lack of interest in cessation and number of cigarettes per day strongly predicted continued smoking following a 2-year program.

  6. A longitudinal study of children's outside play using family environment and perceived physical environment as predictors.

    Science.gov (United States)

    Remmers, Teun; Broeren, Suzanne M L; Renders, Carry M; Hirasing, Remy A; van Grieken, Amy; Raat, Hein

    2014-06-16

    A natural and cheap way of increasing children's physical activity is stimulating unstructured outside play. This study examined whether characteristics of the family and perceived physical environment were associated with the duration of children's outside play. Parents participating in the "Be Active, Eat Right" cluster RCT control group (N = 2007) provided information on potential predictors of outside play (i.e. family and perceived physical environment) of their 5-year-old child by questionnaire. Child outside play was assessed by parental reports both at five and seven years. Linear regression analyses, adjusted for seasonality, were performed to evaluate associations between potential predictors and child outside play. Linear mixed models were fitted to evaluate the relationship between potential predictors and the development of outside play over two years, with season entered as a random factor. Family environment was the strongest construct predicting child outside play, while parent perceived physical environment had no significant association with child outside play. Parental habit strength and the presence of rules were the strongest predictors of increased outside play. Parent perceived difficulty in improving child outside play was the strongest predictor of decreased outside play. Family environment predicted child outside play and not perceived physical environment. Parental rules and habit strength regarding improving outside play were associated with an improvement of child's engagement in outside play.

  7. Predictors of turnover intention in nurse faculty.

    Science.gov (United States)

    Gormley, Denise K; Kennerly, Susan

    2011-04-01

    Turnover of nurse faculty is an increasingly important issue in nursing as the available number of qualified faculty continues to decrease. Understanding the factors that contribute to turnover is important to academic administrators to retain and recruit qualified nursing faculty. The purpose of this study was to examine predictors of turnover intention in nurse faculty working in departments and schools of nursing in Carnegie Doctoral/Research Universities-Extensive, public and private, not-for-profit institutions. The multidimensional model of organizational commitment was used to frame this study. The predictor variables explored were organizational climate, organizational commitment, work role balance, role ambiguity, and role conflict. The work roles examined were research, teaching, and service. Logistical regression was performed to examine the predictors of turnover intention. Organizational climate intimacy and disengagement, affective and continuance organizational commitment, and role ambiguity were shown to predict turnover intention in nurse faculty. Copyright 2011, SLACK Incorporated.

  8. Predictors of Homophobia in Female College Students.

    Science.gov (United States)

    Basow, Susan A.; Johnson, Kelly

    2000-01-01

    Investigated how self-esteem, self-discrepancy, and gender-attribute importance related to homophobia in predominantly white college women, noting sex role attitudes, authoritarian attitudes, and extent of contact with homosexuals. The only significant predictor of homophobia was authoritarian attitudes. Other correlations included belief in sex…

  9. Predictors of distress and anxiety during pregnancy

    African Journals Online (AJOL)

    psychobiological changes associated with pregnancy.31. Finally, lower perceived social support was significantly associated with distress and anxiety at trimester 2 and 3. Level of social support has previously been found to be a predictor of anxiety during pregnancy.12 Studies have shown an association of inadequate ...

  10. Personality predictors of happiness.

    Science.gov (United States)

    Neto, F

    2001-06-01

    The Oxford Happiness Inventory and a battery of personality measures were completed by 171 subjects. The results showed predicted positive correlations for happiness with satisfaction with life, self-esteem, and sociability and negative correlations of happiness with embarrassability, loneliness, shyness, and social anxiety. Four predictors (satisfaction with life, shyness, loneliness, and sociability) accounted for 58% of the variance in happiness scores. These results support previous research as well as validate the Portuguese version of the happiness inventory.

  11. Predictors of transformational leadership of nurse managers.

    Science.gov (United States)

    Echevarria, Ilia M; Patterson, Barbara J; Krouse, Anne

    2017-04-01

    The aim of this study was to examine the relationships among education, leadership experience, emotional intelligence and transformational leadership of nurse managers. Nursing leadership research provides limited evidence of predictors of transformational leadership style in nurse managers. A predictive correlational design was used with a sample of nurse managers (n = 148) working in varied health care settings. Data were collected using the Genos Emotional Intelligence Inventory, the Multi-factor Leadership Questionnaire and a demographic questionnaire. Simple linear and multiple regression analyses were used to examine relationships. A statistically significant relationship was found between emotional intelligence and transformational leadership (r = 0.59, P leadership. Nurse managers should be well informed of the predictors of transformational leadership in order to pursue continuing education and development opportunities related to those predictors. The results of this study emphasise the need for emotional intelligence continuing education, leadership development and leader assessment programmes. © 2016 John Wiley & Sons Ltd.

  12. The dimensions and role of commensality: A theoretical model drawn from the significance of communal eating among adults in Santiago, Chile.

    Science.gov (United States)

    Giacoman, Claudia

    2016-12-01

    This article examines the significance of communal eating among adults from Santiago, Chile, by elaborating on a theoretical model for commensality that is based on empirical material. Based on this objective, 24 group interviews were conducted in Santiago with family members, coworkers, and friends who shared meals with one another. The results showed that the practice of commensality strengthens the cohesion among the members of a group, providing an interactive space in which communal belonging is symbolized and shared norms are respected. However, eating together also is assigned an ambiguous value: On the one hand, commensality is viewed as positive in enabling connections with others. On the other hand, participating in commensality can be viewed as negative, causing tensions depending on the characteristics of the commensal group and the context. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. FUNCTIONAL ABILITIES AS PREDICTORS OF PREADOSLESCENT STUDENTS’ ATHLETIC RESULTS OUTCOME

    Directory of Open Access Journals (Sweden)

    Miroljub Ivanović

    2011-09-01

    Full Text Available Aim of this research has been directed to the functional abilities relation testing (as predictors and athletic results (as criterion of students, who are VII and VIII grade of primary school (Χ= 13, 9 years; SD = 1, 17. The research has been conducted in Valjevo during November 2010. on the sample of 108 examinees. Variables’ sample has been assembled from 3 tests for functional abilities (maximal oxygen consumption, pulse frequency and vital lungs capacity evaluation and 4 athletic disciplines (high jump, long jump, shot put and 60 meters low start sprint from current physical education curriculum. Crombah-alfa coefficient values indicate to satisfactory reliability of applied instruments. In data processing canonical correlation analysis and multiple regression analysis have been used. Achieved canonical correlation analysis results showed that functional abilities set is statistically and significantly related to criterion variables set (R=.67, manifesting one canonical factor on the level p<.03. Achieved determination coefficient (R² = .43 indicates to functional abilities prognostic significance of explained variance 46% criterion. Using hierarchy regression model following statistically significant beta coefficient of functional abilities as partial predictors of athletics outcome have been determined: I for vital lungs capacity- high jump (β = .67, p < .01, II for vital lungs capacity- long jump (β = .55, p < .01, III for vital lungs capacity and pulse frequency- shot put (β =.-.34, p < .01; β =.42, p < .02 and IV for vital lungs capacity- 60 meters sprint (β = .-.39. Regression equation calculation of other applied functional abilities preadolescents’ predictor variables has not statistically and significantly contributed to univariance prediction of criterion variable variance

  14. [Change and Significance of RhoA/ROCK signaling pathway in the model with natural degeneration of the rat endplate chondrocytes].

    Science.gov (United States)

    Ma, Mingming; Xu, Hongguang; Zhang, Xiaoling; Wang, Hong; Zheng, Quan; Xu, Jiajia; Shen, Xiang; Zhang, Shufeng

    2015-11-03

    To explore the change and Significance of RhoA/ROCK signaling pathway in the model with natural degeneration of the rat endplate chondrocytes. Endplate chondrocytes were selected by enzyme digestion and cultured in vitro to divided into control (P2 cells), naturally passaged (P5 cells) groups and treatment group (P5+ROCK Inhibitor Y27632). The phenotype of endplate chondrocytes were identified by toluidine blue stains and F-actin stains. Type II collagen, aggrecan and SOX9 genes were examed by Real-time RT-PCR to verify the degeneration model. The RhoA/ROCK signaling pathway related gene ROCK-1, ROCK-2 were detected by RT-PCR and Western blot. The actived RhoA was examed by active-RhoA detection and Western blot. With the passaging,endplate chondrocytes completely lost the original cell morphology, the levels of type II collagen (P5/P2=0.248, PROCK-1 (P5/P2=0.652, PROCK-2 (P5/P2=2.527, PROCK-1 AND ROCK-2 were down-regulated in the treatment group. And type II collagen, aggrecan, SOX9 significantly increased. The degeneration of endplate chondrocytes with decreased ROCK-1 expression but increased active-RhoA and ROCK-2 expression suggest that RhoA/ROCK signaling pathway play an important role in the in vitro degeneration of endplate chondrocytes.Modulating the expression of RhoA/ROCK signaling pathway may be a new method of solving the problem of the degeneration of intervertebral disc.

  15. Predictors of long-term opioid use among patients with painful lumbar spine conditions

    Science.gov (United States)

    Krebs, Erin E.; Lurie, Jon D.; Fanciullo, Gilbert; Tosteson, Tor D.; Blood, Emily A.; Carey, Timothy S.; Weinstein, James N.

    2009-01-01

    Our objective was to assess predictors of self-reported opioid use among patients with back pain due to lumbar disc herniation or spinal stenosis. Data was from the Spine Patient Outcomes Research Trial (SPORT), a multi-site observational study and randomized trial. We examined characteristics shown or hypothesized to be associated with opioid use. Using generalized estimating equations, we modeled associations of each potential predictor with opioid use at 12 and 24 months. At baseline, 42% of participants reported opioid use. Of these participants, 25% reported continued use at 12 months and 21% reported use at 24 months. In adjusted models, smoking (RR=1.9, p<0.001 at 12 months; RR=1.5, p=0.043 at 24 months) and non-surgical treatment (RR=1.7, p<0.001 at 12 months; RR=1.8, p=0.003 at 24 months) predicted long-term opioid continuation. Among participants not using opioids at baseline, incident use was reported by 8% at 12 and 7% at 24 months. We found no significant predictors of incident use at 12 or 24 months in the main models. In conclusion, nonsurgical treatment and smoking independently predicted long-term continued opioid use. To our knowledge, this is the first longitudinal study to assess predictors of long-term and incident opioid use among patients with lumbar spine conditions. PMID:19628436

  16. Motavizumab, A Neutralizing Anti-Respiratory Syncytial Virus (Rsv Monoclonal Antibody Significantly Modifies The Local And Systemic Cytokine Responses Induced By Rsv In The Mouse Model

    Directory of Open Access Journals (Sweden)

    Jafri Hasan S

    2007-10-01

    Full Text Available Abstract Motavizumab (MEDI-524 is a monoclonal antibody with enhanced neutralizing activity against RSV. In mice, motavizumab suppressed RSV replication which resulted in significant reduction of clinical parameters of disease severity. We evaluated the effect of motavizumab on the local and systemic immune response induced by RSV in the mouse model. Balb/c mice were intranasally inoculated with 106.5 PFU RSV A2 or medium. Motavizumab was given once intraperitoneally (1.25 mg/mouse as prophylaxis, 24 h before virus inoculation. Bronchoalveolar lavage (BAL and serum samples were obtained at days 1, 5 (acute and 28 (long-term post inoculation and analyzed with a multiplex assay (Beadlyte Upstate, NY for simultaneous quantitation of 18 cytokines: IL-1α, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, KC (similar to human IL-8, IL-10, IL-12p40, IL-12p70, IL-13, IL-17, TNF-α, MCP-1, RANTES, IFN-γ and GM-CSF. Overall, cytokine concentrations were lower in serum than in BAL samples. By day 28, only KC was detected in BAL specimens at low concentrations in all groups. Administration of motavizumab significantly reduced (p

  17. In what root-zone N concentration does nitrate start to leach significantly? A reasonable answer from modeling Mediterranean field data and closed root-zone experiments

    Science.gov (United States)

    Kurtzman, D.; Kanner, B.; Levy, Y.; Shapira, R. H.; Bar-Tal, A.

    2017-12-01

    Closed-root-zone experiments (e.g. pots, lyzimeters) reveal in many cases a mineral-nitrogen (N) concentration from which the root-N-uptake efficiency reduces significantly and nitrate leaching below the root-zone increases dramatically. A les-direct way to reveal this threshold concentration in agricultural fields is to calibrate N-transport models of the unsaturated zone to nitrate data of the deep samples (under the root-zone) by fitting the threshold concentration of the nitrate-uptake function. Independent research efforts of these two types in light soils where nitrate problems in underlying aquifers are common reviled: 1) that the threshold exists for most crops (filed, vegetables and orchards); 2) nice agreement on the threshold value between the two very different research methodologies; and 3) the threshold lies within 20-50 mg-N/L. Focusing on being below the threshold is a relatively simple aim in the way to maintain intensive agriculture with limited effects on the nitrate concentration in the underlying water resource. Our experience show that in some crops this threshold coincides with the end-of-rise of the N-yield curve (e.g. corn); in this case, it is relatively easy to convince farmers to fertilize below threshold. In other crops, although significant N is lost to leaching the crop can still use higher N concentration to increase yield (e.g. potato).

  18. Two-step grafting significantly enhances the survival of foetal dopaminergic transplants and induces graft-derived vascularisation in a 6-OHDA model of Parkinson's disease.

    Science.gov (United States)

    Büchele, Fabian; Döbrössy, Máté; Hackl, Christina; Jiang, Wei; Papazoglou, Anna; Nikkhah, Guido

    2014-08-01

    Following transplantation of foetal primary dopamine (DA)-rich tissue for neurorestaurative treatment of Parkinson's disease (PD), only 5-10% of the functionally relevant DAergic cells survive both in experimental models and in clinical studies. The current work tested how a two-step grafting protocol could have a positive impact on graft survival. DAergic tissue is divided in two portions and grafted in two separate sessions into the same target area within a defined time interval. We hypothesized that the first graft creates a "DAergic" microenvironment or "nest" similar to the perinatal substantia nigra that stimulates and protects the second graft. 6-OHDA-lesioned rats were sequentially transplanted with wild-type (GFP-, first graft) and transgenic (GFP+, second graft) DAergic cells in time interims of 2, 5 or 9days. Each group was further divided into two sub-groups receiving either 200k (low cell number groups: 2dL, 5dL, 9dL) or 400k cells (high cell number groups: 2dH, 5dH, 9dH) as first graft. During the second transplantation, all groups received the same amount of 200k GFP+ cells. Controls received either low or high cell numbers in one single session (standard protocol). Drug-induced rotations, at 2 and 6weeks after grafting, showed significant improvement compared to the baseline lesion levels without significant differences between the groups. Rats were sacrificed 8weeks after transplantation for post-mortem histological assessment. Both two-step groups with the time interval of 2days (2dL and 2dH) showed a significantly higher survival of DAergic cells compared to their respective standard control group (2dL, +137%; 2dH, +47%). Interposing longer intervals of 5 or 9days resulted in the loss of statistical significance, neutralising the beneficial two-step grafting effect. Furthermore, the transplants in the 2dL and 2dH groups had higher graft volume and DA-fibre-density values compared to all other two-step groups. They also showed intense growth of

  19. DEVELOPMENT OF A NOVEL RADIATIVELY/CONDUCTIVELY STABILIZED BURNER FOR SIGNIFICANT REDUCTION OF NOx EMISSIONS AND FOR ADVANCING THE MODELING AND UNDERSTANDING OF PULVERIZED COAL COMBUSTION AND EMISSIONS

    Energy Technology Data Exchange (ETDEWEB)

    Noam Lior; Stuart W. Churchill

    2003-10-01

    The primary objective of the proposed study was the study and analysis of, and design recommendations for, a novel radiatively-conductively stabilized combustion (RCSC) process for pulverized coal, which, based on our prior studies with both fluid fuels and pulverized coal, holds a high promise to reduce NO{sub x} production significantly. We have primarily engaged in continuing and improving our process modeling and analysis, obtained a large amount of quantitative information about the effects of the major parameters on NO{sub x} production, conducted an extensive exergy analysis of the process, evaluated the practicalities of employing the Radiatively-Conductively Stabilized Combustor (RCSC) to large power and heat plants, and improved the experimental facility. Prior experimental work has proven the feasibility of the combustor, but slagging during coal combustion was observed and should be dealt with. The primary outcomes and conclusions from the study are: (1) we developed a model and computer program that represents the pulverized coal combustion in the RCSC, (2) the model predicts that NO{sub x} emissions can be reduced by a number of methods, detailed in the report. (3) the exergy analysis points out at least a couple of possible ways to improve the exergetic efficiency in this combustor: increasing the effectiveness of thermal feedback, and adjusting the combustor mixture exit location, (4) because of the low coal flow rates necessitated in this study to obtain complete combustion in the burner, the size of a burner operating under the considered conditions would have to be up to an order of magnitude, larger than comparable commercial burners, but different flow configurations of the RCSC can yield higher feed rates and smaller dimensions, and should be investigated. Related to this contract, eleven papers were published in journals and conference proceedings, and ten invited presentations were given at university and research institutions, as well as at

  20. Predictors of Poor Pregnancy Outcomes Among Antenatal Care Attendees in Primary Health Care Facilities in Cross River State, Nigeria: A Multilevel Model.

    Science.gov (United States)

    Ameh, Soter; Adeleye, Omokhoa A; Kabiru, Caroline W; Agan, Thomas; Duke, Roseline; Mkpanam, Nkese; Nwoha, Doris

    2016-08-01

    Objectives Pregnancy carries a high risk for millions of women and varies by urban-rural location in Nigeria, a country with the second highest maternal deaths in the world. Addressing multilevel predictors of poor pregnancy outcomes among antenatal care (ANC) attendees in primary health care (PHC) facilities could reduce the high maternal mortality rate in Nigeria. This study utilised the "Risk Approach" strategy to (1) compare the risks of poor pregnancy outcomes among ANC attendees by urban-rural location; and (2) determine predictors of poor pregnancy outcomes among ANC attendees in urban-rural PHC facilities in Cross River State, Nigeria. Methods A cross-sectional survey was conducted in 2011 among 400 ANC attendees aged 15-49 years recruited through multistage sampling. Data on risk factors of poor pregnancy outcomes were collected using interviewer-administered questionnaires and clinic records. Respondents were categorised into low, medium or high risk of poor pregnancy outcomes, based on their overall risk scores. Predictors of poor pregnancy outcomes were determined by multilevel ordinal logistic regression. Results A greater proportion of the women in the rural areas were below the middle socio-economic quintile (75 vs. 4 %, p vs. 2 %, p vs. 35 %, p urban areas were older than 35 years (10 vs. 5 %, p care in the urban PHC facilities had a low overall risk of poor pregnancy outcomes than those in the rural facilities (64 vs. 50 %, p = 0.034). Pregnant women in the urban areas had decreased odds of being at high risk of poor pregnancy outcomes versus the combined medium and low risks compared with those in the rural areas (OR 0.55, 95 % CI 0.09-0.65). Conclusions for Practice Pregnant women attending antenatal care in rural PHC facilities are more at risk of poor pregnancy outcomes than those receiving care in the urban facilities. Health programmes that promote safe pregnancy should target pregnant women in rural settings.

  1. Exploring Predictors of Information Use to Self-Manage Blood Pressure in Midwestern African American Women with Hypertension.

    Science.gov (United States)

    Jones, Lenette M; Veinot, Tiffany; Pressler, Susan J; Coleman-Burns, Patricia; McCall, Alecia

    2017-04-05

    Self-management of hypertension requires patients to find, understand, and use information to lower their blood pressure. Little is known about information use among African American women with hypertension, therefore the purpose of this study was to examine predictors of self-reported information use to self-manage blood pressure. Ninety-four Midwestern African American women (mean age = 59) completed questionnaires about information behaviors (seeking, sharing, use) and personal beliefs (attitude, social norms) related to self-management of blood pressure. Linear regression was used to identify significant predictors of information use. The total variance explained by the model was 36%, F(7, 79) = 6.29, p Information sharing was the only significant predictor (beta = .46, p information sharing is a potential health behavior to support intervention strategies for African American women with hypertension.

  2. Interpersonal predictors of stress generation.

    Science.gov (United States)

    Eberhart, Nicole K; Hammen, Constance L

    2009-05-01

    Hammen (1991) provided evidence for a stress generation process in which individuals with a history of depression contributed to the occurrence of stressors, especially interpersonal and conflict events. However, few studies have examined the factors contributing to stress generation. This study examines aspects of individuals' interpersonal style, operationalized as attachment, dependency, and reassurance seeking, as predictors of conflict stress generation within romantic relationships. These effects were examined both prospectively over a 4-week period and cross-sectionally using a 14-day daily diary in a sample of female college students. Overall, there was significant evidence that interpersonal style contributes to the occurrence of interpersonal stressors. Specifically, anxious attachment and reassurance seeking prospectively predicted romantic conflict stress over a 4-week period, and a variety of interpersonal behaviors were associated with romantic conflict stressors on a daily basis. These results are interpreted in relation to previous literature, and limitations and directions for future research are discussed.

  3. Systemic antibiotic therapy does not significantly improve outcome in a rat model of implant-associated osteomyelitis induced by Methicillin susceptible Staphylococcus aureus.

    Science.gov (United States)

    Fölsch, Christian; Federmann, Maike; Lakemeier, Stefan; Kuehn, Klaus D; Kittinger, Clemens; Kerwat, Martina; Fuchs-Winkelmann, Susanne; Paletta, Jürgen R J; Roessler, Philip P

    2016-04-01

    Treatment of implant-associated osteomyelitis regularly involves the use of systemic antibiotics in addition to surgical intervention. However, it remains unclear if perioperative systemic application of bactericide substances can improve overall outcome in models of severe intramedullary infection. The present study investigated the use of systemic gentamicin in addition to a controlled local release from a highly lipophilic gentamicinpalmitate compound while the previous study showed efficacy of sole antibiotic implant-coating. Forty male Sprague-Dawley rats were divided into two groups receiving an intramedullary femoral injection of 10(2) CFU of a common methicillin susceptible Staphylococcus aureus strain (MSSA Rosenbach). Group I received an uncoated implant whereas group II received a coated implant. All animals received a single shot intraperitoneal application of gentamicinsulfate directly after wound closure while the historical control group III (n = 20) had no antibiotic treatment at all. Animals were observed for 28 and 42 days. Serum haptoglobin and relative weight gain were assessed as well as roll over cultures of explanted femur nails and histological scores of periprosthetic infection in dissected femora. Systemic application of gentamicin combined with antibiotic-coated implant did not further reduce bacterial growth significantly compared with systemic or local antibiotic application alone. Combined local and systemic therapy reduced serum haptoglobin significantly after day 7, 28 and 42 whereas systemic application alone did not compare to controls. Systemic perioperative and implant-associated application of antibiotics were both comparably effective to treat implant-associated infections whereas the combined antibiotic therapy further reduced systemic signs of infection time dependent.

  4. The University Matriculation Examination as a Predictor of ...

    African Journals Online (AJOL)

    The University Matriculation Examination as a Predictor of Performance in Post University Matriculation Examination: a Model for Educational development in the 21st Century. SO Uhunmwuangho, O Ogunbadeniyi ...

  5. Predictors of Mortality in Older Homeless Veterans.

    Science.gov (United States)

    Schinka, John A; Curtiss, Glenn; Leventhal, Katherine; Bossarte, Robert M; Lapcevic, William; Casey, Roger

    2017-10-01

    In this analysis of a cohort of older homeless veterans, we examined psychosocial, health, housing, and employment characteristics to identify predictors of mortality. Our sample of 3,620 older veterans entered Veteran Affairs homeless programs in years 2000-2003. Fifteen variables from a structured interview described this sample and served as predictors. National Death Index data for years 2000-2011 were used to ascertain death. Survival table analyses were conducted to estimate and plot cumulative survival functions. To determine predictors and estimate hazard functions, Cox proportional hazards regression analysis was conducted. Five variables (presence of a serious health issue, hospitalization for alcohol abuse, alcohol dependency, unemployment for 3 years, and age 60+) were associated with increased risk of death; three (non-White, drug dependency, and dental problems) were associated with reduced risk. A risk score, based on total unit-weighted risk for all eight predictors, was used to identify three groups that were found to differ significantly in mortality. These analyses underline the jeopardy faced by older homeless veterans in terms of early death. We were able to identify several variables associated with mortality; more importantly, we were able to show that a risk score based on status for these variables was significantly related to survival. Published by Oxford University Press on behalf of The Gerontological Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  6. Are competition and extrinsic motivation reliable predictors of academic cheating?

    Science.gov (United States)

    Orosz, Gábor; Farkas, Dávid; Roland-Lévy, Christine

    2013-01-01

    Previous studies suggest that extrinsic motivation and competition are reliable predictors of academic cheating. The aim of the present questionnaire study was to separate the effects of motivation- and competition-related variables on academic cheating by Hungarian high school students (N = 620, M = 264, F = 356). Structural equation modeling showed that intrinsic motivation has a negative effect, and amotivation has a positive indirect effect on self-reported academic cheating. In contrast, extrinsic motivation had no significant effect. Indirect positive influence on cheating, based on some characteristics of hypercompetition, was also found, whereas attitudes toward self-developmental competition had a mediated negative influence. Neither constructive nor destructive competitive classroom climate had a significant impact on academic dishonesty. Acceptance of cheating and guilt has significant and direct effect on self-reported cheating. In comparison with them, the effects of motivational and competition-related variables are relatively small, even negligible. These results suggest that extrinsic motivation and competition are not amongst the most reliable predictors of academic cheating behavior.

  7. Are competition and extrinsic motivation reliable predictors of academic cheating?

    Directory of Open Access Journals (Sweden)

    Gábor eOrosz

    2013-02-01

    Full Text Available Previous studies suggest that extrinsic motivation and competition are reliable predictors of academic cheating. The aim of the present questionnaire study was to separate the effects of motivation- and competition-related variables on academic cheating by Hungarian high school students (N = 620, M = 264, F = 356. Structural equation modeling showed that intrinsic motivation has a negative effect, and amotivation has a positive indirect effect on self-reported academic cheating. In contrast, extrinsic motivation had no significant effect. Indirect positive influence on cheating, based on some characteristics of hypercompetition, was also found, whereas attitudes towards self-developmental competition had a mediated negative influence. Neither constructive nor destructive competitive classroom climate had a significant impact on academic dishonesty. Acceptance of cheating and guilt has significant and direct effect on self-reported cheating. In comparison with them, the effects of motivational and competition-related variables are relatively small, even negligible. These results suggest that extrinsic motivation and competition are not amongst the most reliable predictors of academic cheating behavior.

  8. Are Competition and Extrinsic Motivation Reliable Predictors of Academic Cheating?

    Science.gov (United States)

    Orosz, Gábor; Farkas, Dávid; Roland-Lévy, Christine

    2013-01-01

    Previous studies suggest that extrinsic motivation and competition are reliable predictors of academic cheating. The aim of the present questionnaire study was to separate the effects of motivation- and competition-related variables on academic cheating by Hungarian high school students (N = 620, M = 264, F = 356). Structural equation modeling showed that intrinsic motivation has a negative effect, and amotivation has a positive indirect effect on self-reported academic cheating. In contrast, extrinsic motivation had no significant effect. Indirect positive influence on cheating, based on some characteristics of hypercompetition, was also found, whereas attitudes toward self-developmental competition had a mediated negative influence. Neither constructive nor destructive competitive classroom climate had a significant impact on academic dishonesty. Acceptance of cheating and guilt has significant and direct effect on self-reported cheating. In comparison with them, the effects of motivational and competition-related variables are relatively small, even negligible. These results suggest that extrinsic motivation and competition are not amongst the most reliable predictors of academic cheating behavior. PMID:23450676

  9. Sociodemographic predictors of elderly's psychological well-being in Malaysia.

    Science.gov (United States)

    Momtaz, Yadollah A; Ibrahim, Rahimah; Hamid, Tengku A; Yahaya, Nurizan

    2011-05-01

    Psychological well-being as one of the most important indicators of successful aging has received substantial attention in the gerontological literature. Prior studies show that sociodemographic factors influencing elderly's psychological well-being are multiple and differ across cultures. The aim of this study was to identify significant sociodemographic predictors of psychological well-being among Malay elders. The study included 1415 older Malays (60-100 years, 722 women), randomly selected through a multistage stratified random method from Peninsular Malaysia. WHO-Five well-being index was used to measure psychological well-being. Data analysis was conducted using the Statistical Package for Social Sciences (SPSS) version 13.0. Using multiple regression analysis a significant model emerged (F(7, 1407) = 20.14, p ≤ 0.001), where age, sex, marital status, and household income were significant predictor variables of psychological well-being among Malay elders. However, level of education, employment status, and place of residence failed to predict psychological well-being. This study showed that the oldest old, elderly women, unmarried, and the poor elderly people are at risk for experiencing low psychological well-being. Therefore, they need special attention from family, policy makers, and those who work with elderly people.

  10. The Biggest Loser Thinks Long-Term: Recency as a Predictor of Success in Weight Management

    OpenAIRE

    Koritzky, Gilly; Rice, Chantelle; Dieterle, Camille; Bechara, Antoine

    2015-01-01

    Only a minority of participants in behavioral weight management lose weight significantly. The ability to predict who is likely to benefit from weight management can improve the efficiency of obesity treatment. Identifying predictors of weight loss can also reveal potential ways to improve existing treatments. We propose a neuro-psychological model that is focused on recency: the reliance on recent information at the expense of time-distant information. Forty-four weight-management patients c...

  11. Chronic administration of ethanol leaf extract of Moringa oleifera Lam. (Moringaceae) may compromise glycaemic efficacy of Sitagliptin with no significant effect in retinopathy in a diabetic rat model.

    Science.gov (United States)

    Olurishe, Comfort; Kwanashie, Helen; Zezi, Abdulkadiri; Danjuma, Nuhu; Mohammed, Bisalla

    2016-12-24

    Moringa oleifera Lam. (Moringaceae) has gained awareness for its antidiabetic effect, and is used as alternative therapy or concurrently with orthodox medicines such as sitagliptin in diabetes mellitus. This is without ascertaining the possibility of drug-herb interactions, which could either lead to enhanced antidiabetic efficacy, increased toxicity, or compromised glycaemic control with negative consequence in diabetic retinopathy. To investigate the effect, of sitagliptin (50mg/kg), Moringa oleifera (300mg/kg) leaf extract, and a combination of both on glycaemic control parameters, lenticular opacity and changes in retinal microvasculature in alloxan (150mg/kg i.p) induced diabetic rat model. Seven groups of eight rats per group were used, with groups I, II and VII as normal (NC), diabetic (DC) and post-prandial controls (PPC). Groups III to VI were diabetic rats on sitagliptin (III), M. oleifera (IV), sitagliptin and M. oleifera (SM) (V), for 42 days with 2 weeks delayed treatment in a post-prandial hyperglycaemic group (PPSM) (VI). Glycaemic control parameters, insulin levels, body weights, and effects of retinal microvasculature on lenticular opacity/morphology were investigated. A significant decrease in fasting blood glucose (FBG) levels was displayed in SM group from day 14(60%) (poleifera showed a progressive decrease in anti-hyperglycaemic effect of sitagliptin, and although it delayed the onset of lenticular opacity (i.e. cataract-like changes) it did not prevent the progression nor ameliorated pathologic lesions in the retina. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  12. Discovery of Highly Potent Tyrosinase Inhibitor, T1, with Significant Anti-Melanogenesis Ability by zebrafish in vivo Assay and Computational Molecular Modeling

    Science.gov (United States)

    Chen, Wang-Chuan; Tseng, Tien-Sheng; Hsiao, Nai-Wan; Lin, Yun-Lian; Wen, Zhi-Hong; Tsai, Chin-Chuan; Lee, Yu-Ching; Lin, Hui-Hsiung; Tsai, Keng-Chang

    2015-01-01

    Tyrosinase is involved in melanin biosynthesis and the abnormal accumulation of melanin pigments leading to hyperpigmentation disorders that can be treated with depigmenting agents. A natural product T1, bis(4-hydroxybenzyl)sulfide, isolated from the Chinese herbal plant, Gastrodia elata, is a strong competitive inhibitor against mushroom tyrosinase (IC50 = 0.53 μM, Ki = 58 +/- 6 nM), outperforms than kojic acid. The cell viability and melanin quantification assay demonstrate that 50 μM of T1 apparently attenuates 20% melanin content of human normal melanocytes without significant cell toxicity. Moreover, the zebrafish in vivo assay reveals that T1 effectively reduces melanogenesis with no adverse side effects. The acute oral toxicity study evidently confirms that T1 molecule is free of discernable cytotoxicity in mice. Furthermore, the molecular modeling demonstrates that the sulfur atom of T1 coordinating with the copper ions in the active site of tyrosinase is essential for mushroom tyrosinase inhibition and the ability of diminishing the human melanin synthesis. These results evident that T1 isolated from Gastrodia elata is a promising candidate in developing pharmacological and cosmetic agents of great potency in skin-whitening.

  13. Predictors of Institutionalization of Dementia Patients in Mild and Moderate Stages: A 4-Year Prospective Analysis

    Science.gov (United States)

    Eska, Kathrin; Graessel, Elmar; Donath, Carolin; Schwarzkopf, Larissa; Lauterberg, Joerg; Holle, Rolf

    2013-01-01

    Background Institutionalization is the most important milestone in the care of dementia patients. This study was aimed at identifying relevant predictors of institutionalization in a broad empirical context and interpreting them on the basis of the predictor model proposed by Luppa et al. [Dement Geriatr Cogn Disord 2008;26:65-78]. Methods At the start of this study, 357 patients with mild to moderate dementia were examined by their general practitioners, and a telephone interview was conducted with their caregivers. Four years later, the outcomes ‘institutionalization’ and ‘death’ were determined from health insurance data. Forty-one variables were examined for their predictive influence by univariate and multivariate Cox regression. Results The risk of institutionalization increased significantly (p ≤ 0.05) with older ages of patients [hazard ratio (HR) = 1.05] and caregivers (HR = 1.03), a higher educational level of the caregiver (HR = 1.83), greater use of community health services (HR = 1.59), greater caregiver burden (HR = 1.02), and when the caregiver and patient lived apart (HR = 1.97). Conclusion The results show that there is a multifactorial influence on institutionalization of dementia patients by sociodemographic, health-related, and psychological aspects as well as the care situation, thus validating the predictor model by Luppa et al. [Dement Geriatr Cogn Disord 2008;26:65-78]. Caregiver burden was found to be the strongest predictor accessible to interventions. PMID:24348504

  14. Predictors of pre-hospital delay in Hong Kong Chinese patients with acute myocardial infarction.

    Science.gov (United States)

    Li, Polly Wc; Yu, Doris Sf

    2018-01-01

    The pre-hospital delay to seek care remains the most significant barrier for effective management of acute myocardial infarction. Many of the previous studies mainly took place in Western countries. Few data are available about the care-seeking behavior of Hong Kong Chinese. The purpose of this study was to identify the predictors of pre-hospital delay in care seeking among Hong Kong Chinese patients with acute myocardial infarction. Adult Chinese patients ( n=301) with a confirmed diagnosis of acute myocardial infarction were recruited from the cardiac units of three regional hospitals in Hong Kong. Various socio-demographic, clinical, symptom presentation characteristics and patient perceptual factors were considered as potential predictors. Multivariate analysis was conducted to identify the independent predictors with pre-hospital delay in care-seeking among acute myocardial infarction patients. Perceived barriers to care seeking constituted the most significant predictor for longer pre-hospital delay in acute myocardial infarction patients. Female gender was also significant in predicting longer delay, whereas a greater extent of symptom congruence and a greater extent of typical symptom presentation were significantly associated with a shorter delay. The final model accounted for 49.6% of the variance in pre-hospital delay as a whole. The most prominent predictors of pre-hospital delay are modifiable in nature, including the perceived barriers to care seeking and symptom congruence. Other sociodemographic and clinical factors also influence patients' decision. Although these are non-modifiable, our findings provide important insight for educating high-risk individuals.

  15. Echocardiographic predictors of atrial fibrillation after mitral valve replacement

    Directory of Open Access Journals (Sweden)

    Al-Shimaa Mohamed Sabry

    2017-12-01

    Conclusion: LA systolic strain and LV global longitudinal strain were significant predictors of POAF. Echocardiographic parameters can identify patients at greater risk of developing POAF who can benefit from preventive measure and guide the selection of prosthesis.

  16. Predictors of Career Adaptability Skill among Higher Education Students in Nigeria

    Directory of Open Access Journals (Sweden)

    Amos Shaibu Ebenehi

    2016-12-01

    Full Text Available This paper examined predictors of career adaptability skill among higher  education students in Nigeria. A sample of 603 higher education students randomly selected from six colleges of education in Nigeria participated in this study.  A set of self-reported questionnaire was used for data collection, and multiple linear regression analysis was used to analyze the data.  Results indicated that 33.3% of career adaptability skill was explained by the model.  Four out of the five predictor variables significantly predicted career adaptability skill among higher education students in Nigeria.  Among the four predictors, career self-efficacy sources was the most statistically significant predictor of career adaptability skill among higher education students in Nigeria, followed by personal goal orientation, career future concern, and perceived social support respectively.  Vocational identity did not statistically predict career adaptability skill among higher education students in Nigeria.  The study suggested that similar study should be replicated in other parts of the world in view of the importance of career adaptability skill to the smooth transition of graduates from school to the labor market.  The study concluded by requesting stakeholders of higher institutions in Nigeria to provide career exploration database for the students, and encourage career intervention program in order to enhance career adaptability skill among the students.

  17. SU-E-T-580: On the Significance of Model Based Dosimetry for Breast and Head and Neck 192Ir HDR Brachytherapy

    Energy Technology Data Exchange (ETDEWEB)

    Peppa, V; Pappas, E; Pantelis, E; Papagiannis, P [Medical Physics Laboratory, Medical School, University of Athens, Athens (Greece); Major, T; Polgar, C [National Institute of Oncology, Budapest (Hungary)

    2015-06-15

    Purpose: To assess the dosimetric and radiobiological differences between TG43-based and model-based dosimetry in the treatment planning of {sup 192}Ir HDR brachytherapy for breast and head and neck cancer. Methods: Two cohorts of 57 Accelerated Partial Breast Irradiation (APBI) and 22 head and neck (H&N) patients with oral cavity carcinoma were studied. Dosimetry for the treatment plans was performed using the TG43 algorithm of the Oncentra Brachy v4.4 treatment planning system (TPS). Corresponding Monte Carlo (MC) simulations were performed using MCNP6 with input files automatically prepared by the BrachyGuide software tool from DICOM RT plan data. TG43 and MC data were compared in terms of % dose differences, Dose Volume Histograms (DVHs) and related indices of clinical interest for the Planning Target Volume (PTV) and the Organs-At-Risk (OARs). A radiobiological analysis was also performed using the Equivalent Uniform Dose (EUD), mean survival fraction (S) and Tumor Control Probability (TCP) for the PTV, and the Normal Tissue Control Probability (N TCP) and the generalized EUD (gEUD) for the OARs. Significance testing of the observed differences performed using the Wilcoxon paired sample test. Results: Differences between TG43 and MC DVH indices, associated with the increased corresponding local % dose differences observed, were statistically significant. This is mainly attributed to their consistency however, since TG43 agrees closely with MC for the majority of DVH and radiobiological parameters in both patient cohorts. Differences varied considerably among patients only for the ipsilateral lung and ribs in the APBI cohort, with a strong correlation to target location. Conclusion: While the consistency and magnitude of differences in the majority of clinically relevant DVH indices imply that no change is needed in the treatment planning practice, individualized dosimetry improves accuracy and addresses instances of inter-patient variability observed. Research

  18. SU-E-T-580: On the Significance of Model Based Dosimetry for Breast and Head and Neck 192Ir HDR Brachytherapy

    International Nuclear Information System (INIS)

    Peppa, V; Pappas, E; Pantelis, E; Papagiannis, P; Major, T; Polgar, C

    2015-01-01

    Purpose: To assess the dosimetric and radiobiological differences between TG43-based and model-based dosimetry in the treatment planning of 192 Ir HDR brachytherapy for breast and head and neck cancer. Methods: Two cohorts of 57 Accelerated Partial Breast Irradiation (APBI) and 22 head and neck (H&N) patients with oral cavity carcinoma were studied. Dosimetry for the treatment plans was performed using the TG43 algorithm of the Oncentra Brachy v4.4 treatment planning system (TPS). Corresponding Monte Carlo (MC) simulations were performed using MCNP6 with input files automatically prepared by the BrachyGuide software tool from DICOM RT plan data. TG43 and MC data were compared in terms of % dose differences, Dose Volume Histograms (DVHs) and related indices of clinical interest for the Planning Target Volume (PTV) and the Organs-At-Risk (OARs). A radiobiological analysis was also performed using the Equivalent Uniform Dose (EUD), mean survival fraction (S) and Tumor Control Probability (TCP) for the PTV, and the Normal Tissue Control Probability (N TCP) and the generalized EUD (gEUD) for the OARs. Significance testing of the observed differences performed using the Wilcoxon paired sample test. Results: Differences between TG43 and MC DVH indices, associated with the increased corresponding local % dose differences observed, were statistically significant. This is mainly attributed to their consistency however, since TG43 agrees closely with MC for the majority of DVH and radiobiological parameters in both patient cohorts. Differences varied considerably among patients only for the ipsilateral lung and ribs in the APBI cohort, with a strong correlation to target location. Conclusion: While the consistency and magnitude of differences in the majority of clinically relevant DVH indices imply that no change is needed in the treatment planning practice, individualized dosimetry improves accuracy and addresses instances of inter-patient variability observed. Research co

  19. Stroke Location Is an Independent Predictor of Cognitive Outcome.

    Science.gov (United States)

    Munsch, Fanny; Sagnier, Sharmila; Asselineau, Julien; Bigourdan, Antoine; Guttmann, Charles R; Debruxelles, Sabrina; Poli, Mathilde; Renou, Pauline; Perez, Paul; Dousset, Vincent; Sibon, Igor; Tourdias, Thomas

    2016-01-01

    On top of functional outcome, accurate prediction of cognitive outcome for stroke patients is an unmet need with major implications for clinical management. We investigated whether stroke location may contribute independent prognostic value to multifactorial predictive models of functional and cognitive outcomes. Four hundred twenty-eight consecutive patients with ischemic stroke were prospectively assessed with magnetic resonance imaging at 24 to 72 hours and at 3 months for functional outcome using the modified Rankin Scale and cognitive outcome using the Montreal Cognitive Assessment (MoCA). Statistical maps of functional and cognitive eloquent regions were derived from the first 215 patients (development sample) using voxel-based lesion-symptom mapping. We used multivariate logistic regression models to study the influence of stroke location (number of eloquent voxels from voxel-based lesion-symptom mapping maps), age, initial National Institutes of Health Stroke Scale and stroke volume on modified Rankin Scale and MoCA. The second part of our cohort was used as an independent replication sample. In univariate analyses, stroke location, age, initial National Institutes of Health Stroke Scale, and stroke volume were all predictive of poor modified Rankin Scale and MoCA. In multivariable analyses, stroke location remained the strongest independent predictor of MoCA and significantly improved the prediction compared with using only age, initial National Institutes of Health Stroke Scale, and stroke volume (area under the curve increased from 0.697-0.771; difference=0.073; 95% confidence interval, 0.008-0.155). In contrast, stroke location did not persist as independent predictor of modified Rankin Scale that was mainly driven by initial National Institutes of Health Stroke Scale (area under the curve going from 0.840 to 0.835). Similar results were obtained in the replication sample. Stroke location is an independent predictor of cognitive outcome (MoCA) at 3

  20. Neuraminidase-1 contributes significantly to the degradation of neuronal B-series gangliosides but not to the bypass of the catabolic block in Tay–Sachs mouse models

    Directory of Open Access Journals (Sweden)

    Z.K. Timur

    2015-09-01

    Full Text Available Tay–Sachs disease is a severe lysosomal storage disorder caused by mutations in the HEXA gene coding for α subunit of lysosomal β-Hexosaminidase A enzyme, which converts GM2 to GM3 ganglioside. HexA−/− mice, depleted of the β-Hexosaminidase A iso-enzyme, remain asymptomatic up to 1 year of age because of a metabolic bypass by neuraminidase(s. These enzymes remove a sialic acid residue converting GM2 to GA2, which is further degraded by the still intact β-Hexosaminidase B iso-enzyme into lactosylceramide. A previously identified ganglioside metabolizing neuraminidase, Neu4, is abundantly expressed in the mouse brain and has activity against gangliosides like GM2 in vitro. Neu4−/− mice showed increased GD1a and decreased GM1 ganglioside in the brain suggesting the importance of the Neu4 in ganglioside catabolism. Mice with targeted disruption of both HexA and Neu4 genes showed accumulating GM2 ganglioside and epileptic seizures with 40% penetrance, indicating that the neuraminidase Neu4 is a modulatory gene, but may not be the only neuraminidase contributing to the metabolic bypass in HexA−/− mice. Therefore, we elucidated the biological role of neuraminidase-1 in ganglioside degradation in mouse. Analysis of HexA−/−Neu1−/− and HexA−/−Neu4−/−Neu1−/− mice models showed significant contribution of neuraminidase-1 on B-series ganglioside degradation in the brain. Therefore, we speculate that other neuraminidase/neuraminidases such as Neu2 and/or Neu3 might be also involved in the ganglioside degradation pathway in HexA−/− mice.

  1. The in vitro mass-produced model mycorrhizal fungus, Rhizophagus irregularis, significantly increases yields of the globally important food security crop cassava.

    Directory of Open Access Journals (Sweden)

    Isabel Ceballos

    Full Text Available The arbuscular mycorrhizal symbiosis is formed between arbuscular mycorrhizal fungi (AMF and plant roots. The fungi provide the plant with inorganic phosphate (P. The symbiosis can result in increased plant growth. Although most global food crops naturally form this symbiosis, very few studies have shown that their practical application can lead to large-scale increases in food production. Application of AMF to crops in the tropics is potentially effective for improving yields. However, a main problem of using AMF on a large-scale is producing cheap inoculum in a clean sterile carrier and sufficiently concentrated to cheaply transport. Recently, mass-produced in vitro inoculum of the model mycorrhizal fungus Rhizophagus irregularis became available, potentially making its use viable in tropical agriculture. One of the most globally important food plants in the tropics is cassava. We evaluated the effect of in vitro mass-produced R. irregularis inoculum on the yield of cassava crops at two locations in Colombia. A significant effect of R. irregularis inoculation on yield occurred at both sites. At one site, yield increases were observed irrespective of P fertilization. At the other site, inoculation with AMF and 50% of the normally applied P gave the highest yield. Despite that AMF inoculation resulted in greater food production, economic analyses revealed that AMF inoculation did not give greater return on investment than with conventional cultivation. However, the amount of AMF inoculum used was double the recommended dose and was calculated with European, not Colombian, inoculum prices. R. irregularis can also be manipulated genetically in vitro, leading to improved plant growth. We conclude that application of in vitro R. irregularis is currently a way of increasing cassava yields, that there is a strong potential for it to be economically profitable and that there is enormous potential to improve this efficiency further in the future.

  2. Fusion protein comprised of the two schistosomal antigens, Sm14 and Sm29, provides significant protection against Schistosoma mansoni in murine infection model.

    Science.gov (United States)

    Mossallam, Shereen F; Amer, Eglal I; Ewaisha, Radwa E; Khalil, Amal M; Aboushleib, Hamida M; Bahey-El-Din, Mohammed

    2015-03-24

    Schistosoma mansoni infection represents a major cause of morbidity and mortality in many areas of the developing world. Effective vaccines against schistosomiasis are not available and disease management relies mainly on treatment with the anthelmintic drug praziquantel. Several promising schistosomal antigens have been evaluated for vaccine efficacy such as Sm14, Sm29 and tetraspanins. However, most investigators examine these promising antigens in animal models individually rather than in properly adjuvanted antigen combinations. In the present study, we made a recombinant fusion protein comprised of the promising schistosomal antigens Sm14 and Sm29. The fusion protein, FSm14/29, was administered to Swiss albino mice either unadjuvanted or adjuvanted with polyinosinic-polycytidylic acid adjuvant, poly(I:C). Mice were challenged with S. mansoni cercariae and different parasitological/immunological parameters were assessed seven weeks post-challenge. Data were analyzed using the ANOVA test with post-hoc Tukey-Kramer test. Mice pre-immunized with unadjuvanted or poly(I:C)-adjuvanted fusion protein showed reduction of adult worm burden of 44.7 and 48.4%, respectively. In addition, significant reduction of tissue egg burdens was observed in mice immunized with the fusion protein when compared with the infected saline/adjuvant negative control groups and groups immunized with the individual Sm14 and Sm29 antigens. Light microscope and scanning electron microscope (SEM) investigation of adult worms recovered from FSm14/29-immunized mice revealed appreciable morphological damage and tegumental deformities. Histopathological examination of liver sections of immunized mice demonstrated reduced granulomatous and inflammatory reactions when compared with infected unvaccinated mice or mice immunized with the individual Sm14 and Sm29 antigens. The findings presented in this study highlight the importance of the fusion protein FSm14/29 as a potential vaccine candidate that is

  3. A Note on Testing Mediated Effects in Structural Equation Models: Reconciling Past and Current Research on the Performance of the Test of Joint Significance

    Science.gov (United States)

    Valente, Matthew J.; Gonzalez, Oscar; Miocevic, Milica; MacKinnon, David P.

    2016-01-01

    Methods to assess the significance of mediated effects in education and the social sciences are well studied and fall into two categories: single sample methods and computer-intensive methods. A popular single sample method to detect the significance of the mediated effect is the test of joint significance, and a popular computer-intensive method…

  4. Predictors of Institutionalization in Patients with Alzheimer's Disease in South Korea.

    Science.gov (United States)

    Park, Dong Gyu; Lee, Soojin; Moon, Young Min; Na, Duk L; Jeong, Ji Hyang; Park, Kyung Won; Lee, Yoon Hwan; Lim, Tae Sung; Choi, Seong Hye; Moon, So Young

    2018-02-28

    We investigated predictors of institutionalization in patients with Alzheimer's disease (AD) in South Korea. In total, 2,470 patients with AD aged 74.5±7.8 years (mean±standard deviation, 68.1% females) were enrolled from November 2005 to December 2013. The dates of institutionalization were identified from the public Long-Term-Care Insurance program in January 2014. We used a Cox proportional-hazards model to identify predictors for future institutionalization among characteristics at the time of diagnosis in 2,470 AD patients. A similar Cox proportional-hazards model was also used to investigate predictors among variables that reflected longitudinal changes in clinical variables before institutionalization in 816 patients who underwent follow-up testing. A lower Mini Mental State Examination score [hazard ratio (HR)=0.95, 95% confidence interval (CI)=0.92-0.97] and higher scores for the Clinical Dementia Rating and Neuro-Psychiatric Inventory (HR=1.01, 95% CI=1.00-1.01) at baseline were independent predictors of institutionalization. The relationship of patients with their main caregivers, presence of the apolipoprotein E e4 allele, and medication at baseline were not significantly associated with the rate of institutionalization. In models with variables that exhibited longitudinal changes, larger annual change in Clinical Dementia Rating Sum of Boxes score (HR=1.15, 95% CI=1.06-1.23) and higher medication possession ratio of antipsychotics (HR=1.89, 95% CI=1.20-2.97) predicted earlier institutionalization. This study shows that among Korean patients with AD, lower cognitive ability, higher dementia severity, more-severe behavioral symptoms at baseline, more-rapid decline in dementia severity, and more-frequent use of antipsychotics are independent predictors of earlier institutionalization.

  5. Predictor-Year Subspace Clustering Based Ensemble Prediction of Indian Summer Monsoon

    Directory of Open Access Journals (Sweden)

    Moumita Saha

    2016-01-01

    Full Text Available Forecasting the Indian summer monsoon is a challenging task due to its complex and nonlinear behavior. A large number of global climatic variables with varying interaction patterns over years influence monsoon. Various statistical and neural prediction models have been proposed for forecasting monsoon, but many of them fail to capture variability over years. The skill of predictor variables of monsoon also evolves over time. In this article, we propose a joint-clustering of monsoon years and predictors for understanding and predicting the monsoon. This is achieved by subspace clustering algorithm. It groups the years based on prevailing global climatic condition using statistical clustering technique and subsequently for each such group it identifies significant climatic predictor variables which assist in better prediction. Prediction model is designed to frame individual cluster using random forest of regression tree. Prediction of aggregate and regional monsoon is attempted. Mean absolute error of 5.2% is obtained for forecasting aggregate Indian summer monsoon. Errors in predicting the regional monsoons are also comparable in comparison to the high variation of regional precipitation. Proposed joint-clustering based ensemble model is observed to be superior to existing monsoon prediction models and it also surpasses general nonclustering based prediction models.

  6. Parity-specific and two-sex utility models of reproductive intentions.

    Science.gov (United States)

    Fried, E S; Hofferth, S L; Udry, J R

    1980-02-01

    This paper uses married couples' anticipated consequences of having a (another) child to predict their reproductive intentions. Parity-specific models identify different variables as predictors of reproductive behavior at different parities but do not yield interpretable patterns of difference by parity. Parity-specific models are not significantly stronger predictors of reproductive behavior. Generally, wife-only models are distinctly superior to husband-only models. Two-sex models are usually better predictors than one-sex models but not enough better to justify the additional cost.

  7. Incidence and predictors of difficult mask ventilation and intubation.

    Science.gov (United States)

    Shah, Prerana N; Sundaram, Vimal

    2012-10-01

    This study is aimed to determine the incidence and predictors of difficult and impossible mask ventilation. Information like age, snoring history, obstructive sleep apnea, dental and mandibular abnormalities, macroglossia, grading like SLUX, Mallampatti, Cormack Lehanne, atlantooccipital extension, presence of beard or moustache, mouth opening were collected. During mask ventilation, the information related to the ventilation and intubation was collected. All variables found to be significant in univariate analysis were subjected to the multivariate logistic regression model to identify independent predictors of measured outcome. Difficult mask ventilation (DMV) was observed in 30 male patients and 9 female patients. Of the 40 patients who had difficult intubation (DI), 7 patients had both DMV and intubation and 1 patient was of impossible mask ventilation/ intubation. Snoring was the lone significant risk factor for DMV. The risk factors identified for DI were snoring, retrognathia, micrognathia, macroglossia, short thick neck, Mallampatti grade [III/IV], abnormal SLUX grade, Cormack Lehanne grade [II,III/IV], abnormal atlantooccipital extension grading, flexion/extension deformity of neck, protuberant teeth, cervical spine abnormality, mouth opening 26 kg/m(2). BMI > 26 kg/m(2) and atlantooccipital extension grade > 3 were independent risk factors for DI and the presence of two of the variables made the sensitivity and specificity of 43% and 99% respectively with a positive predictive value of 74%. The predictive score may lead to a better anticipation of difficult airway management, potentially deceasing the morbidity and mortality resulting from hypoxia or anoxia with failed ventilation.

  8. Predictors of health promotion lifestyle among three ethnic groups of elderly rural women in Taiwan.

    Science.gov (United States)

    Wang, H H

    1999-10-01

    The purpose of this study was to examine the predictors of health promotion lifestyle (HPL) and examine the similarities and differences among three ethnic groups of elderly rural women in Taiwan. Pender's Health Promotion Model was used as the conceptual framework of this study. A convenience sample of 599 elderly rural women was recruited from three rural areas: Kao-Shu, San-Di-Men, and Ma-Chia. Ho-Lo, Hakka, and aboriginal people are the three main ethnic groups in these areas. Of the 599 elderly women, 391 completed all of the interview questions. Subjects ranged from 65 to 91 years old. All instruments used in this study have been evaluated for their content validity. The interrater reliability and alpha coefficient reliability of all instruments were greater than 0.70. A survey-interview method was used to collect data. Findings showed that the predictors of HPL have differences and similarities among elderly rural women from different ethnicities. In the group of elderly Ho-Lo women, age, education, living arrangements, and perceived barriers to health promotion lifestyle (PBaHPL) were significant predictors and they explained 41.9% of total variance in HPL. In the group of elderly Hakka women, education, number of chronic health problems, PBaHPL, and perceived benefits of health promotion lifestyle (PBeHPL) were significant predictors in explaining 53.9% of total variance in HPL. Finally, in the group of elderly aboriginal women, living arrangements, PBaHPL, and PBeHPL were significant predictors in explaining 70.0% of total variance in HPL. Community nurses can use their understanding of different ethnic groups to assess, identify, and use effective health promotion interventions for elderly rural women.

  9. Comparison of Designated Coefficients and their Predictors in Functional Evaluation of Wheelchair Rugby Athletes

    Directory of Open Access Journals (Sweden)

    Zwierzchowska Anna

    2015-12-01

    Full Text Available The objectives of the present study were twofold: to determine differences between groups by means of chosen coefficients and to create significant predictors using regression models for athletes in wheelchair rugby who had the same spinal cord injury (tetraplegia and were classified as low point and high point players. The study sample consisted of 24 subjects, who had sustained cervical spinal cord injury (CSCI. They were divided into low point (n=15 and high point (n=9 groups according to the IWRF Classification System. A one-way ANOVA revealed statistically significant differences in the following coefficients differentiating the groups: AC (η2=0.778, LC (η2=0.687, IC (η2=0.565, SC (η2=0.580. The Tukey’s HSD post-hoc test indicated statistically significant higher values of coefficients in the HP compared to the LP group: AC=0.958 (p=0.022, LC=0.989 (p=0.031, IC=0.971 (p=0.044, SC=0.938 (p=0.039. In the HP group, the most significant predictor was the sum of visceral and trunk fat which was negatively correlated with the SC (what constituted a positive adaptive change in response to training. With regard to the LP group, body height and circumference of the chest appeared to be most significant predictors and were positively correlated with the SC. In the LP group no predictor with respect to the SC was significantly correlated to sports training. Therefore, the functional classification system confirmed lower status of the LP players. The results of the present study indicate that both metabolic and somatic profiles which highly determine potential of wheelchair rugby athletes are significantly different in LP and HP players, what confirms the reliability of the functional classification system.

  10. Predictors of Success Following Muller's Muscle-Conjunctival Resection.

    Science.gov (United States)

    Dan, Joshua; Sinha, Kunal R; Rootman, Daniel B

    2018-01-12

    This study aims to describe Muller's muscle-conjunctival resection surgery in terms of outcomes and potential factors that may predict final positions. This cross-sectional cohort study included patients undergoing Muller's muscle-conjunctival resection surgery for involutional ptosis over a 15-year period. Success was defined in 2 ways: 1) final marginal reflex distance 1 (MRD1) ≥2.5 mm (MRD1 success) and 2) final difference in MRD1 ≤1 mm between eyelids (symmetry success). Percentages of patients achieving both outcomes were calculated. Predictors of outcome were assessed using bivariate analysis and multivariate models. The final sample included 315 eyes in 192 patients. The mean age (standard deviation) was 67.9 (11.9) years, and 60.0% were female. MRD1 ≥2.5 mm was achieved in 65.7% of the sample. Symmetry within 1 mm was achieved in 82.9% of the sample. Significant (p MRD1 success were female sex, concurrent lower eyelid blepharoplasty, and higher preoperative MRD1 in bivariate analysis; preoperative MRD1 and female sex in the multivariate model; and preoperative MRD1 in the a priori model. Significant (p < 0.05) predictors of symmetry success were female sex, previous lower eyelid blepharoplasty, concurrent lateral canthoplasty, preoperative symmetry, and older age in bivariate analysis; only female sex in the multivariate model. Muller's muscle-conjunctival resection is effective for elevating the eyelid in ptosis and may be more effective for achieving symmetry than absolute elevation over 2.5 mm. The results remain difficult to predict based clinical, surgical, or demographic factors.

  11. Landscape patterns as habitat predictors: Building and testing models for cavity-nesting birds in the Uinta Mountains of Utah, USA

    Science.gov (United States)

    Lawler, J.J.; Edwards, T.C.

    2002-01-01

    The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus), tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified, respectively) compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models.

  12. Predictors of first lifetime onset of major depressive disorder in young adulthood.

    Science.gov (United States)

    Klein, Daniel N; Glenn, Catherine R; Kosty, Derek B; Seeley, John R; Rohde, Paul; Lewinsohn, Peter M

    2013-02-01

    The first onset of major depressive disorder (MDD) most frequently occurs in young adulthood. However, few studies have examined predictors of first lifetime MDD during this high-risk period. The present study examined a broad range of demographic, clinical, and psychosocial variables as prospective predictors of first onset of MDD in a large community sample of young adults (N = 502) from the Oregon Adolescent Depression Project. Between ages 19-31, 35.3% of the sample had a first lifetime MDD episode. Female gender, familial loading of mood disorders, history of childhood sexual abuse, prior history of anxiety disorder, poor self-reported physical health, and subthreshold depressive symptoms significantly predicted MDD onset. In a multivariate model, female gender, familial loading of mood disorders, and subthreshold depression each contributed unique variance in predicting first lifetime MDD. This model had a moderate-to-large effect in predicting MDD onset. Gender did not moderate the other predictors, and the magnitude of the effects did not diminish over the course of the follow-up. These findings indicate that a number of risk factors significantly predict first lifetime MDD in young adulthood, and that simple multivariate risk models may be useful for identifying individuals at high risk for MDD. 2013 APA, all rights reserved

  13. Individual predictors of adolescents’ vocational interest stabilities

    OpenAIRE

    Hirschi, Andreas

    2010-01-01

    The study investigated the predictive utility of interest profile differentiation, coherence, elevation, congruence, and vocational identity commitment and career maturity (career planning and exploration) on the 10-month interest stability of 292 Swiss eighth-grade students: profile, rank, and level stabilities were assessed. Controlling for socio-demographic and vocational interest type variables, measures of differentiated and coherent vocational interests were significant predictors of pr...

  14. Performance of joint modelling of time-to-event data with time-dependent predictors: an assessment based on transition to psychosis data

    Directory of Open Access Journals (Sweden)

    Hok Pan Yuen

    2016-10-01

    Full Text Available Joint modelling has emerged to be a potential tool to analyse data with a time-to-event outcome and longitudinal measurements collected over a series of time points. Joint modelling involves the simultaneous modelling of the two components, namely the time-to-event component and the longitudinal component. The main challenges of joint modelling are the mathematical and computational complexity. Recent advances in joint modelling have seen the emergence of several software packages which have implemented some of the computational requirements to run joint models. These packages have opened the door for more routine use of joint modelling. Through simulations and real data based on transition to psychosis research, we compared joint model analysis of time-to-event outcome with the conventional Cox regression analysis. We also compared a number of packages for fitting joint models. Our results suggest that joint modelling do have advantages over conventional analysis despite its potential complexity. Our results also suggest that the results of analyses may depend on how the methodology is implemented.

  15. Predictors of mental health in female teachers.

    Science.gov (United States)

    Seibt, Reingard; Spitzer, Silvia; Druschke, Diana; Scheuch, Klaus; Hinz, Andreas

    2013-12-01

    Teaching profession is characterised by an above-average rate of psychosomatic and mental health impairment due to work-related stress. The aim of the study was to identify predictors of mental health in female teachers. A sample of 630 female teachers (average age 47 ± 7 years) participated in a screening diagnostic inventory. Mental health was surveyed with the General Health Questionnaire GHQ-12. The following parameters were measured: specific work conditions (teacher-specific occupational history), scales of the Effort-Reward-Imbalance (ERI) Questionnaire as well as cardiovascular risk factors, physical complaints (BFB) and personal factors such as inability to recover (FABA), sense of coherence (SOC) and health behaviour. First, mentally fit (MH(+)) and mentally impaired teachers (MH(-)) were differentiated based on the GHQ-12 sum score (MH(+): teachers showed evidence of mental impairment. There were no differences concerning work-related and cardiovascular risk factors as well as health behaviour between MH(+) and MH(-). Binary logistic regressions identified 4 predictors that showed a significant effect on mental health. The effort-reward-ratio proved to be the most relevant predictor, while physical complaints as well as inability to recover and sense of coherence were identified as advanced predictors (explanation of variance: 23%). Contrary to the expectations, classic work-related factors can hardly contribute to the explanation of mental health. Additionally, cardiovascular risk factors and health behaviour have no relevant influence. However, effort-reward-ratio, physical complaints and personal factors are of considerable influence on mental health in teachers. These relevant predictors should become a part of preventive arrangements for the conservation of teachers' health in the future.

  16. Predictors of mental health in female teachers

    Directory of Open Access Journals (Sweden)

    Reingard Seibt

    2013-12-01

    Full Text Available Objective: Teaching profession is characterised by an above-average rate of psychosomatic and mental health impairment due to work-related stress. The aim of the study was to identify predictors of mental health in female teachers. Material and Methods: A sample of 630 female teachers (average age 47±7 years participated in a screening diagnostic inventory. Mental health was surveyed with the General Health Questionnaire GHQ-12. The following parameters were measured: specific work conditions (teacher-specific occupational history, scales of the Effort-Reward-Imbalance (ERI Questionnaire as well as cardiovascular risk factors, physical complaints (BFB and personal factors such as inability to recover (FABA, sense of coherence (SOC and health behaviour. Results: First, mentally fit (MH+ and mentally impaired teachers (MH- were differentiated based on the GHQ-12 sum score (MH+: < 5; MH-: ≥ 5; 18% of the teachers showed evidence of mental impairment. There were no differences concerning work-related and cardiovascular risk factors as well as health behaviour between MH+ and MH-. Binary logistic regressions identified 4 predictors that showed a significant effect on mental health. The effort-reward-ratio proved to be the most relevant predictor, while physical complaints as well as inability to recover and sense of coherence were identified as advanced predictors (explanation of variance: 23%. Conclusion: Contrary to the expectations, classic work-related factors can hardly contribute to the explanation of mental health. Additionally, cardiovascular risk factors and health behaviour have no relevant influence. However, effort-reward-ratio, physical complaints and personal factors are of considerable influence on mental health in teachers. These relevant predictors should become a part of preventive arrangements for the conservation of teachers' health in the future.

  17. Prediction of SO2 pollution incidents near a power station using partially linear models and an historical matrix of predictor-response vectors

    International Nuclear Information System (INIS)

    Prada-Sanchez, J.M.; Febrero-Bande, M.; Gonzalez-Manteiga, W.; Costos-Yanez, T.; Bermudez-Cela, J.L.; Lucas-Dominguez, T.

    2000-01-01

    Atmospheric SO 2 concentrations at sampling stations near the fossil fuel fired power station at As Pontes (La Coruna, Spain) were predicted using a model for the corresponding time series consisting of a self-explicative term and a linear combination of exogenous variables. In a supplementary simulation study, models of this kind behaved better than the corresponding pure self-explicative or pure linear regression models. (Author)

  18. Survival and its predictors from age 75 to 85 in men and women belonging to cohorts with marked survival differences to age 75

    DEFF Research Database (Denmark)

    Heikkinen, E; Kauppinen, M; Schroll, M

    2016-01-01

    were observed between the groups of men, while women survived longer than men and longer in Göteborg than in Glostrup or Jyväskylä. Univariate models revealed 12 predictors of survival. In the multivariate models, the significant predictors among men related to physical fitness, whereas among women...... focusing on different domains of health, functional capacity, and physical and social activities. RESULTS: The proportion of survivors to age 75 was markedly smaller among the Finnish men and women than Danish or Swedish subjects. In the local population no marked differences in survival from age 75 to 85...

  19. Predictors of Traditional and Cyber-Bullying Victimization: A Longitudinal Study of Australian Secondary School Students.

    Science.gov (United States)

    Hemphill, Sheryl A; Tollit, Michelle; Kotevski, Aneta; Heerde, Jessica A

    2015-09-01

    The purpose of the present article is to compare the individual, peer, family, and school risk and protective factors for both traditional and cyber-bullying victimization. This article draws on data from 673 students from Victoria, Australia, to examine Grade 7 (aged 12-13 years) predictors of traditional and cyber-bullying victimization in Grade 9 (aged 14-15 years). Participants completed a modified version of the Communities That Care youth survey. There were few similarities and important differences in the predictors of traditional and cyber-bullying victimization. For Grade 9 cyber-bullying victimization, in the fully adjusted model, having been a victim of traditional bullying in Grade 7 and emotional control in Grade 7 were predictors. For Grade 9 traditional bullying victimization, predictors were Grade 7 traditional bullying victimization, association with antisocial peers, and family conflict, with family attachment and emotional control marginally statistically significant. The use of evidence-based bullying prevention programs is supported to reduce experiences of both traditional and cyber-bullying victimization, as is the implementation of programs to assist students to regulate their emotions effectively. In addition, traditional bullying victimization may be reduced by addressing association with antisocial friends, family conflict, and bonding to families. © The Author(s) 2014.

  20. Occurrence and predictors of vacuum and forceps used sequentially for vaginal birth.

    Science.gov (United States)

    Xie, Ri-Hua; Cao, Huiling; Hong, Bo; Sprague, Ann E; Walker, Mark; Wu Wen, Shi

    2013-04-01

    Sequential use of vacuum and obstetric forceps for vaginal delivery is associated with increased risks of adverse maternal and infant outcomes. We conducted a retrospective cohort study to estimate the frequency of sequential use of vacuum and forceps for planned vaginal delivery and to identify predictors, using data collected in Ontario between 2004 and 2007. Multivariate logistic regression models were used to estimate the adjusted odds ratios and 95% confidence intervals of predictors of sequential use of vacuum and forceps. Of 186 988 pregnant women with a singleton, vertex presentation at term and a planned vaginal birth, 1062 (0.57%) required the sequential use of vacuum and forceps for delivery. The major predictors for sequential use of vacuum and forceps were mother's primary language being other than English or French, nulliparity, a history of Caesarean section, dystocia, use of epidural or other pain relief, labour induction, labour augmentation, fetal macrosomia, and advanced gestational age. In this population-based study we found that 0.57% of planned vaginal births were delivered with sequential use of vacuum and obstetric forceps. Abnormal labour, fetal macrosomia, language barriers, and advanced gestational age are significant predictors of requiring this sequential use.

  1. Nutrition, Balance and Fear of Falling as Predictors of Risk for Falls among Filipino Elderly in Nursing Homes: A Structural Equation Model (SEM)

    Science.gov (United States)

    de Guzman, Allan B.; Ines, Joanna Louise C.; Inofinada, Nina Josefa A.; Ituralde, Nielson Louie J.; Janolo, John Robert E.; Jerezo, Jnyv L.; Jhun, Hyae Suk J.

    2013-01-01

    While a number of empirical studies have been conducted regarding risk for falls among the elderly, there is still a paucity of similar studies in a developing country like the Philippines. This study purports to test through Structural Equation Modeling (SEM) a model that shows the interaction between and among nutrition, balance, fear of…

  2. Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression

    OpenAIRE

    Peter Exterkate; Patrick J.F. Groenen; Christiaan Heij; Dick van Dijk

    2011-01-01

    textabstractThis paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predictive regression model is based on a shrinkage estimator to avoid overfitting. We extend the kernel ridge regression methodology to enable its use for economic time-series forecasting, by ...

  3. Pretreatment Predictors of Adverse Radiation Effects After Radiosurgery for Arteriovenous Malformation

    International Nuclear Information System (INIS)

    Hayhurst, Caroline; Monsalves, Eric; Prooijen, Monique van; Cusimano, Michael; Tsao, May; Menard, Cynthia; Kulkarni, Abhaya V.; Schwartz, Michael; Zadeh, Gelareh

    2012-01-01

    Purpose: To identify vascular and dosimetric predictors of symptomatic T2 signal change and adverse radiation effects after radiosurgery for arteriovenous malformation, in order to define and validate preexisting risk models. Methods and Materials: A total of 125 patients with arteriovenous malformations (AVM) were treated at our institution between 2005 and 2009. Eighty-five patients have at least 12 months of clinical and radiological follow-up. Any new-onset headaches, new or worsening seizures, or neurological deficit were considered adverse events. Follow-up magnetic resonance images were assessed for new onset T2 signal change and the volume calculated. Pretreatment characteristics and dosimetric variables were analyzed to identify predictors of adverse radiation effects. Results: There were 19 children and 66 adults in the study cohort, with a mean age of 34 (range 6–74). Twenty-three (27%) patients suffered adverse radiation effects (ARE), 9 patients with permanent neurological deficit (10.6%). Of these, 5 developed fixed visual field deficits. Target volume and 12 Gy volume were the most significant predictors of adverse radiation effects on univariate analysis (p 3 , above which the rate of ARE increased dramatically. Multivariate analysis target volume and the absence of prior hemorrhage are the only significant predictors of ARE. The volume of T2 signal change correlates to ARE, but only target volume is predictive of a higher volume of T2 signal change. Conclusions: Target volume and the absence of prior hemorrhage is the most accurate predictor of adverse radiation effects and complications after radiosurgery for AVMs. A high percentage of permanent visual field defects in this series suggest the optic radiation is a critical radiosensitive structure.

  4. Prevalence and predictors of poor sleep quality among secondary school students in Gombak District, Selangor.

    Science.gov (United States)

    Kesintha, A; Rampal, L; Sherina, M S; Kalaiselvam, T

    2018-02-01

    Poor sleep quality among adolescents is becoming a major worldwide concern and is widely recognized as a significant public health issue. To determine the prevalence and predictors of poor sleep quality among secondary school students in Gombak District, Selangor. A cross-sectional study was conducted in Gombak District. The sample size was 1,092 based on two group comparison formula. Students were selected using sampling with probability to proportionate to size. Selfadministered pretested questionnaires were used to collect the data. The data were analysed using the Statistical Package for Social Sciences (SPSS) version 22. Chi-square or Fisher's exact test was performed to determine the association between individual categorical variables and sleep quality. Variables with p-value sleep quality was 24.0% (95% CI = 21.5, 26.6). Based on the analysis of simple logistic regression seven variables that were significantly associated with poor sleep quality were age, gender, marital status of parents, depression, anxiety, stress and academic performance found fit in the model. Multivariate logistic analysis showed that the significant predictors of poor sleep quality were age, marital status of parents, depression, anxiety, stress and academic performance. Factors that were not statistically significant were gender, religion, ethnicity, parent's educational level and family income. Prevalence of poor sleep quality among adolescents is high. The predictors of poor sleep quality are age, marital status of parents, depression, anxiety, stress and academic performance.

  5. Interventions preventing ankle sprains; previous injury and high-risk sport participation as predictors of compliance.

    Science.gov (United States)

    Janssen, Kasper W; van der Zwaard, Babette C; Finch, Caroline F; van Mechelen, Willem; Verhagen, Evert A L M

    2016-06-01

    To describe the association between participants' person-related potential predictor variables and cumulative compliance with interventions for preventing ankle sprains: neuromuscular training, wearing an ankle brace, and a combined training and bracing. Secondary analysis of compliance data from a randomized controlled trial (RCT) comparing measures preventing ankle ligament injuries. Ordinal regression with a backward selection method was used to obtain a descriptive statistical model linking participants' person-related potential predictor variables with the monthly cumulative compliance measurements for three interventions preventing ankle ligament injuries. Having had a previous ankle injury was significantly associated with a higher compliance with all of the preventive measures trialed. Overall compliance with bracing and the combined intervention was significantly lower than the compliance with NM training. Per group analysis found that participating in a high-risk sport, like soccer, basketball, and volleyball, was significantly associated with a higher compliance with bracing, or a combined bracing and NM training. In contrast, participating in a high-risk sport was significantly associated with a lower per group compliance with NM training. Future studies should include at least registration of previous ankle sprains, sport participation (high- or low-risk), experience in NM training, and hours of sport exposure as possible predictors of compliance with interventions preventing ankle sprains. Practitioners should take into account these variables when prescribing preventive neuromuscular training or bracing. Copyright © 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  6. Predictors of successful cancer prevention programs.

    Science.gov (United States)

    Porzsolt, Franz; Kirner, Anita; Kaplan, Robert M

    2009-01-01

    Finding the optimal use of health-care resources requires the reliable estimation of costs and consequences. Acquiring these estimates may not be difficult for some common treatments. More difficult is the optimization of resources in the area of diagnostics. Only a few attempts have been made to optimize the use of resources in the area of prevention. Several aspects have to be considered when optimizing the resources for prevention: (1) participation rates in structured prevention programs are low, (2), acquiring data on follow-up and outcomes is difficult, (3) there are concerns about the quality of information available to public, and (4), the public is often unaware of scientific assessments of prevention programs. As prevention programs are costly long-term projects, a strategy to select these programs according to possible predictors of success might be useful. The few analyses of cancer prevention in the literature have been directed towards the most common malignant diseases (as assessed by incidence) such as cancer of the breast, colon, lung and prostate. We argue that incidence is a poor marker for selecting secondary prevention programs. Incidence may be a misleading indicator for two reasons: incidence of disease does not predict efficiency of management or good health outcomes, and incidence does not separate clinically significant from non-significant disease. The traditional strategy is based on the assumption that more screening increases the chance of cure. We propose an alternative outcomes model that suggests better disease management justifies new prevention programs. Indicators for better disease management are effective and efficient treatments as well as high-quality screening (sensitivity and specificity) techniques and possibly "side-effects of prevention programs," which provide early signs of success to motivate the patient's participation, to keep up with the program and finally to succeed.

  7. Predictors of treatment failure for pneumatic retinopexy.

    Science.gov (United States)

    Rootman, Dan B; Luu, Shelly; M Conti, Stephen; Mandell, Mark; Devenyi, Robert; Lam, Wai-Ching; Kertes, Peter J

    2013-12-01

    The purpose of this study was to define the overall anatomic success rate in pneumatic retinopexy and to identify morphologic features that may be predictive of treatment failure in pneumatic retinopexy. Prospective consecutive interventional case series of patients with new-onset primary rhegmatogenous retinal detachments treated with pneumatic retinopexy. In this interventional case series, consecutive patients with new-onset primary rhegmatogenous retinal detachments were treated with pneumatic retinopexy and followed prospectively. Morphologic data were collected on 3-colour fundus drawings. The primary outcome measure was treatment failure, defined as requirement for scleral buckle or vitrectomy within the follow-up period. Rates of failure for each morphologic feature were compared and a logistic regression model was fit. A total of 113 eyes were included in the study. Anatomic success was achieved in 69.6% of patients. Morphologic criteria including the position and number of breaks, position and extent of lattice degeneration, size of the detached area, and macular status were all found not to be significantly related to failure. In multivariate analysis, only 3 predictors, pseudophakic status (p < 0.05, odds ratio [OR] 2.9, 95% CI, 1.06-7.88), presence of retinal break greater than 1 clock-hour (p < 0.05, OR 3.41, 1.06-11.02), and presence of grade C or D proliferative vitreoretinopathy (PVR) (p < 0.01, OR 31.83, 95% CI, 3.59-282.24), gained statistical significance. Only pseudophakia, a large retinal break, and/or PVR was associated with an increased likelihood of failure. Copyright © 2013 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

  8. Temperature response of the cell cycle of Haplopappus gracilis in suspension culture and its significance to the G1 transition probability model.

    Science.gov (United States)

    Gould, A R

    1977-01-01

    The effects of temperature on the cell cycle of Haplopappus gracilis suspension cultures were analysed by the fraction of labelled mitoses method. Sphase in these cultures shows a different temperature optimum as compared to optima derived for G2 and mitosis. G1 phase has a much lower Q10 than the other cell cycle phases and shows no temperature optimum between 22 and 34° C. These results are discussed in relation to a transition probability model of the cell cycle proposed by Smith and Martin (Proc. Natl. Acad. Sci. USA 70, 1263-1267, 1973), in which each cell has a time independent probability of initiating the transition into another round of DNA replication and division. The implications of such a model for cell cycle analysis are discussed and a tentative model for a probabilistic transition trigger is advanced.

  9. Evaluation and clinical significance of the stomach age model for evaluating aging of the stomach-a multicenter study in China

    Science.gov (United States)

    2014-01-01

    Background A higher prevalence of chronic atrophic gastritis (CAG) occurs in younger adults in Asia. We used Stomach Age to examine the different mechanisms of CAG between younger adults and elderly individuals, and established a simple model of cancer risk that can be applied to CAG surveillance. Methods Stomach Age was determined by FISH examination of telomere length in stomach biopsies. Δψm was also determined by flow cytometry. Sixty volunteers were used to confirm the linear relationship between telomere length and age while 120 subjects were used to build a mathematical model by a multivariate analysis. Overall, 146 subjects were used to evaluate the validity of the model, and 1,007 subjects were used to evaluate the relationship between prognosis and Δage (calculated from the mathematical model). ROC curves were used to evaluate the relationship between prognosis and Δage and to determine the cut-off point for Δage. Results We established that a tight linear relationship between the telomere length and the age. The telomere length was obvious different between patients with and without CAG even in the same age. Δψm decreased in individuals whose Stomach Age was greater than real age, especially in younger adults. A mathematical model of Stomach Age (real age + Δage) was successfully constructed which was easy to apply in clinical work. A higher Δage was correlated with a worse outcome. The criterion of Δage >3.11 should be considered as the cut-off to select the subgroup of patients who require endoscopic surveillance. Conclusion Variation in Stomach Age between individuals of the same biological age was confirmed. Attention should be paid to those with a greater Stomach Age, especially in younger adults. The Δage in the Simple Model can be used as a criterion to select CAG patients for gastric cancer surveillance. PMID:25057261

  10. Predictors of condom use behaviour among male street labourers in urban Vietnam using a modified Information-Motivation-Behavioral Skills (IMB) model.

    Science.gov (United States)

    Van Huy, Nguyen; P Dunne, Michael; Debattista, Joseph

    2016-01-01

    HIV risk in vulnerable groups such as itinerant male street labourers is often examined via a focus on individual determinants. This study provides a test of a modified Information-Motivation-Behavioral Skills (IMB) model to predict condom use behaviour among male street workers in urban Vietnam. In a cross-sectional survey using a social mapping technique, 450 male street labourers from 13 districts of Hanoi, Vietnam were recruited and interviewed. Collected data were first examined for completeness; structural equation modelling was then employed to test the model fit. Condoms were used inconsistently by many of these men, and usage varied in relation to a number of factors. A modified IMB model had a better fit than the original IMB model in predicting condom use behaviour. This modified model accounted for 49% of the variance, versus 10% by the original version. In the modified model, the influence of psychosocial factors was moderately high, whilst the influence of HIV prevention information, motivation and perceived behavioural skills was moderately low, explaining in part the limited level of condom use behaviour. This study provides insights into social factors that should be taken into account in public health planning to promote safer sexual behaviour among Asian male street labourers.

  11. A longitudinal study of children’s outside play using family environment and perceived physical environment as predictors

    Science.gov (United States)

    2014-01-01

    Background A natural and cheap way of increasing children’s physical activity is stimulating unstructured outside play. Purpose This study examined whether characteristics of the family and perceived physical environment were associated with the duration of children’s outside play. Methods Parents participating in the “Be Active, Eat Right” cluster RCT control group (N = 2007) provided information on potential predictors of outside play (i.e. family and perceived physical environment) of their 5-year-old child by questionnaire. Child outside play was assessed by parental reports both at five and seven years. Linear regression analyses, adjusted for seasonality, were performed to evaluate associations between potential predictors and child outside play. Linear mixed models were fitted to evaluate the relationship between potential predictors and the development of outside play over two years, with season entered as a random factor. Results Family environment was the strongest construct predicting child outside play, while parent perceived physical environment had no significant association with child outside play. Parental habit strength and the presence of rules were the strongest predictors of increased outside play. Parent perceived difficulty in improving child outside play was the strongest predictor of decreased outside play. Conclusion Family environment predicted child outside play and not perceived physical environment. Parental rules and habit strength regarding improving outside play were associated with an improvement of child’s engagement in outside play. PMID:24934086

  12. Calculation of limits for significant unidirectional changes in two or more serial results of a biomarker based on a computer simulation model

    DEFF Research Database (Denmark)

    Lund, Flemming; Petersen, Per Hyltoft; Fraser, Callum G

    2015-01-01

    BACKGROUND: Reference change values (RCVs) were introduced more than 30 years ago and provide objective tools for assessment of the significance of differences in two consecutive results from an individual. However, in practice, more results are usually available for monitoring, and using the RCV...... the presented factors. The first result is multiplied by the appropriate factor for increase or decrease, which gives the limits for a significant difference.......BACKGROUND: Reference change values (RCVs) were introduced more than 30 years ago and provide objective tools for assessment of the significance of differences in two consecutive results from an individual. However, in practice, more results are usually available for monitoring, and using the RCV......,000 simulated data from healthy individuals, a series of up to 20 results from an individual was generated using different values for the within-subject biological variation plus the analytical variation. Each new result in this series was compared to the initial measurement result. These successive serial...

  13. High-Order Sparse Linear Predictors for Audio Processing

    DEFF Research Database (Denmark)

    Giacobello, Daniele; van Waterschoot, Toon; Christensen, Mads Græsbøll

    2010-01-01

    Linear prediction has generally failed to make a breakthrough in audio processing, as it has done in speech processing. This is mostly due to its poor modeling performance, since an audio signal is usually an ensemble of different sources. Nevertheless, linear prediction comes with a whole set...... of interesting features that make the idea of using it in audio processing not far fetched, e.g., the strong ability of modeling the spectral peaks that play a dominant role in perception. In this paper, we provide some preliminary conjectures and experiments on the use of high-order sparse linear predictors...... in audio processing. These predictors, successfully implemented in modeling the short-term and long-term redundancies present in speech signals, will be used to model tonal audio signals, both monophonic and polyphonic. We will show how the sparse predictors are able to model efficiently the different...

  14. Radiation response and cure rate of human colon adenocarcinoma spheroids of different size: the significance of hypoxia on tumor control modelling.

    Science.gov (United States)

    Buffa, F M; West, C; Byrne, K; Moore, J V; Nahum, A E

    2001-03-15

    To evaluate the adequacy of a Poisson tumor control probability (tcp) model and the impact of hypoxia on tumor cure. A human colon adenocarcinoma cell line, WiDr, was grown as multicellular spheroids of different diameters. Measurements were made of cell survival and spheroid cure following 300-kV X-ray external beam irradiation in air and nitrogen. Cell survival data were fitted using a two-compartment and an oxygen diffusion model. Spheroid cure data were fitted using the tcp model. Hypoxia was seen only for spheroids greater than 500 microm in diameter. For small spheroids tcp estimates of radiosensitivity and clonogenic number showed excellent agreement with experimentally derived values. For large spheroids, although tcp estimates of radiosensitivity were comparable with measurements, estimates of the clonogenic number were considerably lower than the experimental count. Reoxygenation of large spheroids before irradiation resulted in the tcp estimates of the number of clonogenic cells agreeing with measured values. When hypoxia was absent, the tcp model accurately predicted cure from measured radiosensitivity and clonogen number. When hypoxia was present, the number of cells capable of regrowth in situ was considerably lower than the number of clonogenic cells that initially survived irradiation. As this counteracted the decreased radiosensitivity, hypoxia was less important for cure than predicted from cell survival assays. This finding suggests that chronic hypoxia may not limit directly the success of radiation therapy.

  15. Significance of Cultural-Historical Theory of Psychological Development of L.S. Vygotsky for the Development of Modern Models of Social Cognition and Psychotherapy

    Directory of Open Access Journals (Sweden)

    Kholmogorova A.B.,

    2016-12-01

    Full Text Available The article acknowledges the situation of methodical crisis in modern research of social cognition related to the domination of reductive approaches that ignore the uniqueness of human psyche. Heuristicity of concepts of cultural-historical theory of psychological development of L.S. Vygotsky, which serves to overcome the apparent inconsistencies is substantiated. Models of social cognition based on the principles of cultural-historical psychology are described, those being the model of social cognition within phylogenesis of M. Tomasello, and the model of social cognition within ontogenesis of C. Fernyhough. Current situation in the area of mental health is reviewed from the standpoint of cultural-historical psychology, its specifics reflected in the increased burden on reflexive functions, that is, skills lying within the sphere of social cognition is substantiated. Modern psychotherapeutic apparatus directed to compensate social cognition deficits due to various psychiatric disorders is reviewed. The assumption that adolescense is sensitive period for the development of higher forms of social cognition is made, and a summary of researches supporting this assertion is presented. Main contradictions of modern-day maturing are enunciated. To conclude the presented theoretical analysis, a comprehensive multiple-factor model of social cognition is presented based on concepts of cultural-historical theory of L.S. Vygotsky.

  16. Predictors of hope among women with breast cancer during chemotherapy

    Directory of Open Access Journals (Sweden)

    Alessandra Cristina Sartore Balsanelli

    Full Text Available Abstract OBJECTIVE Identifying the predictors of hope in patients with breast cancer during chemotherapy treatment. METHOD A prospective longitudinal study. The sample was composed of 122 women who responded to the instruments of hope, anxiety and depression, coping, fatigue, religiosity and self-esteem in the first and last cycle of chemotherapy. These variables were used in adjusting the logistic regression model that characterized multivariate statistics, allowing identification of predictor variables. RESULT The increase of hope at the end of chemotherapy treatment was statistically significant (p = 0.012. The delay in undergoing treatment from the onset of breast cancer symptoms, Karnofsky Performance Status, depression, self-esteem and pain were characterized as factors being associated to hope by univariate analysis. Among the variables analyzed, pain was the only predicting factor of hope. CONCLUSION Pain was the predicting factor in this sample. Hope increased during treatment and revealed the following associated factors: Karnofsky Performance Status, delay in starting the treatment, depression, self-esteem and pain. This study brought forth a multidisciplinary contribution, allowing for understanding the factors that can influence hope and presenting support to nursing care. The data evidenced conditions of improvement or worsening of hope, which requires interdisciplinary attention in Oncology.

  17. Predictors of psychological resilience amongst medical students following major earthquakes.

    Science.gov (United States)

    Carter, Frances; Bell, Caroline; Ali, Anthony; McKenzie, Janice; Boden, Joseph M; Wilkinson, Timothy; Bell, Caroline

    2016-05-06

    To identify predictors of self-reported psychological resilience amongst medical students following major earthquakes in Canterbury in 2010 and 2011. Two hundred and fifty-three medical students from the Christchurch campus, University of Otago, were invited to participate in an electronic survey seven months following the most severe earthquake. Students completed the Connor-Davidson Resilience Scale, the Depression, Anxiety and Stress Scale, the Post-traumatic Disorder Checklist, the Work and Adjustment Scale, and the Eysenck Personality Questionnaire. Likert scales and other questions were also used to assess a range of variables including demographic and historical variables (eg, self-rated resilience prior to the earthquakes), plus the impacts of the earthquakes. The response rate was 78%. Univariate analyses identified multiple variables that were significantly associated with higher resilience. Multiple linear regression analyses produced a fitted model that was able to explain 35% of the variance in resilience scores. The best predictors of higher resilience were: retrospectively-rated personality prior to the earthquakes (higher extroversion and lower neuroticism); higher self-rated resilience prior to the earthquakes; not being exposed to the most severe earthquake; and less psychological distress following the earthquakes. Psychological resilience amongst medical students following major earthquakes was able to be predicted to a moderate extent.

  18. MetAmyl: a METa-predictor for AMYLoid proteins.

    Directory of Open Access Journals (Sweden)

    Mathieu Emily

    Full Text Available The aggregation of proteins or peptides in amyloid fibrils is associated with a number of clinical disorders, including Alzheimer's, Huntington's and prion diseases, medullary thyroid cancer, renal and cardiac amyloidosis. Despite extensive studies, the molecular mechanisms underlying the initiation of fibril formation remain largely unknown. Several lines of evidence revealed that short amino-acid segments (hot spots, located in amyloid precursor proteins act as seeds for fibril elongation. Therefore, hot spots are potential targets for diagnostic/therapeutic applications, and a current challenge in bioinformatics is the development of methods to accurately predict hot spots from protein sequences. In this paper, we combined existing methods into a meta-predictor for hot spots prediction, called MetAmyl for METapredictor for AMYLoid proteins. MetAmyl is based on a logistic regression model that aims at weighting predictions from a set of popular algorithms, statistically selected as being the most informative and complementary predictors. We evaluated the performances of MetAmyl through a large scale comparative study based on three independent datasets and thus demonstrated its ability to differentiate between amyloidogenic and non-amyloidogenic polypeptides. Compared to 9 other methods, MetAmyl provides significant improvement in prediction on studied datasets. We further show that MetAmyl is efficient to highlight the effect of point mutations involved in human amyloidosis, so we suggest this program should be a useful complementary tool for the diagnosis of these diseases.

  19. Detecting Novelty and Significance

    Science.gov (United States)

    Ferrari, Vera; Bradley, Margaret M.; Codispoti, Maurizio; Lang, Peter J.

    2013-01-01

    Studies of cognition often use an “oddball” paradigm to study effects of stimulus novelty and significance on information processing. However, an oddball tends to be perceptually more novel than the standard, repeated stimulus as well as more relevant to the ongoing task, making it difficult to disentangle effects due to perceptual novelty and stimulus significance. In the current study, effects of perceptual novelty and significance on ERPs were assessed in a passive viewing context by presenting repeated and novel pictures (natural scenes) that either signaled significant information regarding the current context or not. A fronto-central N2 component was primarily affected by perceptual novelty, whereas a centro-parietal P3 component was modulated by both stimulus significance and novelty. The data support an interpretation that the N2 reflects perceptual fluency and is attenuated when a current stimulus matches an active memory representation and that the amplitude of the P3 reflects stimulus meaning and significance. PMID:19400680

  20. Significant NRC Enforcement Actions

    Data.gov (United States)

    Nuclear Regulatory Commission — This dataset provides a list of Nuclear Regulartory Commission (NRC) issued significant enforcement actions. These actions, referred to as "escalated", are issued by...

  1. Estimating overweight risk in childhood from predictors during infancy.

    Science.gov (United States)

    Weng, Stephen F; Redsell, Sarah A; Nathan, Dilip; Swift, Judy A; Yang, Min; Glazebrook, Cris

    2013-08-01

    The aim of this study was to develop and validate a risk score algorithm for childhood overweight based on a prediction model in infants. Analysis was conducted by using the UK Millennium Cohort Study. The cohort was divided randomly by using 80% of the sample for derivation of the risk algorithm and 20% of the sample for validation. Stepwise logistic regression determined a prediction model for childhood overweight at 3 years defined by the International Obesity Task Force criteria. Predictive metrics R(2), area under the receiver operating curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Seven predictors were found to be significantly associated with overweight at 3 years in a mutually adjusted predictor model: gender, birth weight, weight gain, maternal prepregnancy BMI, paternal BMI, maternal smoking in pregnancy, and breastfeeding status. Risk scores ranged from 0 to 59 corresponding to a predicted risk from 4.1% to 73.8%. The model revealed moderately good predictive ability in both the derivation cohort (R(2) = 0.92, AUROC = 0.721, sensitivity = 0.699, specificity = 0.679, PPV = 38%, NPV = 87%) and validation cohort (R(2) = 0.84, AUROC = 0.755, sensitivity = 0.769, specificity = 0.665, PPV = 37%, NPV = 89%). Using a prediction algorithm to identify at-risk infants could reduce levels of child overweight and obesity by enabling health professionals to target prevention more effectively. Further research needs to evaluate the clinical validity, feasibility, and acceptability of communicating this risk.

  2. Sociodemographic and career history predictors of suicide mortality in the United States Army 2004–2009

    Science.gov (United States)

    Gilman, S. E.; Bromet, E. J.; Cox, K. L.; Colpe, L. J.; Fullerton, C. S.; Gruber, M. J.; Heeringa, S.G.; Lewandowski-Romps, L.; Millikan-Bell, A.M.; Naifeh, J. A.; Nock, M. K.; Petukhova, M. V.; Sampson, N. A.; Schoenbaum, M.; Stein, M. B.; Ursano, R. J.; Wessely, S.; Zaslavsky, A.M.; Kessler, R. C.

    2014-01-01

    Background The US Army suicide rate has increased sharply in recent years. Identifying significant predictors of Army suicides in Army and Department of Defense (DoD) administrative records might help focus prevention efforts and guide intervention content. Previous studies of administrative data, although documenting significant predictors, were based on limited samples and models. A career history perspective is used here to develop more textured models. Method The analysis was carried out as part of the Historical Administrative Data Study (HADS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). De-identified data were combined across numerous Army and DoD administrative data systems for all Regular Army soldiers on active duty in 2004–2009. Multivariate associations of sociodemographics and Army career variables with suicide were examined in subgroups defined by time in service, rank and deployment history. Results Several novel results were found that could have intervention implications. The most notable of these were significantly elevated suicide rates (69.6–80.0 suicides per 100000 person-years compared with 18.5 suicides per 100000 person-years in the total Army) among enlisted soldiers deployed either during their first year of service or with less than expected (based on time in service) junior enlisted rank; a substantially greater rise in suicide among women than men during deployment; and a protective effect of marriage against suicide only during deployment. Conclusions A career history approach produces several actionable insights missed in less textured analyses of administrative data predictors. Expansion of analyses to a richer set of predictors might help refine understanding of intervention implications. PMID:25055175

  3. Sociodemographic and career history predictors of suicide mortality in the United States Army 2004-2009.

    Science.gov (United States)

    Gilman, S E; Bromet, E J; Cox, K L; Colpe, L J; Fullerton, C S; Gruber, M J; Heeringa, S G; Lewandowski-Romps, L; Millikan-Bell, A M; Naifeh, J A; Nock, M K; Petukhova, M V; Sampson, N A; Schoenbaum, M; Stein, M B; Ursano, R J; Wessely, S; Zaslavsky, A M; Kessler, R C

    2014-09-01

    The US Army suicide rate has increased sharply in recent years. Identifying significant predictors of Army suicides in Army and Department of Defense (DoD) administrative records might help focus prevention efforts and guide intervention content. Previous studies of administrative data, although documenting significant predictors, were based on limited samples and models. A career history perspective is used here to develop more textured models. The analysis was carried out as part of the Historical Administrative Data Study (HADS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). De-identified data were combined across numerous Army and DoD administrative data systems for all Regular Army soldiers on active duty in 2004-2009. Multivariate associations of sociodemographics and Army career variables with suicide were examined in subgroups defined by time in service, rank and deployment history. Several novel results were found that could have intervention implications. The most notable of these were significantly elevated suicide rates (69.6-80.0 suicides per 100 000 person-years compared with 18.5 suicides per 100 000 person-years in the total Army) among enlisted soldiers deployed either during their first year of service or with less than expected (based on time in service) junior enlisted rank; a substantially greater rise in suicide among women than men during deployment; and a protective effect of marriage against suicide only during deployment. A career history approach produces several actionable insights missed in less textured analyses of administrative data predictors. Expansion of analyses to a richer set of predictors might help refine understanding of intervention implications.

  4. Fusion protein comprised of the two schistosomal antigens, Sm14 and Sm29, provides significant protection against Schistosoma mansoni in murine infection model

    OpenAIRE

    Mossallam, Shereen F; Amer, Eglal I; Ewaisha, Radwa E; Khalil, Amal M; Aboushleib, Hamida M; Bahey-El-Din, Mohammed

    2015-01-01

    Background Schistosoma mansoni infection represents a major cause of morbidity and mortality in many areas of the developing world. Effective vaccines against schistosomiasis are not available and disease management relies mainly on treatment with the anthelmintic drug praziquantel. Several promising schistosomal antigens have been evaluated for vaccine efficacy such as Sm14, Sm29 and tetraspanins. However, most investigators examine these promising antigens in animal models individually rath...

  5. [Predictors of Family Dysfunction among Adolescent Students].

    Science.gov (United States)

    Gómez-Bustamante, Edna Margarita; Castillo-Ávila, Irma; Cogollo, Zuleima

    2013-03-01

    Determination of family dysfunction predictors in adolescent students of Cartagena, Colombia. A cross-sectional analytical research was conducted by means of a probabilistic sample per conglomerate of high-school students. Participation of students between 13 and 17 years was requested. Family dysfunction was identified through the family APGAR scale. Predictors were adjusted by binary logistic regression. A total of 1,730 students agreed to participate, mean age was 14.7 years (SD=1.2), and 52.7% were girls. The family APGAR scale showed a Cronbach alpha of 0.78. A group of 896 students (51.8%) reported family dysfunction. Predictors of family dysfunction were: clinically significant depressive symptoms (OR=3.61; IC 95%: 2.31-5.63), low religiosity (OR=1.73; CI 95%: 1.41-2.13), non-nuclear family (OR=1.71, CI 95% 1.71-2.09) (OR=1.73, 95% CI 1.41-2.13), non-nuclear family (OR=1.71, 95%: CI 1.41-2.09), consumption of any illegal substance in their lives (OR=1.67, CI 95%: 1.15-2.13), residents of depressed neighborhoods (OR = 1.49; CI 95%: 1.19-1.87), and poor academic performance (OR=1.43; CI 95%: 1.15-1.76). Clinically significant depressive symptoms, low religiosity and non-nuclear family are the main predictors of family dysfunction among adolescent students in Cartagena, Colombia. The association is possibly bidirectional. Copyright © 2013 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

  6. Dosimetric Significance of the ICRP's Updated Guidance and Models, 1989-2003, and Implications for U.S. Federal Guidance

    Energy Technology Data Exchange (ETDEWEB)

    Leggett, R.W.

    2003-09-10

    Over the past two decades the U.S. Environmental Protection Agency (EPA) has issued a series of Federal guidance documents for the purpose of providing the Federal and State agencies with technical information to assist their implementation of radiation protection programs. Currently recommended dose conversion factors, annual limits on intake, and derived air concentrations for intake of radionuclides are tabulated in Federal Guidance Report No. 11 (FGR 11), published in 1988. The tabulations in FGR 11 were based on dosimetric quantities and biokinetic and dosimetric models of the International Commission on Radiological Protection (ICRP) developed for application to occupational exposures. Since the publication of FGR 11 the ICRP has revised some of its dosimetric quantities and its models for workers and has also developed age-specific models and dose conversion factors for intake of radionuclides by members of the public. This report examines the extent of the changes in the inhalation and ingestion dose coefficients of FGR 11 implied by the updated recommendations of the ICRP, both for workers and members of the public.

  7. Review: Are we stumbling in our quest to find the best predictor? Over-optimism in sensor-based models for predicting falls in older adults.

    Science.gov (United States)

    Shany, Tal; Wang, Kejia; Liu, Ying; Lovell, Nigel H; Redmond, Stephen J

    2015-08-01

    The field of fall risk testing using wearable sensors is bustling with activity. In this Letter, the authors review publications which incorporated features extracted from sensor signals into statistical models intended to estimate fall risk or predict falls in older people. A review of these studies raises concerns that this body of literature is presenting over-optimistic results in light of small sample sizes, questionable modelling decisions and problematic validation methodologies (e.g. inherent problems with the overly-popular cross-validation technique, lack of external validation). There seem to be substantial issues in the feature selection process, whereby researchers select features before modelling begins based on their relation to the target, and either perform no validation or test the models on the same data used for their training. This, together with potential issues related to the large number of features and their correlations, inevitably leads to models with inflated accuracy that are unlikely to maintain their reported performance during everyday use in relevant populations. Indeed, the availability of rich sensor data and many analytical options provides intellectual and creative freedom for researchers, but should be treated with caution, and such pitfalls must be avoided if we desire to create generalisable prognostic tools of any clinical value.

  8. Multi-tissue DNA methylation age predictor in mouse.

    Science.gov (United States)

    Stubbs, Thomas M; Bonder, Marc Jan; Stark, Anne-Katrien; Krueger, Felix; von Meyenn, Ferdinand; Stegle, Oliver; Reik, Wolf

    2017-04-11

    DNA methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing process. It has also not been shown whether this epigenetic clock is unique to humans or conserved in the more experimentally tractable mouse. We have generated a comprehensive set of genome-scale base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. Many CpG sites show significant tissue-independent correlations with age which allowed us to develop a multi-tissue predictor of age in the mouse. Our model, which estimates age based on DNA methylation at 329 unique CpG sites, has a median absolute error of 3.33 weeks and has similar properties to the recently described human epigenetic clock. Using publicly available datasets, we find that the mouse clock is accurate enough to measure effects on biological age, including in the context of interventions. While females and males show no significant differences in predicted DNA methylation age, ovariectomy results in significant age acceleration in females. Furthermore, we identify significant differences in age-acceleration dependent on the lipid content of the diet. Here we identify and characterise an epigenetic predictor of age in mice, the mouse epigenetic clock. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ticking rate and resetting the clock in vivo to study the impact on biological age.

  9. Predictors and outcomes of patient safety culture in hospitals.

    Science.gov (United States)

    El-Jardali, Fadi; Dimassi, Hani; Jamal, Diana; Jaafar, Maha; Hemadeh, Nour

    2011-02-24

    Developing a patient safety culture was one of the recommendations made by the Institute of Medicine to assist hospitals in improving patient safety. In recent years, a multitude of evidence, mostly originating from developed countries, has been published on patient safety culture. One of the first efforts to assess the culture of safety in the Eastern Mediterranean Region was by El-Jardali et al. (2010) in Lebanon. The study entitled "The Current State of Patient Safety Culture: a study at baseline" assessed the culture of safety in Lebanese hospitals. Based on study findings, the objective of this paper is to explore the association between patient safety culture predictors and outcomes, taking into consideration respondent and hospital characteristics. In addition, it will examine the correlation between patient safety culture composites. Sixty-eight hospitals and 6,807 respondents participated in the study. The study which adopted a cross sectional research design utilized an Arabic-translated version of the Hospital Survey on Patient Safety Culture (HSOPSC). The HSOPSC measures 12 patient safety composites. Two of the composites, in addition to a patient safety grade and the number of events reported, represented the four outcome variables. Bivariate and mixed model regression analyses were used to examine the association between the patient safety culture predictors and outcomes. Significant correlations were observed among all patient safety culture composites but with differences in the strength of the correlation. Generalized Estimating Equations for the patient safety composite scores and respondent and hospital characteristics against the patient safety grade and the number of events reported revealed significant correlations. Significant correlations were also observed by linear mixed models of the same variables against the frequency of events reported and the overall perception of safety. Event reporting, communication, patient safety leadership and

  10. Predictors of Better Self-Care in Patients with Heart Failure after Six Months of Follow-Up Home Visits

    Science.gov (United States)

    Trojahn, Melina Maria; Ruschel, Karen Brasil; Nogueira de Souza, Emiliane; Mussi, Cláudia Motta; Naomi Hirakata, Vânia; Nogueira Mello Lopes, Alexandra; Rabelo-Silva, Eneida Rejane

    2013-01-01

    This study aimed to examine the predictors of better self-care behavior in patients with heart failure (HF) in a home visiting program. This is a longitudinal study nested in a randomized controlled trial (ISRCTN01213862) in which the home-based educational intervention consisted of a six-month followup that included four home visits by a nurse, interspersed with four telephone calls. The self-care score was measured at baseline and at six months using the Brazilian version of the European Heart Failure Self-Care Behaviour Scale. The associations included eight variables: age, sex, schooling, having received the intervention, social support, income, comorbidities, and symptom severity. A simple linear regression model was developed using significant variables (P ≤ 0.20), followed by a multivariate model to determine the predictors of better self-care. One hundred eighty-eight patients completed the study. A better self-care behavior was associated with patients who received intervention (P < 0.001), had more years of schooling (P = 0.016), and had more comorbidities (P = 0.008). Having received the intervention (P < 0.001) and having a greater number of comorbidities (P = 0.038) were predictors of better self-care. In the multivariate regression model, being in the intervention group and having more comorbidities were a predictor of better self-care. PMID:24083023

  11. Predictors of Smartphone Uses for Health Information Seeking in the Korean Elderly.

    Science.gov (United States)

    Oh, Young Sam; Choi, Eun Young; Kim, Young Sun

    2018-01-01

    The purpose of this research is to examine the predictors of smartphone uses for health information-seeking (SHIS) in the Korean elderly. This research applies the comprehensive model of information seeking as a theoretical framework. Data reported in this study are from the 2016 Dementia Literacy Survey, and 235 elderly smartphone users were included in logistic regression model. SHIS was significantly predicted by younger age, higher education levels, having a regular exercise, higher medical expenditures, and health literacy. The findings of this study can help social workers understand the specific features of health information seeking in the Korean elderly.

  12. Gender and distance influence performance predictors in young swimmers

    Directory of Open Access Journals (Sweden)

    Paulo Victor Mezzaroba

    2013-12-01

    Full Text Available Predictors of performance in adult swimmers are constantly changing during youth especially because the training routine begins even before puberty in the modality. Therefore this study aimed to determine the group of parameters that best predict short and middle swimming distance performances of young swimmers of both genders. Thirty-three 10-to 16-years-old male and female competitive swimmers participated in the study. Multiple linear regression (MLR was used considering mean speed of maximum 100, 200 and 400 m efforts as dependent variables, and five parameters groups as possible predictors (anthropometry, body composition, physiological and biomechanical parameters, chronological age/pubic hair. The main results revealed explanatory powers of almost 100% for both genders and all performances, but with different predictors entered in MLR models of each parameter group or all variables. Thus, there are considerable differences in short and middle swimming distance, and males and females predictors that should be considered in training programs.

  13. Hypoxaemia in Mozambican children <5 years of age admitted to hospital with clinical severe pneumonia: clinical features and performance of predictor models.

    Science.gov (United States)

    Bassat, Quique; Lanaspa, Miguel; Machevo, Sónia; O'Callaghan-Gordo, Cristina; Madrid, Lola; Nhampossa, Tacilta; Acácio, Sozinho; Roca, Anna; Alonso, Pedro L

    2016-09-01

    To determine the prevalence of hypoxaemia among under-five children admitted to hospital with clinical severe pneumonia and to assess the performance to diagnose hypoxaemia of models based on clinical signs. We conducted a hospital-based survey in a district hospital from Southern Mozambique. A total of 825 children were recruited after obtaining an informed consent. The prevalence of hypoxaemia on admission was 27.9%, and 19.8% of these children died (OR compared with non-hypoxaemic children 3.22, 95% CI 1.98-5.21, P < 0.001). The model with larger area under the ROC curve (AUC-ROC) to predict hypoxaemia included cyanosis or thoracoabdominal breathing or respiratory rate ≥70 breaths per minute. None of the models performed well when tested in different case scenarios of oxygen availability through mathematical modelling, with over 50% of hypoxaemic children not receiving oxygen even in favourable case scenarios. Clinical signs alone or in combination are not suitable to diagnose hypoxaemia. The use of pulse oximeters should be strongly encouraged. © 2016 John Wiley & Sons Ltd.

  14. Social Support and Motivation to Transfer as Predictors of Training Transfer: Testing Full and Partial Mediation Using Meta-Analytic Structural Equation Modelling

    Science.gov (United States)

    Reinhold, Sarah; Gegenfurtner, Andreas; Lewalter, Doris

    2018-01-01

    Social support and motivation to transfer are important components in conceptual models on transfer of training. Previous research indicates that both support and motivation influence transfer. To date, however, it is not yet clear if social support influences transfer of training directly, or if this influence is mediated by motivation to…

  15. Predictors of Depression Treatment Response in an Intensive CBT Partial Hospital.

    Science.gov (United States)

    Beard, Courtney; Stein, Aliza T; Hearon, Bridget A; Lee, Josephine; Hsu, Kean J; Björgvinsson, Thröstur

    2016-04-01

    Despite the effectiveness of cognitive behavioral therapy (CBT) for depression, a significant number of patients do not respond. Data examining predictors of treatment response in settings in which CBT is delivered naturalistically are lacking. Treatment outcome data collected at a CBT-based partial hospital (n = 956) were used to examine predictors of two types of treatment response: (a) a reliable and clinically significant change in depressive symptoms and (b) a self-rating of "very much" or "much" improved. In multiple logistic regression models, we examined predictors of response in the total sample and separately for patients with a primary diagnosis of major depressive disorder (MDD) versus patients with other primary diagnoses. In the total sample, higher treatment outcome expectations and fewer past hospitalizations predicted clinically significant improvement in depression symptoms, and higher treatment expectations and ethnoracial minority background predicted global improvement. In patients with primary MDD, higher treatment outcome expectations and being referred from the community (vs. inpatient hospitalization) predicted better depression response, and higher treatment outcome expectations predicted global improvement. In patients with other primary diagnoses, higher treatment outcome expectations and fewer borderline personality disorder traits predicted depression reduction, and higher treatment outcome expectations, less relationship difficulty, and female gender predicted global improvement. Results are generally consistent with data from randomized controlled trials on longer term outpatient CBT. Interventions that increase treatment expectancy and modifications to better target men may enhance treatment outcome. Future research should include objective outcome measures and examine mechanisms underlying treatment response. © 2016 Wiley Periodicals, Inc.

  16. Predictors of handgrip strength among adults of a rural community in Malaysia.

    Science.gov (United States)

    Moy, Foong-Ming; Darus, Azlan; Hairi, Noran Naqiah

    2015-03-01

    Handgrip strength is useful for screening the nutritional status of adult population as it is strongly associated with physical disabilities and mortality. Therefore, we aimed to determine the predictors of handgrip strength among adults of a rural community in Malaysia using a cross-sectional study design with multistage sampling. All adults aged 30 years and older from 1250 households were invited to our study. Structured questionnaire on sociodemographic characteristics, medical history, occupation history, lifestyle practices, and measurements, including anthropometry and handgrip strength were taken. There were 2199 respondents with 55.2% females and majority were of Malay ethnicity. Their mean (standard deviation) age was 53.4 (13.2) years. The response rate for handgrip strength was 94.2%. Females had significantly lower handgrip strength than males (P < .05). In the multiple linear regression models, significant predictors of handgrip strength for males were age, height, job groups, and diabetes, while for females, the significant predictors were age, weight, height, and diabetes. © 2013 APJPH.

  17. Patient questionnaires and formal education level as prospective predictors of mortality over 10 years in 97% of 1416 patients with rheumatoid arthritis from 15 United States private practices.

    Science.gov (United States)

    Pincus, Theodore; Keysor, Julie; Sokka, Tuulikki; Krishnan, Eswar; Callahan, Leigh F

    2004-02-01

    To prospectively analyze patient questionnaire scores concerning functional disability as well as formal education level as potential predictors of premature mortality over 10 years in 1416 patients with rheumatoid arthritis (RA) from 15 private practice rheumatology settings in 11 diverse cities in the United States. At baseline in 1985 and periodically over 10 years, patients completed mailed self-report multidimensional health assessment questionnaires (MDHAQ) that included functional disability scores, formal education level, and other demographic and clinical data. Vital status was determined 10 years after baseline. Potential predictors of 10 year mortality were analyzed using descriptive statistics and Cox proportional hazards models. Vital status was accounted for in 1378 patients, 97.3% of the cohort. The standard mortality ratio was 1.6, similar to most reported series of patients with RA, as 401 patients died versus 251 expected over 10 years. Evidence of "dose-response" relations was seen for age, formal education level, functional disability scores, and helplessness scores as predictors of mortality. In Cox proportional hazards models, age, sex, formal education level, functional disability, and helplessness scores remained significant independent predictors of 10 year mortality. Functional disability and low formal education level are significant predictors of premature mortality in people with RA under care in US private practice settings, as in most reported cohorts of patients with RA. This study shows that it is possible to account for more than 95% of patients over 10 years using mailed questionnaires to monitor patient status.

  18. Interframe DPCM with robust median-based predictors for transmission of image sequences over noisy channels.

    Science.gov (United States)

    Song, X; Viero, T; Neuvo, Y

    1996-01-01

    A new image sequence coding technique based on robust median-based predictors is presented for the transmission of image sequences over noisy channels. We analyze the robustness of median-based predictors against channel errors. A heuristic algorithm for the design of a robust predictor from a given median-based predictor is presented. It is shown that with small modifications in terms of a necessary requirement for a median-based predictor to be robust against channel errors, the robustness of a given median-based predictor can be considerably improved. Simulations on a real image sequence show significant improvement over the conventional differential pulse code modulation (DPCM) at high bit error rate (BER) using this new technique. The technique does not increase the transmission rate. It is shown that the quality of reconstructed images obtained by robust median-based predictors can be further improved by postprocessing the image using a nonlinear detail-preserving noise-smoothing filter.

  19. Validation of the AFP model as a predictor of HCC recurrence in patients with viral hepatitis-related cirrhosis who had received a liver transplant for HCC.

    Science.gov (United States)

    Notarpaolo, Andrea; Layese, Richard; Magistri, Paolo; Gambato, Maria; Colledan, Michele; Magini, Giulia; Miglioresi, Lucia; Vitale, Alessandro; Vennarecci, Giovanni; Ambrosio, Cecilia D; Burra, Patrizia; Di Benedetto, Fabrizio; Fagiuoli, Stefano; Colasanti, Marco; Maria Ettorre, Giuseppe; Andreoli, Arnoldo; Cillo, Umberto; Laurent, Alexis; Katsahian, Sandrine; Audureau, Etienne; Roudot-Thoraval, Françoise; Duvoux, Christophe

    2017-03-01

    The AFP model was shown to be superior to the Milan criteria for predicting hepatocellular carcinoma (HCC) recurrence after liver transplantation in a French population. Our aim was to test the AFP model in a non-French, post-hepatitic cirrhosis-based population of HCC candidates. 574 patients transplanted for HCC in four Italian centers were studied. AFP score was assessed at the last evaluation before liver transplantation (LT). Probabilities of recurrence and survival were estimated by the log-rank test or competing risk analysis and compared according to the AFP model. 24.7% patients were beyond Milan criteria. HCC complicated hepatitis C virus (HCV) and hepatitis B virus (HBV) cirrhosis in 58.7% and 24% of the cases, respectively. Five-year probabilities of recurrence differed according to AFP score ⩽2 vs. >2 in the whole population (13.2±1.8% vs. 49.8±8.7%, p2 were 71.7±2.2% vs. 42.2±8.3% (pHCC candidates at low risk of recurrence, otherwise excluded by Milan criteria in a population with a predominance of post-hepatitic-related HCC. The AFP score can be proposed for selection of HCC candidates in programs with a high proportion of viral/HCV-related cirrhosis. Selection criteria for liver transplantation of patients affected with hepatocellular carcinoma (HCC) are based on the Milan criteria, which have been shown to be too restrictive, precluding access to liver transplantation for some patients who might be cured by this operation. Recently, a French group of researchers developed a new selection model called the AFP model, or AFP score, allowing some patients with HCC not meeting Milan criteria to be transplanted with excellent results. In the present work, the AFP score was tested in a population of non-French patients transplanted for HCC occurring mainly on post-hepatitic (HCV or HBV) cirrhosis. The results confirm that in this specific population, as in the original French population of patients, the AFP model better selects patients with HCC

  20. Anabolic-androgenic steroid does not enhance compensatory muscle hypertrophy but significantly diminish muscle damages in the rat surgical ablation model.

    Science.gov (United States)

    Tamaki, Tetsuro; Uchiyama, Yoshiyasu; Okada, Yoshinori; Tono, Kayoko; Nitta, Masahiro; Hoshi, Akio; Akatsuka, Akira

    2009-07-01

    Cellular responses in the compensatory hypertrophied (plantaris) muscle induced by surgical ablation of synergistic muscles (soleus and gastrocnemius) were determined during 10-week anabolic androgenic steroid (AAS) treatment. Adult Wistar male rats were divided randomly into the Control and Steroid groups, and contralateral surgery was performed. Nandrolone decanoate was administered to the Steroid group. [3H]thymidine and [14C]leucine labeling were used to determine the serial changes in cellular mitotic activity and amino acid uptake. Myogenic cells and cellular responses in blood vessels and nerve fibers were analyzed by immunohistochemistry. Significantly lower cellular mitotic activity associated with lower volume of muscle fiber necrosis was observed in the Steroid group during the first week. However, amino acid uptake and final muscle wet weight gain did not differ between the groups. Marked activation/proliferation of muscular, vascular, and peripheral nerve-related cells was seen with the inflammatory responses in both groups. However, this activation was dependent on the volume of muscle fiber damage and was not preferentially accelerated by AAS loading. These results indicated that AAS loading significantly diminished muscle fiber damages, but they did not accelerate final muscle wet weight gain and activation of myogenic, vascular, and peripheral nerve related cells in the compensatory enlarged muscles.

  1. [The significance of the results of crash-tests with the use of the models of the pedestrians' lower extremities for the prevention of the traffic road accidents].

    Science.gov (United States)

    Smirenin, S A; Fetisov, V A; Grigoryan, V G; Gusarov, A A; Kucheryavets, Yu O

    The disabling injuries inflicted during road traffic accidents (RTA) create a serious challenge for the public health services and are at the same time a major socio-economic problem in the majority of the countries throughout the world. The injuries to the lower extremities of the pedestrians make up the largest fraction of the total number of the non-lethal RTA injuries. Most of them are responsible for the considerable deterioration of the quality of life for the participants in the accidents during the subsequent period. The objective of the present study was to summarize the currently available results of experimental testing of the biomechanical models of the pedestrians' lower extremities in the framework of the program for the prevention of the road traffic accidents as proposed by the World Health Organization (WHO, 2004). The European Enhanced Safety Vehicle Committee (EEVC) has developed a series of crash-tests with the use of the models of the pedestrians' lower extremities simulating the vehicle bumper-pedestrian impact. The models are intended for the assessment of the risk of the tibia fractures and the injuries to the knee joint ligaments. The experts of EEVC proposed the biomechanical criteria for the acceleration of the knee and talocrural parts of the lower limbs as well as for the shear displacement of the knee and knee-bending angle. The engineering solution of this problem is based on numerous innovation proposals being implemented in the machine-building industry with the purpose of reducing the stiffness of structural elements of the bumper and other front components of a modern vehicle designed to protect the pedestrians from severe injuries that can be inflicted in the road traffic accidents. The activities of the public health authorities (in the first place, bureaus of forensic medical expertise and analogous facilities) have a direct bearing on the solution of the problem of control of road traffic injuries because they are possessed of

  2. Predictors of musculoskeletal discomfort: A cross-cultural comparison between Malaysian and Australian office workers.

    Science.gov (United States)

    Maakip, Ismail; Keegel, Tessa; Oakman, Jodi

    2017-04-01

    Prevalence and predictors associated with musculoskeletal disorders (MSDs) vary considerably between countries. It is plausible that socio-cultural contexts may contribute to these differences. We conducted a cross-sectional survey with 1184 Malaysian and Australian office workers with the aim to examine predictors associated with MSD discomfort. The 6-month period prevalence of self-reported MSD discomfort for Malaysian office workers was 92.8% and 71.2% among Australian workers. In Malaysia, a model regressing level of musculoskeletal discomfort against possible risk factors was significant overall (F [6, 370] = 17.35; p culture of the target population. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  3. Predictors of science, technology, engineering, and mathematics choice options: A meta-analytic path analysis of the social-cognitive choice model by gender and race/ethnicity.

    Science.gov (United States)

    Lent, Robert W; Sheu, Hung-Bin; Miller, Matthew J; Cusick, Megan E; Penn, Lee T; Truong, Nancy N

    2018-01-01

    We tested the interest and choice portion of social-cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994) in the context of science, technology, engineering, and mathematics (STEM) domains. Data from 143 studies (including 196 independent samples) conducted over a 30-year period (1983 through 2013) were subjected to meta-analytic path analyses. The interest/choice model was found to fit the data well over all samples as well as within samples composed primarily of women and men and racial/ethnic minority and majority persons. The model also accounted for large portions of the variance in interests and choice goals within each path analysis. Despite the general predictive utility of SCCT across gender and racial/ethnic groups, we did find that several parameter estimates differed by group. We present both the group similarities and differences and consider their implications for future research, intervention, and theory refinement. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  4. CRADA Final Report: Weld Predictor App

    Energy Technology Data Exchange (ETDEWEB)

    Billings, Jay Jay [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2018-01-25

    Welding is an important manufacturing process used in a broad range of industries and market sectors, including automotive, aerospace, heavy manufacturing, medical, and defense. During welded fabrication, high localized heat input and subsequent rapid cooling result in the creation of residual stresses and distortion. These residual stresses can significantly affect the fatigue resistance, cracking behavior, and load-carrying capacity of welded structures during service. Further, additional fitting and tacking time is often required to fit distorted subassemblies together, resulting in non-value added cost. Using trial-and-error methods to determine which welding parameters, welding sequences, and fixture designs will most effectively reduce distortion is a time-consuming and expensive process. For complex structures with many welds, this approach can take several months. For this reason, efficient and accurate methods of mitigating distortion are in-demand across all industries where welding is used. Analytical and computational methods and commercial software tools have been developed to predict welding-induced residual stresses and distortion. Welding process parameters, fixtures, and tooling can be optimized to reduce the HAZ softening and minimize weld residual stress and distortion, improving performance and reducing design, fabrication and testing costs. However, weld modeling technology tools are currently accessible only to engineers and designers with a background in finite element analysis (FEA) who work with large manufacturers, research institutes, and universities with access to high-performance computing (HPC) resources. Small and medium enterprises (SMEs) in the US do not typically have the human and computational resources needed to adopt and utilize weld modeling technology. To allow an engineer with no background in FEA and SMEs to gain access to this important design tool, EWI and the Ohio Supercomputer Center (OSC) developed the online weld

  5. The sensitivity and significance analysis of parameters in the model of pH regulation on lactic acid production by Lactobacillus bulgaricus.

    Science.gov (United States)

    Liu, Ke; Zeng, Xiangmiao; Qiao, Lei; Li, Xisheng; Yang, Yubo; Dai, Cuihong; Hou, Aiju; Xu, Dechang

    2014-01-01

    The excessive production of lactic acid by L. bulgaricus during yogurt storage is a phenomenon we are always tried to prevent. The methods used in industry either control the post-acidification inefficiently or kill the probiotics in yogurt. Genetic methods of changing the activity of one enzyme related to lactic acid metabolism make the bacteria short of energy to growth, although they are efficient ways in controlling lactic acid production. A model of pH-induced promoter regulation on the production of lactic acid by L. bulgaricus was built. The modelled lactic acid metabolism without pH-induced promoter regulation fitted well with wild type L. bulgaricus (R2LAC = 0.943, R2LA = 0.942). Both the local sensitivity analysis and Sobol sensitivity analysis indicated parameters Tmax, GR, KLR, S, V0, V1 and dLR were sensitive. In order to guide the future biology experiments, three adjustable parameters, KLR, V0 and V1, were chosen for further simulations. V0 had little effect on lactic acid production if the pH-induced promoter could be well induced when pH decreased to its threshold. KLR and V1 both exhibited great influence on the producing of lactic acid. The proposed method of introducing a pH-induced promoter to regulate a repressor gene could restrain the synthesis of lactic acid if an appropriate strength of promoter and/or an appropriate strength of ribosome binding sequence (RBS) in lacR gene has been designed.

  6. Job satisfaction among nurses: a predictor of burnout levels.

    Science.gov (United States)

    Kalliath, Thomas; Morris, Rita

    2002-12-01

    This study assessed the impact of differential levels of job satisfaction on burnout among nurses, hypothesizing that higher levels of job satisfaction predict lower levels of burnout. Social environmental factors of the workplace arising from organizational restructuring cost containment strategies, diminishing resources, and increasing responsibilities, cause highly stressed, burned out nurses to leave the profession. This study used the Maslach Burnout Inventory (MBI) to measure emotional exhaustion, depersonalization, and personal accomplishment. The job satisfaction scale of Katzell et al was used to measure overall job satisfaction. Statistical tests for significance used were Confirmatory Factor Analysis, Structural Equation Modeling, the chi statistic, Root Mean Square Error of Approximation, Goodness of Fit Index, and Comparative Fit Index. The findings show that job satisfaction has a significant direct negative effect on emotional exhaustion, whereas emotional exhaustion has a direct positive effect on depersonalization. A significant indirect effect was seen of job satisfaction on depersonalization via exhaustion. The path coefficient shows that job satisfaction has both direct and indirect effects on burnout, confirming job satisfaction as a significant predictor of burnout. Collaborative efforts between nurses, administrators, and educators to research and test practical models to improve job satisfaction may work as an antidote to burnout.

  7. Predictors for trismus in patients receiving radiotherapy.

    Science.gov (United States)

    van der Geer, S Joyce; Kamstra, Jolanda I; Roodenburg, Jan L N; van Leeuwen, Marianne; Reintsema, Harry; Langendijk, Johannes A; Dijkstra, Pieter U

    2016-11-01

    Trismus, a restricted mouth opening in head and neck cancer patients may be caused by tumor infiltration in masticatory muscles, radiation-induced fibrosis or scarring after surgery. It may impede oral functioning severely. The aims of our study were to determine: (1) the incidence of trismus at various time points; and (2) the patient, tumor, and treatment characteristics that predict the development of trismus after radiotherapy in head and neck cancer patients using a large database (n = 641). Maximal mouth opening was measured prior to and 6, 12, 18, 24, 36, and 48 months after radiotherapy. Patient, tumor, and treatment characteristics were analyzed as potential predictors for trismus using a multivariable logistic regression analysis. At six months after radiotherapy, 28.1% of the patients without trismus prior to radiotherapy developed trismus for the first time. At subsequent time points the incidence declined. Over a total period of 48 months after radiotherapy, the incidence of trismus was 3.6 per 10 person years at risk. Patients who had tumors located in the oral cavity, oropharynx or nasopharynx, and the salivary glands or ear, and who had a longer overall treatment time of radiotherapy, were more likely to develop trismus in the first six months after radiotherapy. Maximal mouth opening was a predictor for developing trismus at all time points. Incidence of trismus is 3.6 per 10 person years at risk. Tumor localization and overall treatment time of radiotherapy are predictors for developing trismus the first six months after radiotherapy. Maximal mouth opening is a significant predictor for developing trismus at all time points. Regular measurements of maximal mouth opening are needed to predict trismus.

  8. Crowdsourcing novel childhood predictors of adult obesity.

    Directory of Open Access Journals (Sweden)

    Kirsten E Bevelander

    Full Text Available Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age  =  26.5±6.7; BMI  =  29.0±7.0 registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.

  9. Crowdsourcing novel childhood predictors of adult obesity.

    Science.gov (United States)

    Bevelander, Kirsten E; Kaipainen, Kirsikka; Swain, Robert; Dohle, Simone; Bongard, Josh C; Hines, Paul D H; Wansink, Brian

    2014-01-01

    Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age  =  26.5±6.7; BMI  =  29.0±7.0) registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI) and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.

  10. Nurse Work Engagement Impacts Job Outcome and Nurse-Assessed Quality of Care: Model Testing with Nurse Practice Environment and Nurse Work Characteristics as Predictors

    Directory of Open Access Journals (Sweden)

    Peter Mathieu Van Bogaert

    2014-11-01

    Full Text Available Key words: burnout,job satisfaction, nurse retention, nurse practice environment,quality of care, acute health care,structural equation modelling. Aim:To explore the mechanisms through which nurse practice environment dimensions are associated with job outcomes and nurse-assessed quality of care. Mediating variables tested included nurse work characteristics of workload, social capital, decision latitude, as well as work engagement dimensions of vigor, dedication and absorption.Background: Understanding to support and guide the practice community in their daily effort to answer most accurate complex care demands along with a stable nurse workforce are challenging.Design: Cross-sectional survey.Method:Based on previous empirical findings,a structural equation model designed with valid measurement instruments was tested.The study population was registered acute care hospital nurses(N = 1201 in twoindependent hospitals and one hospital group with six hospitals in Belgium.Results: Nurse practice environment dimensions predicted job outcome variables and nurse ratings of quality of care.Analyses were consistent with features of nurses’ work characteristics including perceived workload,decision latitude,and social capital,as well as three dimension of work engagement playing mediating roles between nurse practice environment and outcomes.A revised model adjusted using various fit measures explained 60 % and 47 % of job outcomes and nurse - assessed quality of care,respectively.Conclusion: Study findings show that aspects of nurse work characteristics such as workload,decision latitude and social capital along with nurse work engagement(e.g.vigor, dedication and absorption play a role between how various stakeholders such as executives,nurse managers and physicians will organize care and how nurses perceive job outcomes and quality of care.

  11. Predictors of Outcome in Traumatic Brain Injury: New Insight Using Receiver Operating Curve Indices and Bayesian Network Analysis.

    Directory of Open Access Journals (Sweden)

    Zsolt Zador

    Full Text Available Traumatic brain injury remains a global health problem. Understanding the relative importance of outcome predictors helps optimize our treatment strategies by informing assessment protocols, clinical decisions and trial designs. In this study we establish importance ranking for outcome predictors based on receiver operating indices to identify key predictors of outcome and create simple predictive models. We then explore the associations between key outcome predictors using Bayesian networks to gain further insight into predictor importance.We analyzed the corticosteroid randomization after significant head injury (CRASH trial database of 10008 patients and included patients for whom demographics, injury characteristics, computer tomography (CT findings and Glasgow Outcome Scale (GCS were recorded (total of 13 predictors, which would be available to clinicians within a few hours following the injury in 6945 patients. Predictions of clinical outcome (death or severe disability at 6 months were performed using logistic regression models with 5-fold cross validation. Predictive performance was measured using standardized partial area (pAUC under the receiver operating curve (ROC and we used Delong test for comparisons. Variable importance ranking was based on pAUC targeted at specificity (pAUCSP and sensitivity (pAUCSE intervals of 90-100%. Probabilistic associations were depicted using Bayesian networks.Complete AUC analysis showed very good predictive power (AUC = 0.8237, 95% CI: 0.8138-0.8336 for the complete model. Specificity focused importance ranking highlighted age, pupillary, motor responses, obliteration of basal cisterns/3rd ventricle and midline shift. Interestingly when targeting model sensitivity, the highest-ranking variables were age, severe extracranial injury, verbal response, hematoma on CT and motor response. Simplified models, which included only these key predictors, had similar performance (pAUCSP = 0.6523, 95% CI: 0

  12. Model for end-stage liver disease (MELD score as a predictor and monitor of mortality in patients with Vibrio vulnificus necrotizing skin and soft tissue infections.

    Directory of Open Access Journals (Sweden)

    Kuo-Chin Huang

    2015-04-01

    Full Text Available Vibrio vulnificus necrotizing skin and soft tissue infections (VNSSTIs usually predispose patients with or without preexisting liver disease to septic shock, and then evolve to multiple organ dysfunction syndrome (MODS, thus resulting in high mortality in humans. However, clinicians do not have a valid prediction model to provide a reliable estimate of case-fatality rate when caring for these acutely and/or critically ill patients.We retrospectively analyzed 39 consecutive patients with VNSSTIs (mean age: 65.7 ± 11.3 years at our institution between 2007 and 2010. All patients were treated with the same protocol. Demographic and clinical characteristics, disease severity on admission, treatment details, and outcomes were collected for each patient and extracted for analyses. We studied the predictive value of the model for end-stage liver disease (MELD, modified MELD including sodium (MELD-Na, and laboratory risk indicator for necrotizing fasciitis (LRINEC scores for case-fatality. Logistic regression and receiver operating characteristic (ROC curve analyses were performed. The mean MELD, MELD-Na and LRINEC scores on admission were 15.1 ± 1.1, 17.7 ± 1.1, and 3.4 ± 0.4 points, respectively. After admission, these patients had temporary or progressive deterioration of nearly all their scores and lab values. The area under the ROC curve for the MELD and ΔMELD scoring models were 0.929 (p = 0.002 and 0.897 (p = 0.005, respectively. An optimal MELD/ΔMELD cutoff value ≥ 20/2 had a good sensitivity and specificity (all > 80%, with a 64/13-fold increased odds for case-fatality. Additionally, the development of severe forms of anemia (p = 0.014 and hypoalbuminemia (p = 0.019 were associated with an increased case-fatality rate.The MELD/ΔMELD scoring model is an effective risk stratification indicator at the time of admission and also an excellent condition monitor during hospitalization for medical care of acutely and/or critically ill patients

  13. Internationally educated nurses in Canada: predictors of workforce integration.

    Science.gov (United States)

    Covell, Christine L; Primeau, Marie-Douce; Kilpatrick, Kelley; St-Pierre, Isabelle

    2017-04-04

    Global trends in migration accompanied with recent changes to the immigrant selection process may have influenced the demographic and human capital characteristics of internationally educated nurses (IENs) in Canada and in turn the assistance required to facilitate their workforce integration. This study aimed to describe the demographic and human capital profile of IENs in Canada, to explore recent changes to the profile, and to identify predictors of IENs' workforce integration. A cross-sectional, descriptive, correlational survey design was used. Eligible IENs were immigrants, registered and employed as regulated nurses in Canada. Data were collected in 2014 via online and paper questionnaires. Descriptive statistics were used to examine the data by year of immigration. Logistic regression modeling was employed to identify predictors of IENs' workforce integration measured as passing the licensure exam to acquire professional recertification and securing employment. The sample consisted of 2280 IENs, representative of all Canadian provincial jurisdictions. Since changes to the immigrant selection process in 2002, the IEN population in Canada has become more racially diverse with greater numbers emigrating from developing countries. Recent arrivals (after 2002) had high levels of human capital (knowledge, professional experience, language proficiency). Some, but not all, benefited from the formal and informal assistance available to facilitate their workforce integration. Professional experience and help studying significantly predicted if IENs passed the licensure exam on their first attempt. Bridging program participation and assistance from social networks in Canada were significant predictors if IENs had difficulty securing employment. Nurses will continue to migrate from a wide variety of countries throughout the world that have dissimilar nursing education and health systems. Thus, IENs are not a homogenous group, and a "one size fits all" model may not be

  14. The orthogeriatrics model of care: systematic review of predictors of institutionalization and mortality in post-hip fracture patients and evidence for interventions.

    Science.gov (United States)

    Martinez-Reig, Marta; Ahmad, Laura; Duque, Gustavo

    2012-11-01

    Hip fracture is a common serious complication of osteoporosis, which is associated with high morbidity and mortality. In nursing home residents, incidence rates of hip fractures are at least twice to three times higher than in community-dwellers of the same age and sex. Older adults with hip fracture have a 5- to 8-fold increased risk for all-cause mortality and much higher risk of institutionalization. Therefore, interventions to prevent institutionalization, prevent a second fracture in institutionalized patients, and decrease mortality after a hip fracture are highly needed. The orthogeriatrics model of care is a shared-care approach to patients after suffering a hip fracture. This program, which has been studied in models run by geriatricians with the assistance of a multidisciplinary team, includes a comprehensive medical and nursing admission assessment focusing on the patient's premorbid function, cognition, comorbidities, and risks is followed by a comprehensive care plan design. This systematic review describes and analyzes the interrelation between hip fracture and nursing home placement taking into consideration those evidence-based interventions to prevent later complications and future institutionalization. Copyright © 2012 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

  15. Molecular modeling and simulation studies of recombinant laccase from Yersinia enterocolitica suggests significant role in the biotransformation of non-steroidal anti-inflammatory drugs

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Deepti; Rawat, Surender [Laboratory of Enzymology and Recombinant DNA Technology, Department of Microbiology, Maharshi Dayanand University, Rohtak 124001, Haryana (India); Waseem, Mohd; Gupta, Sunita; Lynn, Andrew [School of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067 (India); Nitin, Mukesh; Ramchiary, Nirala [School of Life Sciences, Jawaharlal Nehru University, New Delhi 110067 (India); Sharma, Krishna Kant, E-mail: kekulsharma@gmail.com [Laboratory of Enzymology and Recombinant DNA Technology, Department of Microbiology, Maharshi Dayanand University, Rohtak 124001, Haryana (India)

    2016-01-08

    The YacK gene from Yersinia enterocolitica strain 7, cloned in pET28a vector and expressed in Escherichia coli BL21 (DE3), showed laccase activity when oxidized with 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and guaiacol. The recombinant laccase protein was purified and characterized biochemically with a molecular mass of ≈58 KDa on SDS-PAGE and showed positive zymogram with ABTS. The protein was highly robust with optimum pH 9.0 and stable at 70 °C upto 12 h with residual activity of 70%. Kinetic constants, K{sub m} values, for ABTS and guaiacol were 675 μM and 2070 μM, respectively, with corresponding Vmax values of 0.125 μmol/ml/min and 6500 μmol/ml/min. It also possess antioxidative property against BSA and Cu{sup 2+}/H{sub 2}O{sub 2} model system. Constant pH MD simulation studies at different protonation states of the system showed ABTS to be most stable at acidic pH, whereas, diclofenac at neutral pH. Interestingly, aspirin drifted out of the binding pocket at acidic and neutral pH, but showed stable binding at alkaline pH. The biotransformation of diclofenac and aspirin by laccase also corroborated the in silico results. This is the first report on biotransformation of non-steroidal anti-inflammatory drugs (NSAIDs) using recombinant laccase from gut bacteria, supported by in silico simulation studies. - Highlights: • Laccase from Yersinia enterocolitica strain 7 was expressed in Escherichia coli BL21 (DE3). • Recombinant laccase was found to be thermostable and alkali tolerant. • The in silico and experimental studied proves the biotransformation of NSAIDs. • Laccase binds to ligands differentially under different protonation state. • Laccase also possesses free radical scavenging property.

  16. Molecular modeling and simulation studies of recombinant laccase from Yersinia enterocolitica suggests significant role in the biotransformation of non-steroidal anti-inflammatory drugs

    International Nuclear Information System (INIS)

    Singh, Deepti; Rawat, Surender; Waseem, Mohd; Gupta, Sunita; Lynn, Andrew; Nitin, Mukesh; Ramchiary, Nirala; Sharma, Krishna Kant

    2016-01-01

    The YacK gene from Yersinia enterocolitica strain 7, cloned in pET28a vector and expressed in Escherichia coli BL21 (DE3), showed laccase activity when oxidized with 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and guaiacol. The recombinant laccase protein was purified and characterized biochemically with a molecular mass of ≈58 KDa on SDS-PAGE and showed positive zymogram with ABTS. The protein was highly robust with optimum pH 9.0 and stable at 70 °C upto 12 h with residual activity of 70%. Kinetic constants, K m values, for ABTS and guaiacol were 675 μM and 2070 μM, respectively, with corresponding Vmax values of 0.125 μmol/ml/min and 6500 μmol/ml/min. It also possess antioxidative property against BSA and Cu 2+ /H 2 O 2 model system. Constant pH MD simulation studies at different protonation states of the system showed ABTS to be most stable at acidic pH, whereas, diclofenac at neutral pH. Interestingly, aspirin drifted out of the binding pocket at acidic and neutral pH, but showed stable binding at alkaline pH. The biotransformation of diclofenac and aspirin by laccase also corroborated the in silico results. This is the first report on biotransformation of non-steroidal anti-inflammatory drugs (NSAIDs) using recombinant laccase from gut bacteria, supported by in silico simulation studies. - Highlights: • Laccase from Yersinia enterocolitica strain 7 was expressed in Escherichia coli BL21 (DE3). • Recombinant laccase was found to be thermostable and alkali tolerant. • The in silico and experimental studied proves the biotransformation of NSAIDs. • Laccase binds to ligands differentially under different protonation state. • Laccase also possesses free radical scavenging property.

  17. Is parenting style a predictor of suicide attempts in a representative sample of adolescents?

    Science.gov (United States)

    2014-01-01

    Background Suicidal ideation and suicide attempts are serious but not rare conditions in adolescents. However, there are several research and practical suicide-prevention initiatives that discuss the possibility of preventing serious self-harm. Profound knowledge about risk and protective factors is therefore necessary. The aim of this study is a) to clarify the role of parenting behavior and parenting styles in adolescents’ suicide attempts and b) to identify other statistically significant and clinically relevant risk and protective factors for suicide attempts in a representative sample of German adolescents. Methods In the years 2007/2008, a representative written survey of N = 44,610 students in the 9th grade of different school types in Germany was conducted. In this survey, the lifetime prevalence of suicide attempts was investigated as well as potential predictors including parenting behavior. A three-step statistical analysis was carried out: I) As basic model, the association between parenting and suicide attempts was explored via binary logistic regression controlled for age and sex. II) The predictive values of 13 additional potential risk/protective factors were analyzed with single binary logistic regression analyses for each predictor alone. Non-significant predictors were excluded in Step III. III) In a multivariate binary logistic regression analysis, all significant predictor variables from Step II and the parenting styles were included after testing for multicollinearity. Results Three parental variables showed a relevant association with suicide attempts in adolescents – (all protective): mother’s warmth and father’s warmth in childhood and mother’s control in adolescence (Step I). In the full model (Step III), Authoritative parenting (protective: OR: .79) and Rejecting-Neglecting parenting (risk: OR: 1.63) were identified as significant predictors (p < .001) for suicidal attempts. Seven further variables were interpreted to be

  18. Distillation Column Flooding Predictor

    Energy Technology Data Exchange (ETDEWEB)

    George E. Dzyacky

    2010-11-23

    The Flooding Predictor™ is a patented advanced control technology proven in research at the Separations Research Program, University of Texas at Austin, to increase distillation column throughput by over 6%, while also increasing energy efficiency by 10%. The research was conducted under a U. S. Department of Energy Cooperative Agreement awarded to George Dzyacky of 2ndpoint, LLC. The Flooding Predictor™ works by detecting the incipient flood point and controlling the column closer to its actual hydraulic limit than historical practices have allowed. Further, the technology uses existing column instrumentation, meaning no additional refining infrastructure is required. Refiners often push distillation columns to maximize throughput, improve separation, or simply to achieve day-to-day optimization. Attempting to achieve such operating objectives is a tricky undertaking that can result in flooding. Operators and advanced control strategies alike rely on the conventional use of delta-pressure instrumentation to approximate the column’s approach to flood. But column delta-pressure is more an inference of the column’s approach to flood than it is an actual measurement of it. As a consequence, delta pressure limits are established conservatively in order to operate in a regime where the column is never expected to flood. As a result, there is much “left on the table” when operating in such a regime, i.e. the capacity difference between controlling the column to an upper delta-pressure limit and controlling it to the actual hydraulic limit. The Flooding Predictor™, an innovative pattern recognition technology, controls columns at their actual hydraulic limit, which research shows leads to a throughput increase of over 6%. Controlling closer to the hydraulic limit also permits operation in a sweet spot of increased energy-efficiency. In this region of increased column loading, the Flooding Predictor is able to exploit the benefits of higher liquid

  19. Severe virus associated community acquired pneumonia: predictors of lethality

    Directory of Open Access Journals (Sweden)

    T. O. Pertseva

    2016-06-01

    Full Text Available Despite the fact that the influenza virus pathogenicity factors have been well studied in vitro, in vivo lack is presented in understanding of the those risk factors, objective and laboratory parameters, which related most of all to the fatal virus-associated community-aquired pneumonia (CAP. That is why the purpose of the study was to study the clinical and laboratory characteristics of patients with severe virus-associated CAP during the 2015–2016 influenza epidemic and their role as predictors of patients’ mortality. To do this, patients with severe virus-associated CAP were examined. They were divided into 2 groups depending on the outcome of treatment: 1st- deaths from the virus-associated severe CAP and 2nd - patients with successful treatment of the severe virus-associated CAP. Special statistical method was used – one-dimensional analysis of variance to compare individual parameters between the two groups of patients (surviving and deceased. Pearson χ2 test (contingency table was used for categorical variables. Factors that were significant predictors of mortality as a result of univariate analysis were tested using multifactorial analysis using logistic regression. In the final model, each parameter must have had a significant impact on mortality. It was found that risk factors for death in patients with severe virus-associated CAP according to univariate analysis were: presence of obesity, disorders of consciousness, BH≥35 min, SaO2<80%, PaO2<50 mm Hg, mmHg PaCO2 ≥50 mmHg during hospitalization. Independent predictors of mortality according to the logistic regression are the presence of obesity, disorders of consciousness, PaO2<50 mm Hg, mmHg PaCO2 ≥50 mmHg. Given that among clinical and laboratory parameters key parameters that significantly influence the outcome, are indicators of the severity of hypoxia and hypoxemia, a major step in determining the severity of the patients with virus-associated severe emergency is

  20. Significant Tsunami Events

    Science.gov (United States)

    Dunbar, P. K.; Furtney, M.; McLean, S. J.; Sweeney, A. D.

    2014-12-01

    Tsunamis have inflicted death and destruction on the coastlines of the world throughout history. The occurrence of tsunamis and the resulting effects have been collected and studied as far back as the second millennium B.C. The knowledge gained from cataloging and examining these events has led to significant changes in our understanding of tsunamis, tsunami sources, and methods to mitigate the effects of tsunamis. The most significant, not surprisingly, are often the most devastating, such as the 2011 Tohoku, Japan earthquake and tsunami. The goal of this poster is to give a brief overview of the occurrence of tsunamis and then focus specifically on several significant tsunamis. There are various criteria to determine the most significant tsunamis: the number of deaths, amount of damage, maximum runup height, had a major impact on tsunami science or policy, etc. As a result, descriptions will include some of the most costly (2011 Tohoku, Japan), the most deadly (2004 Sumatra, 1883 Krakatau), and the highest runup ever observed (1958 Lituya Bay, Alaska). The discovery of the Cascadia subduction zone as the source of the 1700 Japanese "Orphan" tsunami and a future tsunami threat to the U.S. northwest coast, contributed to the decision to form the U.S. National Tsunami Hazard Mitigation Program. The great Lisbon earthquake of 1755 marked the beginning of the modern era of seismology. Knowledge gained from the 1964 Alaska earthquake and tsunami helped confirm the theory of plate tectonics. The 1946 Alaska, 1952 Kuril Islands, 1960 Chile, 1964 Alaska, and the 2004 Banda Aceh, tsunamis all resulted in warning centers or systems being established.The data descriptions on this poster were extracted from NOAA's National Geophysical Data Center (NGDC) global historical tsunami database. Additional information about these tsunamis, as well as water level data can be found by accessing the NGDC website www.ngdc.noaa.gov/hazard/

  1. Predictors of Total Antibiotic Use among a National Network of Academic Hospitals

    Science.gov (United States)

    Holmer, Haley K; McGregor, Jessina C; Elman, Miriam R; Hohmann, Samuel; Kuper, Kristi; Pakyz, Amy

    2017-01-01

    Abstract Background The Centers for Disease Control and Prevention National Healthcare Safety Network (NHSN) provides hospitals a mechanism to report antibiotic use (AU) data to benchmark against peer institutions and direct antibiotic stewardship efforts. Differences in patient populations need to be adjusted for to ensure unbiased comparisons across hospitals. Our objective was to identify predictors of total AU across a nationwide network of hospitals. Methods Data from 126 academic hospitals were extracted from the Vizient Clinical Data Base Resource Manager for adult inpatients (age ≥ 18 years) in 2015. AU was expressed as total antibiotic days of therapy/patient-days. We constructed a negative binomial regression model to ex