WorldWideScience

Sample records for activity predicts responsiveness

  1. Striatal Activation Predicts Differential Therapeutic Responses to Methylphenidate and Atomoxetine.

    Science.gov (United States)

    Schulz, Kurt P; Bédard, Anne-Claude V; Fan, Jin; Hildebrandt, Thomas B; Stein, Mark A; Ivanov, Iliyan; Halperin, Jeffrey M; Newcorn, Jeffrey H

    2017-07-01

    Methylphenidate has prominent effects in the dopamine-rich striatum that are absent for the selective norepinephrine transporter inhibitor atomoxetine. This study tested whether baseline striatal activation would predict differential response to the two medications in youth with attention-deficit/hyperactivity disorder (ADHD). A total of 36 youth with ADHD performed a Go/No-Go test during functional magnetic resonance imaging at baseline and were treated with methylphenidate and atomoxetine using a randomized cross-over design. Whole-brain task-related activation was regressed on clinical response. Task-related activation in right caudate nucleus was predicted by an interaction of clinical responses to methylphenidate and atomoxetine (F 1,30  = 17.00; p atomoxetine. The rate of robust response was higher for methylphenidate than for atomoxetine in youth with high (94.4% vs. 38.8%; p = .003; number needed to treat = 2, 95% CI = 1.31-3.73) but not low (33.3% vs. 50.0%; p = .375) caudate activation. Furthermore, response to atomoxetine predicted motor cortex activation (F 1,30  = 14.99; p atomoxetine in youth with ADHD, purportedly reflecting the dopaminergic effects of methylphenidate but not atomoxetine in the striatum, whereas motor cortex activation may predict response to atomoxetine. These data do not yet translate directly to the clinical setting, but the approach is potentially important for informing future research and illustrates that it may be possible to predict differential treatment response using a biomarker-driven approach. Stimulant Versus Nonstimulant Medication for Attention Deficit Hyperactivity Disorder in Children; https://clinicaltrials.gov/; NCT00183391. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

  2. Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses.

    Science.gov (United States)

    Mulej Bratec, Satja; Xie, Xiyao; Schmid, Gabriele; Doll, Anselm; Schilbach, Leonhard; Zimmer, Claus; Wohlschläger, Afra; Riedl, Valentin; Sorg, Christian

    2015-12-01

    Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Predictive Factors of Clinical Response of Infliximab Therapy in Active Nonradiographic Axial Spondyloarthritis Patients

    Directory of Open Access Journals (Sweden)

    Zhiming Lin

    2015-01-01

    Full Text Available Objectives. To evaluate the efficiency and the predictive factors of clinical response of infliximab in active nonradiographic axial spondyloarthritis patients. Methods. Active nonradiographic patients fulfilling ESSG criteria for SpA but not fulfilling modified New York criteria were included. All patients received infliximab treatment for 24 weeks. The primary endpoint was ASAS20 response at weeks 12 and 24. The abilities of baseline parameters and response at week 2 to predict ASAS20 response at weeks 12 and 24 were assessed using ROC curve and logistic regression analysis, respectively. Results. Of 70 axial SpA patients included, the proportions of patients achieving an ASAS20 response at weeks 2, 6, 12, and 24 were 85.7%, 88.6%, 87.1%, and 84.3%, respectively. Baseline MRI sacroiliitis score (AUC = 0.791; P=0.005, CRP (AUC = 0.75; P=0.017, and ASDAS (AUC = 0.778, P=0.007 significantly predicted ASAS20 response at week 12. However, only ASDAS (AUC = 0.696, P=0.040 significantly predicted ASAS20 response at week 24. Achievement of ASAS20 response after the first infliximab infusion was a significant predictor of subsequent ASAS20 response at weeks 12 and 24 (wald χ2=6.87, P=0.009, and wald χ2=5.171, P=0.023. Conclusions. Infliximab shows efficiency in active nonradiographic axial spondyloarthritis patients. ASDAS score and first-dose response could help predicting clinical efficacy of infliximab therapy in these patients.

  4. Resting lateralized activity predicts the cortical response and appraisal of emotions: an fNIRS study.

    Science.gov (United States)

    Balconi, Michela; Grippa, Elisabetta; Vanutelli, Maria Elide

    2015-12-01

    This study explored the effect of lateralized left-right resting brain activity on prefrontal cortical responsiveness to emotional cues and on the explicit appraisal (stimulus evaluation) of emotions based on their valence. Indeed subjective responses to different emotional stimuli should be predicted by brain resting activity and should be lateralized and valence-related (positive vs negative valence). A hemodynamic measure was considered (functional near-infrared spectroscopy). Indeed hemodynamic resting activity and brain response to emotional cues were registered when subjects (N = 19) viewed emotional positive vs negative stimuli (IAPS). Lateralized index response during resting state, LI (lateralized index) during emotional processing and self-assessment manikin rating were considered. Regression analysis showed the significant predictive effect of resting activity (more left or right lateralized) on both brain response and appraisal of emotional cues based on stimuli valence. Moreover, significant effects were found as a function of valence (more right response to negative stimuli; more left response to positive stimuli) during emotion processing. Therefore, resting state may be considered a predictive marker of the successive cortical responsiveness to emotions. The significance of resting condition for emotional behavior was discussed. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  5. Lateral prefrontal cortex activity during cognitive control of emotion predicts response to social stress in schizophrenia

    Directory of Open Access Journals (Sweden)

    Laura M. Tully, PhD

    2014-01-01

    Full Text Available LPFC dysfunction is a well-established neural impairment in schizophrenia and is associated with worse symptoms. However, how LPFC activation influences symptoms is unclear. Previous findings in healthy individuals demonstrate that lateral prefrontal cortex (LPFC activation during cognitive control of emotional information predicts mood and behavior in response to interpersonal conflict, thus impairments in these processes may contribute to symptom exacerbation in schizophrenia. We investigated whether schizophrenia participants show LPFC deficits during cognitive control of emotional information, and whether these LPFC deficits prospectively predict changes in mood and symptoms following real-world interpersonal conflict. During fMRI, 23 individuals with schizophrenia or schizoaffective disorder and 24 healthy controls completed the Multi-Source Interference Task superimposed on neutral and negative pictures. Afterwards, schizophrenia participants completed a 21-day online daily-diary in which they rated the extent to which they experienced mood and schizophrenia-spectrum symptoms, as well as the occurrence and response to interpersonal conflict. Schizophrenia participants had lower dorsal LPFC activity (BA9 during cognitive control of task-irrelevant negative emotional information. Within schizophrenia participants, DLPFC activity during cognitive control of emotional information predicted changes in positive and negative mood on days following highly distressing interpersonal conflicts. Results have implications for understanding the specific role of LPFC in response to social stress in schizophrenia, and suggest that treatments targeting LPFC-mediated cognitive control of emotion could promote adaptive response to social stress in schizophrenia.

  6. The negativity bias predicts response rate to Behavioral Activation for depression.

    Science.gov (United States)

    Gollan, Jackie K; Hoxha, Denada; Hunnicutt-Ferguson, Kallio; Norris, Catherine J; Rosebrock, Laina; Sankin, Lindsey; Cacioppo, John

    2016-09-01

    This treatment study investigated the extent to which asymmetric dimensions of affective responding, specifically the positivity offset and the negativity bias, at pretreatment altered the rate of response to Behavioral Activation treatment for depression. Forty-one depressed participants were enrolled into 16 weekly sessions of BA. An additional 36 lifetime healthy participants were evaluated prospectively for 16 weeks to compare affective responding between healthy and remitted patients at post-treatment. All participants were assessed at Weeks 0, 8 and 16 using repeated measures, involving a structured clinical interview for DSM-IV Axis I disorders, questionnaires, and a computerized task designed to measure affective responses to unpleasant, neutral, and pleasant images. The negativity bias at pre-treatment predicted the rate of response to BA, while the positivity offset did not. Only one treatment condition was used in this study and untreated depressed participants were not enrolled, limiting our ability to compare the effect of BA. Baseline negativity bias may serve as a signal for patients to engage in and benefit from the goal-directed BA strategies, thereby accelerating rate of response. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Predicting Social Responsibility and Belonging in Urban After-School Physical Activity Programs with Underserved Children

    Science.gov (United States)

    Martin, Jeffrey J.; Byrd, Brigid; Garn, Alex; McCaughtry, Nate; Kulik, Noel; Centeio, Erin

    2016-01-01

    The purpose of this cross sectional study was to predict feelings of belonging and social responsibility based on the motivational climate perceptions and contingent self-worth of children participating in urban after-school physical activity programs. Three-hundred and four elementary school students from a major Midwestern city participated.…

  8. Enrichment of conserved synaptic activity-responsive element in neuronal genes predicts a coordinated response of MEF2, CREB and SRF.

    Directory of Open Access Journals (Sweden)

    Fernanda M Rodríguez-Tornos

    Full Text Available A unique synaptic activity-responsive element (SARE sequence, composed of the consensus binding sites for SRF, MEF2 and CREB, is necessary for control of transcriptional upregulation of the Arc gene in response to synaptic activity. We hypothesize that this sequence is a broad mechanism that regulates gene expression in response to synaptic activation and during plasticity; and that analysis of SARE-containing genes could identify molecular mechanisms involved in brain disorders. To search for conserved SARE sequences in the mammalian genome, we used the SynoR in silico tool, and found the SARE cluster predominantly in the regulatory regions of genes expressed specifically in the nervous system; most were related to neural development and homeostatic maintenance. Two of these SARE sequences were tested in luciferase assays and proved to promote transcription in response to neuronal activation. Supporting the predictive capacity of our candidate list, up-regulation of several SARE containing genes in response to neuronal activity was validated using external data and also experimentally using primary cortical neurons and quantitative real time RT-PCR. The list of SARE-containing genes includes several linked to mental retardation and cognitive disorders, and is significantly enriched in genes that encode mRNA targeted by FMRP (fragile X mental retardation protein. Our study thus supports the idea that SARE sequences are relevant transcriptional regulatory elements that participate in plasticity. In addition, it offers a comprehensive view of how activity-responsive transcription factors coordinate their actions and increase the selectivity of their targets. Our data suggest that analysis of SARE-containing genes will reveal yet-undescribed pathways of synaptic plasticity and additional candidate genes disrupted in mental disease.

  9. Caregiver Responsiveness to the Family Bereavement Program: What predicts responsiveness? What does responsiveness predict?

    OpenAIRE

    Schoenfelder, Erin N.; Sandler, Irwin N.; Millsap, Roger E.; Wolchik, Sharlene A.; Berkel, Cady; Ayers, Timothy S.

    2013-01-01

    The study developed a multi-dimensional measure to assess participant responsiveness to a preventive intervention, and applied this measure to study how participant baseline characteristics predict responsiveness and how responsiveness predicts program outcomes. The study was conducted with caregivers who participated in the parenting-focused component of the Family Bereavement Program (FBP), a prevention program for families that have experienced parental death. The sample consisted of 89 ca...

  10. Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands.

    Science.gov (United States)

    Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

    2014-01-01

    Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person's response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color-word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute "cognitive readiness," which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.

  11. Prediction of adolescents doing physical activity after completing secondary education.

    Science.gov (United States)

    Moreno-Murcia, Juan Antonio; Huéscar, Elisa; Cervelló, Eduardo

    2012-03-01

    The purpose of this study, based on the self-determination theory (Ryan & Deci, 2000) was to test the prediction power of student's responsibility, psychological mediators, intrinsic motivation and the importance attached to physical education in the intention to continue to practice some form of physical activity and/or sport, and the possible relationships that exist between these variables. We used a sample of 482 adolescent students in physical education classes, with a mean age of 14.3 years, which were measured for responsibility, psychological mediators, sports motivation, the importance of physical education and intention to be physically active. We completed an analysis of structural equations modelling. The results showed that the responsibility positively predicted psychological mediators, and this predicted intrinsic motivation, which positively predicted the importance students attach to physical education, and this, finally, positively predicted the intention of the student to continue doing sport. Results are discussed in relation to the promotion of student's responsibility towards a greater commitment to the practice of physical exercise.

  12. Sulfotransferase activity in plucked hair follicles predicts response to topical minoxidil in the treatment of female androgenetic alopecia.

    Science.gov (United States)

    Roberts, Janet; Desai, Nisha; McCoy, John; Goren, Andy

    2014-01-01

    Two percent topical minoxidil is the only US Food and Drug Administration-approved drug for the treatment of female androgenetic alopecia (AGA). Its success has been limited by the low percentage of responders. Meta-analysis of several studies reporting the number of responders to 2% minoxidil monotherapy indicates moderate hair regrowth in only 13-20% of female patients. Five percent minoxidil solution, when used off-label, may increase the percentage of responders to as much as 40%. As such, a biomarker for predicting treatment response would have significant clinical utility. In a previous study, Goren et al. reported an association between sulfotransferase activity in plucked hair follicles and minoxidil response in a mixed cohort of male and female patients. The aim of this study was to replicate these findings in a well-defined cohort of female patients with AGA treated with 5% minoxidil daily for a period of 6 months. Consistent with the prior study, we found that sulfotransferase activity in plucked hair follicles predicts treatment response with 93% sensitivity and 83% specificity. Our study further supports the importance of minoxidil sulfation in eliciting a therapeutic response and provides further insight into novel targets for increasing minoxidil efficacy. © 2014 Wiley Periodicals, Inc.

  13. A model for predicting lung cancer response to therapy

    International Nuclear Information System (INIS)

    Seibert, Rebecca M.; Ramsey, Chester R.; Hines, J. Wesley; Kupelian, Patrick A.; Langen, Katja M.; Meeks, Sanford L.; Scaperoth, Daniel D.

    2007-01-01

    Purpose: Volumetric computed tomography (CT) images acquired by image-guided radiation therapy (IGRT) systems can be used to measure tumor response over the course of treatment. Predictive adaptive therapy is a novel treatment technique that uses volumetric IGRT data to actively predict the future tumor response to therapy during the first few weeks of IGRT treatment. The goal of this study was to develop and test a model for predicting lung tumor response during IGRT treatment using serial megavoltage CT (MVCT). Methods and Materials: Tumor responses were measured for 20 lung cancer lesions in 17 patients that were imaged and treated with helical tomotherapy with doses ranging from 2.0 to 2.5 Gy per fraction. Five patients were treated with concurrent chemotherapy, and 1 patient was treated with neoadjuvant chemotherapy. Tumor response to treatment was retrospectively measured by contouring 480 serial MVCT images acquired before treatment. A nonparametric, memory-based locally weight regression (LWR) model was developed for predicting tumor response using the retrospective tumor response data. This model predicts future tumor volumes and the associated confidence intervals based on limited observations during the first 2 weeks of treatment. The predictive accuracy of the model was tested using a leave-one-out cross-validation technique with the measured tumor responses. Results: The predictive algorithm was used to compare predicted verse-measured tumor volume response for all 20 lesions. The average error for the predictions of the final tumor volume was 12%, with the true volumes always bounded by the 95% confidence interval. The greatest model uncertainty occurred near the middle of the course of treatment, in which the tumor response relationships were more complex, the model has less information, and the predictors were more varied. The optimal days for measuring the tumor response on the MVCT images were on elapsed Days 1, 2, 5, 9, 11, 12, 17, and 18 during

  14. Novelty response and 50 kHz ultrasonic vocalizations: Differential prediction of locomotor and affective response to amphetamine in Sprague-Dawley rats.

    Science.gov (United States)

    Garcia, Erik J; Cain, Mary E

    2016-02-01

    Novelty and sensation seeking (NSS) predisposes humans and rats to experiment with psychostimulants. In animal models, different tests of NSS predict different phases of drug dependence. Ultrasonic vocalizations (USVs) are evoked by psychomotor stimulants and measure the affective/motivation response to stimuli, yet the role NSS has on USVs in response to amphetamine is not determined. The aim of the present study was to determine if individual differences in NSS and USVs can predict locomotor and USV response to amphetamine (0.0, 0.3, and 1.0 mg/kg) after acute and chronic exposure. Thirty male rats were tested for their response to novelty (IEN), choice to engage in novelty (NPP), and heterospecific play (H-USV). Rats were administered non-contingent amphetamine or saline for seven exposures, and USVs and locomotor activity were measured. After a 14-day rest, rats were administered a challenge dose of amphetamine. Regression analyses indicated that amphetamine dose-dependently increased locomotor activity and the NPP test negatively predicted treatment-induced locomotor activity. The H-USV test predicted treatment-induced frequency-modulated (FM) USVs, but the strength of prediction depended on IEN response. Results provide evidence that locomotor activity and FM USVs induced by amphetamine represent different behavioral responses. The prediction of amphetamine-induced FM USVs by the H-USV screen was changed by the novelty response, indicating that the affective value of amphetamine-measured by FM USVs-depends on novelty response. This provides evidence that higher novelty responders may develop a tolerance faster and may escalate intake faster.

  15. Human oocyte calcium analysis predicts the response to assisted oocyte activation in patients experiencing fertilization failure after ICSI.

    Science.gov (United States)

    Ferrer-Buitrago, M; Dhaenens, L; Lu, Y; Bonte, D; Vanden Meerschaut, F; De Sutter, P; Leybaert, L; Heindryckx, B

    2018-01-10

    Can human oocyte calcium analysis predict fertilization success after assisted oocyte activation (AOA) in patients experiencing fertilization failure after ICSI? ICSI-AOA restores the fertilization rate only in patients displaying abnormal Ca2+ oscillations during human oocyte activation. Patients capable of activating mouse oocytes and who showed abnormal Ca2+ profiles after mouse oocyte Ca2+ analysis (M-OCA), have variable responses to ICSI-AOA. It remains unsettled whether human oocyte Ca2+ analysis (H-OCA) would yield an improved accuracy to predict fertilization success after ICSI-AOA. Sperm activation potential was first evaluated by MOAT. Subsequently, Ca2+ oscillatory patterns were determined with sperm from patients showing moderate to normal activation potential based on the capacity of human sperm to generate Ca2+ responses upon microinjection in mouse and human oocytes. Altogether, this study includes a total of 255 mouse and 122 human oocytes. M-OCA was performed with 16 different sperm samples before undergoing ICSI-AOA treatment. H-OCA was performed for 11 patients who finally underwent ICSI-AOA treatment. The diagnostic accuracy to predict fertilization success was calculated based on the response to ICSI-AOA. Patients experiencing low or total failed fertilization after conventional ICSI were included in the study. All participants showed moderate to high rates of activation after MOAT. Metaphase II (MII) oocytes from B6D2F1 mice were used for M-OCA. Control fertile sperm samples were used to obtain a reference Ca2+ oscillation profile elicited in human oocytes. Donated human oocytes, non-suitable for IVF treatments, were collected and vitrified at MII stage for further analysis by H-OCA. M-OCA and H-OCA predicted the response to ICSI-AOA in 8 out of 11 (73%) patients. Compared to M-OCA, H-OCA detected the presence of sperm activation deficiencies with greater sensitivity (75 vs 100%, respectively). ICSI-AOA never showed benefit to overcome

  16. Advanced Computational Modeling Approaches for Shock Response Prediction

    Science.gov (United States)

    Derkevorkian, Armen; Kolaini, Ali R.; Peterson, Lee

    2015-01-01

    Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., 100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.

  17. MTR-18 Predictive Biomarkers Of Bevacizumab Response In Recurrent Glioblastoma Patients

    DEFF Research Database (Denmark)

    Urup, Thomas; Michaelsen, Signe Regner; Olsen, Lars Rønn

    2015-01-01

    Bevacizumab (BEV) plus chemotherapy has shown activity in recurrent glioblastoma (GBM). However, the prognosis varies and only one third of patients have a durable clinical response to BEV combination therapy. Recent findings from a randomized phase-3 study (AVAglio) indicate that patients...... with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study...... was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination...

  18. Prediction of transcriptional regulatory elements for plant hormone responses based on microarray data

    Directory of Open Access Journals (Sweden)

    Yamaguchi-Shinozaki Kazuko

    2011-02-01

    Full Text Available Abstract Background Phytohormones organize plant development and environmental adaptation through cell-to-cell signal transduction, and their action involves transcriptional activation. Recent international efforts to establish and maintain public databases of Arabidopsis microarray data have enabled the utilization of this data in the analysis of various phytohormone responses, providing genome-wide identification of promoters targeted by phytohormones. Results We utilized such microarray data for prediction of cis-regulatory elements with an octamer-based approach. Our test prediction of a drought-responsive RD29A promoter with the aid of microarray data for response to drought, ABA and overexpression of DREB1A, a key regulator of cold and drought response, provided reasonable results that fit with the experimentally identified regulatory elements. With this succession, we expanded the prediction to various phytohormone responses, including those for abscisic acid, auxin, cytokinin, ethylene, brassinosteroid, jasmonic acid, and salicylic acid, as well as for hydrogen peroxide, drought and DREB1A overexpression. Totally 622 promoters that are activated by phytohormones were subjected to the prediction. In addition, we have assigned putative functions to 53 octamers of the Regulatory Element Group (REG that have been extracted as position-dependent cis-regulatory elements with the aid of their feature of preferential appearance in the promoter region. Conclusions Our prediction of Arabidopsis cis-regulatory elements for phytohormone responses provides guidance for experimental analysis of promoters to reveal the basis of the transcriptional network of phytohormone responses.

  19. From Vivaldi to Beatles and back: predicting lateralized brain responses to music.

    Science.gov (United States)

    Alluri, Vinoo; Toiviainen, Petri; Lund, Torben E; Wallentin, Mikkel; Vuust, Peter; Nandi, Asoke K; Ristaniemi, Tapani; Brattico, Elvira

    2013-12-01

    We aimed at predicting the temporal evolution of brain activity in naturalistic music listening conditions using a combination of neuroimaging and acoustic feature extraction. Participants were scanned using functional Magnetic Resonance Imaging (fMRI) while listening to two musical medleys, including pieces from various genres with and without lyrics. Regression models were built to predict voxel-wise brain activations which were then tested in a cross-validation setting in order to evaluate the robustness of the hence created models across stimuli. To further assess the generalizability of the models we extended the cross-validation procedure by including another dataset, which comprised continuous fMRI responses of musically trained participants to an Argentinean tango. Individual models for the two musical medleys revealed that activations in several areas in the brain belonging to the auditory, limbic, and motor regions could be predicted. Notably, activations in the medial orbitofrontal region and the anterior cingulate cortex, relevant for self-referential appraisal and aesthetic judgments, could be predicted successfully. Cross-validation across musical stimuli and participant pools helped identify a region of the right superior temporal gyrus, encompassing the planum polare and the Heschl's gyrus, as the core structure that processed complex acoustic features of musical pieces from various genres, with or without lyrics. Models based on purely instrumental music were able to predict activation in the bilateral auditory cortices, parietal, somatosensory, and left hemispheric primary and supplementary motor areas. The presence of lyrics on the other hand weakened the prediction of activations in the left superior temporal gyrus. Our results suggest spontaneous emotion-related processing during naturalistic listening to music and provide supportive evidence for the hemispheric specialization for categorical sounds with realistic stimuli. We herewith introduce

  20. Towards personalized therapy for multiple sclerosis: prediction of individual treatment response.

    Science.gov (United States)

    Kalincik, Tomas; Manouchehrinia, Ali; Sobisek, Lukas; Jokubaitis, Vilija; Spelman, Tim; Horakova, Dana; Havrdova, Eva; Trojano, Maria; Izquierdo, Guillermo; Lugaresi, Alessandra; Girard, Marc; Prat, Alexandre; Duquette, Pierre; Grammond, Pierre; Sola, Patrizia; Hupperts, Raymond; Grand'Maison, Francois; Pucci, Eugenio; Boz, Cavit; Alroughani, Raed; Van Pesch, Vincent; Lechner-Scott, Jeannette; Terzi, Murat; Bergamaschi, Roberto; Iuliano, Gerardo; Granella, Franco; Spitaleri, Daniele; Shaygannejad, Vahid; Oreja-Guevara, Celia; Slee, Mark; Ampapa, Radek; Verheul, Freek; McCombe, Pamela; Olascoaga, Javier; Amato, Maria Pia; Vucic, Steve; Hodgkinson, Suzanne; Ramo-Tello, Cristina; Flechter, Shlomo; Cristiano, Edgardo; Rozsa, Csilla; Moore, Fraser; Luis Sanchez-Menoyo, Jose; Laura Saladino, Maria; Barnett, Michael; Hillert, Jan; Butzkueven, Helmut

    2017-09-01

    Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of

  1. Novel enzymatic assay predicts minoxidil response in the treatment of androgenetic alopecia.

    Science.gov (United States)

    Goren, Andy; Castano, Juan Antonio; McCoy, John; Bermudez, Fernando; Lotti, Torello

    2014-01-01

    Topical minoxidil is the most common drug used for the treatment of androgenetic alopecia (AGA) in men and women. Although topical minoxidil exhibits a good safety profile, the efficacy in the overall population remains relatively low at 30-40%. To observe significant improvement in hair growth, minoxidil is typically used daily for a period of at least 3-4 months. Due to the significant time commitment and low response rate, a biomarker for predicting patient response prior to therapy would be advantageous. Minoxidil is converted in the scalp to its active form, minoxidil sulfate, by the sulfotransferase enzyme SULT1A1. We hypothesized that SULT1A1 enzyme activity in the hair follicle correlates with minoxidil response for the treatment of AGA. Our preliminary retrospective study of a SULT1A1 activity assay demonstrates 95% sensitivity and 73% specificity in predicting minoxidil treatment response for AGA. A larger prospective study is now under way to further validate this novel assay. © 2013 Wiley Periodicals, Inc.

  2. Transcription-based prediction of response to IFNbeta using supervised computational methods.

    Directory of Open Access Journals (Sweden)

    Sergio E Baranzini

    2005-01-01

    Full Text Available Changes in cellular functions in response to drug therapy are mediated by specific transcriptional profiles resulting from the induction or repression in the activity of a number of genes, thereby modifying the preexisting gene activity pattern of the drug-targeted cell(s. Recombinant human interferon beta (rIFNbeta is routinely used to control exacerbations in multiple sclerosis patients with only partial success, mainly because of adverse effects and a relatively large proportion of nonresponders. We applied advanced data-mining and predictive modeling tools to a longitudinal 70-gene expression dataset generated by kinetic reverse-transcription PCR from 52 multiple sclerosis patients treated with rIFNbeta to discover higher-order predictive patterns associated with treatment outcome and to define the molecular footprint that rIFNbeta engraves on peripheral blood mononuclear cells. We identified nine sets of gene triplets whose expression, when tested before the initiation of therapy, can predict the response to interferon beta with up to 86% accuracy. In addition, time-series analysis revealed potential key players involved in a good or poor response to interferon beta. Statistical testing of a random outcome class and tolerance to noise was carried out to establish the robustness of the predictive models. Large-scale kinetic reverse-transcription PCR, coupled with advanced data-mining efforts, can effectively reveal preexisting and drug-induced gene expression signatures associated with therapeutic effects.

  3. Momentary assessment of contextual influences on affective response during physical activity.

    Science.gov (United States)

    Dunton, Genevieve Fridlund; Liao, Yue; Intille, Stephen; Huh, Jimi; Leventhal, Adam

    2015-12-01

    Higher positive and lower negative affective response during physical activity may reinforce motivation to engage in future activity. However, affective response during physical activity is typically examined under controlled laboratory conditions. This research used ecological momentary assessment (EMA) to examine social and physical contextual influences on momentary affective response during physical activity in naturalistic settings. Participants included 116 adults (mean age = 40.3 years, 73% female) who completed 8 randomly prompted EMA surveys per day for 4 days across 3 semiannual waves. EMA surveys measured current activity level, social context, and physical context. Participants also rated their current positive and negative affect. Multilevel models assessed whether momentary physical activity level moderated differences in affective response across contexts controlling for day of the week, time of day, and activity intensity (measured by accelerometer). The Activity Level × Alone interaction was significant for predicting positive affect (β = -0.302, SE = 0.133, p = .024). Greater positive affect during physical activity was reported when with other people (vs. alone). The Activity Level × Outdoors interaction was significant for predicting negative affect (β = -0.206, SE = 0.097, p = .034). Lower negative affect during physical activity was reported outdoors (vs. indoors). Being with other people may enhance positive affective response during physical activity, and being outdoors may dampen negative affective response during physical activity. (c) 2015 APA, all rights reserved).

  4. Prediction signatures in the brain: Semantic pre-activation during language comprehension

    Directory of Open Access Journals (Sweden)

    Burkhard Maess

    2016-11-01

    Full Text Available There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: Highly predictive (that is more informative verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns.

  5. Birth weight predicted baseline muscular efficiency, but not response of energy expenditure to calorie restriction: An empirical test of the predictive adaptive response hypothesis.

    Science.gov (United States)

    Workman, Megan; Baker, Jack; Lancaster, Jane B; Mermier, Christine; Alcock, Joe

    2016-07-01

    Aiming to test the evolutionary significance of relationships linking prenatal growth conditions to adult phenotypes, this study examined whether birth size predicts energetic savings during fasting. We specifically tested a Predictive Adaptive Response (PAR) model that predicts greater energetic saving among adults who were born small. Data were collected from a convenience sample of young adults living in Albuquerque, NM (n = 34). Indirect calorimetry quantified changes in resting energy expenditure (REE) and active muscular efficiency that occurred in response to a 29-h fast. Multiple regression analyses linked birth weight to baseline and postfast metabolic values while controlling for appropriate confounders (e.g., sex, body mass). Birth weight did not moderate the relationship between body size and energy expenditure, nor did it predict the magnitude change in REE or muscular efficiency observed from baseline to after fasting. Alternative indicators of birth size were also examined (e.g., low v. normal birth weight, comparison of tertiles), with no effects found. However, baseline muscular efficiency improved by 1.1% per 725 g (S.D.) increase in birth weight (P = 0.037). Birth size did not influence the sensitivity of metabolic demands to fasting-neither at rest nor during activity. Moreover, small birth size predicted a reduction in the efficiency with which muscles convert energy expended into work accomplished. These results do not support the ascription of adaptive function to phenotypes associated with small birth size. © 2015 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:484-492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  6. A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

    Science.gov (United States)

    Loboda, Andrey; Nebozhyn, Michael; Klinghoffer, Rich; Frazier, Jason; Chastain, Michael; Arthur, William; Roberts, Brian; Zhang, Theresa; Chenard, Melissa; Haines, Brian; Andersen, Jannik; Nagashima, Kumiko; Paweletz, Cloud; Lynch, Bethany; Feldman, Igor; Dai, Hongyue; Huang, Pearl; Watters, James

    2010-06-30

    Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

  7. A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

    Directory of Open Access Journals (Sweden)

    Paweletz Cloud

    2010-06-01

    Full Text Available Abstract Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90% sensitivity but relatively low (50% specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical

  8. Prediction of treatment response to adalimumab

    DEFF Research Database (Denmark)

    Krintel, S B; Dehlendorff, C; Hetland, M L

    2016-01-01

    At least 30% of patients with rheumatoid arthritis (RA) do not respond to biologic agents, which emphasizes the need of predictive biomarkers. We aimed to identify microRNAs (miRNAs) predictive of response to adalimumab in 180 treatment-naïve RA patients enrolled in the OPtimized treatment algori...... of low expression of miR-22 and high expression of miR-886.3p was associated with EULAR good response. Future studies to assess the utility of these miRNAs as predictive biomarkers are needed.The Pharmacogenomics Journal advance online publication, 5 May 2015; doi:10.1038/tpj.2015.30....

  9. Human medial frontal cortex activity predicts learning from errors.

    Science.gov (United States)

    Hester, Robert; Barre, Natalie; Murphy, Kevin; Silk, Tim J; Mattingley, Jason B

    2008-08-01

    Learning from errors is a critical feature of human cognition. It underlies our ability to adapt to changing environmental demands and to tune behavior for optimal performance. The posterior medial frontal cortex (pMFC) has been implicated in the evaluation of errors to control behavior, although it has not previously been shown that activity in this region predicts learning from errors. Using functional magnetic resonance imaging, we examined activity in the pMFC during an associative learning task in which participants had to recall the spatial locations of 2-digit targets and were provided with immediate feedback regarding accuracy. Activity within the pMFC was significantly greater for errors that were subsequently corrected than for errors that were repeated. Moreover, pMFC activity during recall errors predicted future responses (correct vs. incorrect), despite a sizeable interval (on average 70 s) between an error and the next presentation of the same recall probe. Activity within the hippocampus also predicted future performance and correlated with error-feedback-related pMFC activity. A relationship between performance expectations and pMFC activity, in the absence of differing reinforcement value for errors, is consistent with the idea that error-related pMFC activity reflects the extent to which an outcome is "worse than expected."

  10. Response to intravenous fentanyl infusion predicts subsequent response to transdermal fentanyl.

    Science.gov (United States)

    Hayashi, Norihito; Kanai, Akifumi; Suzuki, Asaha; Nagahara, Yuki; Okamoto, Hirotsugu

    2016-04-01

    Prediction of the response to transdermal fentanyl (FENtd) before its use for chronic pain is desirable. We tested the hypothesis that the response to intravenous fentanyl infusion (FENiv) can predict the response to FENtd, including the analgesic and adverse effects. The study subjects were 70 consecutive patients with chronic pain. The response to fentanyl at 0.1 mg diluted in 50 ml of physiological saline and infused over 30 min was tested. This was followed by treatment with FENtd (Durotep MT patch 2.1 mg) at a dose of 12.5 µg/h for 2 weeks. Pain intensity before and after FENiv and 2 weeks after FENtd, and the response to treatment, were assessed by the numerical rating scale (NRS), clinical global impression-improvement scale (CGI-I), satisfaction scale (SS), and adverse effects. The NRS score decreased significantly from 7 (4-9) [median (range)] at baseline to 3 (0-8) after FENiv (p 0.04, each). The analgesic and side effects after intravenous fentanyl infusion can be used to predict the response to short-term transdermal treatment with fentanyl.

  11. Merck Ad5/HIV induces broad innate immune activation that predicts CD8⁺ T-cell responses but is attenuated by preexisting Ad5 immunity.

    Science.gov (United States)

    Zak, Daniel E; Andersen-Nissen, Erica; Peterson, Eric R; Sato, Alicia; Hamilton, M Kristina; Borgerding, Joleen; Krishnamurty, Akshay T; Chang, Joanne T; Adams, Devin J; Hensley, Tiffany R; Salter, Alexander I; Morgan, Cecilia A; Duerr, Ann C; De Rosa, Stephen C; Aderem, Alan; McElrath, M Juliana

    2012-12-11

    To better understand how innate immune responses to vaccination can lead to lasting protective immunity, we used a systems approach to define immune signatures in humans over 1 wk following MRKAd5/HIV vaccination that predicted subsequent HIV-specific T-cell responses. Within 24 h, striking increases in peripheral blood mononuclear cell gene expression associated with inflammation, IFN response, and myeloid cell trafficking occurred, and lymphocyte-specific transcripts decreased. These alterations were corroborated by marked serum inflammatory cytokine elevations and egress of circulating lymphocytes. Responses of vaccinees with preexisting adenovirus serotype 5 (Ad5) neutralizing antibodies were strongly attenuated, suggesting that enhanced HIV acquisition in Ad5-seropositive subgroups in the Step Study may relate to the lack of appropriate innate activation rather than to increased systemic immune activation. Importantly, patterns of chemoattractant cytokine responses at 24 h and alterations in 209 peripheral blood mononuclear cell transcripts at 72 h were predictive of subsequent induction and magnitude of HIV-specific CD8(+) T-cell responses. This systems approach provides a framework to compare innate responses induced by vectors, as shown here by contrasting the more rapid, robust response to MRKAd5/HIV with that to yellow fever vaccine. When applied iteratively, the findings may permit selection of HIV vaccine candidates eliciting innate immune response profiles more likely to drive HIV protective immunity.

  12. Regional brain activation and affective response to physical activity among healthy adolescents

    OpenAIRE

    Schneider, Margaret; Graham, Dan; Grant, Arthur; King, Pamela; Cooper, Dan

    2009-01-01

    Research has shown that frontal brain activation, assessed via electroencephalographic (EEG) asymmetry, predicts the post-exercise affective response to exercise among adults. Building on this evidence, the present study investigates the utility of resting cortical asymmetry for explaining variance in the affective response both during and after exercise at two different intensities among healthy adolescents. Resting EEG was obtained from 98 adolescents (55% male), who also completed two 30-m...

  13. Ventromedial Prefrontal Cortex Activation Is Associated with Memory Formation for Predictable Rewards

    Science.gov (United States)

    Bialleck, Katharina A.; Schaal, Hans-Peter; Kranz, Thorsten A.; Fell, Juergen; Elger, Christian E.; Axmacher, Nikolai

    2011-01-01

    During reinforcement learning, dopamine release shifts from the moment of reward consumption to the time point when the reward can be predicted. Previous studies provide consistent evidence that reward-predicting cues enhance long-term memory (LTM) formation of these items via dopaminergic projections to the ventral striatum. However, it is less clear whether memory for items that do not precede a reward but are directly associated with reward consumption is also facilitated. Here, we investigated this question in an fMRI paradigm in which LTM for reward-predicting and neutral cues was compared to LTM for items presented during consumption of reliably predictable as compared to less predictable rewards. We observed activation of the ventral striatum and enhanced memory formation during reward anticipation. During processing of less predictable as compared to reliably predictable rewards, the ventral striatum was activated as well, but items associated with less predictable outcomes were remembered worse than items associated with reliably predictable outcomes. Processing of reliably predictable rewards activated the ventromedial prefrontal cortex (vmPFC), and vmPFC BOLD responses were associated with successful memory formation of these items. Taken together, these findings show that consumption of reliably predictable rewards facilitates LTM formation and is associated with activation of the vmPFC. PMID:21326612

  14. Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa.

    Science.gov (United States)

    DeGuzman, Marisa; Shott, Megan E; Yang, Tony T; Riederer, Justin; Frank, Guido K W

    2017-06-01

    Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Female adolescents with anorexia nervosa (N=21; mean age, 16.4 years [SD=1.9]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 15.2 years [SD=2.4]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs.

  15. Spatially pooled contrast responses predict neural and perceptual similarity of naturalistic image categories.

    Directory of Open Access Journals (Sweden)

    Iris I A Groen

    Full Text Available The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis. Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task.

  16. Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories

    Science.gov (United States)

    Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven

    2012-01-01

    The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs) in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis). Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task. PMID:23093921

  17. The cortisol response to anticipated intergroup interactions predicts self-reported prejudice.

    Science.gov (United States)

    Bijleveld, Erik; Scheepers, Daan; Ellemers, Naomi

    2012-01-01

    While prejudice has often been shown to be rooted in experiences of threat, the biological underpinnings of this threat-prejudice association have received less research attention. The present experiment aims to test whether activations of the hypothalamus-pituitary-adrenal (HPA) axis, due to anticipated interactions with out-group members, predict self-reported prejudice. Moreover, we explore potential moderators of this relationship (i.e., interpersonal similarity; subtle vs. blatant prejudice). Participants anticipated an interaction with an out-group member who was similar or dissimilar to the self. To index HPA activation, cortisol responses to this event were measured. Then, subtle and blatant prejudices were measured via questionnaires. Findings indicated that only when people anticipated an interaction with an out-group member who was dissimilar to the self, their cortisol response to this event significantly predicted subtle (r = .50) and blatant (r = .53) prejudice. These findings indicate that prejudicial attitudes are linked to HPA-axis activity. Furthermore, when intergroup interactions are interpreted to be about individuals (and not so much about groups), experienced threat (or its biological substrate) is less likely to relate to prejudice. This conclusion is discussed in terms of recent insights from social neuroscience.

  18. Clinical responses to ERK inhibition in BRAFV600E-mutant colorectal cancer predicted using a computational model.

    Science.gov (United States)

    Kirouac, Daniel C; Schaefer, Gabriele; Chan, Jocelyn; Merchant, Mark; Orr, Christine; Huang, Shih-Min A; Moffat, John; Liu, Lichuan; Gadkar, Kapil; Ramanujan, Saroja

    2017-01-01

    Approximately 10% of colorectal cancers harbor BRAF V600E mutations, which constitutively activate the MAPK signaling pathway. We sought to determine whether ERK inhibitor (GDC-0994)-containing regimens may be of clinical benefit to these patients based on data from in vitro (cell line) and in vivo (cell- and patient-derived xenograft) studies of cetuximab (EGFR), vemurafenib (BRAF), cobimetinib (MEK), and GDC-0994 (ERK) combinations. Preclinical data was used to develop a mechanism-based computational model linking cell surface receptor (EGFR) activation, the MAPK signaling pathway, and tumor growth. Clinical predictions of anti-tumor activity were enabled by the use of tumor response data from three Phase 1 clinical trials testing combinations of EGFR, BRAF, and MEK inhibitors. Simulated responses to GDC-0994 monotherapy (overall response rate = 17%) accurately predicted results from a Phase 1 clinical trial regarding the number of responding patients (2/18) and the distribution of tumor size changes ("waterfall plot"). Prospective simulations were then used to evaluate potential drug combinations and predictive biomarkers for increasing responsiveness to MEK/ERK inhibitors in these patients.

  19. Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia.

    Science.gov (United States)

    Dang-Vu, Thien Thanh; Hatch, Benjamin; Salimi, Ali; Mograss, Melodee; Boucetta, Soufiane; O'Byrne, Jordan; Brandewinder, Marie; Berthomier, Christian; Gouin, Jean-Philippe

    2017-11-01

    While cognitive-behavioral therapy for insomnia constitutes the first-line treatment for chronic insomnia, only few reports have investigated how sleep architecture relates to response to this treatment. In this pilot study, we aimed to determine whether pre-treatment sleep spindle density predicts treatment response to cognitive-behavioral therapy for insomnia. Twenty-four participants with chronic primary insomnia participated in a 6-week cognitive-behavioral therapy for insomnia performed in groups of 4-6 participants. Treatment response was assessed using the Pittsburgh Sleep Quality Index and the Insomnia Severity Index measured at pre- and post-treatment, and at 3- and 12-months' follow-up assessments. Secondary outcome measures were extracted from sleep diaries over 7 days and overnight polysomnography, obtained at pre- and post-treatment. Spindle density during stage N2-N3 sleep was extracted from polysomnography at pre-treatment. Hierarchical linear modeling analysis assessed whether sleep spindle density predicted response to cognitive-behavioral therapy. After adjusting for age, sex, and education level, lower spindle density at pre-treatment predicted poorer response over the 12-month follow-up, as reflected by a smaller reduction in Pittsburgh Sleep Quality Index over time. Reduced spindle density also predicted lower improvements in sleep diary sleep efficiency and wake after sleep onset immediately after treatment. There were no significant associations between spindle density and changes in the Insomnia Severity Index or polysomnography variables over time. These preliminary results suggest that inter-individual differences in sleep spindle density in insomnia may represent an endogenous biomarker predicting responsiveness to cognitive-behavioral therapy. Insomnia with altered spindle activity might constitute an insomnia subtype characterized by a neurophysiological vulnerability to sleep disruption associated with impaired responsiveness to

  20. Challenges and progress in predicting biological responses to incorporated radioactivity

    International Nuclear Information System (INIS)

    Howell, R. W.; Neti, P. V. S. V.; Pinto, M.; Gerashchenko, B. I.; Narra, V. R.; Azzam, E. I.

    2006-01-01

    Prediction of risks and therapeutic outcome in nuclear medicine largely rely on calculation of the absorbed dose. Absorbed dose specification is complex due to the wide variety of radiations emitted, non-uniform activity distribution, biokinetics, etc. Conventional organ absorbed dose estimates assumed that radioactivity is distributed uniformly throughout the organ. However, there have been dramatic improvements in dosimetry models that reflect the substructure of organs as well as tissue elements within them. These models rely on improved nuclear medicine imaging capabilities that facilitate determination of activity within voxels that represent tissue elements of ∼0.2-1 cm 3 . However, even these improved approaches assume that all cells within the tissue element receive the same dose. The tissue element may be comprised of a variety of cells having different radiosensitivities and different incorporated radioactivity. Furthermore, the extent to which non-uniform distributions of radioactivity within a small tissue element impact the absorbed dose distribution is strongly dependent on the number, type, and energy of the radiations emitted by the radionuclide. It is also necessary to know whether the dose to a given cell arises from radioactive decays within itself (self-dose) or decays in surrounding cells (cross-dose). Cellular response to self-dose can be considerably different than its response to cross-dose from the same radiopharmaceutical. Bystander effects can also play a role in the response. Evidence shows that even under conditions of 'uniform' distribution of radioactivity, a combination of organ dosimetry, voxel dosimetry and dosimetry at the cellular and multicellular levels can be required to predict response. (authors)

  1. Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

    Science.gov (United States)

    Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

    2016-05-01

    Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

  2. Neural activity to a partner's facial expression predicts self-regulation after conflict

    Science.gov (United States)

    Hooker, Christine I.; Gyurak, Anett; Verosky, Sara; Miyakawa, Asako; Ayduk, Özlem

    2009-01-01

    Introduction Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to the regulation of emotional experience in response to lab-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk-factor for mood and behavior problems after an interpersonal stressor. However, it remains unclear whether LPFC activity to a lab-based affective challenge predicts self-regulation in real-life. Method We investigated whether LPFC activity to a lab-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During an fMRI scan, healthy, adult participants in committed, dating relationships (N = 27) viewed positive, negative, and neutral facial expressions of their partners. In an online daily-diary, participants reported conflict occurrence, level of negative mood, rumination, and substance-use. Results LPFC activity in response to the lab-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to the change in mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted the change in mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance-use. Conclusions Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. PMID:20004365

  3. Neural activity to a partner's facial expression predicts self-regulation after conflict.

    Science.gov (United States)

    Hooker, Christine I; Gyurak, Anett; Verosky, Sara C; Miyakawa, Asako; Ayduk, Ozlem

    2010-03-01

    Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to emotion regulation in response to laboratory-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk factor for mood and behavior problems after an interpersonal conflict. However, it remains unclear whether LPFC activity to a laboratory-based affective challenge predicts self-regulation in real life. We investigated whether LPFC activity to a laboratory-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During a functional magnetic resonance imaging scan, healthy, adult participants in committed relationships (n = 27) viewed positive, negative, and neutral facial expressions of their partners. In a three-week online daily diary, participants reported conflict occurrence, level of negative mood, rumination, and substance use. LPFC activity in response to the laboratory-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance use. Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. Copyright 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  4. The Cortisol Response to Anticipated Intergroup Interactions Predicts Self-Reported Prejudice

    Science.gov (United States)

    Bijleveld, Erik; Scheepers, Daan; Ellemers, Naomi

    2012-01-01

    Objectives While prejudice has often been shown to be rooted in experiences of threat, the biological underpinnings of this threat–prejudice association have received less research attention. The present experiment aims to test whether activations of the hypothalamus-pituitary-adrenal (HPA) axis, due to anticipated interactions with out-group members, predict self-reported prejudice. Moreover, we explore potential moderators of this relationship (i.e., interpersonal similarity; subtle vs. blatant prejudice). Methodology/Principal findings Participants anticipated an interaction with an out-group member who was similar or dissimilar to the self. To index HPA activation, cortisol responses to this event were measured. Then, subtle and blatant prejudices were measured via questionnaires. Findings indicated that only when people anticipated an interaction with an out-group member who was dissimilar to the self, their cortisol response to this event significantly predicted subtle (r = .50) and blatant (r = .53) prejudice. Conclusions These findings indicate that prejudicial attitudes are linked to HPA-axis activity. Furthermore, when intergroup interactions are interpreted to be about individuals (and not so much about groups), experienced threat (or its biological substrate) is less likely to relate to prejudice. This conclusion is discussed in terms of recent insights from social neuroscience. PMID:22442709

  5. Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

    Science.gov (United States)

    Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

    2013-12-01

    Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

  6. Climate modelling, uncertainty and responses to predictions of change

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    1996-01-01

    Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can't yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes

  7. Failure of 111In-labeled bleomycin tumor scanning to predict response to bleomycin (NSC-125066) treatment

    International Nuclear Information System (INIS)

    Jones, S.E.; Salmon, S.E.; Durie, B.G.M.

    1974-01-01

    The question of whether or not 111 In-labeled bleomycin is predictive of the response of tumors to bleomycin treatment is answered in the negative. The real test of the value of labeled bleomycin as a predictor of response will be possible only when a tightly labeled bleomycin with fully preserved biologic activity is synthesized. The negative results of this study do not invalidate further investigations of the predictive values of labeled anticancer drugs

  8. Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

    Science.gov (United States)

    Limongi, Roberto; Silva, Angélica M

    2016-11-01

    The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

  9. Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures

    Science.gov (United States)

    Ye, Zheng; Rae, Charlotte L.; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle‐Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R.; Maxwell, Helen; Sahakian, Barbara J.; Barker, Roger A.; Robbins, Trevor W.

    2016-01-01

    Abstract Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double‐blind randomized three‐way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion‐weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave‐one‐out cross‐validation (LOOCV) to predict patients’ responses in terms of improved stopping efficiency. We identified two optimal models: (1) a “clinical” model that predicted the response of an individual patient with 77–79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion‐weighted imaging scan; and (2) a “mechanistic” model that explained the behavioral response with 85% accuracy for each drug, using drug‐induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. Hum Brain Mapp 37:1026–1037

  10. Reward System Activation in Response to Alcohol Advertisements Predicts College Drinking.

    Science.gov (United States)

    Courtney, Andrea L; Rapuano, Kristina M; Sargent, James D; Heatherton, Todd F; Kelley, William M

    2018-01-01

    In this study, we assess whether activation of the brain's reward system in response to alcohol advertisements is associated with college drinking. Previous research has established a relationship between exposure to alcohol marketing and underage drinking. Within other appetitive domains, the relationship between cue exposure and behavioral enactment is known to rely on activation of the brain's reward system. However, the relationship between neural activation to alcohol advertisements and alcohol consumption has not been studied in a nondisordered population. In this cross-sectional study, 53 college students (32 women) completed a functional magnetic resonance imaging scan while viewing alcohol, food, and control (car and technology) advertisements. Afterward, they completed a survey about their alcohol consumption (including frequency of drinking, typical number of drinks consumed, and frequency of binge drinking) over the previous month. In 43 participants (24 women) meeting inclusion criteria, viewing alcohol advertisements elicited activation in the left orbitofrontal cortex and bilateral ventral striatum-regions of the reward system that typically activate to other appetitive rewards and relate to consumption behaviors. Moreover, the level of self-reported drinking correlated with the magnitude of activation in the left orbitofrontal cortex. Results suggest that alcohol cues are processed within the reward system in a way that may motivate drinking behavior.

  11. Performance of immunological response in predicting virological failure.

    Science.gov (United States)

    Ingole, Nayana; Mehta, Preeti; Pazare, Amar; Paranjpe, Supriya; Sarkate, Purva

    2013-03-01

    In HIV-infected individuals on antiretroviral therapy (ART), the decision on when to switch from first-line to second-line therapy is dictated by treatment failure, and this can be measured in three ways: clinically, immunologically, and virologically. While viral load (VL) decreases and CD4 cell increases typically occur together after starting ART, discordant responses may be seen. Hence the current study was designed to determine the immunological and virological response to ART and to evaluate the utility of immunological response to predict virological failure. All treatment-naive HIV-positive individuals aged >18 years who were eligible for ART were enrolled and assessed at baseline, 6 months, and 12 months clinically and by CD4 cell count and viral load estimations. The patients were categorized as showing concordant favorable (CF), immunological only (IO), virological only (VO), and concordant unfavorable responses (CU). The efficiency of immunological failure to predict virological failure was analyzed across various levels of virological failure (VL>50, >500, and >5,000 copies/ml). At 6 months, 87(79.81%), 7(5.5%), 13 (11.92%), and 2 (1.83%) patients and at 12 months 61(69.3%), 9(10.2%), 16 (18.2%), and 2 (2.3%) patients had CF, IO, VO, and CU responses, respectively. Immunological failure criteria had a very low sensitivity (11.1-40%) and positive predictive value (8.3-25%) to predict virological failure. Immunological criteria do not accurately predict virological failure resulting in significant misclassification of therapeutic responses. There is an urgent need for inclusion of viral load testing in the initiation and monitoring of ART.

  12. Predicting response to epigenetic therapy

    DEFF Research Database (Denmark)

    Treppendahl, Marianne B; Sommer Kristensen, Lasse; Grønbæk, Kirsten

    2014-01-01

    of good pretreatment predictors of response is of great value. Many clinical parameters and molecular targets have been tested in preclinical and clinical studies with varying results, leaving room for optimization. Here we provide an overview of markers that may predict the efficacy of FDA- and EMA...

  13. Prediction of psilocybin response in healthy volunteers.

    Science.gov (United States)

    Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X

    2012-01-01

    Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin.

  14. Prediction of psilocybin response in healthy volunteers.

    Directory of Open Access Journals (Sweden)

    Erich Studerus

    Full Text Available Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin.

  15. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  16. Utility of the whole-kidney and parenchymal time-activity curves for a prediction of diuretic response

    International Nuclear Information System (INIS)

    Samal, M.; Mostbeck, A.; Bergmann, H.; Nimmon, C.C.; Staudenherz, A.; Dudczak, R.

    2002-01-01

    Full text: In a retrospective study, MAG3 dynamic renal data (90 kidneys in 57 children) have been analyzed with the aim to test a prediction of diuretic response. Whole-kidney (WK) and parenchymal (PA) curves were extracted from 20 min pre-diuretic phase using standard and fuzzy ROIs. Peak time (PT), half time (HT), ratio of the curve value in 20th min to the curve maximum (RM), mean transit time (TT), and output efficiency (OE) were calculated for each curve. With PA curves, also the transit time index (PI) was calculated. The curve parameters were compared with the maximum elimination rate of urine after diuretic (EM) using paired correlation and Fisher's linear discriminate function. The highest correlation was found between ln EM and OE-PA (0.61), RM-PA (-0.58), TT-PA (-0.57), and PI (-0.57). Best diagnostic accuracy in prediction of EM ≤ 7 % (a sign of obstruction) was obtained with OE-PA (87 %), PI (87 %), and both PT-PA and RM-PA (83 %). Parameters of WK curves had higher sensitivity, those of PA curves higher specificity. Most parameters had a high predictive value of negative result (NPV > 90 %) but low predictive value of positive result (PPV < 50 %). Best discrimination of low EM was obtained with a combination of both WK and PA parameters (diagnostic accuracy of 90 %). Using PA curves in kidneys with late PT-WK made possible to increase the diagnostic accuracy from 70 - 80 % (with WK parameters only) to 95 %. Our results demonstrate that PA curves carry additional clinical information and may help to predict and Interpret a diuretic response especially in kidneys with late peak of the WK curves. (author)

  17. The Brain Activity in Brodmann Area 17: A Potential Bio-Marker to Predict Patient Responses to Antiepileptic Drugs.

    Directory of Open Access Journals (Sweden)

    Yida Hu

    Full Text Available In this study, we aimed to predict newly diagnosed patient responses to antiepileptic drugs (AEDs using resting-state functional magnetic resonance imaging tools to explore changes in spontaneous brain activity. We recruited 21 newly diagnosed epileptic patients, 8 drug-resistant (DR patients, 11 well-healed (WH patients, and 13 healthy controls. After a 12-month follow-up, 11 newly diagnosed epileptic patients who showed a poor response to AEDs were placed into the seizures uncontrolled (SUC group, while 10 patients were enrolled in the seizure-controlled (SC group. By calculating the amplitude of fractional low-frequency fluctuations (fALFF of blood oxygen level-dependent signals to measure brain activity during rest, we found that the SUC patients showed increased activity in the bilateral occipital lobe, particularly in the cuneus and lingual gyrus compared with the SC group and healthy controls. Interestingly, DR patients also showed increased activity in the identical cuneus and lingual gyrus regions, which comprise Brodmann's area 17 (BA17, compared with the SUC patients; however, these abnormalities were not observed in SC and WH patients. The receiver operating characteristic (ROC curves indicated that the fALFF value of BA17 could differentiate SUC patients from SC patients and healthy controls with sufficient sensitivity and specificity prior to the administration of medication. Functional connectivity analysis was subsequently performed to evaluate the difference in connectivity between BA17 and other brain regions in the SUC, SC and control groups. Regions nearby the cuneus and lingual gyrus were found positive connectivity increased changes or positive connectivity changes with BA17 in the SUC patients, while remarkably negative connectivity increased changes or positive connectivity decreased changes were found in the SC patients. Additionally, default mode network (DMN regions showed negative connectivity increased changes or

  18. Response surface optimisation for activation of bentonite with microwave irradiation

    Directory of Open Access Journals (Sweden)

    Rožić Ljiljana S.

    2011-01-01

    Full Text Available In this study, the statistical design of the experimental method was applied on the acid activation process of bentonite with microwave irradiation. The influence of activation parameters (time, acid normality and microwave heating power on the selected process response of the activated bentonite samples was studied. The specific surface area was chosen for the process response, because the chemical, surface and structural properties of the activated clay determine and limit its potential applications. The relationship of various process parameters with the specific surface area of bentonite was examined. A mathematical model was developed using a second-order response surface model (RSM with a central composite design incorporating the above mentioned process parameters. The mathematical model developed helped in predicting the variation in specific surface area of activated bentonite with time (5-21 min, acid normality (2-7 N and microwave heating power (63-172 W. The calculated regression models were found to be statistically significant at the required range and presented little variability. Furthermore, high values of R2 (0.957 and R2 (adjusted (0.914 indicate a high dependence and correlation between the observed and the predicted values of the response. These high values also indicate that about 96% of the result of the total variation can be explained by this model. In addition, the model shows that increasing the time and acid normality improves the textural properties of bentonites, resulting in increased specific surface area. This model also can be useful for setting an optimum value of the activation parameters for achieving the maximum specific surface area. An optimum specific surface area of 142 m2g-1 was achieved with an acid normality of 5.2 N, activation time of 7.38 min and microwave power of 117 W. Acid activation of bentonite was found to occur faster with microwave irradiation than with conventional heating. Microwave

  19. Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

    Science.gov (United States)

    Marasco, Addolorata; de Paris, Alessandro; Migliore, Michele

    2016-04-01

    The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration.

  20. Neural response to pictorial health warning labels can predict smoking behavioral change.

    Science.gov (United States)

    Riddle, Philip J; Newman-Norlund, Roger D; Baer, Jessica; Thrasher, James F

    2016-11-01

    In order to improve our understanding of how pictorial health warning labels (HWLs) influence smoking behavior, we examined whether brain activity helps to explain smoking behavior above and beyond self-reported effectiveness of HWLs. We measured the neural response in the ventromedial prefrontal cortex (vmPFC) and the amygdala while adult smokers viewed HWLs. Two weeks later, participants' self-reported smoking behavior and biomarkers of smoking behavior were reassessed. We compared multiple models predicting change in self-reported smoking behavior (cigarettes per day [CPD]) and change in a biomarkers of smoke exposure (expired carbon monoxide [CO]). Brain activity in the vmPFC and amygdala not only predicted changes in CO, but also accounted for outcome variance above and beyond self-report data. Neural data were most useful in predicting behavioral change as quantified by the objective biomarker (CO). This pattern of activity was significantly modulated by individuals' intention to quit. The finding that both cognitive (vmPFC) and affective (amygdala) brain areas contributed to these models supports the idea that smokers respond to HWLs in a cognitive-affective manner. Based on our findings, researchers may wish to consider using neural data from both cognitive and affective networks when attempting to predict behavioral change in certain populations (e.g. cigarette smokers). © The Author (2016). Published by Oxford University Press.

  1. Accuracies of fecal calprotectin, lactoferrin, M2-pyruvate kinase, neopterin and zonulin to predict the response to infliximab in ulcerative colitis.

    Science.gov (United States)

    Frin, Anne-Claire; Filippi, Jérôme; Boschetti, Gilles; Flourie, Bernard; Drai, Jocelyne; Ferrari, Patricia; Hebuterne, Xavier; Nancey, Stéphane

    2017-01-01

    Fecal markers might predict the response to anti-TNFα in ulcerative colitis (UC). To compare the performance of fecal calprotectin (fCal), lactoferrin (fLact), M2-PK (fM2-PK), neopterin (fNeo), and zonulin (fZon) to predict the response to therapy in active UC patients. Disease activity from 31 consecutive patients with an active UC, treated with infliximab (IFX) was assessed by the Mayo score at baseline and at week 14 and by the partial Mayo score at W52 and stool samples collected for fecal marker measurements at W0, W2, and W14. At W14, 19 patients (61%) were responders to IFX induction. The median levels of fCal, fLact and fM2-PK drop dramatically from baseline to W14 in clinical responders. At W2, fM2-PK, fLact and fCal levels predicted accurately the response to IFX induction. At W14, fLact, fCal, and fM2-PK were individually reliable markers to predict sustained response at W52. The performances of fNeo and fZon were weaker in this setting. The performance of fM2-PK at W2 to predict response to induction therapy with IFX was superior to that of fLact and fCal, whereas monitoring fLact was the best tool to predict adequately the course of the disease at one year under maintenance IFX in UC. Copyright © 2016. Published by Elsevier Ltd.

  2. Metabolic activity by {sup 18}F-FDG-PET/CT is predictive of early response after nivolumab in previously treated NSCLC

    Energy Technology Data Exchange (ETDEWEB)

    Kaira, Kyoichi; Altan, Bolag [Gunma University Graduate School of Medicine, Department of Oncology Clinical Development, Maebashi, Gunma (Japan); Higuchi, Tetsuya; Arisaka, Yukiko; Tokue, Azusa [Gunma University Graduate School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Maebashi, Gunma (Japan); Naruse, Ichiro [Hidaka Hospital, Department of Respiratory Medicine, Hidaka (Japan); Suda, Satoshi [Hidaka Hospital, Department of Radiology, Hidaka (Japan); Mogi, Akira; Shimizu, Kimihiro [Gunma University Graduate School of Medicine, Department of General Surgical Science, Maebashi, Gunma (Japan); Sunaga, Noriaki [Gunma University Hospital, Oncology Center, Maebashi, Gunma (Japan); Hisada, Takeshi [Gunma University Hospital, Department of Respiratory Medicine, Maebashi, Gunma (Japan); Kitano, Shigehisa [National Cancer Center Hospital, Department of Experimental Therapeutics, Tokyo (Japan); Obinata, Hideru; Asao, Takayuki [Gunma University Initiative for Advanced Research, Big Data Center for Integrative Analysis, Maebashi, Gunma (Japan); Yokobori, Takehiko [Gunma University Initiative for Advanced Research, Division of Integrated Oncology Research, Research Program for Omics-based Medical Science, Maebashi, Gunma (Japan); Mori, Keita [Clinical Research Support Center, Shizuoka Cancer Center, Suntou-gun (Japan); Nishiyama, Masahiko [Gunma University Graduate School of Medicine, Department of Molecular Pharmacology and Oncology, Maebashi, Gunma (Japan); Tsushima, Yoshihito [Gunma University Graduate School of Medicine, Department of Diagnostic Radiology and Nuclear Medicine, Maebashi, Gunma (Japan); Gunma University Initiative for Advanced Research (GIAR), Research Program for Diagnostic and Molecular Imaging, Division of Integrated Oncology Research, Maebashi, Gunma (Japan)

    2018-01-15

    Nivolumab, an anti-programmed death-1 (PD-1) antibody, is administered in patients with previously treated non-small cell lung cancer. However, little is known about the established biomarker predicting the efficacy of nivolumab. Here, we conducted a preliminary study to investigate whether {sup 18}F-FDG-PET/CT could predict the therapeutic response of nivolumab at the early phase. Twenty-four patients were enrolled in this study. {sup 18}F-FDG-PET/CT was carried out before and 1 month after nivolumab therapy. SUV{sub max}, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were calculated. Immunohistochemical analysis of PD-L1 expression and tumour-infiltrating lymphocytes was conducted. Among all patients, a partial metabolic response to nivolumab was observed in 29% on SUV{sub max}, 25% on MTV, and 33% on TLG, whereas seven (29%) patients achieved a partial response (PR) based on RECIST v1.1. The predictive probability of PR (100% vs. 29%, p = 0.021) and progressive disease (100% vs. 22.2%, p = 0.002) at 1 month after nivolumab initiation was significantly higher in {sup 18}F-FDG on PET/CT than in CT scans. Multivariate analysis confirmed that {sup 18}F-FDG uptake after administration of nivolumab was an independent prognostic factor. PD-L1 expression and nivolumab plasma concentration could not precisely predict the early therapeutic efficacy of nivolumab. Metabolic response by {sup 18}F-FDG was effective in predicting efficacy and survival at 1 month after nivolumab treatment. (orig.)

  3. Dopamine reward prediction error responses reflect marginal utility.

    Science.gov (United States)

    Stauffer, William R; Lak, Armin; Schultz, Wolfram

    2014-11-03

    Optimal choices require an accurate neuronal representation of economic value. In economics, utility functions are mathematical representations of subjective value that can be constructed from choices under risk. Utility usually exhibits a nonlinear relationship to physical reward value that corresponds to risk attitudes and reflects the increasing or decreasing marginal utility obtained with each additional unit of reward. Accordingly, neuronal reward responses coding utility should robustly reflect this nonlinearity. In two monkeys, we measured utility as a function of physical reward value from meaningful choices under risk (that adhered to first- and second-order stochastic dominance). The resulting nonlinear utility functions predicted the certainty equivalents for new gambles, indicating that the functions' shapes were meaningful. The monkeys were risk seeking (convex utility function) for low reward and risk avoiding (concave utility function) with higher amounts. Critically, the dopamine prediction error responses at the time of reward itself reflected the nonlinear utility functions measured at the time of choices. In particular, the reward response magnitude depended on the first derivative of the utility function and thus reflected the marginal utility. Furthermore, dopamine responses recorded outside of the task reflected the marginal utility of unpredicted reward. Accordingly, these responses were sufficient to train reinforcement learning models to predict the behaviorally defined expected utility of gambles. These data suggest a neuronal manifestation of marginal utility in dopamine neurons and indicate a common neuronal basis for fundamental explanatory constructs in animal learning theory (prediction error) and economic decision theory (marginal utility). Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Predicting fluid responsiveness with transthoracic echocardiography is not yet evidence based

    DEFF Research Database (Denmark)

    Wetterslev, M; Haase, N; Johansen, R R

    2013-01-01

    an integrated tool in the intensive care unit, this systematic review examined studies evaluating the predictive value of TTE for fluid responsiveness. In October 2012, we searched Pubmed, EMBASE and Web of Science for studies evaluating the predictive value of TTE-derived variables for fluid responsiveness...... responsiveness. Of the 4294 evaluated citations, only one study fully met our inclusion criteria. In this study, the predictive value of variations in inferior vena cava diameter (> 16%) for fluid responsiveness was moderate with sensitivity of 71% [95% confidence interval (CI) 44-90], specificity of 100% (95......% CI 73-100) and an area under the receiver operating curve of 0.90 (95% CI 0.73-0.98). Only one study of TTE-based methods fulfilled the criteria for valid assessment of fluid responsiveness. Before recommending the use of TTE in predicting fluid responsiveness, proper evaluation including...

  5. CERAPP: Collaborative estrogen receptor activity prediction project

    DEFF Research Database (Denmark)

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra

    2016-01-01

    ). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. oBjectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project...... States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical......: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. conclusion: This project demonstrated...

  6. Predicting clinical outcome using brain activation associated with set-shifting and central coherence skills in Anorexia Nervosa.

    Science.gov (United States)

    Garrett, Amy S; Lock, James; Datta, Nandini; Beenhaker, Judy; Kesler, Shelli R; Reiss, Allan L

    2014-10-01

    Patients with Anorexia Nervosa (AN) have neuropsychological deficits in Set-Shifting (SS) and central coherence (CC) consistent with an inflexible thinking style and overly detailed processing style, respectively. This study investigates brain activation during SS and CC tasks in patients with AN and tests whether this activation is a biomarker that predicts response to treatment. FMRI data were collected from 21 females with AN while performing an SS task (the Wisconsin Card Sort) and a CC task (embedded figures), and used to predict outcome following 16 weeks of treatment (either 16 weeks of cognitive behavioral therapy or 8 weeks cognitive remediation therapy followed by 8 weeks of cognitive behavioral therapy). Significant activation during the SS task included bilateral dorsolateral and ventrolateral prefrontal cortex and left anterior middle frontal gyrus. Higher scores on the neuropsychological test of SS (measured outside the scanner at baseline) were correlated with greater DLPFC and VLPFC/insula activation. Improvements in SS following treatment were significantly predicted by a combination of low VLPFC/insula and high anterior middle frontal activation (R squared = .68, p = .001). For the CC task, visual and parietal cortical areas were activated, but were not significantly correlated with neuropsychological measures of CC and did not predict outcome. Cognitive flexibility requires the support of several prefrontal cortex resources. As previous studies suggest that the VLPFC is important for selecting context-appropriate responses, patients who have difficulties with this skill may benefit the most from cognitive therapy with or without cognitive remediation therapy. The ability to sustain inhibition of an unwanted response, subserved by the anterior middle frontal gyrus, is a cognitive feature that predicts favorable outcome to cognitive treatment. CC deficits may not be an effective predictor of clinical outcome. Copyright © 2014 Elsevier Ltd. All

  7. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

    Science.gov (United States)

    Cheval, Boris; Sarrazin, Philippe; Pelletier, Luc

    2014-01-01

    Understanding the determinants of non-exercise activity thermogenesis (NEAT) is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91) completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA) and sedentary behaviors (IASB). Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a) positively predicted by IAPA, (b) negatively predicted by IASB, and (c) was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

  8. Error-related anterior cingulate cortex activity and the prediction of conscious error awareness

    Directory of Open Access Journals (Sweden)

    Catherine eOrr

    2012-06-01

    Full Text Available Research examining the neural mechanisms associated with error awareness has consistently identified dorsal anterior cingulate activity (ACC as necessary but not predictive of conscious error detection. Two recent studies (Steinhauser and Yeung, 2010; Wessel et al. 2011 have found a contrary pattern of greater dorsal ACC activity (in the form of the error-related negativity during detected errors, but suggested that the greater activity may instead reflect task influences (e.g., response conflict, error probability and or individual variability (e.g., statistical power. We re-analyzed fMRI BOLD data from 56 healthy participants who had previously been administered the Error Awareness Task, a motor Go/No-go response inhibition task in which subjects make errors of commission of which they are aware (Aware errors, or unaware (Unaware errors. Consistent with previous data, the activity in a number of cortical regions was predictive of error awareness, including bilateral inferior parietal and insula cortices, however in contrast to previous studies, including our own smaller sample studies using the same task, error-related dorsal ACC activity was significantly greater during aware errors when compared to unaware errors. While the significantly faster RT for aware errors (compared to unaware was consistent with the hypothesis of higher response conflict increasing ACC activity, we could find no relationship between dorsal ACC activity and the error RT difference. The data suggests that individual variability in error awareness is associated with error-related dorsal ACC activity, and therefore this region may be important to conscious error detection, but it remains unclear what task and individual factors influence error awareness.

  9. Basal blood DHEA-S/cortisol levels predicts EMDR treatment response in adolescents with PTSD.

    Science.gov (United States)

    Usta, Mirac Baris; Gumus, Yusuf Yasin; Say, Gokce Nur; Bozkurt, Abdullah; Şahin, Berkan; Karabekiroğlu, Koray

    2018-04-01

    In literature, recent evidence has shown that the hypothalamic-pituitary-adrenal (HPA) axis can be dysregulated in patients with post-traumatic stress disorder (PTSD) and HPA axis hormones may predict the psychotherapy treatment response in patients with PTSD. In this study, it was aimed to investigate changing cortisol and DHEA-S levels post-eye movement desensitization and reprocessing (EMDR) therapy and the relationship between treatment response and basal cortisol, and DHEA-S levels before treatment. The study group comprised 40 adolescents (age, 12-18 years) with PTSD. The PTSD symptoms were assessed using the Child Depression Inventory (CDI) and Child Post-traumatic Stress Reaction Index (CPSRI) and the blood cortisol and DHEA-S were measured with the chemiluminescence method before and after treatment. A maximum of six sessions of EMDR therapy were conducted by an EMDR level-1 trained child psychiatry resident. Treatment response was measured by the pre- to post-treatment decrease in self-reported and clinical PTSD severity. Pre- and post-treatment DHEA-S and cortisol levels did not show any statistically significant difference. Pre-treatment CDI scores were negatively correlated with pre-treatment DHEA-S levels (r: -0.39). ROC analysis demonstrated that the DHEA-S/cortisol ratio predicts treatment response at a medium level (AUC: 0.703, p: .030, sensitivity: 0.65, specificity: 0.86). The results of this study suggested that the DHEA-S/cortisol ratio may predict treatment response in adolescents with PTSD receiving EMDR therapy. The biochemical parameter of HPA-axis activity appears to be an important predictor of positive clinical response in adolescent PTSD patients, and could be used in clinical practice to predict PTSD treatment in the future.

  10. Sound induced activity in voice sensitive cortex predicts voice memory ability

    Directory of Open Access Journals (Sweden)

    Rebecca eWatson

    2012-04-01

    Full Text Available The ‘temporal voice areas’ (TVAs (Belin et al., 2000 of the human brain show greater neuronal activity in response to human voices than to other categories of nonvocal sounds. However, a direct link between TVA activity and voice perceptionbehaviour has not yet been established. Here we show that a functional magnetic resonance imaging (fMRI measure of activity in the TVAs predicts individual performance at a separately administered voice memory test. This relation holds whengeneral sound memory ability is taken into account. These findings provide the first evidence that the TVAs are specifically involved in voice cognition.

  11. Metabolomics biomarkers to predict acamprosate treatment response in alcohol-dependent subjects.

    Science.gov (United States)

    Hinton, David J; Vázquez, Marely Santiago; Geske, Jennifer R; Hitschfeld, Mario J; Ho, Ada M C; Karpyak, Victor M; Biernacka, Joanna M; Choi, Doo-Sup

    2017-05-31

    Precision medicine for alcohol use disorder (AUD) allows optimal treatment of the right patient with the right drug at the right time. Here, we generated multivariable models incorporating clinical information and serum metabolite levels to predict acamprosate treatment response. The sample of 120 patients was randomly split into a training set (n = 80) and test set (n = 40) five independent times. Treatment response was defined as complete abstinence (no alcohol consumption during 3 months of acamprosate treatment) while nonresponse was defined as any alcohol consumption during this period. In each of the five training sets, we built a predictive model using a least absolute shrinkage and section operator (LASSO) penalized selection method and then evaluated the predictive performance of each model in the corresponding test set. The models predicted acamprosate treatment response with a mean sensitivity and specificity in the test sets of 0.83 and 0.31, respectively, suggesting our model performed well at predicting responders, but not non-responders (i.e. many non-responders were predicted to respond). Studies with larger sample sizes and additional biomarkers will expand the clinical utility of predictive algorithms for pharmaceutical response in AUD.

  12. An observation on the variance of a predicted response in ...

    African Journals Online (AJOL)

    ... these properties and computational simplicity. To avoid over fitting, along with the obvious advantage of having a simpler equation, it is shown that the addition of a variable to a regression equation does not reduce the variance of a predicted response. Key words: Linear regression; Partitioned matrix; Predicted response ...

  13. Influential Factors for Accurate Load Prediction in a Demand Response Context

    DEFF Research Database (Denmark)

    Wollsen, Morten Gill; Kjærgaard, Mikkel Baun; Jørgensen, Bo Nørregaard

    2016-01-01

    Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence....... Next, the time of day that is being predicted greatly influence the prediction which is related to the weather pattern. By presenting these results we hope to improve the modeling of building loads and algorithms for Demand Response planning.......Accurate prediction of a buildings electricity load is crucial to respond to Demand Response events with an assessable load change. However, previous work on load prediction lacks to consider a wider set of possible data sources. In this paper we study different data scenarios to map the influence...

  14. Prediction of Human Activity by Discovering Temporal Sequence Patterns.

    Science.gov (United States)

    Li, Kang; Fu, Yun

    2014-08-01

    Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

  15. Assessing Prediction Performance of Neoadjuvant Chemotherapy Response in Bladder Cancer

    OpenAIRE

    Cremer, Chris

    2016-01-01

    Neoadjuvant chemotherapy is a treatment routinely prescribed to patients diagnosed with muscle-invasive bladder cancer. Unfortunately, not all patients are responsive to this treatment and would greatly benefit from an accurate prediction of their expected response to chemotherapy. In this project, I attempt to develop a model that will predict response using tumour microarray data. I show that using my dataset, every method is insufficient at accurately classifying responders and non-respond...

  16. Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III alpha Polymerase Activity.

    Science.gov (United States)

    Parasuram, Ramya; Coulther, Timothy A; Hollander, Judith M; Keston-Smith, Elise; Ondrechen, Mary Jo; Beuning, Penny J

    2018-02-20

    The process of DNA replication is carried out with high efficiency and accuracy by DNA polymerases. The replicative polymerase in E. coli is DNA Pol III, which is a complex of 10 different subunits that coordinates simultaneous replication on the leading and lagging strands. The 1160-residue Pol III alpha subunit is responsible for the polymerase activity and copies DNA accurately, making one error per 10 5 nucleotide incorporations. The goal of this research is to determine the residues that contribute to the activity of the polymerase subunit. Homology modeling and the computational methods of THEMATICS and POOL were used to predict functionally important amino acid residues through their computed chemical properties. Site-directed mutagenesis and biochemical assays were used to validate these predictions. Primer extension, steady-state single-nucleotide incorporation kinetics, and thermal denaturation assays were performed to understand the contribution of these residues to the function of the polymerase. This work shows that the top 15 residues predicted by POOL, a set that includes the three previously known catalytic aspartate residues, seven remote residues, plus five previously unexplored first-layer residues, are important for function. Six previously unidentified residues, R362, D405, K553, Y686, E688, and H760, are each essential to Pol III activity; three additional residues, Y340, R390, and K758, play important roles in activity.

  17. Response predictions using the observed autocorrelation function

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; H. Brodtkorb, Astrid; Jensen, Jørgen Juncher

    2018-01-01

    This article studies a procedure that facilitates short-time, deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine......-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input...... show that predictions can be successfully made in a time horizon corresponding to about 8-9 wave periods ahead of current time (the moment of action)....

  18. Simple regional strain pattern analysis to predict response to cardiac resynchronization therapy

    DEFF Research Database (Denmark)

    Risum, Niels; Jons, Christian; Olsen, Niels T

    2012-01-01

    A classical strain pattern of early contraction in one wall and prestretching of the opposing wall followed by late contraction has previously been associated with left bundle branch block (LBBB) activation and short-term response to cardiac resynchronization therapy (CRT). Aims of this study were...... to establish the long-term predictive value of an LBBB-related strain pattern and to identify changes in contraction patterns during short-term and long-term CRT....

  19. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

    Directory of Open Access Journals (Sweden)

    Boris Cheval

    Full Text Available Understanding the determinants of non-exercise activity thermogenesis (NEAT is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91 completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA and sedentary behaviors (IASB. Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a positively predicted by IAPA, (b negatively predicted by IASB, and (c was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

  20. Associations of Affective Responses During Free-Living Physical Activity and Future Physical Activity Levels: an Ecological Momentary Assessment Study.

    Science.gov (United States)

    Liao, Yue; Chou, Chih-Ping; Huh, Jimi; Leventhal, Adam; Dunton, Genevieve

    2017-08-01

    Affective response during physical activity may influence motivation to perform future physical activity behavior. However, affective response during physical activity is often assessed under controlled laboratory conditions. The current study used ecological momentary assessment (EMA) to capture affective responses during free-living physical activity performed by adults, and determined whether these affective responses predict future moderate-to-vigorous physical activity (MVPA) levels after 6 and 12 months. At baseline, electronic EMA surveys were randomly prompted across 4 days asking about current activities and affective states (e.g., happy, stressed, energetic, tired). Affective response during physical activity was operationalized as the level of positive or negative affect reported when concurrent physical activity (e.g., exercise or sports) was also reported. Data were available for 82 adults. Future levels of moderate-to-vigorous physical activity (MVPA) were measured using accelerometers, worn for seven consecutive days at 6 and 12 months after the baseline assessment. Feeling more energetic during physical activity was associated with performing more minutes of daily MVPA after both 6 and 12 months. Feeling less negative affect during physical activity was associated with engaging in more daily MVPA minutes after 12 months only. This study demonstrated how EMA can be used to capture affective responses during free-living physical activity. Results found that feelings more energetic and less negative during physical activity were associated with more future physical activity, suggesting that positive emotional benefits may reinforce behavior.

  1. Music-induced emotions can be predicted from a combination of brain activity and acoustic features.

    Science.gov (United States)

    Daly, Ian; Williams, Duncan; Hallowell, James; Hwang, Faustina; Kirke, Alexis; Malik, Asad; Weaver, James; Miranda, Eduardo; Nasuto, Slawomir J

    2015-12-01

    It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music. We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to r=0.234,pmusic induced emotions can be predicted by their neural activity and the properties of the music. Given the large amount of noise, non-stationarity, and non-linearity in both EEG and music, this is an encouraging result. Additionally, the combination of measures of brain activity and acoustic features describing the music played to our participants allows us to predict music-induced emotions with significantly higher accuracies than either feature type alone (p<0.01). Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Drug response prediction in high-risk multiple myeloma

    DEFF Research Database (Denmark)

    Vangsted, A J; Helm-Petersen, S; Cowland, J B

    2018-01-01

    from high-risk patients by GEP70 at diagnosis from Total Therapy 2 and 3A to predict the response by the DRP score of drugs used in the treatment of myeloma patients. The DRP score stratified patients further. High-risk myeloma with a predicted sensitivity to melphalan by the DRP score had a prolonged...

  3. Predicting and measuring fluid responsiveness with echocardiography

    Directory of Open Access Journals (Sweden)

    Ashley Miller

    2016-06-01

    Full Text Available Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart–lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid esuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately.

  4. Suprathreshold Heat Pain Response Predicts Activity-Related Pain, but Not Rest-Related Pain, in an Exercise-Induced Injury Model

    Science.gov (United States)

    Coronado, Rogelio A.; Simon, Corey B.; Valencia, Carolina; Parr, Jeffrey J.; Borsa, Paul A.; George, Steven Z.

    2014-01-01

    Exercise-induced injury models are advantageous for studying pain since the onset of pain is controlled and both pre-injury and post-injury factors can be utilized as explanatory variables or predictors. In these studies, rest-related pain is often considered the primary dependent variable or outcome, as opposed to a measure of activity-related pain. Additionally, few studies include pain sensitivity measures as predictors. In this study, we examined the influence of pre-injury and post-injury factors, including pain sensitivity, for induced rest and activity-related pain following exercise induced muscle injury. The overall goal of this investigation was to determine if there were convergent or divergent predictors of rest and activity-related pain. One hundred forty-three participants provided demographic, psychological, and pain sensitivity information and underwent a standard fatigue trial of resistance exercise to induce injury of the dominant shoulder. Pain at rest and during active and resisted shoulder motion were measured at 48- and 96-hours post-injury. Separate hierarchical models were generated for assessing the influence of pre-injury and post-injury factors on 48- and 96-hour rest-related and activity-related pain. Overall, we did not find a universal predictor of pain across all models. However, pre-injury and post-injury suprathreshold heat pain response (SHPR), a pain sensitivity measure, was a consistent predictor of activity-related pain, even after controlling for known psychological factors. These results suggest there is differential prediction of pain. A measure of pain sensitivity such as SHPR appears more influential for activity-related pain, but not rest-related pain, and may reflect different underlying processes involved during pain appraisal. PMID:25265560

  5. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

  6. Assays for predicting and monitoring responses to lung cancer immunotherapy

    International Nuclear Information System (INIS)

    Teixidó, Cristina; Karachaliou, Niki; González-Cao, Maria; Morales-Espinosa, Daniela; Rosell, Rafael

    2015-01-01

    Immunotherapy has become a key strategy for cancer treatment, and two immune checkpoints, namely, programmed cell death 1 (PD-1) and its ligand (PD-L1), have recently emerged as important targets. The interaction blockade of PD-1 and PD-L1 demonstrated promising activity and antitumor efficacy in early phase clinical trials for advanced solid tumors such as non-small cell lung cancer (NSCLC). Many cell types in multiple tissues express PD-L1 as well as several tumor types, thereby suggesting that the ligand may play important roles in inhibiting immune responses throughout the body. Therefore, PD-L1 is a critical immunomodulating component within the lung microenvironment, but the correlation between PD-L1 expression and prognosis is controversial. More evidence is required to support the use of PD-L1 as a potential predictive biomarker. Clinical trials have measured PD-L1 in tumor tissues by immunohistochemistry (IHC) with different antibodies, but the assessment of PD-L1 is not yet standardized. Some commercial antibodies lack specificity and their reproducibility has not been fully evaluated. Further studies are required to clarify the optimal IHC assay as well as to predict and monitor the immune responses of the PD-1/PD-L1 pathway

  7. Predicting behavioural responses to novel organisms: state-dependent detection theory.

    Science.gov (United States)

    Trimmer, Pete C; Ehlman, Sean M; Sih, Andrew

    2017-01-25

    Human activity alters natural habitats for many species. Understanding variation in animals' behavioural responses to these changing environments is critical. We show how signal detection theory can be used within a wider framework of state-dependent modelling to predict behavioural responses to a major environmental change: novel, exotic species. We allow thresholds for action to be a function of reserves, and demonstrate how optimal thresholds can be calculated. We term this framework 'state-dependent detection theory' (SDDT). We focus on behavioural and fitness outcomes when animals continue to use formerly adaptive thresholds following environmental change. In a simple example, we show that exposure to novel animals which appear dangerous-but are actually safe-(e.g. ecotourists) can have catastrophic consequences for 'prey' (organisms that respond as if the new organisms are predators), significantly increasing mortality even when the novel species is not predatory. SDDT also reveals that the effect on reproduction can be greater than the effect on lifespan. We investigate factors that influence the effect of novel organisms, and address the potential for behavioural adjustments (via evolution or learning) to recover otherwise reduced fitness. Although effects of environmental change are often difficult to predict, we suggest that SDDT provides a useful route ahead. © 2017 The Author(s).

  8. Predicting behavioural responses to novel organisms: state-dependent detection theory

    Science.gov (United States)

    Sih, Andrew

    2017-01-01

    Human activity alters natural habitats for many species. Understanding variation in animals' behavioural responses to these changing environments is critical. We show how signal detection theory can be used within a wider framework of state-dependent modelling to predict behavioural responses to a major environmental change: novel, exotic species. We allow thresholds for action to be a function of reserves, and demonstrate how optimal thresholds can be calculated. We term this framework ‘state-dependent detection theory’ (SDDT). We focus on behavioural and fitness outcomes when animals continue to use formerly adaptive thresholds following environmental change. In a simple example, we show that exposure to novel animals which appear dangerous—but are actually safe—(e.g. ecotourists) can have catastrophic consequences for ‘prey’ (organisms that respond as if the new organisms are predators), significantly increasing mortality even when the novel species is not predatory. SDDT also reveals that the effect on reproduction can be greater than the effect on lifespan. We investigate factors that influence the effect of novel organisms, and address the potential for behavioural adjustments (via evolution or learning) to recover otherwise reduced fitness. Although effects of environmental change are often difficult to predict, we suggest that SDDT provides a useful route ahead. PMID:28100814

  9. Physiological stress responses predict sexual functioning and satisfaction differently in women who have and have not been sexually abused in childhood.

    Science.gov (United States)

    Meston, Cindy M; Lorenz, Tierney A

    2013-07-01

    Physiological responses to sexual stimuli may contribute to the increased rate of sexual problems seen in women with childhood sexual abuse (CSA) histories. We compared two physiological stress responses as predictors of sexual function and satisfaction, sympathetic nervous system (SNS) activation and cortisol in women with (CSA, N = 136) and without CSA histories (NSA, N = 102). In CSA survivors, cortisol response to sexual stimuli did not significantly predict sexual functioning; however, in NSA women, cortisol increases were associated with poorer sexual functioning, and decreases with higher functioning. For women with CSA histories, lower SNS activity was associated with poorer sexual functioning. For CSA survivors with low lifetime trauma, lower SNS activity was associated with higher sexual satisfaction; for women with high lifetime trauma, the reverse was true. Decreased SNS activity during sexual stimuli predicted higher sexual functioning in NSA women with low lifetime exposure to traumatic events, but lower sexual functioning in those with high exposure. Differences between women with and without CSA histories in the association between cortisol and SNS response and sexual functioning and satisfaction suggests that CSA causes disruptions in both short and long-term stress responses to sexual stimuli that perpetuate into adulthood.

  10. Exploring the Inflammatory Metabolomic Profile to Predict Response to TNF-α Inhibitors in Rheumatoid Arthritis.

    Directory of Open Access Journals (Sweden)

    Bart V J Cuppen

    Full Text Available In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA respond insufficiently to TNF-α inhibitors (TNFis. The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124. The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC, sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI. The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28, erythrocyte sedimentation rate (ESR or C-reactive protein (CRP. Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6, sn1-LPC(15:0, ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01. The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23 and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05. Our study established an accurate

  11. Response prediction of long flexible risers subject to forced harmonic vibration

    OpenAIRE

    Riveros, Carlos Alberto; Utsunomiya, Tomoaki; Maeda, Katsuya; Itoh, Kazuaki

    2010-01-01

    Several research efforts have been directed toward the development of models for response prediction of flexible risers. The main difficulties arise from the fact that the dynamic response of flexible risers involves highly nonlinear behavior and a self-regulated process. This article presents a quasi-steady approach for response prediction of oscillating flexible risers. Amplitude-dependent lift coefficients are considered, as is an increased mean drag coefficient model during synchronizatio...

  12. Specific predictive power of automatic spider-related affective associations for controllable and uncontrollable fear responses toward spiders

    NARCIS (Netherlands)

    Huijdlng, J; de Jong, PJ; Huijding, J.

    This study examined the predictive power of automatically activated spider-related affective associations for automatic and controllable fear responses. The Extrinsic Affective Simon Task (EAST; De Houwer, 2003) was used to indirectly assess automatic spider fear-related associations. The EAST and

  13. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Data.gov (United States)

    U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

  14. Nonlinear dynamical modeling and prediction of the terrestrial magnetospheric activity

    International Nuclear Information System (INIS)

    Vassiliadis, D.

    1992-01-01

    The irregular activity of the magnetosphere results from its complex internal dynamics as well as the external influence of the solar wind. The dominating self-organization of the magnetospheric plasma gives rise to repetitive, large-scale coherent behavior manifested in phenomena such as the magnetic substorm. Based on the nonlinearity of the global dynamics this dissertation examines the magnetosphere as a nonlinear dynamical system using time series analysis techniques. Initially the magnetospheric activity is modeled in terms of an autonomous system. A dimension study shows that its observed time series is self-similar, but the correlation dimension is high. The implication of a large number of degrees of freedom is confirmed by other state space techniques such as Poincare sections and search for unstable periodic orbits. At the same time a stability study of the time series in terms of Lyapunov exponents suggests that the series is not chaotic. The absence of deterministic chaos is supported by the low predictive capability of the autonomous model. Rather than chaos, it is an external input which is largely responsible for the irregularity of the magnetospheric activity. In fact, the external driving is so strong that the above state space techniques give results for magnetospheric and solar wind time series that are at least qualitatively similar. Therefore the solar wind input has to be included in a low-dimensional nonautonomous model. Indeed it is shown that such a model can reproduce the observed magnetospheric behavior up to 80-90 percent. The characteristic coefficients of the model show little variation depending on the external disturbance. The impulse response is consistent with earlier results of linear prediction filters. The model can be easily extended to contain nonlinear features of the magnetospheric activity and in particular the loading-unloading behavior of substorms

  15. Deterministic Predictions of Vessel Responses Based on Past Measurements

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; Jensen, Jørgen Juncher

    2017-01-01

    The paper deals with a prediction procedure from which global wave-induced responses can be deterministically predicted a short time, 10-50 s, ahead of current time. The procedure relies on the autocorrelation function and takes into account prior measurements only; i.e. knowledge about wave...

  16. Predicting the unpredictable: Critical analysis and practical implications of predictive anticipatory activity

    Directory of Open Access Journals (Sweden)

    Julia eMossbridge

    2014-03-01

    Full Text Available A recent meta-analysis of experiments from seven independent laboratories (n=26 published since 1978 indicates that the human body can apparently detect randomly delivered stimuli occurring 1-10 seconds in the future (Mossbridge, Tressoldi, & Utts, 2012. The key observation in these studies is that human physiology appears to be able to distinguish between unpredictable dichotomous future stimuli, such as emotional vs. neutral images or sound vs. silence. This phenomenon has been called presentiment (as in feeling the future. In this paper we call it predictive anticipatory activity or PAA. The phenomenon is predictive because it can distinguish between upcoming stimuli; it is anticipatory because the physiological changes occur before a future event; and it is an activity because it involves changes in the cardiopulmonary, skin, and/or nervous systems. PAA is an unconscious phenomenon that seems to be a time-reversed reflection of the usual physiological response to a stimulus. It appears to resemble precognition (consciously knowing something is going to happen before it does, but PAA specifically refers to unconscious physiological reactions as opposed to conscious premonitions. Though it is possible that PAA underlies the conscious experience of precognition, experiments testing this idea have not produced clear results. The first part of this paper reviews the evidence for PAA and examines the two most difficult challenges for obtaining valid evidence for it: expectation bias and multiple analyses. The second part speculates on possible mechanisms and the theoretical implications of PAA for understanding physiology and consciousness. The third part examines potential practical applications.

  17. Activations in gray and white matter are modulated by uni-manual responses during within and inter-hemispheric transfer: effects of response hand and right-handedness.

    Science.gov (United States)

    Diwadkar, Vaibhav A; Bellani, Marcella; Chowdury, Asadur; Savazzi, Silvia; Perlini, Cinzia; Marinelli, Veronica; Zoccatelli, Giada; Alessandrini, Franco; Ciceri, Elisa; Rambaldelli, Gianluca; Ruggieri, Mirella; Carlo Altamura, A; Marzi, Carlo A; Brambilla, Paolo

    2017-08-14

    Because the visual cortices are contra-laterally organized, inter-hemispheric transfer tasks have been used to behaviorally probe how information briefly presented to one hemisphere of the visual cortex is integrated with responses resulting from the ipsi- or contra-lateral motor cortex. By forcing rapid information exchange across diverse regions, these tasks robustly activate not only gray matter regions, but also white matter tracts. It is likely that the response hand itself (dominant or non-dominant) modulates gray and white matter activations during within and inter-hemispheric transfer. Yet the role of uni-manual responses and/or right hand dominance in modulating brain activations during such basic tasks is unclear. Here we investigated how uni-manual responses with either hand modulated activations during a basic visuo-motor task (the established Poffenberger paradigm) alternating between inter- and within-hemispheric transfer conditions. In a large sample of strongly right-handed adults (n = 49), we used a factorial combination of transfer condition [Inter vs. Within] and response hand [Dominant(Right) vs. Non-Dominant (Left)] to discover fMRI-based activations in gray matter, and in narrowly defined white matter tracts. These tracts were identified using a priori probabilistic white matter atlases. Uni-manual responses with the right hand strongly modulated activations in gray matter, and notably in white matter. Furthermore, when responding with the left hand, activations during inter-hemispheric transfer were strongly predicted by the degree of right-hand dominance, with increased right-handedness predicting decreased fMRI activation. Finally, increasing age within the middle-aged sample was associated with a decrease in activations. These results provide novel evidence of complex relationships between uni-manual responses in right-handed subjects, and activations during within- and inter-hemispheric transfer suggest that the organization of the

  18. Neural responses to exclusion predict susceptibility to social influence.

    Science.gov (United States)

    Falk, Emily B; Cascio, Christopher N; O'Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G

    2014-05-01

    Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American adolescents, traffic-related crashes are leading causes of nonfatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents' vulnerability to peer influence. We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately 1 week after the neuroimaging session. Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside the neuroimaging laboratory 1 week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. These results address the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging laboratory. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.

  19. Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

    OpenAIRE

    Marasco, Addolorata; De Paris, Alessandro; Migliore, Michele

    2016-01-01

    The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific o...

  20. Prediction of therapy response to interferon-alpha in chronic viral hepatitis-B by liver and hepatobiliary scintigraphy

    International Nuclear Information System (INIS)

    Caglar, M.; Sari, O.; Akcan, Y.

    2002-01-01

    Interferon (IFN) provides effective treatment in some patients with chronic hepatitis. The clarification of factors predictive of therapy response would be helpful in identifying patients who would benefit from treatment. In this study, we evaluated the potential utility of Tc-99m sulfur colloid liver/spleen and Tc-99m-disofenin hepatobiliary scintigraphy to predict therapy response to IFN in patients with chronic active hepatitis. The study group consisted of ten patients with chronic viral hepatitis B who were treated with 4.5 units of interferon alpha for 12 months. Prior to the start of the therapy, sulfur colloid scintigraphy was obtained by which the liver/spleen ratios were derived. Hepatobiliary scintigraphy was performed on a separate day and time-activity curves were generated from regions of interest drawn over the liver, heart and gall-bladder. The index of blood and liver clearance time was calculated. Histological grading and laboratory values were obtained for clinical correlation. Responders (n=6) to IFN were defined as those who improved clinically with normalized transaminase levels and had hepatitis B envelope antigen (HBeAg) seroconversion. On sulfur colloid (SC) scintigraphy, the liver/spleen ratio of non-responders was significantly lower than responders (median values: 0.69 vs. 1.16, p=0.01) but on hepatobiliary scintigraphy no statistically significant parameters were found to predict response to interferon therapy. (author)

  1. Mothers' labeling responses to infants' gestures predict vocabulary outcomes.

    Science.gov (United States)

    Olson, Janet; Masur, Elise Frank

    2015-11-01

    Twenty-nine infants aged 1;1 and their mothers were videotaped while interacting with toys for 18 minutes. Six experimental stimuli were presented to elicit infant communicative bids in two communicative intent contexts - proto-declarative and proto-imperative. Mothers' verbal responses to infants' gestural and non-gestural communicative bids were coded for object and action labels. Relations between maternal labeling responses and infants' vocabularies at 1;1 and 1;5 were examined. Mothers' labeling responses to infants' gestural communicative bids were concurrently and predictively related to infants' vocabularies, whereas responses to non-gestural communicative bids were not. Mothers' object labeling following gestures in the proto-declarative context mediated the association from infants' gesturing in the proto-declarative context to concurrent noun lexicons and was the strongest predictor of subsequent noun lexicons. Mothers' action labeling after infants' gestural bids in the proto-imperative context predicted infants' acquisition of action words at 1;5. Findings show that mothers' responsive labeling explain specific relations between infants' gestures and their vocabulary development.

  2. Prediction of permeability changes in an excavation response zone

    International Nuclear Information System (INIS)

    Kinoshita, Naoto; Ishii, Takashi; Kuroda, Hidetaka; Tada, Hiroyuki

    1992-01-01

    In geologic disposal of radioactive wastes, stress changes due to cavern excavation may expand the existing fractures and create possible bypasses for groundwater. This paper proposes a simple method for predicting permeability changes in the excavation response zones. Numerical analyses using this method predict that the response zones created by cavern excavation would differ greatly in thickness and permeability depending on the depth of the cavern site and the initial in-situ stress, that when the cavern site is deeper, response zones would expand more and permeability would increases more, and that if the ratio of horizontal to vertical in-situ stress is small, extensive permeable zones at the crown and the bottom would occur, whereas if the ratio is large, extensive permeable zones would occur in the side walls. (orig.)

  3. Linear filters as a method of real-time prediction of geomagnetic activity

    International Nuclear Information System (INIS)

    McPherron, R.L.; Baker, D.N.; Bargatze, L.F.

    1985-01-01

    Important factors controlling geomagnetic activity include the solar wind velocity, the strength of the interplanetary magnetic field (IMF), and the field orientation. Because these quantities change so much in transit through the solar wind, real-time monitoring immediately upstream of the earth provides the best input for any technique of real-time prediction. One such technique is linear prediction filtering which utilizes past histories of the input and output of a linear system to create a time-invariant filter characterizing the system. Problems of nonlinearity or temporal changes of the system can be handled by appropriate choice of input parameters and piecewise approximation in various ranges of the input. We have created prediction filters for all the standard magnetic indices and tested their efficiency. The filters show that the initial response of the magnetosphere to a southward turning of the IMF peaks in 20 minutes and then again in 55 minutes. After a northward turning, auroral zone indices and the midlatitude ASYM index return to background within 2 hours, while Dst decays exponentially with a time constant of about 8 hours. This paper describes a simple, real-time system utilizing these filters which could predict a substantial fraction of the variation in magnetic activity indices 20 to 50 minutes in advance

  4. Outcome Prediction in Mathematical Models of Immune Response to Infection.

    Directory of Open Access Journals (Sweden)

    Manuel Mai

    Full Text Available Clinicians need to predict patient outcomes with high accuracy as early as possible after disease inception. In this manuscript, we show that patient-to-patient variability sets a fundamental limit on outcome prediction accuracy for a general class of mathematical models for the immune response to infection. However, accuracy can be increased at the expense of delayed prognosis. We investigate several systems of ordinary differential equations (ODEs that model the host immune response to a pathogen load. Advantages of systems of ODEs for investigating the immune response to infection include the ability to collect data on large numbers of 'virtual patients', each with a given set of model parameters, and obtain many time points during the course of the infection. We implement patient-to-patient variability v in the ODE models by randomly selecting the model parameters from distributions with coefficients of variation v that are centered on physiological values. We use logistic regression with one-versus-all classification to predict the discrete steady-state outcomes of the system. We find that the prediction algorithm achieves near 100% accuracy for v = 0, and the accuracy decreases with increasing v for all ODE models studied. The fact that multiple steady-state outcomes can be obtained for a given initial condition, i.e. the basins of attraction overlap in the space of initial conditions, limits the prediction accuracy for v > 0. Increasing the elapsed time of the variables used to train and test the classifier, increases the prediction accuracy, while adding explicit external noise to the ODE models decreases the prediction accuracy. Our results quantify the competition between early prognosis and high prediction accuracy that is frequently encountered by clinicians.

  5. RAMAN SPECTROSCOPIC STUDY ON PREDICTION OF TREATMENT RESPONSE IN CERVICAL CANCERS

    Directory of Open Access Journals (Sweden)

    S. RUBINA

    2013-04-01

    Full Text Available Concurrent chemoradiotherapy (CCRT is the choice of treatment for locally advanced cervical cancers; however, tumors exhibit diverse response to treatment. Early prediction of tumor response leads to individualizing treatment regimen. Response evaluation criteria in solid tumors (RECIST, the current modality of tumor response assessment, is often subjective and carried out at the first visit after treatment, which is about four months. Hence, there is a need for better predictive tool for radioresponse. Optical spectroscopic techniques, sensitive to molecular alteration, are being pursued as potential diagnostic tools. Present pilot study aims to explore the fiber-optic-based Raman spectroscopy approach in prediction of tumor response to CCRT, before taking up extensive in vivo studies. Ex vivo Raman spectra were acquired from biopsies collected from 11 normal (148 spectra, 16 tumor (201 spectra and 13 complete response (151 CR spectra, one partial response (8 PR spectra and one nonresponder (8 NR spectra subjects. Data was analyzed using principal component linear discriminant analysis (PC-LDA followed by leave-one-out cross-validation (LOO-CV. Findings suggest that normal tissues can be efficiently classified from both pre- and post-treated tumor biopsies, while there is an overlap between pre- and post-CCRT tumor tissues. Spectra of CR, PR and NR tissues were subjected to principal component analysis (PCA and a tendency of classification was observed, corroborating previous studies. Thus, this study further supports the feasibility of Raman spectroscopy in prediction of tumor radioresponse and prospective noninvasive in vivo applications.

  6. The Pupillary Orienting Response Predicts Adaptive Behavioral Adjustment after Errors.

    Directory of Open Access Journals (Sweden)

    Peter R Murphy

    Full Text Available Reaction time (RT is commonly observed to slow down after an error. This post-error slowing (PES has been thought to arise from the strategic adoption of a more cautious response mode following deployment of cognitive control. Recently, an alternative account has suggested that PES results from interference due to an error-evoked orienting response. We investigated whether error-related orienting may in fact be a pre-cursor to adaptive post-error behavioral adjustment when the orienting response resolves before subsequent trial onset. We measured pupil dilation, a prototypical measure of autonomic orienting, during performance of a choice RT task with long inter-stimulus intervals, and found that the trial-by-trial magnitude of the error-evoked pupil response positively predicted both PES magnitude and the likelihood that the following response would be correct. These combined findings suggest that the magnitude of the error-related orienting response predicts an adaptive change of response strategy following errors, and thereby promote a reconciliation of the orienting and adaptive control accounts of PES.

  7. Depression and anxiety predict sex-specific cortisol responses to interpersonal stress.

    Science.gov (United States)

    Powers, Sally I; Laurent, Heidemarie K; Gunlicks-Stoessel, Meredith; Balaban, Susan; Bent, Eileen

    2016-07-01

    Clinical theories posit interpersonal stress as an important factor in the emergence and exacerbation of depression and anxiety, while neuroendocrine research confirms the association of these syndromes with dysregulation in a major stress response system, the hypothalamic-pituitary-adrenal (HPA) axis. However, the proposal that depression and anxiety symptoms and diagnoses are associated with problematic HPA responses to close relationship stress has not been directly tested. We examined 196 heterosexual dating couples' depression and anxiety symptoms and diagnoses, assessed with questionnaires and diagnostic interviews, in relation to cortisol responses to discussion of an unresolved relationship conflict. Participants provided seven salivary samples in anticipation of and directly following the discussion, and throughout an hour-long recovery period, which were assayed for cortisol. Multilevel models of the HPA response predicted by symptoms or diagnoses showed that women's depressive symptoms predicted attenuated cortisol levels, with a flatter response curve. In contrast, men's depression symptoms and women's anxiety symptoms and diagnoses predicted higher cortisol levels. These findings highlight the importance of examining sex differences in responses to interpersonal stressors for understanding HPA dysregulation in internalizing psychopathology. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. From feedback- to response-based performance monitoring in active and observational learning.

    Science.gov (United States)

    Bellebaum, Christian; Colosio, Marco

    2014-09-01

    Humans can adapt their behavior by learning from the consequences of their own actions or by observing others. Gradual active learning of action-outcome contingencies is accompanied by a shift from feedback- to response-based performance monitoring. This shift is reflected by complementary learning-related changes of two ACC-driven ERP components, the feedback-related negativity (FRN) and the error-related negativity (ERN), which have both been suggested to signal events "worse than expected," that is, a negative prediction error. Although recent research has identified comparable components for observed behavior and outcomes (observational ERN and FRN), it is as yet unknown, whether these components are similarly modulated by prediction errors and thus also reflect behavioral adaptation. In this study, two groups of 15 participants learned action-outcome contingencies either actively or by observation. In active learners, FRN amplitude for negative feedback decreased and ERN amplitude in response to erroneous actions increased with learning, whereas observational ERN and FRN in observational learners did not exhibit learning-related changes. Learning performance, assessed in test trials without feedback, was comparable between groups, as was the ERN following actively performed errors during test trials. In summary, the results show that action-outcome associations can be learned similarly well actively and by observation. The mechanisms involved appear to differ, with the FRN in active learning reflecting the integration of information about own actions and the accompanying outcomes.

  9. Activity, exposure rate and spectrum prediction with Java programming

    International Nuclear Information System (INIS)

    Sahin, D.; Uenlue, K.

    2009-01-01

    In order to envision the radiation exposure during Neutron Activation Analysis (NAA) experiments, a software called Activity Predictor is developed using Java TM programming language. The Activity Predictor calculates activities, exposure rates and gamma spectra of activated samples for NAA experiments performed at Radiation Science and Engineering Center (RSEC), Penn State Breazeale Reactor (PSBR). The calculation procedure for predictions involves both analytical and Monte Carlo methods. The Activity Predictor software is validated with a series of activation experiments. It has been found that Activity Predictor software calculates the activities and exposure rates precisely. The software also predicts gamma spectrum for each measurement. The predicted spectra agreed partially with measured spectra. The error in net photo peak areas varied from 4.8 to 51.29%, which is considered to be due to simplistic modeling, statistical fluctuations and unknown contaminants in the samples. (author)

  10. Features and prospects of juridical predicting of entrepreneurial activity

    Directory of Open Access Journals (Sweden)

    Natalya V. Rubtsova

    2017-03-01

    Full Text Available Objective to identify characteristics and prospects of predicting the business activity. Methods historical sociological logical systematicstructural formallegal comparativelegal legal modeling method. Results in article suggests the legal definition of prediction of business activity as a scientific and practical study aimed at the determination of the future state and prospects of development of business activity consisting of the evaluation of legal regulation and analysis of the prospectsof further socioeconomic development which aims to select the optimal solution for the further development of entrepreneurship through legal regulators. The work proves the necessity of achieving a balanced legal regulation of social relations by changing the legislation in the field of business agreements investment and innovation. Scientific novelty the article for the first time formulates the concept characteristics and features of legal prediction of business activity substantiates the impact of predicting on the development of legal regulation of social relations. Practical significance the main provisions and conclusions of the article can be used in research and teaching while considering the issues of predicting both the socioeconomic processes in general and business activity in particular.

  11. A community computational challenge to predict the activity of pairs of compounds.

    Science.gov (United States)

    Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

    2014-12-01

    Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

  12. Resting state functional connectivity predicts neurofeedback response

    Directory of Open Access Journals (Sweden)

    Dustin eScheinost

    2014-09-01

    Full Text Available Tailoring treatments to the specific needs and biology of individual patients – personalized medicine – requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD. Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI, to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC and anterior prefrontal cortex, Brodmann area (BA 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety.

  13. Citric Acid Metabolism in Resistant Hypertension: Underlying Mechanisms and Metabolic Prediction of Treatment Response.

    Science.gov (United States)

    Martin-Lorenzo, Marta; Martinez, Paula J; Baldan-Martin, Montserrat; Ruiz-Hurtado, Gema; Prado, Jose Carlos; Segura, Julian; de la Cuesta, Fernando; Barderas, Maria G; Vivanco, Fernando; Ruilope, Luis Miguel; Alvarez-Llamas, Gloria

    2017-11-01

    Resistant hypertension (RH) affects 9% to 12% of hypertensive adults. Prolonged exposure to suboptimal blood pressure control results in end-organ damage and cardiovascular risk. Spironolactone is the most effective drug for treatment, but not all patients respond and side effects are not negligible. Little is known on the mechanisms responsible for RH. We aimed to identify metabolic alterations in urine. In addition, a potential capacity of metabolites to predict response to spironolactone was investigated. Urine was collected from 29 patients with RH and from a group of 13 subjects with pseudo-RH. For patients, samples were collected before and after spironolactone administration and were classified in responders (n=19) and nonresponders (n=10). Nuclear magnetic resonance was applied to identify altered metabolites and pathways. Metabolites were confirmed by liquid chromatography-mass spectrometry. Citric acid cycle was the pathway most significantly altered ( P citric acid cycle and deregulation of reactive oxygen species homeostasis control continue its activation after hypertension was developed. A metabolic panel showing alteration before spironolactone treatment and predicting future response of patients is shown. These molecular indicators will contribute optimizing the rate of control of RH patients with spironolactone. © 2017 American Heart Association, Inc.

  14. The BUMP model of response planning: intermittent predictive control accounts for 10 Hz physiological tremor.

    Science.gov (United States)

    Bye, Robin T; Neilson, Peter D

    2010-10-01

    Physiological tremor during movement is characterized by ∼10 Hz oscillation observed both in the electromyogram activity and in the velocity profile. We propose that this particular rhythm occurs as the direct consequence of a movement response planning system that acts as an intermittent predictive controller operating at discrete intervals of ∼100 ms. The BUMP model of response planning describes such a system. It forms the kernel of Adaptive Model Theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (1) analyzing sensory information, (2) planning a desired optimal response, and (3) execution of that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete-time interval in which to generate a minimum acceleration trajectory to connect the actual response with the predicted future state of the target and compensate for executional error. We have shown previously that a response planning time of 100 ms accounts for the intermittency observed experimentally in visual tracking studies and for the psychological refractory period observed in double stimulation reaction time studies. We have also shown that simulations of aimed movement, using this same planning interval, reproduce experimentally observed speed-accuracy tradeoffs and movement velocity profiles. Here we show, by means of a simulation study of constant velocity tracking movements, that employing a 100 ms planning interval closely reproduces the measurement discontinuities and power spectra of electromyograms, joint-angles, and angular velocities of physiological tremor reported experimentally. We conclude that intermittent predictive control through sequential operation of BUMPs is a fundamental mechanism of 10 Hz physiological tremor in movement. Copyright © 2010 Elsevier B.V. All rights reserved.

  15. Improving behavioral performance under full attention by adjusting response criteria to changes in stimulus predictability.

    Science.gov (United States)

    Katzner, Steffen; Treue, Stefan; Busse, Laura

    2012-09-04

    One of the key features of active perception is the ability to predict critical sensory events. Humans and animals can implicitly learn statistical regularities in the timing of events and use them to improve behavioral performance. Here, we used a signal detection approach to investigate whether such improvements in performance result from changes of perceptual sensitivity or rather from adjustments of a response criterion. In a regular sequence of briefly presented stimuli, human observers performed a noise-limited motion detection task by monitoring the stimulus stream for the appearance of a designated target direction. We manipulated target predictability through the hazard rate, which specifies the likelihood that a target is about to occur, given it has not occurred so far. Analyses of response accuracy revealed that improvements in performance could be accounted for by adjustments of the response criterion; a growing hazard rate was paralleled by an increasing tendency to report the presence of a target. In contrast, the hazard rate did not affect perceptual sensitivity. Consistent with previous research, we also found that reaction time decreases as the hazard rate grows. A simple rise-to-threshold model could well describe this decrease and attribute predictability effects to threshold adjustments rather than changes in information supply. We conclude that, even under conditions of full attention and constant perceptual sensitivity, behavioral performance can be optimized by dynamically adjusting the response criterion to meet ongoing changes in the likelihood of a target.

  16. Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

    Science.gov (United States)

    Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

    2014-08-01

    Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Predicting Solar Activity Using Machine-Learning Methods

    Science.gov (United States)

    Bobra, M.

    2017-12-01

    Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to [1] empirically determine the signatures of this mechanism in solar image data and [2] use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.

  18. Pre-treatment amygdala volume predicts electroconvulsive therapy response

    NARCIS (Netherlands)

    ten Doesschate, Freek; van Eijndhoven, Philip; Tendolkar, Indira; van Wingen, Guido A.; van Waarde, Jeroen A.

    2014-01-01

    Electroconvulsive therapy (ECT) is an effective treatment for patients with severe depression. Knowledge on factors predicting therapeutic response may help to identify patients who will benefit most from the intervention. Based on the neuroplasticity hypothesis, volumes of the amygdala and

  19. Frontal responses during learning predict vulnerability to the psychotogenic effects of ketamine : Linking cognition, brain activity, and psychosis

    NARCIS (Netherlands)

    Corlett, Philip R.; Honey, Garry D.; Aitken, Michael R. F.; Dickinson, Anthony; Shanks, David R.; Absalom, Anthony R.; Lee, Michael; Pomarol-Clotet, Edith; Murray, Graham K.; McKenna, Peter J.; Robbins, Trevor W.; Bullmore, Edward T.; Fletcher, Paul C.

    Context: Establishing a neurobiological account of delusion formation that links cognitive processes, brain activity, and symptoms is important to furthering our understanding of psychosis. Objective: To explore a theoretical model of delusion formation that implicates prediction error - dependent

  20. Preoperative neutrophil response as a predictive marker of clinical outcome following open heart surgery and the impact of leukocyte filtration.

    LENUS (Irish Health Repository)

    Soo, Alan W

    2010-11-01

    Open heart surgery is associated with a massive systemic inflammatory response. Neutrophils, are the main mediator of this response. We hypothesised that the degree of neutrophil activation and inflammatory response to open heart surgery varies individually and correlates with clinical outcome. The aim of this study was to determine if individual clinical outcome can be predicted preoperatively through assessment of in-vitro stimulated neutrophil responses. Following that, the effects of neutrophil depletion through leukocyte filters are examined.

  1. Acupuncture-Evoked Response in Somatosensory and Prefrontal Cortices Predicts Immediate Pain Reduction in Carpal Tunnel Syndrome

    Directory of Open Access Journals (Sweden)

    Yumi Maeda

    2013-01-01

    Full Text Available The linkage between brain response to acupuncture and subsequent analgesia remains poorly understood. Our aim was to evaluate this linkage in chronic pain patients with carpal tunnel syndrome (CTS. Brain response to electroacupuncture (EA was evaluated with functional MRI. Subjects were randomized to 3 groups: (1 EA applied at local acupoints on the affected wrist (PC-7 to TW-5, (2 EA at distal acupoints (contralateral ankle, SP-6 to LV-4, and (3 sham EA at nonacupoint locations on the affected wrist. Symptom ratings were evaluated prior to and following the scan. Subjects in the local and distal groups reported reduced pain. Verum EA produced greater reduction of paresthesia compared to sham. Compared to sham EA, local EA produced greater activation in insula and S2 and greater deactivation in ipsilateral S1, while distal EA produced greater activation in S2 and deactivation in posterior cingulate cortex. Brain response to distal EA in prefrontal cortex (PFC and brain response to verum EA in S1, SMA, and PFC were correlated with pain reduction following stimulation. Thus, while greater activation to verum acupuncture in these regions may predict subsequent analgesia, PFC activation may specifically mediate reduced pain when stimulating distal acupoints.

  2. Analytical predictions of SGEMP response and comparisons with computer calculations

    International Nuclear Information System (INIS)

    de Plomb, E.P.

    1976-01-01

    An analytical formulation for the prediction of SGEMP surface current response is presented. Only two independent dimensionless parameters are required to predict the peak magnitude and rise time of SGEMP induced surface currents. The analysis applies to limited (high fluence) emission as well as unlimited (low fluence) emission. Cause-effect relationships for SGEMP response are treated quantitatively, and yield simple power law dependencies between several physical variables. Analytical predictions for a large matrix of SGEMP cases are compared with an array of about thirty-five computer solutions of similar SGEMP problems, which were collected from three independent research groups. The theoretical solutions generally agree with the computer solutions as well as the computer solutions agree with one another. Such comparisons typically show variations less than a ''factor of two.''

  3. Decreased activation and subsyndromal manic symptoms predict lower remission rates in bipolar depression.

    Science.gov (United States)

    Caldieraro, Marco Antonio; Walsh, Samantha; Deckersbach, Thilo; Bobo, William V; Gao, Keming; Ketter, Terence A; Shelton, Richard C; Reilly-Harrington, Noreen A; Tohen, Mauricio; Calabrese, Joseph R; Thase, Michael E; Kocsis, James H; Sylvia, Louisa G; Nierenberg, Andrew A

    2017-11-01

    Activation encompasses energy and activity and is a central feature of bipolar disorder. However, the impact of activation on treatment response of bipolar depression requires further exploration. The aims of this study were to assess the association of decreased activation and sustained remission in bipolar depression and test for factors that could affect this association. We assessed participants with Diagnostic and Statistical Manual of Mental Disorders (4th ed) bipolar depression ( n = 303) included in a comparative effectiveness study of lithium- and quetiapine-based treatments (the Bipolar CHOICE study). Activation was evaluated using items from the Bipolar Inventory of Symptoms Scale. The selection of these items was based on a dimension of energy and interest symptoms associated with poorer treatment response in major depression. Decreased activation was associated with lower remission rates in the raw analyses and in a logistic regression model adjusted for baseline severity and subsyndromal manic symptoms (odds ratio = 0.899; p = 0.015). The manic features also predicted lower remission (odds ratio = 0.934; p bipolar depression. Patients with these features may require specific treatment approaches, but new studies are necessary to identify treatments that could improve outcomes in this population.

  4. Prediction of First-Order Vessel Responses with Applications to Decision Support Systems

    DEFF Research Database (Denmark)

    Nielsen, Ulrik D.; Iseki, Toshio

    2015-01-01

    The paper presents a practical and simple approach for making vessel response predictions. Features of the procedure include a) predictions which are scaled so to better agree with corresponding true, future values to be measured at the time the predictions apply at; and b) predictions that are a...

  5. HLA Class-II Associated HIV Polymorphisms Predict Escape from CD4+ T Cell Responses.

    Directory of Open Access Journals (Sweden)

    Nathan Erdmann

    2015-08-01

    Full Text Available Antiretroviral therapy, antibody and CD8+ T cell-mediated responses targeting human immunodeficiency virus-1 (HIV-1 exert selection pressure on the virus necessitating escape; however, the ability of CD4+ T cells to exert selective pressure remains unclear. Using a computational approach on HIV gag/pol/nef sequences and HLA-II allelic data, we identified 29 HLA-II associated HIV sequence polymorphisms or adaptations (HLA-AP in an African cohort of chronically HIV-infected individuals. Epitopes encompassing the predicted adaptation (AE or its non-adapted (NAE version were evaluated for immunogenicity. Using a CD8-depleted IFN-γ ELISpot assay, we determined that the magnitude of CD4+ T cell responses to the predicted epitopes in controllers was higher compared to non-controllers (p<0.0001. However, regardless of the group, the magnitude of responses to AE was lower as compared to NAE (p<0.0001. CD4+ T cell responses in patients with acute HIV infection (AHI demonstrated poor immunogenicity towards AE as compared to NAE encoded by their transmitted founder virus. Longitudinal data in AHI off antiretroviral therapy demonstrated sequence changes that were biologically confirmed to represent CD4+ escape mutations. These data demonstrate an innovative application of HLA-associated polymorphisms to identify biologically relevant CD4+ epitopes and suggests CD4+ T cells are active participants in driving HIV evolution.

  6. Doppler laser imaging predicts response to topical minoxidil in the treatment of female pattern hair loss.

    Science.gov (United States)

    McCoy, J; Kovacevic, M; Situm, M; Stanimirovic, A; Bolanca, Z; Goren, A

    2016-01-01

    Topical minoxidil is the only drug approved by the US FDA for the treatment of female pattern hair loss. Unfortunately, following 16 weeks of daily application, less than 40% of patients regrow hair. Several studies have demonstrated that sulfotransferase enzyme activity in plucked hair follicles predicts topical minoxidil response in female pattern hair loss patients. However, due to patients’ discomfort with the procedure, and the time required to perform the enzymatic assay it would be ideal to develop a rapid, non-invasive test for sulfotransferase enzyme activity. Minoxidil is a pro-drug converted to its active form, minoxidil sulfate, by sulfotransferase enzymes in the outer root sheath of hair. Minoxidil sulfate is the active form required for both the promotion of hair regrowth and the vasodilatory effects of minoxidil. We thus hypothesized that laser Doppler velocimetry measurement of scalp blood perfusion subsequent to the application of topical minoxidil would correlate with sulfotransferase enzyme activity in plucked hair follicles. In this study, plucked hair follicles from female pattern hair loss patients were analyzed for sulfotransferase enzyme activity. Additionally, laser Doppler velocimetry was used to measure the change in scalp perfusion at 15, 30, 45, and 60 minutes, after the application of minoxidil. In agreement with our hypothesis, we discovered a correlation (r=1.0) between the change in scalp perfusion within 60 minutes after topical minoxidil application and sulfotransferase enzyme activity in plucked hairs. To our knowledge, this is the first study demonstrating the feasibility of using laser Doppler imaging as a rapid, non-invasive diagnostic test to predict topical minoxidil response in the treatment of female pattern hair loss.

  7. Individual differences in maternal response to immune challenge predict offspring behavior: Contribution of environmental factors

    Science.gov (United States)

    Bronson, Stefanie L.; Ahlbrand, Rebecca; Horn, Paul S.; Kern, Joseph R.; Richtand, Neil M.

    2011-01-01

    Maternal infection during pregnancy elevates risk for schizophrenia and related disorders in offspring. Converging evidence suggests the maternal inflammatory response mediates the interaction between maternal infection, altered brain development, and behavioral outcome. The extent to which individual differences in the maternal response to immune challenge influence the development of these abnormalities is unknown. The present study investigated the impact of individual differences in maternal response to the viral mimic polyinosinic:polycytidylic acid (poly I:C) on offspring behavior. We observed significant variability in body weight alterations of pregnant rats induced by administration of poly I:C on gestational day 14. Furthermore, the presence or absence of maternal weight loss predicted MK-801 and amphetamine stimulated locomotor abnormalities in offspring. MK-801 stimulated locomotion was altered in offspring of all poly I:C treated dams; however, the presence or absence of maternal weight loss resulted in decreased and modestly increased locomotion, respectively. Adult offspring of poly I:C treated dams that lost weight exhibited significantly decreased amphetamine stimulated locomotion, while offspring of poly I:C treated dams without weight loss performed similarly to vehicle controls. Social isolation and increased maternal age predicted weight loss in response to poly I:C but not vehicle injection. In combination, these data identify environmental factors associated with the maternal response to immune challenge and functional outcome of offspring exposed to maternal immune activation. PMID:21255612

  8. Patient-ventilator asynchrony affects pulse pressure variation prediction of fluid responsiveness.

    Science.gov (United States)

    Messina, Antonio; Colombo, Davide; Cammarota, Gianmaria; De Lucia, Marta; Cecconi, Maurizio; Antonelli, Massimo; Corte, Francesco Della; Navalesi, Paolo

    2015-10-01

    During partial ventilatory support, pulse pressure variation (PPV) fails to adequately predict fluid responsiveness. This prospective study aims to investigate whether patient-ventilator asynchrony affects PPV prediction of fluid responsiveness during pressure support ventilation (PSV). This is an observational physiological study evaluating the response to a 500-mL fluid challenge in 54 patients receiving PSV, 27 without (Synch) and 27 with asynchronies (Asynch), as assessed by visual inspection of ventilator waveforms by 2 skilled blinded physicians. The area under the curve was 0.71 (confidence interval, 0.57-0.83) for the overall population, 0.86 (confidence interval, 0.68-0.96) in the Synch group, and 0.53 (confidence interval, 0.33-0.73) in the Asynch group (P = .018). Sensitivity and specificity of PPV were 78% and 89% in the Synch group and 36% and 46% in the Asynch group. Logistic regression showed that the PPV prediction was influenced by patient-ventilator asynchrony (odds ratio, 8.8 [2.0-38.0]; P < .003). Of the 27 patients without asynchronies, 12 had a tidal volume greater than or equal to 8 mL/kg; in this subgroup, the rate of correct classification was 100%. Patient-ventilator asynchrony affects PPV performance during partial ventilatory support influencing its efficacy in predicting fluid responsiveness. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Prefrontal mediation of the reading network predicts intervention response in dyslexia.

    Science.gov (United States)

    Aboud, Katherine S; Barquero, Laura A; Cutting, Laurie E

    2018-04-01

    A primary challenge facing the development of interventions for dyslexia is identifying effective predictors of intervention response. While behavioral literature has identified core cognitive characteristics of response, the distinction of reading versus executive cognitive contributions to response profiles remains unclear, due in part to the difficulty of segregating these constructs using behavioral outputs. In the current study we used functional neuroimaging to piece apart the mechanisms of how/whether executive and reading network relationships are predictive of intervention response. We found that readers who are responsive to intervention have more typical pre-intervention functional interactions between executive and reading systems compared to nonresponsive readers. These findings suggest that intervention response in dyslexia is influenced not only by domain-specific reading regions, but also by contributions from intervening domain-general networks. Our results make a significant gain in identifying predictive bio-markers of outcomes in dyslexia, and have important implications for the development of personalized clinical interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Prediction of human population responses to toxic compounds by a collaborative competition.

    Science.gov (United States)

    Eduati, Federica; Mangravite, Lara M; Wang, Tao; Tang, Hao; Bare, J Christopher; Huang, Ruili; Norman, Thea; Kellen, Mike; Menden, Michael P; Yang, Jichen; Zhan, Xiaowei; Zhong, Rui; Xiao, Guanghua; Xia, Menghang; Abdo, Nour; Kosyk, Oksana; Friend, Stephen; Dearry, Allen; Simeonov, Anton; Tice, Raymond R; Rusyn, Ivan; Wright, Fred A; Stolovitzky, Gustavo; Xie, Yang; Saez-Rodriguez, Julio

    2015-09-01

    The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.

  11. Predictive value of brain perfusion SPECT for ketamine response in hyperalgesic fibromyalgia

    Energy Technology Data Exchange (ETDEWEB)

    Guedj, Eric; Cammilleri, Serge; Colavolpe, Cecile; Taieb, David; Laforte, Catherine de; Mundler, Olivier [Centre Hospitalo-Universitaire de la Timone, Service Central de Biophysique et de Medecine Nucleaire, Assistance Publique des Hopitaux de Marseille, Marseille Cedex 5 (France); Niboyet, Jean [Clinique La Phoceanne, Unite d' Etude et de Traitement de la Douleur, Marseille (France)

    2007-08-15

    Ketamine has been used successfully in various proportions of fibromyalgia (FM) patients. However, the response to this specific treatment remains largely unpredictable. We evaluated brain SPECT perfusion before treatment with ketamine, using voxel-based analysis. The objective was to determine the predictive value of brain SPECT for ketamine response. Seventeen women with FM (48 {+-} 11 years; ACR criteria) were enrolled in the study. Brain SPECT was performed before any change was made in therapy in the pain care unit. We considered that a patient was a good responder to ketamine if the VAS score for pain decreased by at least 50% after treatment. A voxel-by-voxel group analysis was performed using SPM2, in comparison to a group of ten healthy women matched for age. The VAS score for pain was 81.8 {+-} 4.2 before ketamine and 31.8 {+-} 27.1 after ketamine. Eleven patients were considered ''good responders'' to ketamine. Responder and non-responder subgroups were similar in terms of pain intensity before ketamine. In comparison to responding patients and healthy subjects, non-responding patients exhibited a significant reduction in bilateral perfusion of the medial frontal gyrus. This cluster of hypoperfusion was highly predictive of non-response to ketamine (positive predictive value 100%, negative predictive value 91%). Brain perfusion SPECT may predict response to ketamine in hyperalgesic FM patients. (orig.)

  12. Predictive value of brain perfusion SPECT for ketamine response in hyperalgesic fibromyalgia

    International Nuclear Information System (INIS)

    Guedj, Eric; Cammilleri, Serge; Colavolpe, Cecile; Taieb, David; Laforte, Catherine de; Mundler, Olivier; Niboyet, Jean

    2007-01-01

    Ketamine has been used successfully in various proportions of fibromyalgia (FM) patients. However, the response to this specific treatment remains largely unpredictable. We evaluated brain SPECT perfusion before treatment with ketamine, using voxel-based analysis. The objective was to determine the predictive value of brain SPECT for ketamine response. Seventeen women with FM (48 ± 11 years; ACR criteria) were enrolled in the study. Brain SPECT was performed before any change was made in therapy in the pain care unit. We considered that a patient was a good responder to ketamine if the VAS score for pain decreased by at least 50% after treatment. A voxel-by-voxel group analysis was performed using SPM2, in comparison to a group of ten healthy women matched for age. The VAS score for pain was 81.8 ± 4.2 before ketamine and 31.8 ± 27.1 after ketamine. Eleven patients were considered ''good responders'' to ketamine. Responder and non-responder subgroups were similar in terms of pain intensity before ketamine. In comparison to responding patients and healthy subjects, non-responding patients exhibited a significant reduction in bilateral perfusion of the medial frontal gyrus. This cluster of hypoperfusion was highly predictive of non-response to ketamine (positive predictive value 100%, negative predictive value 91%). Brain perfusion SPECT may predict response to ketamine in hyperalgesic FM patients. (orig.)

  13. Prediction of Early Response to Chemotherapy in Lung Cancer by Using Diffusion-Weighted MR Imaging

    Directory of Open Access Journals (Sweden)

    Jing Yu

    2014-01-01

    Full Text Available Purpose. To determine whether change of apparent diffusion coefficient (ADC value could predict early response to chemotherapy in lung cancer. Materials and Methods. Twenty-five patients with advanced non-small cell lung cancer underwent chest MR imaging including DWI before and at the end of the first cycle of chemotherapy. The tumor’s mean ADC value and diameters on MR images were calculated and compared. The grouping reference was based on serial CT scans according to Response Evaluation Criteria in Solid Tumors. Logistic regression was applied to assess treatment response prediction ability of ADC value and diameters. Results. The change of ADC value in partial response group was higher than that in stable disease group (P=0.004. ROC curve showed that ADC value could predict treatment response with 100% sensitivity, 64.71% specificity, 57.14% positive predictive value, 100% negative predictive value, and 82.7% accuracy. The area under the curve for combination of ADC value and longest diameter change was higher than any parameter alone (P≤0.01. Conclusions. The change of ADC value may be a sensitive indicator to predict early response to chemotherapy in lung cancer. Prediction ability could be improved by combining the change of ADC value and longest diameter.

  14. Levels of active tyrosine kinase receptor determine the tumor response to Zalypsis

    International Nuclear Information System (INIS)

    Moneo, Victoria; Serelde, Beatriz G; Blanco-Aparicio, Carmen; Diaz-Uriarte, Ramon; Avilés, Pablo; Santamaría, Gemma; Tercero, Juan C; Cuevas, Carmen; Carnero, Amancio

    2014-01-01

    Zalypsis® is a marine compound in phase II clinical trials for multiple myeloma, cervical and endometrial cancer, and Ewing’s sarcoma. However, the determinants of the response to Zalypsis are not well known. The identification of biomarkers for Zalypsis activity would also contribute to broaden the spectrum of tumors by selecting those patients more likely to respond to this therapy. Using in vitro drug sensitivity data coupled with a set of molecular data from a panel of sarcoma cell lines, we developed molecular signatures that predict sensitivity to Zalypsis. We verified these results in culture and in vivo xenograft studies. Zalypsis resistance was dependent on the expression levels of PDGFRα or constitutive phosphorylation of c-Kit, indicating that the activation of tyrosine kinase receptors (TKRs) may determine resistance to Zalypsis. To validate our observation, we measured the levels of total and active (phosphorylated) forms of the RTKs PDGFRα/β, c-Kit, and EGFR in a new panel of diverse solid tumor cell lines and found that the IC50 to the drug correlated with RTK activation in this new panel. We further tested our predictions about Zalypsis determinants for response in vivo in xenograft models. All cells lines expressing low levels of RTK signaling were sensitive to Zalypsis in vivo, whereas all cell lines except two with high levels of RTK signaling were resistant to the drug. RTK activation might provide important signals to overcome the cytotoxicity of Zalypsis and should be taken into consideration in current and future clinical trials

  15. Use of molecular markers for predicting therapy response in cancer patients.

    LENUS (Irish Health Repository)

    Duffy, Michael J

    2012-02-01

    Predictive markers are factors that are associated with upfront response or resistance to a particular therapy. Predictive markers are important in oncology as tumors of the same tissue of origin vary widely in their response to most available systemic therapies. Currently recommended oncological predictive markers include both estrogen and progesterone receptors for identifying patients with breast cancers likely to benefit from hormone therapy, HER-2 for the identification of breast cancer patients likely to benefit from trastuzumab, specific K-RAS mutations for the identification of patients with advanced colorectal cancer unlikely to benefit from either cetuximab or panitumumab and specific EGFR mutations for selecting patients with advanced non-small-cell lung cancer for treatment with tyrosine kinase inhibitors such as gefitinib and erlotinib. The availability of predictive markers should increase drug efficacy and decrease toxicity, thus leading to a more personalized approach to cancer treatment.

  16. Predicting survey responses: how and why semantics shape survey statistics on organizational behaviour.

    Directory of Open Access Journals (Sweden)

    Jan Ketil Arnulf

    Full Text Available Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60-86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.

  17. Predictive value of brain perfusion SPECT for rTMS response in pharmacoresistant depression

    International Nuclear Information System (INIS)

    Richieri, Raphaelle; Lancon, Christophe; Boyer, Laurent; Farisse, Jean; Colavolpe, Cecile; Mundler, Olivier; Guedj, Eric

    2011-01-01

    The aim of this study was to determine the predictive value of whole-brain voxel-based regional cerebral blood flow (rCBF) for repetitive transcranial magnetic stimulation (rTMS) response in patients with pharmacoresistant depression. Thirty-three right-handed patients who met DSM-IV criteria for major depressive disorder (unipolar or bipolar depression) were included before rTMS. rTMS response was defined as at least 50% reduction in the baseline Beck Depression Inventory scores. The predictive value of 99m Tc-ethyl cysteinate dimer (ECD) single photon emission computed tomography (SPECT) for rTMS response was studied before treatment by comparing rTMS responders to non-responders at voxel level using Statistical Parametric Mapping (SPM) (p 0.10). In comparison to responders, non-responders showed significant hypoperfusions (p < 0.001, uncorrected) in the left medial and bilateral superior frontal cortices (BA10), the left uncus/parahippocampal cortex (BA20/BA35) and the right thalamus. The area under the curve for the combination of SPECT clusters to predict rTMS response was 0.89 (p < 0.001). Sensitivity, specificity, positive predictive value and negative predictive value for the combination of clusters were: 94, 73, 81 and 92%, respectively. This study shows that, in pharmacoresistant depression, pretreatment rCBF of specific brain regions is a strong predictor for response to rTMS in patients with homogeneous demographic/clinical features. (orig.)

  18. DISIS: prediction of drug response through an iterative sure independence screening.

    Directory of Open Access Journals (Sweden)

    Yun Fang

    Full Text Available Prediction of drug response based on genomic alterations is an important task in the research of personalized medicine. Current elastic net model utilized a sure independence screening to select relevant genomic features with drug response, but it may neglect the combination effect of some marginally weak features. In this work, we applied an iterative sure independence screening scheme to select drug response relevant features from the Cancer Cell Line Encyclopedia (CCLE dataset. For each drug in CCLE, we selected up to 40 features including gene expressions, mutation and copy number alterations of cancer-related genes, and some of them are significantly strong features but showing weak marginal correlation with drug response vector. Lasso regression based on the selected features showed that our prediction accuracies are higher than those by elastic net regression for most drugs.

  19. Estimating confidence intervals in predicted responses for oscillatory biological models.

    Science.gov (United States)

    St John, Peter C; Doyle, Francis J

    2013-07-29

    The dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network's structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model's parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is difficult to assess the confidence associated with these in silico predictions. In particular, models with complex dynamics - such as oscillations - must be fit with computationally expensive global optimization routines, and cannot take advantage of existing measures of identifiability. Despite their difficulty to model mathematically, limit cycle oscillations play a key role in many biological processes, including cell cycling, metabolism, neuron firing, and circadian rhythms. In this study, we employ an efficient parameter estimation technique to enable a bootstrap uncertainty analysis for limit cycle models. Since the primary role of systems biology models is the insight they provide on responses to rate perturbations, we extend our uncertainty analysis to include first order sensitivity coefficients. Using a literature model of circadian rhythms, we show how predictive precision is degraded with decreasing sample points and increasing relative error. Additionally, we show how this method can be used for model discrimination by comparing the output identifiability of two candidate model structures to published literature data. Our method permits modellers of oscillatory systems to confidently

  20. Predictive computational modeling of the mucosal immune responses during Helicobacter pylori infection.

    Directory of Open Access Journals (Sweden)

    Adria Carbo

    Full Text Available T helper (Th cells play a major role in the immune response and pathology at the gastric mucosa during Helicobacter pylori infection. There is a limited mechanistic understanding regarding the contributions of CD4+ T cell subsets to gastritis development during H. pylori colonization. We used two computational approaches: ordinary differential equation (ODE-based and agent-based modeling (ABM to study the mechanisms underlying cellular immune responses to H. pylori and how CD4+ T cell subsets influenced initiation, progression and outcome of disease. To calibrate the model, in vivo experimentation was performed by infecting C57BL/6 mice intragastrically with H. pylori and assaying immune cell subsets in the stomach and gastric lymph nodes (GLN on days 0, 7, 14, 30 and 60 post-infection. Our computational model reproduced the dynamics of effector and regulatory pathways in the gastric lamina propria (LP in silico. Simulation results show the induction of a Th17 response and a dominant Th1 response, together with a regulatory response characterized by high levels of mucosal Treg cells. We also investigated the potential role of peroxisome proliferator-activated receptor γ (PPARγ activation on the modulation of host responses to H. pylori by using loss-of-function approaches. Specifically, in silico results showed a predominance of Th1 and Th17 cells in the stomach of the cell-specific PPARγ knockout system when compared to the wild-type simulation. Spatio-temporal, object-oriented ABM approaches suggested similar dynamics in induction of host responses showing analogous T cell distributions to ODE modeling and facilitated tracking lesion formation. In addition, sensitivity analysis predicted a crucial contribution of Th1 and Th17 effector responses as mediators of histopathological changes in the gastric mucosa during chronic stages of infection, which were experimentally validated in mice. These integrated immunoinformatics approaches

  1. On the best learning algorithm for web services response time prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Popentiu-Vladicescu, Florin

    2013-01-01

    In this article we will examine the effect of different learning algorithms, while training the MLP (Multilayer Perceptron) with the intention of predicting web services response time. Web services do not necessitate a user interface. This may seem contradictory to most people's concept of what...... an application is. A Web service is better imagined as an application "segment," or better as a program enabler. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the response of web services during their operation is very important....

  2. Can quantitative sensory testing predict responses to analgesic treatment?

    Science.gov (United States)

    Grosen, K; Fischer, I W D; Olesen, A E; Drewes, A M

    2013-10-01

    The role of quantitative sensory testing (QST) in prediction of analgesic effect in humans is scarcely investigated. This updated review assesses the effectiveness in predicting analgesic effects in healthy volunteers, surgical patients and patients with chronic pain. A systematic review of English written, peer-reviewed articles was conducted using PubMed and Embase (1980-2013). Additional studies were identified by chain searching. Search terms included 'quantitative sensory testing', 'sensory testing' and 'analgesics'. Studies on the relationship between QST and response to analgesic treatment in human adults were included. Appraisal of the methodological quality of the included studies was based on evaluative criteria for prognostic studies. Fourteen studies (including 720 individuals) met the inclusion criteria. Significant correlations were observed between responses to analgesics and several QST parameters including (1) heat pain threshold in experimental human pain, (2) electrical and heat pain thresholds, pressure pain tolerance and suprathreshold heat pain in surgical patients, and (3) electrical and heat pain threshold and conditioned pain modulation in patients with chronic pain. Heterogeneity among studies was observed especially with regard to application of QST and type and use of analgesics. Although promising, the current evidence is not sufficiently robust to recommend the use of any specific QST parameter in predicting analgesic response. Future studies should focus on a range of different experimental pain modalities rather than a single static pain stimulation paradigm. © 2013 European Federation of International Association for the Study of Pain Chapters.

  3. Physiological stress responses predict sexual functioning and satisfaction differently in women who have and have not been sexually abused in childhood

    OpenAIRE

    Meston, Cindy M.; Lorenz, Tierney A.

    2012-01-01

    Physiological responses to sexual stimuli may contribute to the increased rate of sexual problems seen in women with childhood sexual abuse (CSA) histories. We compared two physiological stress responses as predictors of sexual function and satisfaction, sympathetic nervous system (SNS) activation and cortisol in women with (CSA, N = 136) and without CSA histories (NSA, N = 102). In CSA survivors, cortisol response to sexual stimuli did not significantly predict sexual functioning; however, i...

  4. Prepotent response inhibition predicts treatment outcome in attention deficit/hyperactivity disorder

    NARCIS (Netherlands)

    van der Oord, S.; Geurts, H.M.; Prins, P.J.M.; Emmelkamp, P.M.G.; Oosterlaan, J.

    2012-01-01

    Objective: Inhibition deficits, including deficits in prepotent response inhibition and interference control, are core deficits in ADHD. The predictive value of prepotent response inhibition and interference control was assessed for outcome in a 10-week treatment trial with methylphenidate. Methods:

  5. Computational modeling predicts the ionic mechanism of late-onset responses in Unipolar Brush Cells

    Directory of Open Access Journals (Sweden)

    Sathyaa eSubramaniyam

    2014-08-01

    Full Text Available Unipolar Brush Cells (UBCs have been suggested to have a strong impact on cerebellar granular layer functioning, yet the corresponding cellular mechanisms remain poorly understood. UBCs have recently been reported to generate, in addition to early-onset glutamatergic synaptic responses, a late-onset response (LOR composed of a slow depolarizing ramp followed by a spike burst (Locatelli et al., 2013. The LOR activates as a consequence of synaptic activity and involves an intracellular cascade modulating H- and TRP-current gating. In order to assess the LOR mechanisms, we have developed a UBC multi-compartmental model (including soma, dendrite, initial segment and axon incorporating biologically realistic representations of ionic currents and a generic coupling mechanism regulating TRP and H channel gating. The model finely reproduced UBC responses to current injection, including a low-threshold spike sustained by CaLVA currents, a persistent discharge sustained by CaHVA currents, and a rebound burst following hyperpolarization sustained by H- and CaLVA-currents. Moreover, the model predicted that H- and TRP-current regulation was necessary and sufficient to generate the LOR and its dependence on the intensity and duration of mossy fiber activity. Therefore, the model showed that, using a basic set of ionic channels, UBCs generate a rich repertoire of delayed bursts, which could take part to the formation of tunable delay-lines in the local microcircuit.

  6. Computational modeling predicts the ionic mechanism of late-onset responses in unipolar brush cells.

    Science.gov (United States)

    Subramaniyam, Sathyaa; Solinas, Sergio; Perin, Paola; Locatelli, Francesca; Masetto, Sergio; D'Angelo, Egidio

    2014-01-01

    Unipolar Brush Cells (UBCs) have been suggested to play a critical role in cerebellar functioning, yet the corresponding cellular mechanisms remain poorly understood. UBCs have recently been reported to generate, in addition to early-onset glutamate receptor-dependent synaptic responses, a late-onset response (LOR) composed of a slow depolarizing ramp followed by a spike burst (Locatelli et al., 2013). The LOR activates as a consequence of synaptic activity and involves an intracellular cascade modulating H- and TRP-current gating. In order to assess the LOR mechanisms, we have developed a UBC multi-compartmental model (including soma, dendrite, initial segment, and axon) incorporating biologically realistic representations of ionic currents and a cytoplasmic coupling mechanism regulating TRP and H channel gating. The model finely reproduced UBC responses to current injection, including a burst triggered by a low-threshold spike (LTS) sustained by CaLVA currents, a persistent discharge sustained by CaHVA currents, and a rebound burst following hyperpolarization sustained by H- and CaLVA-currents. Moreover, the model predicted that H- and TRP-current regulation was necessary and sufficient to generate the LOR and its dependence on the intensity and duration of mossy fiber activity. Therefore, the model showed that, using a basic set of ionic channels, UBCs generate a rich repertoire of bursts, which could effectively implement tunable delay-lines in the local microcircuit.

  7. Prediction of heat-illness symptoms with the prediction of human vascular response in hot environment under resting condition.

    Science.gov (United States)

    Aggarwal, Yogender; Karan, Bhuwan Mohan; Das, Barsa Nand; Sinha, Rakesh Kumar

    2008-04-01

    The thermoregulatory control of human skin blood flow is vital to maintain the body heat storage during challenges of thermal homeostasis under heat stress. Whenever thermal homeostasis disturbed, the heat load exceeds heat dissipation capacity, which alters the cutaneous vascular responses along with other body physiological variables. Whole body skin blood flow has been calculated from the forearm blood flow. Present model has been designed using electronics circuit simulator (Multisim 8.0, National Instruments, USA), is to execute a series of predictive equations for early prediction of physiological parameters of young nude subjects during resting condition at various level of dry heat stress under almost still air to avoid causalities associated with hot environmental. The users can execute the model by changing the environmental temperature in degrees C and exposure time in minutes. The model would be able to predict and detect the changes in human vascular responses along with other physiological parameters and from this predicted values heat related-illness symptoms can be inferred.

  8. Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

    Science.gov (United States)

    Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

    2018-05-10

    Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

  9. Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.

    Directory of Open Access Journals (Sweden)

    Maxwell R Bennett

    Full Text Available Measurements of blood oxygenation level dependent (BOLD signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular connections.

  10. Buffering social influence: neural correlates of response inhibition predict driving safety in the presence of a peer.

    Science.gov (United States)

    Cascio, Christopher N; Carp, Joshua; O'Donnell, Matthew Brook; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G; Falk, Emily B

    2015-01-01

    Adolescence is a period characterized by increased sensitivity to social cues, as well as increased risk-taking in the presence of peers. For example, automobile crashes are the leading cause of death for adolescents, and driving with peers increases the risk of a fatal crash. Growing evidence points to an interaction between neural systems implicated in cognitive control and social and emotional context in predicting adolescent risk. We tested such a relationship in recently licensed teen drivers. Participants completed an fMRI session in which neural activity was measured during a response inhibition task, followed by a separate driving simulator session 1 week later. Participants drove alone and with a peer who was randomly assigned to express risk-promoting or risk-averse social norms. The experimentally manipulated social context during the simulated drive moderated the relationship between individual differences in neural activity in the hypothesized cognitive control network (right inferior frontal gyrus, BG) and risk-taking in the driving context a week later. Increased activity in the response inhibition network was not associated with risk-taking in the presence of a risky peer but was significantly predictive of safer driving in the presence of a cautious peer, above and beyond self-reported susceptibility to peer pressure. Individual differences in recruitment of the response inhibition network may allow those with stronger inhibitory control to override risky tendencies when in the presence of cautious peers. This relationship between social context and individual differences in brain function expands our understanding of neural systems involved in top-down cognitive control during adolescent development.

  11. Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with Leisure Activities

    Directory of Open Access Journals (Sweden)

    Brenda eHanna-Pladdy

    2012-07-01

    Full Text Available Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years on preserved cognitive functioning in advanced age . These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to nonmusical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study examined the type of leisure activity (musical versus other as well as the timing of engagement (age of acquisition, past versus recent in predictive models of successful cognitive aging. Seventy age and education matched older musicians (> 10 years and nonmusicians (ages 59-80 were evaluated on neuropsychological tests and life-style activities (AAP. Partition analyses were conducted on significant cognitive measures to explain performance variance in musicians. Musicians scored higher on tests of phonemic fluency, verbal immediate recall, judgment of line orientation (JLO, and Letter Number Sequencing (LNS, but not the AAP. The first partition analysis revealed education best predicted JLO in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (< 9 years predicted enhanced LNS in musicians, while analyses for AAP, verbal recall and fluency were not predictive. Recent and past musical activity, but not leisure activity, predicted variability across verbal and visuospatial domains in aging. Early musical acquisition predicted auditory

  12. A new constitutive model for prediction of impact rates response of polypropylene

    Directory of Open Access Journals (Sweden)

    Buckley C.P.

    2012-08-01

    Full Text Available This paper proposes a new constitutive model for predicting the impact rates response of polypropylene. Impact rates, as used here, refer to strain rates greater than 1000 1/s. The model is a physically based, three-dimensional constitutive model which incorporates the contributions of the amorphous, crystalline, pseudo-amorphous and entanglement networks to the constitutive response of polypropylene. The model mathematics is based on the well-known Glass-Rubber model originally developed for glassy polymers but the arguments have herein been extended to semi-crystalline polymers. In order to predict the impact rates behaviour of polypropylene, the model exploits the well-known framework of multiple processes yielding of polymers. This work argues that two dominant viscoelastic relaxation processes – the alpha- and beta-processes – can be associated with the yield responses of polypropylene observed at low-rate-dominant and impact-rates dominant loading regimes. Compression test data on polypropylene have been used to validate the model. The study has found that the model predicts quite well the experimentally observed nonlinear rate-dependent impact response of polypropylene.

  13. Consumer factors predicting level of treatment response to illness management and recovery.

    Science.gov (United States)

    White, Dominique A; McGuire, Alan B; Luther, Lauren; Anderson, Adrienne I; Phalen, Peter; McGrew, John H

    2017-12-01

    This study aims to identify consumer-level predictors of level of treatment response to illness management and recovery (IMR) to target the appropriate consumers and aid psychiatric rehabilitation settings in developing intervention adaptations. Secondary analyses from a multisite study of IMR were conducted. Self-report data from consumer participants of the parent study (n = 236) were analyzed for the current study. Consumers completed prepost surveys assessing illness management, coping, goal-related hope, social support, medication adherence, and working alliance. Correlations and multiple regression analyses were run to identify self-report variables that predicted level of treatment response to IMR. Analyses revealed that goal-related hope significantly predicted level of improved illness self-management, F(1, 164) = 10.93, p consumer-level predictors of level of treatment response have not been explored for IMR. Although 2 significant predictors were identified, study findings suggest more work is needed. Future research is needed to identify additional consumer-level factors predictive of IMR treatment response in order to identify who would benefit most from this treatment program. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  14. Predicting human activities in sequences of actions in RGB-D videos

    Science.gov (United States)

    Jardim, David; Nunes, Luís.; Dias, Miguel

    2017-03-01

    In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

  15. On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal Response

    Science.gov (United States)

    Jen, Chian-Li; Tilwick, Leon

    2000-01-01

    This paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.

  16. Active load management in an intelligent building using model predictive control strategy

    DEFF Research Database (Denmark)

    Zong, Yi; Kullmann, Daniel; Thavlov, Anders

    2011-01-01

    This paper introduces PowerFlexHouse, a research facility for exploring the technical potential of active load management in a distributed power system (SYSLAB) with a high penetration of renewable energy and presents in detail on how to implement a thermal model predictive controller for load...... shifting in PowerFlexHouse heaters' power consumption scheme. With this demand side control study, it is expected that this method of demand response can dramatically raise energy efficiencies and improve grid reliability, when there is a high penetration of intermittent energy resources in the power...

  17. Angiotensinogen and HLA class II predict bevacizumab response in recurrent glioblastoma patients

    DEFF Research Database (Denmark)

    Urup, Thomas; Michaelsen, Signe Regner; Olsen, Lars Rønn

    2016-01-01

    Background: Bevacizumab combination therapy is among the most frequently used treatments in recurrent glioblastoma and patients who achieve response to bevacizumab have improved survival as well as quality of life. Accordingly, the aim of this study was to identify predictive biomarkers for bevac......Background: Bevacizumab combination therapy is among the most frequently used treatments in recurrent glioblastoma and patients who achieve response to bevacizumab have improved survival as well as quality of life. Accordingly, the aim of this study was to identify predictive biomarkers...... for bevacizumab response in recurrent glioblastoma patients. Methods: The study included a total of 82 recurrent glioblastoma patients treated with bevacizumab combination therapy whom were both response and biomarker evaluable. Gene expression of tumor tissue was analyzed by using a customized Nano...

  18. Prediction-error in the context of real social relationships modulates reward system activity.

    Science.gov (United States)

    Poore, Joshua C; Pfeifer, Jennifer H; Berkman, Elliot T; Inagaki, Tristen K; Welborn, Benjamin L; Lieberman, Matthew D

    2012-01-01

    The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward-social validation-and this activity's relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants' expectations for their romantic partners' positive regard of them were confirmed (validated) or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

  19. Attachment predicts cortisol response and closeness in dyadic social interaction.

    Science.gov (United States)

    Ketay, Sarah; Beck, Lindsey A

    2017-06-01

    The present study examined how the interplay of partners' attachment styles influences cortisol response, actual closeness, and desired closeness during friendship initiation. Participants provided salivary cortisol samples at four timepoints throughout either a high or low closeness task that facilitated high or low levels of self-disclosure with a potential friend (i.e., another same-sex participant). Levels of actual closeness and desired closeness following the task were measured via inclusion of other in the self. Results from multi-level modeling indicated that the interaction of both participants' attachment avoidance predicted cortisol response patterns, with participants showing the highest cortisol response when there was a mismatch between their own and their partners' attachment avoidance. Further, the interaction between both participants' attachment anxiety predicted actual closeness and desired closeness, with participants both feeling and wanting the most closeness with partners when both they and their partners were low in attachment anxiety. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Predicting responsiveness to intervention in dyslexia using dynamic assessment

    NARCIS (Netherlands)

    Aravena, S.; Tijms, J.; Snellings, P.; van der Molen, M.W.

    In the current study we examined the value of a dynamic test for predicting responsiveness to reading intervention for children diagnosedwith dyslexia. The test consisted of a 20-minute training aimed at learning eight basic letter–speech sound correspondences within an artificial orthography,

  1. Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task

    Science.gov (United States)

    Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.

    2000-06-01

    When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.

  2. Processing of action- but not stimulus-related prediction errors differs between active and observational feedback learning.

    Science.gov (United States)

    Kobza, Stefan; Bellebaum, Christian

    2015-01-01

    Learning of stimulus-response-outcome associations is driven by outcome prediction errors (PEs). Previous studies have shown larger PE-dependent activity in the striatum for learning from own as compared to observed actions and the following outcomes despite comparable learning rates. We hypothesised that this finding relates primarily to a stronger integration of action and outcome information in active learners. Using functional magnetic resonance imaging, we investigated brain activations related to action-dependent PEs, reflecting the deviation between action values and obtained outcomes, and action-independent PEs, reflecting the deviation between subjective values of response-preceding cues and obtained outcomes. To this end, 16 active and 15 observational learners engaged in a probabilistic learning card-guessing paradigm. On each trial, active learners saw one out of five cues and pressed either a left or right response button to receive feedback (monetary win or loss). Each observational learner observed exactly those cues, responses and outcomes of one active learner. Learning performance was assessed in active test trials without feedback and did not differ between groups. For both types of PEs, activations were found in the globus pallidus, putamen, cerebellum, and insula in active learners. However, only for action-dependent PEs, activations in these structures and the anterior cingulate were increased in active relative to observational learners. Thus, PE-related activity in the reward system is not generally enhanced in active relative to observational learning but only for action-dependent PEs. For the cerebellum, additional activations were found across groups for cue-related uncertainty, thereby emphasising the cerebellum's role in stimulus-outcome learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Gut Microbiota Signatures Predict Host and Microbiota Responses to Dietary Interventions in Obese Individuals

    Science.gov (United States)

    Korpela, Katri; Flint, Harry J.; Johnstone, Alexandra M.; Lappi, Jenni; Poutanen, Kaisa; Dewulf, Evelyne; Delzenne, Nathalie; de Vos, Willem M.; Salonen, Anne

    2014-01-01

    Background Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host. Methodology Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set – test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters. Principal Findings Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC  =  0.77–1; predicted vs. observed correlation  =  0.67–0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health. Conclusion This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of

  4. A noise level prediction method based on electro-mechanical frequency response function for capacitors.

    Science.gov (United States)

    Zhu, Lingyu; Ji, Shengchang; Shen, Qi; Liu, Yuan; Li, Jinyu; Liu, Hao

    2013-01-01

    The capacitors in high-voltage direct-current (HVDC) converter stations radiate a lot of audible noise which can reach higher than 100 dB. The existing noise level prediction methods are not satisfying enough. In this paper, a new noise level prediction method is proposed based on a frequency response function considering both electrical and mechanical characteristics of capacitors. The electro-mechanical frequency response function (EMFRF) is defined as the frequency domain quotient of the vibration response and the squared capacitor voltage, and it is obtained from impulse current experiment. Under given excitations, the vibration response of the capacitor tank is the product of EMFRF and the square of the given capacitor voltage in frequency domain, and the radiated audible noise is calculated by structure acoustic coupling formulas. The noise level under the same excitations is also measured in laboratory, and the results are compared with the prediction. The comparison proves that the noise prediction method is effective.

  5. Expression of estrogen-related gene markers in breast cancer tissue predicts aromatase inhibitor responsiveness.

    Directory of Open Access Journals (Sweden)

    Irene Moy

    Full Text Available Aromatase inhibitors (AIs are the most effective class of drugs in the endocrine treatment of breast cancer, with an approximate 50% treatment response rate. Our objective was to determine whether intratumoral expression levels of estrogen-related genes are predictive of AI responsiveness in postmenopausal women with breast cancer. Primary breast carcinomas were obtained from 112 women who received AI therapy after failing adjuvant tamoxifen therapy and developing recurrent breast cancer. Tumor ERα and PR protein expression were analyzed by immunohistochemistry (IHC. Messenger RNA (mRNA levels of 5 estrogen-related genes-AKR1C3, aromatase, ERα, and 2 estradiol/ERα target genes, BRCA1 and PR-were measured by real-time PCR. Tumor protein and mRNA levels were compared with breast cancer progression rates to determine predictive accuracy. Responsiveness to AI therapy-defined as the combined complete response, partial response, and stable disease rates for at least 6 months-was 51%; rates were 56% in ERα-IHC-positive and 14% in ERα-IHC-negative tumors. Levels of ERα, PR, or BRCA1 mRNA were independently predictive for responsiveness to AI. In cross-validated analyses, a combined measurement of tumor ERα and PR mRNA levels yielded a more superior specificity (36% and identical sensitivity (96% to the current clinical practice (ERα/PR-IHC. In patients with ERα/PR-IHC-negative tumors, analysis of mRNA expression revealed either non-significant trends or statistically significant positive predictive values for AI responsiveness. In conclusion, expression levels of estrogen-related mRNAs are predictive for AI responsiveness in postmenopausal women with breast cancer, and mRNA expression analysis may improve patient selection.

  6. Clinical utility of pretreatment prediction of chemoradiotherapy response in rectal cancer: a review.

    Science.gov (United States)

    Yoo, Byong Chul; Yeo, Seung-Gu

    2017-03-01

    Approximately 20% of all patients with locally advanced rectal cancer experience pathologically complete responses following neoadjuvant chemoradiotherapy (CRT) and standard surgery. The utility of radical surgery for patients exhibiting good CRT responses has been challenged. Organ-sparing strategies for selected patients exhibiting complete clinical responses include local excision or no immediate surgery. The subjects of this tailored management are patients whose presenting disease corresponds to current indications of neoadjuvant CRT, and their post-CRT tumor response is assessed by clinical and radiological examinations. However, a model predictive of the CRT response, applied before any treatment commenced, would be valuable to facilitate such a personalized approach. This would increase organ preservation, particularly in patients for whom upfront CRT is not generally prescribed. Molecular biomarkers hold the greatest promise for development of a pretreatment predictive model of CRT response. A combination of clinicopathological, radiological, and molecular markers will be necessary to render the model robust. Molecular research will also contribute to the development of drugs that can overcome the radioresistance of rectal tumors. Current treatments for rectal cancer are based on the expected prognosis given the presenting disease extent. In the future, treatment schemes may be modified by including the predicted CRT response evaluated at presentation.

  7. Predictive value of European Scleroderma Group Activity Index in an early scleroderma cohort.

    Science.gov (United States)

    Nevskaya, Tatiana; Baron, Murray; Pope, Janet E

    2017-07-01

    To estimate the effect of disease activity, as measured by the European Scleroderma Research Group Activity Index (EScSG-AI), on the risk of subsequent organ damage in a large systemic sclerosis (SSc) cohort. Of 421 SSc patients from the Canadian Scleroderma Research Group database with disease duration of ⩽ 3 years, 197 who had no evidence of end-stage organ damage initially and available 3 year follow-up were included. Disease activity was assessed by the EScSG-AI with two variability measures: the adjusted mean EScSG-AI (the area under the curve of the EScSG-AI over the observation period) and persistently active disease/flare. Outcomes were based on the Medsger severity scale and included accrual of a new severity score (Δ ⩾ 1) overall and within organ systems or reaching a significant level of deterioration in health status. After adjustment for covariates, the adjusted mean EScSG-AI was the most consistent predictor of risk across the study outcomes over 3 years in dcSSc: disease progression defined as Δ ⩾ 1 in any major internal organ, significant decline in forced vital capacity and diffusing capacity of carbon monoxide, severity of visceral disease and HAQ Disability Index worsening. In multivariate analysis, progression of lung disease was predicted solely by adjusted mean EScSG-AI, while the severity of lung disease was predicted the adjusted mean EScSG-AI, older age, modified Rodnan skin score (mRSS) and initial severity. The EScSG-AI was associated with patient- and physician-assessed measures of health status and overpowered the mRSS in predicting disease outcomes. Disease activity burden quantified with the adjusted mean EScSG-AI predicted the risk of deterioration in health status and severe organ involvement in dcSSc. The EScSG-AI is more responsive when done repeatedly and averaged. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email

  8. Direct-to-consumer advertising of predictive genetic tests: a health belief model based examination of consumer response.

    Science.gov (United States)

    Rollins, Brent L; Ramakrishnan, Shravanan; Perri, Matthew

    2014-01-01

    Direct-to-consumer (DTC) advertising of predictive genetic tests (PGTs) has added a new dimension to health advertising. This study used an online survey based on the health belief model framework to examine and more fully understand consumers' responses and behavioral intentions in response to a PGT DTC advertisement. Overall, consumers reported moderate intentions to talk with their doctor and seek more information about PGTs after advertisement exposure, though consumers did not seem ready to take the advertised test or engage in active information search. Those who perceived greater threat from the disease, however, had significantly greater behavioral intentions and information search behavior.

  9. Paired hormone response elements predict caveolin-1 as a glucocorticoid target gene.

    Directory of Open Access Journals (Sweden)

    Marinus F van Batenburg

    2010-01-01

    Full Text Available Glucocorticoids act in part via glucocorticoid receptor binding to hormone response elements (HREs, but their direct target genes in vivo are still largely unknown. We developed the criterion that genomic occurrence of paired HREs at an inter-HRE distance less than 200 bp predicts hormone responsiveness, based on synergy of multiple HREs, and HRE information from known target genes. This criterion predicts a substantial number of novel responsive genes, when applied to genomic regions 10 kb upstream of genes. Multiple-tissue in situ hybridization showed that mRNA expression of 6 out of 10 selected genes was induced in a tissue-specific manner in mice treated with a single dose of corticosterone, with the spleen being the most responsive organ. Caveolin-1 was strongly responsive in several organs, and the HRE pair in its upstream region showed increased occupancy by glucocorticoid receptor in response to corticosterone. Our approach allowed for discovery of novel tissue specific glucocorticoid target genes, which may exemplify responses underlying the permissive actions of glucocorticoids.

  10. Mood Predicts Response to Placebo CPAP

    Directory of Open Access Journals (Sweden)

    Carl J. Stepnowsky

    2012-01-01

    Full Text Available Study Objectives. Continuous positive airway pressure (CPAP therapy is efficacious for treating obstructive sleep apnea (OSA, but recent studies with placebo CPAP (CPAP administered at subtherapeutic pressure have revealed nonspecific (or placebo responses to CPAP treatment. This study examined baseline psychological factors associated with beneficial effects from placebo CPAP treatment. Participants. Twenty-five participants were studied with polysomnography at baseline and after treatment with placebo CPAP. Design. Participants were randomized to either CPAP treatment or placebo CPAP. Baseline mood was assessed with the Profile of Mood States (POMS. Total mood disturbance (POMS-Total was obtained by summing the six POMS subscale scores, with Vigor weighted negatively. The dependent variable was changed in apnea-hypopnea index (ΔAHI, calculated by subtracting pre- from post-CPAP AHI. Negative values implied improvement. Hierarchical regression analysis was performed, with pre-CPAP AHI added as a covariate to control for baseline OSA severity. Results. Baseline emotional distress predicted the drop in AHI in response to placebo CPAP. Highly distressed patients showed greater placebo response, with a 34% drop (i.e., improvement in AHI. Conclusion. These findings underscore the importance of placebo-controlled studies of CPAP treatment. Whereas such trials are routinely included in drug trials, this paper argues for their importance even in mechanical-oriented sleep interventions.

  11. Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy.

    Science.gov (United States)

    Mani, Subramani; Chen, Yukun; Li, Xia; Arlinghaus, Lori; Chakravarthy, A Bapsi; Abramson, Vandana; Bhave, Sandeep R; Levy, Mia A; Xu, Hua; Yankeelov, Thomas E

    2013-01-01

    To employ machine learning methods to predict the eventual therapeutic response of breast cancer patients after a single cycle of neoadjuvant chemotherapy (NAC). Quantitative dynamic contrast-enhanced MRI and diffusion-weighted MRI data were acquired on 28 patients before and after one cycle of NAC. A total of 118 semiquantitative and quantitative parameters were derived from these data and combined with 11 clinical variables. We used Bayesian logistic regression in combination with feature selection using a machine learning framework for predictive model building. The best predictive models using feature selection obtained an area under the curve of 0.86 and an accuracy of 0.86, with a sensitivity of 0.88 and a specificity of 0.82. With the numerous options for NAC available, development of a method to predict response early in the course of therapy is needed. Unfortunately, by the time most patients are found not to be responding, their disease may no longer be surgically resectable, and this situation could be avoided by the development of techniques to assess response earlier in the treatment regimen. The method outlined here is one possible solution to this important clinical problem. Predictive modeling approaches based on machine learning using readily available clinical and quantitative MRI data show promise in distinguishing breast cancer responders from non-responders after the first cycle of NAC.

  12. Nomogram for predicting pathologically complete response after neoadjuvant chemoradiotherapy for oesophageal cancer

    International Nuclear Information System (INIS)

    Toxopeus, Eelke Lucie Anne; Nieboer, Daan; Shapiro, Joel; Biermann, Katharina; Gaast, Ate van der; Rij, Carolien M. van; Steyerberg, Ewout Willem; Lanschot, Joseph Jan Baptiste van; Wijnhoven, Bas Peter Louis

    2015-01-01

    Background: A pathologically complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) is seen in 30% of the patients with oesophageal cancer. The aim is to identify patient and tumour characteristics associated with a pCR and to develop a nomogram for the prediction of pCR. Patients and methods: Patients who underwent nCRT followed by surgery were identified and response to nCRT was assessed according to a modified Mandard classification in the resection specimen. A model was developed with age, gender, histology and location of the tumour, differentiation grade, alcohol use, smoking, percentage weight loss, Charlson Comorbidity Index (CCI), cT-stage and cN-stage as potential predictors for pCR. Probability of pCR was studied via logistic regression. Performance of the prediction nomogram was quantified using the concordance statistic (c-statistic) and corrected for optimism. Results: A total of 381 patients were included. After surgery, 27.6% of the tumours showed a pCR. Female sex, squamous cell histology, poor differentiation grade, and low cT-stage were predictive for a pCR with a c-statistic of 0.64 (corrected for optimism). Conclusion: A nomogram for the prediction of pathologically complete response after neoadjuvant chemoradiotherapy was developed, with a reasonable predictive power. This nomogram needs external validation before it can be used for individualised clinical decision-making

  13. Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness

    Directory of Open Access Journals (Sweden)

    Luca Marchetti

    2017-01-01

    Full Text Available Systems biology has been recently applied to vaccinology to better understand immunological responses to the influenza vaccine. Particular attention has been paid to the identification of early signatures capable of predicting vaccine immunogenicity. Building from previous studies, we employed a recently established algorithm for signature-based clustering of expression profiles, SCUDO, to provide new insights into why blood-derived transcriptome biomarkers often fail to predict the seroresponse to the influenza virus vaccination. Specifically, preexisting immunity against one or more vaccine antigens, which was found to negatively affect the seroresponse, was identified as a confounding factor able to decouple early transcriptome from later antibody responses, resulting in the degradation of a biomarker predictive power. Finally, the broadly accepted definition of seroresponse to influenza virus vaccine, represented by the maximum response across the vaccine-targeted strains, was compared to a composite measure integrating the responses against all strains. This analysis revealed that composite measures provide a more accurate assessment of the seroresponse to multicomponent influenza vaccines.

  14. Prediction of Positions of Active Compounds Makes It Possible To Increase Activity in Fragment-Based Drug Development

    Directory of Open Access Journals (Sweden)

    Yoshifumi Fukunishi

    2011-05-01

    Full Text Available We have developed a computational method that predicts the positions of active compounds, making it possible to increase activity as a fragment evolution strategy. We refer to the positions of these compounds as the active position. When an active fragment compound is found, the following lead generation process is performed, primarily to increase activity. In the current method, to predict the location of the active position, hydrogen atoms are replaced by small side chains, generating virtual compounds. These virtual compounds are docked to a target protein, and the docking scores (affinities are examined. The hydrogen atom that gives the virtual compound with good affinity should correspond to the active position and it should be replaced to generate a lead compound. This method was found to work well, with the prediction of the active position being 2 times more efficient than random synthesis. In the current study, 15 examples of lead generation were examined. The probability of finding active positions among all hydrogen atoms was 26%, and the current method accurately predicted 60% of the active positions.

  15. Predicting physical activity energy expenditure in wheelchair users with a multisensor device.

    Science.gov (United States)

    Nightingale, T E; Walhin, J P; Thompson, D; Bilzon, J L J

    2015-01-01

    To assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration (IC) method. 15 manual wheelchair users (36±10 years, 72±11 kg) completed 10 activities: resting, folding clothes, wheelchair propulsion on a 1% gradient (3456 and 7 km/h) and propulsion at 4 km/h (with an additional 8% of body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. Criterion PAEE was measured using a computerised indirect calorimetry system. Participants wore a combined accelerometer and heart rate monitor (Actiheart). They also performed an incremental arm crank ergometry test to exhaustion which permitted retrospective individual calibration of the Actiheart for the activity protocol. Linear regression analysis was conducted between criterion (indirect calorimetry) and estimated PAEE from the Actiheart using the manufacturer's proprietary algorithms (group calibration, GC) or IC. Bland-Altman plots were used and mean absolute error was calculated to assess the agreement between criterion values and estimated PAEE. Predicted PAEE was significantly (p<0.01) correlated with criterion PAEE (GC, r=0.76 and IC, r=0.95). The absolute bias ±95% limits of agreement were 0.51±3.75 and -0.22±0.96 kcal/min for GC and IC, respectively. Mean absolute errors across the activity protocol were 51.4±38.9% using GC and 16.8±15.8% using IC. PAEE can be accurately and precisely estimated using a combined accelerometer and heart rate monitor device, with integration of an IC. Interindividual variance in cardiovascular function and response to exercise is high in this population. Therefore, in manual wheelchair users, we advocate the use of an IC when using the Actiheart to predict PAEE.

  16. Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact.

    Science.gov (United States)

    Dijkstra, J; Kebreab, E; Mills, J A N; Pellikaan, W F; López, S; Bannink, A; France, J

    2007-02-01

    Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product composition, excretion of nutrients to the environment, and nutrition related disorders. The change from a requirement to a response system to meet the needs of various stakeholders requires prediction of the profile of absorbed nutrients and its subsequent utilisation for various purposes. This contribution examines the challenges to predicting the profile of nutrients available for absorption in dairy cattle and provides guidelines for further improved prediction with regard to animal production responses and environmental pollution.The profile of nutrients available for absorption comprises volatile fatty acids, long-chain fatty acids, amino acids and glucose. Thus the importance of processes in the reticulo-rumen is obvious. Much research into rumen fermentation is aimed at determination of substrate degradation rates. Quantitative knowledge on rates of passage of nutrients out of the rumen is rather limited compared with that on degradation rates, and thus should be an important theme in future research. Current systems largely ignore microbial metabolic variation, and extant mechanistic models of rumen fermentation give only limited attention to explicit representation of microbial metabolic activity. Recent molecular techniques indicate that knowledge on the presence and activity of various microbial species is far from complete. Such techniques may give a wealth of information, but to include such findings in systems predicting the nutrient profile requires close collaboration between molecular scientists and mathematical modellers on interpreting and evaluating quantitative data. Protozoal metabolism is of particular interest here given the paucity of quantitative data

  17. Cortical activity patterns predict robust speech discrimination ability in noise

    Science.gov (United States)

    Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

    2012-01-01

    The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

  18. A pilot validation of a modified Illness Perceptions Questionnaire designed to predict response to cognitive therapy for psychosis.

    Science.gov (United States)

    Marcus, Elena; Garety, Philippa; Weinman, John; Emsley, Richard; Dunn, Graham; Bebbington, Paul; Freeman, Daniel; Kuipers, Elizabeth; Fowler, David; Hardy, Amy; Waller, Helen; Jolley, Suzanne

    2014-12-01

    Clinical responsiveness to cognitive behavioural therapy for psychosis (CBTp) varies. Recent research has demonstrated that illness perceptions predict active engagement in therapy, and, thereby, better outcomes. In this study, we aimed to investigate the psychometric properties of a modification of the Illness Perceptions Questionnaire (M-IPQ) designed to predict response following CBTp. Fifty-six participants with persistent, distressing delusions completed the M-IPQ; forty before a brief CBT intervention targeting persecutory ideation and sixteen before and after a control condition. Additional predictors of outcome (delusional conviction, symptom severity and belief inflexibility) were assessed at baseline. Outcomes were assessed at baseline and at follow-up four to eight weeks later. The M-IPQ comprised two factors measuring problem duration and therapy-specific perceptions of Cure/Control. Associated subscales, formed by summing the relevant items for each factor, were reliable in their structure. The Cure/Control subscale was also reliable over time; showed convergent validity with other predictors of outcome; predicted therapy outcomes; and differentially predicted treatment effects. We measured outcome without an associated measure of engagement, in a small sample. Findings are consistent with hypothesis and existing research, but require replication in a larger, purposively recruited sample. The Cure/Control subscale of the M-IPQ shows promise as a predictor of response to therapy. Specifically targeting these illness perceptions in the early stages of cognitive behavioural therapy may improve engagement and, consequently, outcomes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli.

    Directory of Open Access Journals (Sweden)

    Elisa M Tartaglia

    2015-02-01

    Full Text Available Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming sensory information. The mechanistic and functional relationship between these two basic neurophysiological signatures of working memory remains elusive. We propose that match signals are generated as a result of transient changes in local network excitability brought about by persistent activity. Neurons more active will be more excitable, and thus more responsive to external inputs. Accordingly, network responses are jointly determined by the incoming stimulus and the ongoing pattern of persistent activity. Using a spiking model network, we show that this mechanism is able to reproduce most of the experimental phenomenology of match effects as exposed by single-cell recordings during delayed-response tasks. The model provides a unified, parsimonious mechanistic account of the main neuronal correlates of working memory, makes several experimentally testable predictions, and demonstrates a new functional role for persistent activity.

  20. Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

    Science.gov (United States)

    Frady, Gregory P.; Duvall, Lowery D.; Fulcher, Clay W. G.; Laverde, Bruce T.; Hunt, Ronald A.

    2011-01-01

    rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for component-loaded curved orthogrid panels typical of launch vehicle skin structures. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was applied to correlate the measured input sound pressures across the energized panel. This application quantifies the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software developed for the RPTF method allows easy replacement of the diffuse acoustic field with other pressure fields such as a turbulent boundary layer (TBL) model suitable for vehicle ascent. Structural responses

  1. Predictive value of brain perfusion SPECT for rTMS response in pharmacoresistant depression

    Energy Technology Data Exchange (ETDEWEB)

    Richieri, Raphaelle; Lancon, Christophe [Sainte-Marguerite University Hospital, Department of Psychiatry, Marseille (France); La Timone University, EA 3279 - Self-perceived Health Assessment Research Unit, School of Medicine, Marseille (France); Boyer, Laurent [La Timone University, EA 3279 - Self-perceived Health Assessment Research Unit, School of Medicine, Marseille (France); La Timone University Hospital, Assistance Publique - Hopitaux de Marseille, Department of Public Health, Marseille (France); Farisse, Jean [Sainte-Marguerite University Hospital, Department of Psychiatry, Marseille (France); Colavolpe, Cecile; Mundler, Olivier [La Timone University Hospital, Assistance Publique - Hopitaux de Marseille, Service Central de Biophysique et Medecine Nucleaire, Marseille (France); Universite de la Mediterranee, Centre Europeen de Recherche en Imagerie Medicale (CERIMED), Marseille (France); Guedj, Eric [La Timone University Hospital, Assistance Publique - Hopitaux de Marseille, Service Central de Biophysique et Medecine Nucleaire, Marseille (France); Universite de la Mediterranee, Centre Europeen de Recherche en Imagerie Medicale (CERIMED), Marseille (France); Hopital de la Timone, Service Central de Biophysique et de Medecine Nucleaire, Marseille Cedex 5 (France)

    2011-09-15

    The aim of this study was to determine the predictive value of whole-brain voxel-based regional cerebral blood flow (rCBF) for repetitive transcranial magnetic stimulation (rTMS) response in patients with pharmacoresistant depression. Thirty-three right-handed patients who met DSM-IV criteria for major depressive disorder (unipolar or bipolar depression) were included before rTMS. rTMS response was defined as at least 50% reduction in the baseline Beck Depression Inventory scores. The predictive value of {sup 99m}Tc-ethyl cysteinate dimer (ECD) single photon emission computed tomography (SPECT) for rTMS response was studied before treatment by comparing rTMS responders to non-responders at voxel level using Statistical Parametric Mapping (SPM) (p < 0.001, uncorrected). Of the patients, 18 (54.5%) were responders to rTMS and 15 were non-responders (45.5%). There were no statistically significant differences in demographic and clinical characteristics (p > 0.10). In comparison to responders, non-responders showed significant hypoperfusions (p < 0.001, uncorrected) in the left medial and bilateral superior frontal cortices (BA10), the left uncus/parahippocampal cortex (BA20/BA35) and the right thalamus. The area under the curve for the combination of SPECT clusters to predict rTMS response was 0.89 (p < 0.001). Sensitivity, specificity, positive predictive value and negative predictive value for the combination of clusters were: 94, 73, 81 and 92%, respectively. This study shows that, in pharmacoresistant depression, pretreatment rCBF of specific brain regions is a strong predictor for response to rTMS in patients with homogeneous demographic/clinical features. (orig.)

  2. Predicting Emotional Responses to Horror Films from Cue-Specific Affect.

    Science.gov (United States)

    Neuendorf, Kimberly A.; Sparks, Glenn G.

    1988-01-01

    Assesses individuals' fear and enjoyment reactions to horror films, applying theories of cognition and affect that predict emotional responses to a stimulus on the basis of prior affect toward specific cues included in that stimulus. (MM)

  3. Predicting forest insect flight activity: A Bayesian network approach.

    Directory of Open Access Journals (Sweden)

    Stephen M Pawson

    Full Text Available Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model's predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways.

  4. Quitting smoking: The importance of non-smoker identity in predicting smoking behaviour and responses to a smoking ban.

    Science.gov (United States)

    Meijer, Eline; Gebhardt, Winifred A; Dijkstra, Arie; Willemsen, Marc C; Van Laar, Colette

    2015-01-01

    We examined how 'smoker' and 'non-smoker' self- and group-identities and socio-economic status (SES) may predict smoking behaviour and responses to antismoking measures (i.e., the Dutch smoking ban in hospitality venues). We validated a measure of responses to the smoking ban. Longitudinal online survey study with one-year follow-up (N = 623 at T1 in 2011; N = 188 at T2 in 2012) among daily smokers. Intention to quit, quit attempts and 'rejecting', 'victimizing', 'socially conscious smoking' and 'active quitting' responses to the smoking ban. Non-smoker identities are more important than smoker identities in predicting intention to quit, quit attempts and responses to the smoking ban, even when controlling for other important predictors such as nicotine dependence. Smokers with stronger non-smoker identities had stronger intentions to quit, were more likely to attempt to quit between measurements, and showed less negative and more positive responses to the smoking ban. The association between non-smoker self-identity and intention to quit was stronger among smokers with lower than higher SES. Antismoking measures might be more effective if they would focus also on the identity of smokers, and help smokers to increase identification with non-smoking and non-smokers.

  5. Assessment of Predictive Markers of Response to Neoadjuvant Chemotherapy in Breast Cancer

    Directory of Open Access Journals (Sweden)

    Mallika Tewari

    2010-10-01

    Conclusion: Of all parameters examined, only the apoptosis-related genes (Bcl-2 and BAX seemed to exert some influence on the response to NACT, and neither by itself was sufficient to predict pCR; however, 50 patients is not sufficient to simultaneously analyse several predictive markers.

  6. Predicting environmental restoration activities through static simulation

    International Nuclear Information System (INIS)

    Ross, T.L.; King, D.A.; Wilkins, M.L.; Forward, M.F.

    1994-12-01

    This paper discusses a static simulation model that predicts several performance measures of environmental restoration activities over different remedial strategies. Basic model operation consists of manipulating and processing waste streams via selecting and applying remedial technologies according to the strategy. Performance measure prediction is possible for contaminated soil, solid waste, surface water, groundwater, storage tank, and facility sites. Simulations are performed for the U.S. Department of Energy in support of its Programmatic Environmental Impact Statement

  7. Authoritarian parenting predicts reduced electrocortical response to observed adolescent offspring rewards

    Science.gov (United States)

    Speed, Brittany C.; Nelson, Brady; Bress, Jennifer N.; Hajcak, Greg

    2017-01-01

    Abstract Parenting styles are robust predictors of offspring outcomes, yet little is known about their neural underpinnings. In this study, 44 parent-adolescent dyads (Mage of adolescent = 12.9) completed a laboratory guessing task while EEG was continuously recorded. In the task, each pair member received feedback about their own monetary wins and losses and also observed the monetary wins and losses of the other member of the pair. We examined the association between self-reported parenting style and parents’ electrophysiological responses to watching their adolescent winning and losing money, dubbed the observational Reward Positivity (RewP) and observational feedback negativity (FN), respectively. Self-reported authoritarian parenting predicted reductions in parents’ observational RewP but not FN. This predictive relationship remained after adjusting for sex of both participants, parents’ responsiveness to their own wins, and parental psychopathology. ‘Exploratory analyses found that permissive parenting was associated with a blunting of the adolescents’ response to their parents’ losses’. These findings suggest that parents’ rapid neural responses to their child’s successes may relate to the harsh parenting behaviors associated with authoritarian parenting. PMID:27613780

  8. Hypoxia-dependent sequestration of an oxygen sensor by a widespread structural motif can shape the hypoxic response - a predictive kinetic model

    Directory of Open Access Journals (Sweden)

    Novák Béla

    2010-10-01

    Full Text Available Abstract Background The activity of the heterodimeric transcription factor hypoxia inducible factor (HIF is regulated by the post-translational, oxygen-dependent hydroxylation of its α-subunit by members of the prolyl hydroxylase domain (PHD or EGLN-family and by factor inhibiting HIF (FIH. PHD-dependent hydroxylation targets HIFα for rapid proteasomal degradation; FIH-catalysed asparaginyl-hydroxylation of the C-terminal transactivation domain (CAD of HIFα suppresses the CAD-dependent subset of the extensive transcriptional responses induced by HIF. FIH can also hydroxylate ankyrin-repeat domain (ARD proteins, a large group of proteins which are functionally unrelated but share common structural features. Competition by ARD proteins for FIH is hypothesised to affect FIH activity towards HIFα; however the extent of this competition and its effect on the HIF-dependent hypoxic response are unknown. Results To analyse if and in which way the FIH/ARD protein interaction affects HIF-activity, we created a rate equation model. Our model predicts that an oxygen-regulated sequestration of FIH by ARD proteins significantly shapes the input/output characteristics of the HIF system. The FIH/ARD protein interaction is predicted to create an oxygen threshold for HIFα CAD-hydroxylation and to significantly sharpen the signal/response curves, which not only focuses HIFα CAD-hydroxylation into a defined range of oxygen tensions, but also makes the response ultrasensitive to varying oxygen tensions. Our model further suggests that the hydroxylation status of the ARD protein pool can encode the strength and the duration of a hypoxic episode, which may allow cells to memorise these features for a certain time period after reoxygenation. Conclusions The FIH/ARD protein interaction has the potential to contribute to oxygen-range finding, can sensitise the response to changes in oxygen levels, and can provide a memory of the strength and the duration of a

  9. Prediction-error in the context of real social relationships modulates reward system activity

    Directory of Open Access Journals (Sweden)

    Joshua ePoore

    2012-08-01

    Full Text Available The human reward system is sensitive to both social (e.g., validation and non-social rewards (e.g., money and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward—social validation—and this activity’s relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants’ expectations for their romantic partners’ positive regard of them were confirmed (validated or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

  10. Dynamic Variables Fail to Predict Fluid Responsiveness in an Animal Model With Pericardial Effusion.

    Science.gov (United States)

    Broch, Ole; Renner, Jochen; Meybohm, Patrick; Albrecht, Martin; Höcker, Jan; Haneya, Assad; Steinfath, Markus; Bein, Berthold; Gruenewald, Matthias

    2016-10-01

    The reliability of dynamic and volumetric variables of fluid responsiveness in the presence of pericardial effusion is still elusive. The aim of the present study was to investigate their predictive power in a porcine model with hemodynamic relevant pericardial effusion. A single-center animal investigation. Twelve German domestic pigs. Pigs were studied before and during pericardial effusion. Instrumentation included a pulmonary artery catheter and a transpulmonary thermodilution catheter in the femoral artery. Hemodynamic variables like cardiac output (COPAC) and stroke volume (SVPAC) derived from pulmonary artery catheter, global end-diastolic volume (GEDV), stroke volume variation (SVV), and pulse-pressure variation (PPV) were obtained. At baseline, SVV, PPV, GEDV, COPAC, and SVPAC reliably predicted fluid responsiveness (area under the curve 0.81 [p = 0.02], 0.82 [p = 0.02], 0.74 [p = 0.07], 0.74 [p = 0.07], 0.82 [p = 0.02]). After establishment of pericardial effusion the predictive power of dynamic variables was impaired and only COPAC and SVPAC and GEDV allowed significant prediction of fluid responsiveness (area under the curve 0.77 [p = 0.04], 0.76 [p = 0.05], 0.83 [p = 0.01]) with clinically relevant changes in threshold values. In this porcine model, hemodynamic relevant pericardial effusion abolished the ability of dynamic variables to predict fluid responsiveness. COPAC, SVPAC, and GEDV enabled prediction, but their threshold values were significantly changed. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Prediction of residual metabolic activity after treatment in NSCLC patients

    International Nuclear Information System (INIS)

    Rios Velazquez, Emmanuel; Aerts, Hugo J.W.L.; Oberije, Cary; Ruysscher, Dirk De; Lambin, Philippe

    2010-01-01

    Purpose. Metabolic response assessment is often used as a surrogate of local failure and survival. Early identification of patients with residual metabolic activity is essential as this enables selection of patients who could potentially benefit from additional therapy. We report on the development of a pre-treatment prediction model for metabolic response using patient, tumor and treatment factors. Methods. One hundred and one patients with inoperable NSCLC (stage I-IV), treated with 3D conformal radical (chemo)-radiotherapy were retrospectively included in this study. All patients received a pre and post-radiotherapy fluorodeoxyglucose positron emission tomography-computed tomography FDG-PET-CT scan. The electronic medical record system and the medical patient charts were reviewed to obtain demographic, clinical, tumor and treatment data. Primary outcome measure was examined using a metabolic response assessment on a post-radiotherapy FDG-PET-CT scan. Radiotherapy was delivered in fractions of 1.8 Gy, twice a day, with a median prescribed dose of 60 Gy. Results. Overall survival was worse in patients with residual metabolic active areas compared with the patients with a complete metabolic response (p=0.0001). In univariate analysis, three variables were significantly associated with residual disease: larger primary gross tumor volume (GTVprimary, p=0.002), higher pre-treatment maximum standardized uptake value (SUV max , p=0.0005) in the primary tumor and shorter overall treatment time (OTT, p=0.046). A multivariate model including GTVprimary, SUV max , equivalent radiation dose at 2 Gy corrected for time (EQD2, T) and OTT yielded an area under the curve assessed by the leave-one-out cross validation of 0.71 (95% CI, 0.65-0.76). Conclusion. Our results confirmed the validity of metabolic response assessment as a surrogate of survival. We developed a multivariate model that is able to identify patients at risk of residual disease. These patients may benefit from

  12. Prediction of response to radiotherapy in the treatment of esophageal cancer using stem cell markers

    International Nuclear Information System (INIS)

    Smit, Justin K.; Faber, Hette; Niemantsverdriet, Maarten; Baanstra, Mirjam; Bussink, Johan; Hollema, Harry; Os, Ronald P. van; Plukker, John Th. M.; Coppes, Robert P.

    2013-01-01

    Background and purpose: In this study, we investigated whether cancer stem cell marker expressing cells can be identified that predict for the response of esophageal cancer (EC) to CRT. Materials and methods: EC cell-lines OE-33 and OE-21 were used to assess in vitro, stem cell activity, proliferative capacity and radiation response. Xenograft tumors were generated using NOD/SCID mice to assess in vivo proliferative capacity and tumor hypoxia. Archival and fresh EC biopsy tissue was used to confirm our in vitro and in vivo results. Results: We showed that the CD44+/CD24− subpopulation of EC cells exerts a higher proliferation rate and sphere forming potential and is more radioresistant in vitro, when compared to unselected or CD44+/CD24+ cells. Moreover, CD44+/CD24− cells formed xenograft tumors faster and were often located in hypoxic tumor areas. In a study of archival pre-neoadjuvant CRT biopsy material from EC adenocarcinoma patients (N = 27), this population could only be identified in 50% (9/18) of reduced-responders to neoadjuvant CRT, but never (0/9) in the complete responders (P = 0.009). Conclusion: These results warrant further investigation into the possible clinical benefit of CD44+/CD24− as a predictive marker in EC patients for the response to chemoradiation

  13. Autonomous Motivation Predicts 7-Day Physical Activity in Hong Kong Students.

    Science.gov (United States)

    Ha, Amy S; Ng, Johan Y Y

    2015-07-01

    Autonomous motivation predicts positive health behaviors such as physical activity. However, few studies have examined the relation between motivational regulations and objectively measured physical activity and sedentary behaviors. Thus, we investigated whether different motivational regulations (autonomous motivation, controlled motivation, and amotivation) predicted 7-day physical activity, sedentary behaviors, and health-related quality of life (HRQoL) of students. A total of 115 students (mean age = 11.6 years, 55.7% female) self-reported their motivational regulations and health-related quality of life. Physical activity and sedentary behaviors were measured using accelerometers for seven days. Using multilevel modeling, we found that autonomous motivation predicted higher levels of moderate-to-vigorous physical activity, less sedentary behaviors, and better HRQoL. Controlled motivation and amotivation each only negatively predicted one facet of HRQoL. Results suggested that autonomous motivation could be an important predictor of physical activity behaviors in Hong Kong students. Promotion of this form of motivational regulation may also increase HRQoL. © 2015 The International Association of Applied Psychology.

  14. Can quantitative contrast-enhanced ultrasonography predict cervical tumor response to neoadjuvant chemotherapy?

    Energy Technology Data Exchange (ETDEWEB)

    Peng, Chuan; Liu, Long-Zhong; Zheng, Wei [Department of Ultrasound, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060 (China); Xie, Yan-Jun [Department of Gynecology and Obstetrics, Zhongcun Town hospital, 140 Renmin Road, Zhongcun Town, Panyu District, Guangzhou, 511400 (China); Xiong, Yong-Hong; Li, An-Hua [Department of Ultrasound, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060 (China); Pei, Xiao-Qing, E-mail: peixq@sysucc.org.cn [Department of Ultrasound, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060 (China)

    2016-11-15

    Highlights: • We assessed the clinical value of quantitative CEUS for prediction of cervical tumor perfusion response to NACT. • IMAX, RT, and TTP changed significantly after one NACT cycle. • Pre-treatment IMAX positively correlated with the absolute and percentage changes in all cervical tumor IMAX after NACT. • Pre-treatment IMAX may be predictive of NACT perfusion response in cervical tumor. - Abstract: Objective: To evaluate the feasibility of quantitative contrast-enhanced ultrasonography (CEUS) for predicting and assessing cervical tumor response to neoadjuvant chemotherapy (NACT). Methods: Thirty-eight cases with stage IB2 or IIA cervical cancer were studied using CEUS before and after one cycle of NACT. The quantitative CEUS parameters maximum intensity (IMAX), rise time (RT), time to peak (TTP), and mean transit time (MTT) were compared between cervical tumors and myometrium (reference zone) using Sonoliver software. Absolute and relative changes in quantitative CEUS parameters were also compared among complete response, partial response, and non-responsive groups. Correlations between pre-treatment IMAX and changes in quantitative parameters were assessed after one cycle of NACT. Results: There were significant changes in cervical tumor IMAX (P < 0.001), RT (P < 0.05), and TTP (P < 0.05) after one cycle of NACT. According to the Response Evaluation Criteria In Solid Tumors guidelines, the enrollments were divided into complete response, partial response, stable disease and progressive disease groups. There were no significant differences in quantitative CEUS parameters among complete response, partial response, and non-responsive groups (P > 0.05). In the stable disease group (n = 17), cervical tumor IMAX, RT, and TTP decreased significantly after NACT (P < 0.001). The absolute and percentage changes in IMAX were positively correlated with pre-treatment IMAX in all 38 patients (r = 0.576, P < 0.001 and r = 0.429, P < 0.001). Conclusion

  15. Use of Germline Polymorphisms in Predicting Concurrent Chemoradiotherapy Response in Esophageal Cancer

    International Nuclear Information System (INIS)

    Chen, Pei-Chun; Chen, Yen-Ching; Lai, Liang-Chuan; Tsai, Mong-Hsun; Chen, Shin-Kuang; Yang, Pei-Wen; Lee, Yung-Chie; Hsiao, Chuhsing K.; Lee, Jang-Ming; Chuang, Eric Y.

    2012-01-01

    Purpose: To identify germline polymorphisms to predict concurrent chemoradiation therapy (CCRT) response in esophageal cancer patients. Materials and Methods: A total of 139 esophageal cancer patients treated with CCRT (cisplatin-based chemotherapy combined with 40 Gy of irradiation) and subsequent esophagectomy were recruited at the National Taiwan University Hospital between 1997 and 2008. After excluding confounding factors (i.e., females and patients aged ≥70 years), 116 patients were enrolled to identify single nucleotide polymorphisms (SNPs) associated with specific CCRT responses. Genotyping arrays and mass spectrometry were used sequentially to determine germline polymorphisms from blood samples. These polymorphisms remain stable throughout disease progression, unlike somatic mutations from tumor tissues. Two-stage design and additive genetic models were adopted in this study. Results: From the 26 SNPs identified in the first stage, 2 SNPs were found to be significantly associated with CCRT response in the second stage. Single nucleotide polymorphism rs16863886, located between SGPP2 and FARSB on chromosome 2q36.1, was significantly associated with a 3.93-fold increase in pathologic complete response to CCRT (95% confidence interval 1.62–10.30) under additive models. Single nucleotide polymorphism rs4954256, located in ZRANB3 on chromosome 2q21.3, was associated with a 3.93-fold increase in pathologic complete response to CCRT (95% confidence interval 1.57–10.87). The predictive accuracy for CCRT response was 71.59% with these two SNPs combined. Conclusions: This is the first study to identify germline polymorphisms with a high accuracy for predicting CCRT response in the treatment of esophageal cancer.

  16. A Framework for Prediction of Response to HCV Therapy Using Different Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Enas M. F. El Houby

    2014-01-01

    Full Text Available Hepatitis C which is a widely spread disease all over the world is a fatal liver disease caused by Hepatitis C Virus (HCV. The only approved therapy is interferon plus ribavirin. The number of responders to this treatment is low, while its cost is high and side effects are undesirable. Treatment response prediction will help in reducing the patients who suffer from the side effects and high costs without achieving recovery. The aim of this research is to develop a framework which can select the best model to predict HCV patients’ response to the treatment of HCV from clinical information. The framework contains three phases which are preprocessing phase to prepare the data for applying Data Mining (DM techniques, DM phase to apply different DM techniques, and evaluation phase to evaluate and compare the performance of the built models and select the best model as the recommended one. Different DM techniques had been applied which are associative classification, artificial neural network, and decision tree to evaluate the framework. The experimental results showed the effectiveness of the framework in selecting the best model which is the model built by associative classification using histology activity index, fibrosis stage, and alanine amino transferase.

  17. The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks.

    Science.gov (United States)

    Witt, Clara J; Richards, Allen L; Masuoka, Penny M; Foley, Desmond H; Buczak, Anna L; Musila, Lillian A; Richardson, Jason H; Colacicco-Mayhugh, Michelle G; Rueda, Leopoldo M; Klein, Terry A; Anyamba, Assaf; Small, Jennifer; Pavlin, Julie A; Fukuda, Mark M; Gaydos, Joel; Russell, Kevin L; Wilkerson, Richard C; Gibbons, Robert V; Jarman, Richard G; Myint, Khin S; Pendergast, Brian; Lewis, Sheri; Pinzon, Jorge E; Collins, Kathrine; Smith, Matthew; Pak, Edwin; Tucker, Compton; Linthicum, Kenneth; Myers, Todd; Mansour, Moustafa; Earhart, Ken; Kim, Heung Chul; Jiang, Ju; Schnabel, Dave; Clark, Jeffrey W; Sang, Rosemary C; Kioko, Elizabeth; Abuom, David C; Grieco, John P; Richards, Erin E; Tobias, Steven; Kasper, Matthew R; Montgomery, Joel M; Florin, Dave; Chretien, Jean-Paul; Philip, Trudy L

    2011-03-04

    The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program's ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia.

  18. The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks

    Science.gov (United States)

    2011-01-01

    The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program’s ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia. PMID:21388561

  19. Blunted hypothalamo-pituitary adrenal axis response to predator odor predicts high stress reactivity.

    Science.gov (United States)

    Whitaker, Annie M; Gilpin, Nicholas W

    2015-08-01

    Individuals with trauma- and stress-related disorders exhibit increases in avoidance of trauma-related stimuli, heightened anxiety and altered neuroendocrine stress responses. Our laboratory uses a rodent model of stress that mimics the avoidance symptom cluster associated with stress-related disorders. Animals are classified as 'Avoiders' or 'Non-Avoiders' post-stress based on avoidance of predator-odor paired context. Utilizing this model, we are able to examine subpopulation differences in stress reactivity. Here, we used this predator odor model of stress to examine differences in anxiety-like behavior and hypothalamo-pituitary adrenal (HPA) axis function in animals that avoid a predator-paired context relative to those that do not. Rats were exposed to predator odor stress paired with a context and tested for avoidance (24h and 11days), anxiety-like behavior (48h and 5days) and HPA activation following stress. Control animals were exposed to room air. Predator odor stress produced avoidance in approximately 65% of the animals at 24h that persisted 11days post-stress. Both Avoiders and Non-Avoiders exhibited a heightened anxiety-like behavior at 48h and 5days post-stress when compared to unstressed Controls. Non-Avoiders exhibited significant increases in circulating adrenocorticotropin hormone (ACTH) and corticosterone (CORT) concentrations immediately following predator odor stress compared to Controls and this response was significantly attenuated in Avoiders. There was an inverse correlation between circulating ACTH/CORT concentrations and avoidance, indicating that lower levels of ACTH/CORT predicted higher levels of avoidance. These results suggest that stress effects on HPA stress axis activation predict long-term avoidance of stress-paired stimuli, and build on previous data showing the utility of this model for exploring the neurobiological mechanisms of trauma- and stress-related disorders. Copyright © 2015. Published by Elsevier Inc.

  20. Application of Avco data analysis and prediction techniques (ADAPT) to prediction of sunspot activity

    Science.gov (United States)

    Hunter, H. E.; Amato, R. A.

    1972-01-01

    The results are presented of the application of Avco Data Analysis and Prediction Techniques (ADAPT) to derivation of new algorithms for the prediction of future sunspot activity. The ADAPT derived algorithms show a factor of 2 to 3 reduction in the expected 2-sigma errors in the estimates of the 81-day running average of the Zurich sunspot numbers. The report presents: (1) the best estimates for sunspot cycles 20 and 21, (2) a comparison of the ADAPT performance with conventional techniques, and (3) specific approaches to further reduction in the errors of estimated sunspot activity and to recovery of earlier sunspot historical data. The ADAPT programs are used both to derive regression algorithm for prediction of the entire 11-year sunspot cycle from the preceding two cycles and to derive extrapolation algorithms for extrapolating a given sunspot cycle based on any available portion of the cycle.

  1. Integrating circadian activity and gene expression profiles to predict chronotoxicity of Drosophila suzukii response to insecticides.

    Science.gov (United States)

    Hamby, Kelly A; Kwok, Rosanna S; Zalom, Frank G; Chiu, Joanna C

    2013-01-01

    Native to Southeast Asia, Drosophila suzukii (Matsumura) is a recent invader that infests intact ripe and ripening fruit, leading to significant crop losses in the U.S., Canada, and Europe. Since current D. suzukii management strategies rely heavily on insecticide usage and insecticide detoxification gene expression is under circadian regulation in the closely related Drosophila melanogaster, we set out to determine if integrative analysis of daily activity patterns and detoxification gene expression can predict chronotoxicity of D. suzukii to insecticides. Locomotor assays were performed under conditions that approximate a typical summer or winter day in Watsonville, California, where D. suzukii was first detected in North America. As expected, daily activity patterns of D. suzukii appeared quite different between 'summer' and 'winter' conditions due to differences in photoperiod and temperature. In the 'summer', D. suzukii assumed a more bimodal activity pattern, with maximum activity occurring at dawn and dusk. In the 'winter', activity was unimodal and restricted to the warmest part of the circadian cycle. Expression analysis of six detoxification genes and acute contact bioassays were performed at multiple circadian times, but only in conditions approximating Watsonville summer, the cropping season, when most insecticide applications occur. Five of the genes tested exhibited rhythmic expression, with the majority showing peak expression at dawn (ZT0, 6am). We observed significant differences in the chronotoxicity of D. suzukii towards malathion, with highest susceptibility at ZT0 (6am), corresponding to peak expression of cytochrome P450s that may be involved in bioactivation of malathion. High activity levels were not found to correlate with high insecticide susceptibility as initially hypothesized. Chronobiology and chronotoxicity of D. suzukii provide valuable insights for monitoring and control efforts, because insect activity as well as insecticide timing

  2. Integrating environmental and genetic effects to predict responses of tree populations to climate.

    Science.gov (United States)

    Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

    2010-01-01

    Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

  3. Prediction of treatment response and metastatic disease in soft tissue sarcoma

    Science.gov (United States)

    Farhidzadeh, Hamidreza; Zhou, Mu; Goldgof, Dmitry B.; Hall, Lawrence O.; Raghavan, Meera.; Gatenby, Robert A.

    2014-03-01

    Soft tissue sarcomas (STS) are a heterogenous group of malignant tumors comprised of more than 50 histologic subtypes. Based on spatial variations of the tumor, predictions of the development of necrosis in response to therapy as well as eventual progression to metastatic disease are made. Optimization of treatment, as well as management of therapy-related side effects, may be improved using progression information earlier in the course of therapy. Multimodality pre- and post-gadolinium enhanced magnetic resonance images (MRI) were taken before and after treatment for 30 patients. Regional variations in the tumor bed were measured quantitatively. The voxel values from the tumor region were used as features and a fuzzy clustering algorithm was used to segment the tumor into three spatial regions. The regions were given labels of high, intermediate and low based on the average signal intensity of pixels from the post-contrast T1 modality. These spatially distinct regions were viewed as essential meta-features to predict the response of the tumor to therapy based on necrosis (dead tissue in tumor bed) and metastatic disease (spread of tumor to sites other than primary). The best feature was the difference in the number of pixels in the highest intensity regions of tumors before and after treatment. This enabled prediction of patients with metastatic disease and lack of positive treatment response (i.e. less necrosis). The best accuracy, 73.33%, was achieved by a Support Vector Machine in a leave-one-out cross validation on 30 cases predicting necrosis treatment and metastasis.

  4. Multivariate prediction of spontaneous repetitive responses in ventricular myocardium exposed in vitro to simulated ischemic conditions.

    Science.gov (United States)

    Schiariti, M; Puddu, P E; Rouet, R

    1994-06-01

    Guinea-pig ventricular myocardium was partly exposed to normal Tyrode's superfusion and partly to altered conditions (using modified Tyrode's solution) set to simulate acute myocardial ischemia (PO2 80 +/- 10 mmHg; no glucose; pH 7.00 +/- 0.05; K+ 12 mM). Using a double-chamber tissue bath and standard microelectrode technique, the occurrence of spontaneous repetitive responses was investigated during simulated ischemia (occlusion) and after reperfusing the previously ischemic superfused tissue with normal Tyrode's solution (reperfusion). In 62 experiments (42 animals) the effects of: (1) duration of simulated ischemia (1321 +/- 435 s), (2) stimulation rate (1002 +/- 549 ms) and (3) number of successive simulated ischemic periods (occlusions) (1.58 +/- 0.92) on: (1) resting membrane potential, (2) action potential amplitude, (3) duration of 50 and 90% action potentials and (4) maximal upstroke velocity of action potential were studied. All variables were considered as gradients (delta) between normal and ischemic tissue. Both during occlusion and upon reperfusion, spontaneous repetitive responses were coded as single, couplets, salvos (three to nine and > 10) or total spontaneous repetitive responses (coded present when at least one of the above-mentioned types was seen). The incidence of total spontaneous repetitive responses was 31% (19/62) on occlusion and 85% (53/62) upon reperfusion. Cox's models (forced and stepwise) were used to predict multivariately the occurrence of arrhythmic events considered as both total spontaneous repetitive responses and as separate entities. These models were applicable since continuous monitoring of the experiments enabled exact timing of spontaneous repetitive response onset during both occlusion and reperfusion. In predicting reperfusion spontaneous repetitive responses, total spontaneous repetitive responses and blocks observed during the occlusion period were also considered. Total occlusion spontaneous repetitive responses

  5. Stress responsiveness predicts individual variation in mate selectivity.

    Science.gov (United States)

    Vitousek, Maren N; Romero, L Michael

    2013-06-15

    Steroid hormones, including glucocorticoids, mediate a variety of behavioral and physiological processes. Circulating hormone concentrations vary substantially within populations, and although hormone titers predict reproductive success in several species, little is known about how individual variation in circulating hormone concentrations is linked with most reproductive behaviors in free-living organisms. Mate choice is an important and often costly component of reproduction that also varies substantially within populations. We examined whether energetically costly mate selection behavior in female Galápagos marine iguanas (Amblyrhynchus cristatus) was associated with individual variation in the concentrations of hormones previously shown to differ between reproductive and non-reproductive females during the breeding season (corticosterone and testosterone). Stress-induced corticosterone levels - which are suppressed in female marine iguanas during reproduction - were individually repeatable throughout the seven-week breeding period. Mate selectivity was strongly predicted by individual variation in stress-induced corticosterone: reproductive females that secreted less corticosterone in response to a standardized stressor assessed more displaying males. Neither baseline corticosterone nor testosterone predicted variation in mate selectivity. Scaled body mass was not significantly associated with mate selectivity, but females that began the breeding period in lower body condition showed a trend towards being less selective about potential mates. These results provide the first evidence that individual variation in the corticosterone stress response is associated with how selective females are in their choice of a mate, an important contributor to fitness in many species. Future research is needed to determine the functional basis of this association, and whether transient acute increases in circulating corticosterone directly mediate mate choice behaviors

  6. O6-Methylguanine DNA Methyltransferase Status Does Not Predict Response or Resistance to Alkylating Agents in Well-Differentiated Pancreatic Neuroendocrine Tumors.

    Science.gov (United States)

    Raj, Nitya; Klimstra, David S; Horvat, Natally; Zhang, Liying; Chou, Joanne F; Capanu, Marinela; Basturk, Olca; Do, Richard Kinh Gian; Allen, Peter J; Reidy-Lagunes, Diane

    2017-07-01

    Alkylating agents have activity in well-differentiated pancreatic neuroendocrine tumors (WD panNETs). In glioblastoma multiforme, decreased activity of O-methylguanine DNA methyltransferase (MGMT) predicts response; in panNETs, MGMT relevance is unknown. We identified patients with WD panNETs treated with alkylating agents, determined best overall response by Response Evaluation Criteria In Solid Tumors (RECIST) 1.1, and performed MGMT activity testing. Fifty-six patients were identified; 26 (46%) of the 56 patients experienced partial response, 24 (43%) of 56 experienced stable disease, and 6 (11%) of 56 experienced progression of disease. O-methylguanine DNA methyltransferase status was available for 36 tumors. For tumors with partial response, 10 (67%) of 15 were MGMT deficient, and 5 (33%) of 15 were MGMT intact. For tumors with stable disease, 7 (47%) of 15 were MGMT deficient, and 8 (53%) of 15 were MGMT intact. For tumors with progression of disease, 3 (50%) of 6 were MGMT deficient, and 3 (50%) of 6 were MGMT intact. We observed response and resistance to alkylating agents in MGMT-deficient and MGMT-intact tumors. O-methylguanine DNA methyltransferase status should not guide alkylating agent therapy in WD panNETs.

  7. Familial social support predicts a reduced cortisol response to stress in sexual minority young adults.

    Science.gov (United States)

    Burton, C L; Bonanno, G A; Hatzenbuehler, M L

    2014-09-01

    Social support has been repeatedly associated with mental and physical health outcomes, with hypothalamic-pituitary-adrenocortical (HPA) axis activity posited as a potential mechanism. The influence of social bonds appears particularly important in the face of stigma-related stress; however, there is a dearth of research examining social support and HPA axis response among members of a stigmatized group. To address this gap in the literature, we tested in a sample of 70 lesbian, gay, and bisexual (LGB) young adults whether family support or peer support differentially predict cortisol reactivity in response to a laboratory stressor, the Trier Social Stress Test. While greater levels of family support were associated with reduced cortisol reactivity, neither peer support nor overall support satisfaction was associated with cortisol response. These findings suggest that the association between social support and neuroendocrine functioning differs according to the source of support among members of one stigmatized group. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Bronchodilator Response in Patients with Persistent Allergic Asthma Could Not Predict Airway Hyperresponsiveness

    Directory of Open Access Journals (Sweden)

    Petanjek Bojana B

    2007-12-01

    Full Text Available Anticholinergics, or specific antimuscarinic agents, by inhibition of muscarinic receptors cause bronchodilatation, which might correlate with activation of these receptors by the muscarinic agonist methacholine. The aim of this study was to determine whether a positive bronchodilator response to the anticholinergic ipratropium bromide could predict airway hyperresponsiveness in patients with persistent allergic asthma. The study comprised 40 patients with mild and moderate persistent allergic asthma. Diagnosis was established by clinical and functional follow-up (skin-prick test, spirometry, bronchodilator tests with salbutamol and ipratropium bromide, and methacholine challenge testing. The bronchodilator response was positive to both bronchodilator drugs in all patients. After salbutamol inhalation, forced expiratory volume in 1 second (FEV1 increased by 18.39 ± 6.18%, p 1 increased by 19.14 ± 6.74%, p 1 decreased by 25.75 ± 5.16%, p 20 FEV1 [provocative concentration of methacholine that results in a 20% fall in FEV1] from 0.026 to 1.914 mg/mL. Using linear regression, between methacholine challenge testing and bronchodilator response to salbutamol, a positive, weak, and stastistically significant correlation for FEV1 was found (p

  9. Applications of NASA and NOAA Satellite Observations by NASA's Short-term Prediction Research and Transition (SPoRT) Center in Response to Natural Disasters

    Science.gov (United States)

    Molthan, Andrew L.; Burks, Jason E.; McGrath, Kevin M.; Jedlovec, Gary J.

    2012-01-01

    NASA s Short-term Prediction Research and Transition (SPoRT) Center supports the transition of unique NASA and NOAA research activities to the operational weather forecasting community. SPoRT emphasizes real-time analysis and prediction out to 48 hours. SPoRT partners with NOAA s National Weather Service (NWS) Weather Forecast Offices (WFOs) and National Centers to improve current products, demonstrate future satellite capabilities and explore new data assimilation techniques. Recently, the SPoRT Center has been involved in several activities related to disaster response, in collaboration with NOAA s National Weather Service, NASA s Applied Sciences Disasters Program, and other partners.

  10. Predictive coding of music--brain responses to rhythmic incongruity.

    Science.gov (United States)

    Vuust, Peter; Ostergaard, Leif; Pallesen, Karen Johanne; Bailey, Christopher; Roepstorff, Andreas

    2009-01-01

    During the last decades, models of music processing in the brain have mainly discussed the specificity of brain modules involved in processing different musical components. We argue that predictive coding offers an explanatory framework for functional integration in musical processing. Further, we provide empirical evidence for such a network in the analysis of event-related MEG-components to rhythmic incongruence in the context of strong metric anticipation. This is seen in a mismatch negativity (MMNm) and a subsequent P3am component, which have the properties of an error term and a subsequent evaluation in a predictive coding framework. There were both quantitative and qualitative differences in the evoked responses in expert jazz musicians compared with rhythmically unskilled non-musicians. We propose that these differences trace a functional adaptation and/or a genetic pre-disposition in experts which allows for a more precise rhythmic prediction.

  11. Incremental-hinge piping analysis methods for inelastic seismic response prediction

    International Nuclear Information System (INIS)

    Jaquay, K.R.; Castle, W.R.; Larson, J.E.

    1989-01-01

    This paper proposes nonlinear seismic response prediction methods for nuclear piping systems based on simplified plastic hinge analyses. The simplified plastic hinge analyses utilize an incremental series of flat response spectrum loadings and replace yielded components with hinge elements when a predefined hinge moment is reached. These hinge moment values, developed by Rodabaugh, result in inelastic energy dissipation of the same magnitude as observed in seismic tests of piping components. Two definitions of design level equivalent loads are employed: one conservatively based on the peaks of the design acceleration response spectra, the other based on inelastic frequencies determined by the method of Krylov and Bogolyuboff recently extended by Lazzeri to piping. Both definitions account for piping system inelastic energy dissipation using Newmark-Hall inelastic response spectrum reduction factors and the displacement ductility results of the incremental-hinge analysis. Two ratchet-fatigue damage models are used: one developed by Rodabaugh that conservatively correlates Markl static fatigue expressions to seismic tests to failure of piping components; the other developed by Severud that uses the ratchet expression of Bree for elbows and Edmunds and Beer for straights, and defines ratchet-fatigue interaction using Coffin's ductility based fatigue equation. Comparisons of predicted behavior versus experimental results are provided for a high-level seismic test of a segment of a representative nuclear plant piping system. (orig.)

  12. Distributed BOLD-response in association cortex vector state space predicts reaction time during selective attention.

    Science.gov (United States)

    Musso, Francesco; Konrad, Andreas; Vucurevic, Goran; Schäffner, Cornelius; Friedrich, Britta; Frech, Peter; Stoeter, Peter; Winterer, Georg

    2006-02-15

    Human cortical information processing is thought to be dominated by distributed activity in vector state space (Churchland, P.S., Sejnowski, T.J., 1992. The Computational Brain. MIT Press, Cambridge.). In principle, it should be possible to quantify distributed brain activation with independent component analysis (ICA) through vector-based decomposition, i.e., through a separation of a mixture of sources. Using event-related functional magnetic resonance imaging (fMRI) during a selective attention-requiring task (visual oddball), we explored how the number of independent components within activated cortical areas is related to reaction time. Prior to ICA, the activated cortical areas were determined on the basis of a General linear model (GLM) voxel-by-voxel analysis of the target stimuli (checkerboard reversal). Two activated cortical areas (temporoparietal cortex, medial prefrontal cortex) were further investigated as these cortical regions are known to be the sites of simultaneously active electromagnetic generators which give rise to the compound event-related potential P300 during oddball task conditions. We found that the number of independent components more strongly predicted reaction time than the overall level of "activation" (GLM BOLD-response) in the left temporoparietal area whereas in the medial prefrontal cortex both ICA and GLM predicted reaction time equally well. Comparable correlations were not seen when principle components were used instead of independent components. These results indicate that the number of independently activated components, i.e., a high level of cortical activation complexity in cortical vector state space, may index particularly efficient information processing during selective attention-requiring tasks. To our best knowledge, this is the first report describing a potential relationship between neuronal generators of cognitive processes, the associated electrophysiological evidence for the existence of distributed networks

  13. Neuroscience of inhibition for addiction medicine: from prediction of initiation to prediction of relapse.

    Science.gov (United States)

    Moeller, Scott J; Bederson, Lucia; Alia-Klein, Nelly; Goldstein, Rita Z

    2016-01-01

    A core deficit in drug addiction is the inability to inhibit maladaptive drug-seeking behavior. Consistent with this deficit, drug-addicted individuals show reliable cross-sectional differences from healthy nonaddicted controls during tasks of response inhibition accompanied by brain activation abnormalities as revealed by functional neuroimaging. However, it is less clear whether inhibition-related deficits predate the transition to problematic use, and, in turn, whether these deficits predict the transition out of problematic substance use. Here, we review longitudinal studies of response inhibition in children/adolescents with little substance experience and longitudinal studies of already addicted individuals attempting to sustain abstinence. Results show that response inhibition and its underlying neural correlates predict both substance use outcomes (onset and abstinence). Neurally, key roles were observed for multiple regions of the frontal cortex (e.g., inferior frontal gyrus, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex). In general, less activation of these regions during response inhibition predicted not only the onset of substance use, but interestingly also better abstinence-related outcomes among individuals already addicted. The role of subcortical areas, although potentially important, is less clear because of inconsistent results and because these regions are less classically reported in studies of healthy response inhibition. Overall, this review indicates that response inhibition is not simply a manifestation of current drug addiction, but rather a core neurocognitive dimension that predicts key substance use outcomes. Early intervention in inhibitory deficits could have high clinical and public health relevance. © 2016 Elsevier B.V. All rights reserved.

  14. Nonlinear Predictive Sliding Mode Control for Active Suspension System

    Directory of Open Access Journals (Sweden)

    Dazhuang Wang

    2018-01-01

    Full Text Available An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

  15. Authoritarian parenting predicts reduced electrocortical response to observed adolescent offspring rewards.

    Science.gov (United States)

    Levinson, Amanda R; Speed, Brittany C; Nelson, Brady; Bress, Jennifer N; Hajcak, Greg

    2017-03-01

    Parenting styles are robust predictors of offspring outcomes, yet little is known about their neural underpinnings. In this study, 44 parent-adolescent dyads (Mage of adolescent = 12.9) completed a laboratory guessing task while EEG was continuously recorded. In the task, each pair member received feedback about their own monetary wins and losses and also observed the monetary wins and losses of the other member of the pair. We examined the association between self-reported parenting style and parents' electrophysiological responses to watching their adolescent winning and losing money, dubbed the observational Reward Positivity (RewP) and observational feedback negativity (FN), respectively. Self-reported authoritarian parenting predicted reductions in parents' observational RewP but not FN. This predictive relationship remained after adjusting for sex of both participants, parents' responsiveness to their own wins, and parental psychopathology. 'Exploratory analyses found that permissive parenting was associated with a blunting of the adolescents' response to their parents' losses'. These findings suggest that parents' rapid neural responses to their child's successes may relate to the harsh parenting behaviors associated with authoritarian parenting. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  16. Predicting post-traumatic stress disorder treatment response in refugees: Multilevel analysis.

    Science.gov (United States)

    Haagen, Joris F G; Ter Heide, F Jackie June; Mooren, Trudy M; Knipscheer, Jeroen W; Kleber, Rolf J

    2017-03-01

    Given the recent peak in refugee numbers and refugees' high odds of developing post-traumatic stress disorder (PTSD), finding ways to alleviate PTSD in refugees is of vital importance. However, there are major differences in PTSD treatment response between refugees, the determinants of which are largely unknown. This study aimed at improving PTSD treatment for adult refugees by identifying PTSD treatment response predictors. A prospective longitudinal multilevel modelling design was used to predict PTSD severity scores over time. We analysed data from a randomized controlled trial with pre-, post-, and follow-up measurements of the safety and efficacy of eye movement desensitization and reprocessing and stabilization in asylum seekers and refugees suffering from PTSD. Lack of refugee status, comorbid depression, demographic, trauma-related and treatment-related variables were analysed as potential predictors of PTSD treatment outcome. Treatment outcome data from 72 participants were used. The presence (B = 6.5, p = .03) and severity (B = 6.3, p disorder predicted poor treatment response and explained 39% of the variance between individuals. Refugee patients who suffer from PTSD and severe comorbid depression benefit less from treatment aimed at alleviating PTSD. Results highlight the need for treatment adaptations for PTSD and comorbid severe depression in traumatized refugees, including testing whether initial targeting of severe depressive symptoms increases PTSD treatment effectiveness. There are differences in post-traumatic stress disorder (PTSD) treatment response between traumatized refugees. Comorbid depressive disorder and depression severity predict poor PTSD response. Refugees with PTSD and severe depression may not benefit from PTSD treatment. Targeting comorbid severe depression before PTSD treatment is warranted. This study did not correct for multiple hypothesis testing. Comorbid depression may differentially impact alternative PTSD treatments

  17. Predictive value of early viriological response for sustained viriological response in chronic hepatitis c with conventional interferon therapy

    International Nuclear Information System (INIS)

    Awan, A.; Umar, M.; Khaar, H.T.B.; Kulsoom, A.; Minhas, Z.; Ambreen, S.; Habib, N.; Mumtaz, W.; Habib, F.

    2016-01-01

    Background: Hepatitis is a major public health problem in Pakistan due to its strong association with liver failure and hepatocellular carcinoma. In Pakistan, conventional interferon therapy along with Ribavirin is favoured especially in Government funded programs for treatment of Hepatitis C, over the more expensive Pegylated Interferon and Ribavirin combination therapy as recommended by Pakistan society of Gastroenterology and GI endoscopy due to its favourable results observed in genotype 3 which is the dominant genotype of this region. Objective of our study was to assess the viriological responses with standard interferon therapy and to determine the predictive values of early viriological response (EVR) for Sustained Viriological Response (SVR) in chronic hepatitis C patients treated with standard interferon therapy. Methods: A cross sectional study was conducted on patients with chronic hepatitis C having received standard interferon and ribavirin therapy for six months. EVR and SVR were noted for analysis. Positive and negative predictive values of EVR on SVR were calculated. Results: Out of the total sample (N=3075), 1946 (63.3 percentage) patients were tested for EVR. 1386 (71.2 percentage) were positive while 560 (28.8 percentage) were negative while 516 (16.8 percentage) were tested for SVR. Two hundred and eighty-five (55.2 percentage) were positive while 231 (44.8 percentage) were negative. EVR and SVR tested were N=117. Positive predictive value of EVR on SVR was 67.1 percentage and negative predictive value was 65.8 percentage. Statistically significant association between EVR and SVR was determined with Chi square statistic of 11.8 (p-value <0.0001). Conclusion: EVR is a good predictor of response of patients to standard interferon and ribavirin therapy. In the absence of an EVR, it seems imperative to stop further treatment. Virilogical responses with conventional interferon therapy are comparable to those of pegylated interferon therapy so

  18. Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.

    Directory of Open Access Journals (Sweden)

    Kyriaki Sidiropoulou

    Full Text Available Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC, which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS and an intrinsic bursting (IB model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given

  19. Emotional Responses to Suicidal Patients: Factor Structure, Construct, and Predictive Validity of the Therapist Response Questionnaire-Suicide Form

    OpenAIRE

    Shira Barzilay; Zimri S. Yaseen; Zimri S. Yaseen; Mariah Hawes; Bernard Gorman; Rachel Altman; Adriana Foster; Alan Apter; Paul Rosenfield; Igor Galynker; Igor Galynker

    2018-01-01

    BackgroundMental health professionals have a pivotal role in suicide prevention. However, they also often have intense emotional responses, or countertransference, during encounters with suicidal patients. Previous studies of the Therapist Response Questionnaire-Suicide Form (TRQ-SF), a brief novel measure aimed at probing a distinct set of suicide-related emotional responses to patients found it to be predictive of near-term suicidal behavior among high suicide-risk inpatients. The purpose o...

  20. Predicting methylphenidate response in attention deficit hyperactivity disorder: a preliminary study.

    Science.gov (United States)

    Johnston, Blair A; Coghill, David; Matthews, Keith; Steele, J Douglas

    2015-01-01

    Methylphenidate (MPH) is established as the main pharmacological treatment for patients with attention deficit hyperactivity disorder (ADHD). Whilst MPH is generally a highly effective treatment, not all patients respond, and some experience adverse reactions. Currently, there is no reliable method to predict how patients will respond, other than by exposure to a trial of medication. In this preliminary study, we sought to investigate whether an accurate predictor of clinical response to methylphenidate could be developed for individual patients, using sociodemographic, clinical and neuropsychological measures. Of the 43 boys with ADHD included in this proof-of-concept study, 30 were classed as responders and 13 as non-responders to MPH, with no significant differences in age nor verbal intelligence quotient (IQ) between the groups. Here we report the application of a multivariate analysis approach to the prediction of clinical response to MPH, which achieved an accuracy of 77% (p = 0.005). The most important variables to the classifier were performance on a 'go/no go' task and comorbid conduct disorder. This preliminary study suggested that further investigation is merited. Achieving a highly significant accuracy of 77% for the prediction of MPH response is an encouraging step towards finding a reliable and clinically useful method that could minimise the number of children needlessly being exposed to MPH. © The Author(s) 2014.

  1. Prediction of postoperative pain by preoperative pain response to heat stimulation in total knee arthroplasty

    DEFF Research Database (Denmark)

    Lunn, Troels H; Gaarn-Larsen, Lissi; Kehlet, Henrik

    2013-01-01

    It has been estimated that up to 54% of the variance in postoperative pain experience may be predicted with preoperative pain responses to experimental stimuli, with suprathreshold heat pain as the most consistent test modality. We aimed to explore if 2 heat test paradigms could predict postopera......It has been estimated that up to 54% of the variance in postoperative pain experience may be predicted with preoperative pain responses to experimental stimuli, with suprathreshold heat pain as the most consistent test modality. We aimed to explore if 2 heat test paradigms could predict...... and logistic regressions analyses were carried out including 8 potential preoperative explanatory variables (among these anxiety, depression, preoperative pain and pain catastrophizing) to assess pain response to preoperative heat pain stimulation as independent predictor for postoperative pain. 100 patients...... by the linear and logistic regression analyses, where only anxiety, preoperative pain and pain catastrophizing were significant explanatory variables (but with low R-Squares;0.05-0.08). Pain responses to 2 types of preoperative heat stimuli were not independent clinical relevant predictors for postoperative...

  2. Spatial fidelity of workers predicts collective response to disturbance in a social insect.

    Science.gov (United States)

    Crall, James D; Gravish, Nick; Mountcastle, Andrew M; Kocher, Sarah D; Oppenheimer, Robert L; Pierce, Naomi E; Combes, Stacey A

    2018-04-03

    Individuals in social insect colonies cooperate to perform collective work. While colonies often respond to changing environmental conditions by flexibly reallocating workers to different tasks, the factors determining which workers switch and why are not well understood. Here, we use an automated tracking system to continuously monitor nest behavior and foraging activity of uniquely identified workers from entire bumble bee (Bombus impatiens) colonies foraging in a natural outdoor environment. We show that most foraging is performed by a small number of workers and that the intensity and distribution of foraging is actively regulated at the colony level in response to forager removal. By analyzing worker nest behavior before and after forager removal, we show that spatial fidelity of workers within the nest generates uneven interaction with relevant localized information sources, and predicts which workers initiate foraging after disturbance. Our results highlight the importance of spatial fidelity for structuring information flow and regulating collective behavior in social insect colonies.

  3. Seismic response prediction for cabinets of nuclear power plants by using impact hammer test

    Energy Technology Data Exchange (ETDEWEB)

    Koo, Ki Young [Department of Civil and Structural Engineering, University of Sheffield, Sheffield (United Kingdom); Gook Cho, Sung [JACE KOREA, Gyeonggi-do (Korea, Republic of); Cui, Jintao [Department of Civil Engineering, Kunsan National University, Jeonbuk (Korea, Republic of); Kim, Dookie, E-mail: kim2kie@kunsan.ac.k [Department of Civil Engineering, Kunsan National University, Jeonbuk (Korea, Republic of)

    2010-10-15

    An effective method to predict the seismic response of electrical cabinets of nuclear power plants is developed. This method consists of three steps: (1) identification of the earthquake-equivalent force based on the idealized lumped-mass system of the cabinet, (2) identification of the state-space equation (SSE) model of the system using input-output measurements from impact hammer tests, and (3) seismic response prediction by calculating the output of the identified SSE model under the identified earthquake-equivalent force. A three-dimensional plate model of cabinet structures is presented for the numerical verification of the proposed method. Experimental validation of the proposed method is carried out on a three-story frame which represents the structure of a cabinet. The SSE model of the frame is accurately identified by impact hammer tests with high fitness values over 85% of the actual frame characteristics. Shaking table tests are performed using El Centro, Kobe, and Northridge earthquakes as input motions and the acceleration responses are measured. The responses of the model under the three earthquakes are predicted and then compared with the measured responses. The predicted and measured responses agree well with each other with fitness values of 65-75%. The proposed method is more advantageous over other methods that are based on finite element (FE) model updating since it is free from FE modeling errors. It will be especially effective for cabinet structures in nuclear power plants where conducting shaking table tests may not be feasible. Limitations of the proposed method are also discussed.

  4. Online communication predicts Belgian adolescents' initiation of romantic and sexual activity.

    Science.gov (United States)

    Vandenbosch, Laura; Beyens, Ine; Vangeel, Laurens; Eggermont, Steven

    2016-04-01

    Online communication is associated with offline romantic and sexual activity among college students. Yet, it is unknown whether online communication is associated with the initiation of romantic and sexual activity among adolescents. This two-wave panel study investigated whether chatting, visiting dating websites, and visiting erotic contact websites predicted adolescents' initiation of romantic and sexual activity. We analyzed two-wave panel data from 1163 Belgian adolescents who participated in the MORES Study. We investigated the longitudinal impact of online communication on the initiation of romantic relationships and sexual intercourse using logistic regression analyses. The odds ratios of initiating a romantic relationship among romantically inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites were two to three times larger than those of non-users. Among sexually inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites, the odds ratios of initiating sexual intercourse were two to five times larger than that among non-users, even after a number of other relevant factors were introduced. This is the first study to demonstrate that online communication predicts the initiation of offline sexual and romantic activity as early as adolescence. Practitioners and parents need to consider the role of online communication in adolescents' developing sexuality. • Adolescents increasingly communicate online with peers. • Online communication predicts romantic and sexual activity among college students. What is New: • Online communication predicts adolescents' offline romantic activity over time. • Online communication predicts adolescents' offline sexual activity over time.

  5. Prediction of electroconvulsive therapy response and remission in major depression : meta-analysis

    OpenAIRE

    Diermen, van, Linda; Ameele, van den, Seline; Kamperman, Astrid M.; Sabbe, Bernard G.C.; Vermeulen, Tom; Schrijvers, Didier; Birkenhager, Tom K.

    2018-01-01

    Abstract: Background Electroconvulsive therapy (ECT) is considered to be the most effective treatment in severe major depression. The identification of reliable predictors of ECT response could contribute to a more targeted patient selection and consequently increased ECT response rates. Aims To investigate the predictive value of age, depression severity, psychotic and melancholic features for ECT response and remission in major depression. Method A meta-analysis was conducted according to t...

  6. Prediction of elastic-plastic response of structural elements subjected to cyclic loading

    International Nuclear Information System (INIS)

    El Haddad, M.H.; Samaan, S.

    1985-01-01

    A simplified elastic-plastic analysis is developed to predict stress strain and force deformation response of structural metallic elements subjected to irregular cyclic loadings. In this analysis a simple elastic-plastic method for predicting the skeleton force deformation curve is developed. In this method, elastic and fully plastic solutions are first obtained for unknown quantities, such as deflection or local strains. Elastic and fully plastic contributions are then combined to obtain an elastic-plastic solution. The skeleton curve is doubled to establish the shape of the hysteresis loop. The complete force deformation response can therefore be simulated through reversal by reversal in accordance with hysteresis looping and material memory. Several examples of structural elements with various cross sections made from various materials and subjected to irregular cyclic loadings, are analysed. A close agreement is obtained between experimental results found in the literature and present predictions. (orig.)

  7. Prediction of response to neoadjuvant chemotherapy in breast cancer: a radiomic study

    Science.gov (United States)

    Wu, Guolin; Fan, Ming; Zhang, Juan; Zheng, Bin; Li, Lihua

    2017-03-01

    Breast cancer is one of the most malignancies among women in worldwide. Neoadjuvant Chemotherapy (NACT) has gained interest and is increasingly used in treatment of breast cancer in recent years. Therefore, it is necessary to find a reliable non-invasive assessment and prediction method which can evaluate and predict the response of NACT. Recent studies have highlighted the use of MRI for predicting response to NACT. In addition, molecular subtype could also effectively identify patients who are likely have better prognosis in breast cancer. In this study, a radiomic analysis were performed, by extracting features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and immunohistochemistry (IHC) to determine subtypes. A dataset with fifty-seven breast cancer patients were included, all of them received preoperative MRI examination. Among them, 47 patients had complete response (CR) or partial response (PR) and 10 had stable disease (SD) to chemotherapy based on the RECIST criterion. A total of 216 imaging features including statistical characteristics, morphology, texture and dynamic enhancement were extracted from DCE-MRI. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.923 (P = 0.0002) in leave-one-out crossvalidation. The performance of the classifier increased to 0.960, 0.950 and 0.936 when status of HER2, Luminal A and Luminal B subtypes were added into the statistic model, respectively. The results of this study demonstrated that IHC determined molecular status combined with radiomic features from DCE-MRI could be used as clinical marker that is associated with response to NACT.

  8. Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

    Science.gov (United States)

    Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

    2011-01-01

    Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

  9. Recent and past musical activity predicts cognitive aging variability: direct comparison with general lifestyle activities.

    Science.gov (United States)

    Hanna-Pladdy, Brenda; Gajewski, Byron

    2012-01-01

    Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years) on preserved cognitive functioning in advanced age. These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59-80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not general lifestyle activities, predicted variability

  10. Optimization Of Activated Carbon Preparation From Spent Mushroom Farming Waste (SMFW) Via Box- Behnken Design Of Response Surface Methodology

    International Nuclear Information System (INIS)

    Nurul Shuhada Md Desa; Zaidi Ab Ghani; Suhaimi Abdul-Talib; Chia-Chay, T.

    2016-01-01

    This study focuses on activated carbon preparation from spent mushroom farming waste (SMFW) via chemical activation using Box-Behnken design (BBD) of Response Surface Methodology (RSM). Potassium hydroxide (KOH) functions as activating reagent and it play an important role in enhancing the activated carbon porosity. Three input parameters and two responses were evaluated via this software generated experimental design. The effects of three preparation parameters of impregnation ratio, activation time and activation temperature as well as two responses of carbon yield and iodine number were investigated. The optimum conditions for preparing activated carbon from SMFW was found at SMFW: KOH impregnation ratio of 0.25, activation time of 30 min and activation temperature of 400 degree Celsius which resulted in 28.23 % of carbon yield and 314.14 mg/ g of iodine number with desirability of 0.994. The predicted results were well corresponded with experimental results. This study is important in economical large scale SMFW activated carbon preparation for application study of adsorption process for metal treatment in wastewater with minimum chemical and energy input. (author)

  11. Can neural activation in dorsolateral prefrontal cortex predict responsiveness to information? An application to egg production systems and campaign advertising.

    Directory of Open Access Journals (Sweden)

    Brandon R McFadden

    Full Text Available Consumers prefer to pay low prices and increase animal welfare; however consumers are typically forced to make tradeoffs between price and animal welfare. Campaign advertising (i.e., advertising used during the 2008 vote on Proposition 2 in California may affect how consumers make tradeoffs between price and animal welfare. Neuroimaging data was used to determine the effects of brain activation in dorsolateral prefrontal cortex (dlPFC on choices making a tradeoff between price and animal welfare and responsiveness to campaign advertising. Results indicated that activation in the dlPFC was greater when making choices that forced a tradeoff between price and animal welfare, compared to choices that varied only by price or animal welfare. Furthermore, greater activation differences in right dlPFC between choices that forced a tradeoff and choices that did not, indicated greater responsiveness to campaign advertising.

  12. Can neural activation in dorsolateral prefrontal cortex predict responsiveness to information? An application to egg production systems and campaign advertising.

    Science.gov (United States)

    McFadden, Brandon R; Lusk, Jayson L; Crespi, John M; Cherry, J Bradley C; Martin, Laura E; Aupperle, Robin L; Bruce, Amanda S

    2015-01-01

    Consumers prefer to pay low prices and increase animal welfare; however consumers are typically forced to make tradeoffs between price and animal welfare. Campaign advertising (i.e., advertising used during the 2008 vote on Proposition 2 in California) may affect how consumers make tradeoffs between price and animal welfare. Neuroimaging data was used to determine the effects of brain activation in dorsolateral prefrontal cortex (dlPFC) on choices making a tradeoff between price and animal welfare and responsiveness to campaign advertising. Results indicated that activation in the dlPFC was greater when making choices that forced a tradeoff between price and animal welfare, compared to choices that varied only by price or animal welfare. Furthermore, greater activation differences in right dlPFC between choices that forced a tradeoff and choices that did not, indicated greater responsiveness to campaign advertising.

  13. A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

    Science.gov (United States)

    2017-02-01

    affecting the function of Fanconi Anemia (FA) genes ( FANCA /B/C/D2/E/F/G/I/J/L/M, PALB2) or DNA damage response genes involved in HR 5 (ATM, ATR...Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...To) 15 July 2010 – 2 Nov.2016 4. TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP

  14. XBeach-G: a tool for predicting gravel barrier response to extreme storm conditions

    Science.gov (United States)

    Masselink, Gerd; Poate, Tim; McCall, Robert; Roelvink, Dano; Russell, Paul; Davidson, Mark

    2014-05-01

    Gravel beaches protect low-lying back-barrier regions from flooding during storm events and their importance to society is widely acknowledged. Unfortunately, breaching and extensive storm damage has occurred at many gravel sites and this is likely to increase as a result of sea-level rise and enhanced storminess due to climate change. Limited scientific guidance is currently available to provide beach managers with operational management tools to predict the response of gravel beaches to storms. The New Understanding and Prediction of Storm Impacts on Gravel beaches (NUPSIG) project aims to improve our understanding of storm impacts on gravel coastal environments and to develop a predictive capability by modelling these impacts. The NUPSIG project uses a 5-pronged approach to address its aim: (1) analyse hydrodynamic data collected during a proto-type laboratory experiment on a gravel beach; (2) collect hydrodynamic field data on a gravel beach under a range of conditions, including storm waves with wave heights up to 3 m; (3) measure swash dynamics and beach response on 10 gravel beaches during extreme wave conditions with wave heights in excess of 3 m; (4) use the data collected under 1-3 to develop and validate a numerical model to model hydrodynamics and morphological response of gravel beaches under storm conditions; and (5) develop a tool for end-users, based on the model formulated under (4), for predicting storm response of gravel beaches and barriers. The aim of this presentation is to present the key results of the NUPSIG project and introduce the end-user tool for predicting storm response on gravel beaches. The model is based on the numerical model XBeach, and different forcing scenarios (wave and tides), barrier configurations (dimensions) and sediment characteristics are easily uploaded for model simulations using a Graphics User Interface (GUI). The model can be used to determine the vulnerability of gravel barriers to storm events, but can also be

  15. [Prediction of the molecular response to pertubations from single cell measurements].

    Science.gov (United States)

    Remacle, Françoise; Levine, Raphael D

    2014-12-01

    The response of protein signalization networks to perturbations is analysed from single cell measurements. This experimental approach allows characterizing the fluctuations in protein expression levels from cell to cell. The analysis is based on an information theoretic approach grounded in thermodynamics leading to a quantitative version of Le Chatelier principle which allows to predict the molecular response. Two systems are investigated: human macrophages subjected to lipopolysaccharide challenge, analogous to the immune response against Gram-negative bacteria and the response of the proteins involved in the mTOR signalizing network of GBM cancer cells to changes in partial oxygen pressure. © 2014 médecine/sciences – Inserm.

  16. Predictive feedback can account for biphasic responses in the lateral geniculate nucleus.

    Directory of Open Access Journals (Sweden)

    Janneke F M Jehee

    2009-05-01

    Full Text Available Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN, primary visual cortex (V1, and middle temporal area (MT. We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain.

  17. Early prediction of the response of breast tumors to neoadjuvant chemotherapy using quantitative MRI and machine learning.

    Science.gov (United States)

    Mani, Subramani; Chen, Yukun; Arlinghaus, Lori R; Li, Xia; Chakravarthy, A Bapsi; Bhave, Sandeep R; Welch, E Brian; Levy, Mia A; Yankeelov, Thomas E

    2011-01-01

    The ability to predict early in the course of treatment the response of breast tumors to neoadjuvant chemotherapy can stratify patients based on response for patient-specific treatment strategies. Currently response to neoadjuvant chemotherapy is evaluated based on physical exam or breast imaging (mammogram, ultrasound or conventional breast MRI). There is a poor correlation among these measurements and with the actual tumor size when measured by the pathologist during definitive surgery. We tested the feasibility of using quantitative MRI as a tool for early prediction of tumor response. Between 2007 and 2010 twenty consecutive patients diagnosed with Stage II/III breast cancer and receiving neoadjuvant chemotherapy were enrolled on a prospective imaging study. Our study showed that quantitative MRI parameters along with routine clinical measures can predict responders from non-responders to neoadjuvant chemotherapy. The best predictive model had an accuracy of 0.9, a positive predictive value of 0.91 and an AUC of 0.96.

  18. Horticultural activity predicts later localized limb status in a contemporary pre-industrial population.

    Science.gov (United States)

    Stieglitz, Jonathan; Trumble, Benjamin C; Kaplan, Hillard; Gurven, Michael

    2017-07-01

    Modern humans may have gracile skeletons due to low physical activity levels and mechanical loading. Tests using pre-historic skeletons are limited by the inability to assess behavior directly, while modern industrialized societies possess few socio-ecological features typical of human evolutionary history. Among Tsimane forager-horticulturalists, we test whether greater activity levels and, thus, increased loading earlier in life are associated with greater later-life bone status and diminished age-related bone loss. We used quantitative ultrasonography to assess radial and tibial status among adults aged 20+ years (mean ± SD age = 49 ± 15; 52% female). We conducted systematic behavioral observations to assess earlier-life activity patterns (mean time lag between behavioural observation and ultrasound = 12 years). For a subset of participants, physical activity was again measured later in life, via accelerometry, to determine whether earlier-life time use is associated with later-life activity levels. Anthropometric and demographic data were collected during medical exams. Structural decline with age is reduced for the tibia (female: -0.25 SDs/decade; male: 0.05 SDs/decade) versus radius (female: -0.56 SDs/decade; male: -0.20 SDs/decade), which is expected if greater loading mitigates bone loss. Time allocation to horticulture, but not hunting, positively predicts later-life radial status (β Horticulture  = 0.48, p = 0.01), whereas tibial status is not significantly predicted by subsistence or sedentary leisure participation. Patterns of activity- and age-related change in bone status indicate localized osteogenic responses to loading, and are generally consistent with the logic of bone functional adaptation. Nonmechanical factors related to subsistence lifestyle moderate the association between activity patterns and bone structure. © 2017 Wiley Periodicals, Inc.

  19. An Analysis of Natural T Cell Responses to Predicted Tumor Neoepitopes

    Directory of Open Access Journals (Sweden)

    Anne-Mette Bjerregaard

    2017-11-01

    Full Text Available Personalization of cancer immunotherapies such as therapeutic vaccines and adoptive T-cell therapy may benefit from efficient identification and targeting of patient-specific neoepitopes. However, current neoepitope prediction methods based on sequencing and predictions of epitope processing and presentation result in a low rate of validation, suggesting that the determinants of peptide immunogenicity are not well understood. We gathered published data on human neopeptides originating from single amino acid substitutions for which T cell reactivity had been experimentally tested, including both immunogenic and non-immunogenic neopeptides. Out of 1,948 neopeptide-HLA (human leukocyte antigen combinations from 13 publications, 53 were reported to elicit a T cell response. From these data, we found an enrichment for responses among peptides of length 9. Even though the peptides had been pre-selected based on presumed likelihood of being immunogenic, we found using NetMHCpan-4.0 that immunogenic neopeptides were predicted to bind significantly more strongly to HLA compared to non-immunogenic peptides. Investigation of the HLA binding strength of the immunogenic peptides revealed that the vast majority (96% shared very strong predicted binding to HLA and that the binding strength was comparable to that observed for pathogen-derived epitopes. Finally, we found that neopeptide dissimilarity to self is a predictor of immunogenicity in situations where neo- and normal peptides share comparable predicted binding strength. In conclusion, these results suggest new strategies for prioritization of mutated peptides, but new data will be needed to confirm their value.

  20. Music-related reward responses predict episodic memory performance.

    Science.gov (United States)

    Ferreri, Laura; Rodriguez-Fornells, Antoni

    2017-12-01

    Music represents a special type of reward involving the recruitment of the mesolimbic dopaminergic system. According to recent theories on episodic memory formation, as dopamine strengthens the synaptic potentiation produced by learning, stimuli triggering dopamine release could result in long-term memory improvements. Here, we behaviourally test whether music-related reward responses could modulate episodic memory performance. Thirty participants rated (in terms of arousal, familiarity, emotional valence, and reward) and encoded unfamiliar classical music excerpts. Twenty-four hours later, their episodic memory was tested (old/new recognition and remember/know paradigm). Results revealed an influence of music-related reward responses on memory: excerpts rated as more rewarding were significantly better recognized and remembered. Furthermore, inter-individual differences in the ability to experience musical reward, measured through the Barcelona Music Reward Questionnaire, positively predicted memory performance. Taken together, these findings shed new light on the relationship between music, reward and memory, showing for the first time that music-driven reward responses are directly implicated in higher cognitive functions and can account for individual differences in memory performance.

  1. Predictive display design for the vehicles with time delay in dynamic response

    Science.gov (United States)

    Efremov, A. V.; Tiaglik, M. S.; Irgaleev, I. H.; Efremov, E. V.

    2018-02-01

    The two ways for the improvement of flying qualities are considered: the predictive display (PD) and the predictive display integrated with the flight control system (FCS). The both ways allow to transforming the controlled element dynamics in the crossover frequency range, to improve the accuracy of tracking and to suppress the effect of time delay in the vehicle response too. The technique for optimization of the predictive law is applied to the landing task. The results of the mathematical modeling and experimental investigations carried out for this task are considered in the paper.

  2. Response-driven imaging biomarkers for predicting radiation necrosis of the brain

    International Nuclear Information System (INIS)

    Nazem-Zadeh, Mohammad-Reza; Chapman, Christopher H; Lawrence, Theodore S; Ten Haken, Randall K; Tsien, Christina I; Cao, Yue; Chenevert, Thomas

    2014-01-01

    Radiation necrosis is an uncommon but severe adverse effect of brain radiation therapy (RT). Current predictive models based on radiation dose have limited accuracy. We aimed to identify early individual response biomarkers based upon diffusion tensor (DT) imaging and incorporated them into a response model for prediction of radiation necrosis. Twenty-nine patients with glioblastoma received six weeks of intensity modulated RT and concurrent temozolomide. Patients underwent DT-MRI scans before treatment, at three weeks during RT, and one, three, and six months after RT. Cases with radiation necrosis were classified based on generalized equivalent uniform dose (gEUD) of whole brain and DT index early changes in the corpus callosum and its substructures. Significant covariates were used to develop normal tissue complication probability models using binary logistic regression. Seven patients developed radiation necrosis. Percentage changes of radial diffusivity (RD) in the splenium at three weeks during RT and at six months after RT differed significantly between the patients with and without necrosis (p = 0.05 and p = 0.01). Percentage change of RD at three weeks during RT in the 30 Gy dose–volume of the splenium and brain gEUD combined yielded the best-fit logistic regression model. Our findings indicate that early individual response during the course of RT, assessed by radial diffusivity, has the potential to aid the prediction of delayed radiation necrosis, which could provide guidance in dose-escalation trials. (paper)

  3. Evaluation of a fast power demand response strategy using active and passive building cold storages for smart grid applications

    International Nuclear Information System (INIS)

    Cui, Borui; Wang, Shengwei; Yan, Chengchu; Xue, Xue

    2015-01-01

    Highlights: • A fast power demand response strategy is developed for smart grid applications. • The developed strategy can provide immediate and stepped power demand reduction. • The demand reduction and building indoor temperature can be predicted accurately. • The demand reduction during the DR event is stable. - Abstract: Smart grid is considered as a promising solution in improving the power reliability and sustainability where demand response is one important ingredient. Demand response (DR) is a set of demand-side activities to reduce or shift electricity use to improve the electric grid efficiency and reliability. This paper presents the investigations on the power demand alternation potential for buildings involving both active and passive cold storages to support the demand response of buildings connected to smart grids. A control strategy is developed to provide immediate and stepped power demand reduction through shutting chiller(s) down when requested. The primary control objective of the developed control strategy is to restrain the building indoor temperature rise as to maintain indoor thermal comfort within certain level during the DR event. The chiller power reduction is also controlled under certain power reduction set-point. The results show that stepped and significant power reduction can be achieved through shutting chiller(s) down when requested. The power demand reduction and indoor temperature during the DR event can be also predicted accurately. The power demand reduction is stable which is predictable for the system operators

  4. A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound.

    Science.gov (United States)

    Tadayyon, Hadi; Sannachi, Lakshmanan; Gangeh, Mehrdad J; Kim, Christina; Ghandi, Sonal; Trudeau, Maureen; Pritchard, Kathleen; Tran, William T; Slodkowska, Elzbieta; Sadeghi-Naini, Ali; Czarnota, Gregory J

    2017-04-12

    Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival.

  5. Nerve Ultrasound Predicts Treatment Response in Chronic Inflammatory Demyelinating Polyradiculoneuropathy-a Prospective Follow-Up.

    Science.gov (United States)

    Härtig, Florian; Ross, Marlene; Dammeier, Nele Maria; Fedtke, Nadin; Heiling, Bianka; Axer, Hubertus; Décard, Bernhard F; Auffenberg, Eva; Koch, Marilin; Rattay, Tim W; Krumbholz, Markus; Bornemann, Antje; Lerche, Holger; Winter, Natalie; Grimm, Alexander

    2018-04-01

    As reliable biomarkers of disease activity are lacking, monitoring of therapeutic response in chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) remains a challenge. We sought to determine whether nerve ultrasound and electrophysiology scoring could close this gap. In CIDP patients (fulfilling EFNS/PNS criteria), we performed high-resolution nerve ultrasound to determine ultrasound pattern sum scores (UPSS) and predominant echotexture nerve conduction study scores (NCSS) as well as Medical Research Council sum scores (MRCSS) and inflammatory neuropathy cause and treatment disability scores (INCAT) at baseline and after 12 months of standard treatment. We retrospectively correlated ultrasound morphology with nerve histology when available. 72/80 CIDP patients featured multifocal nerve enlargement, and 35/80 were therapy-naïve. At baseline, clinical scores correlated with NCSS (r 2  = 0.397 and r 2  = 0.443, p  50% of measured segments, possibly reflecting axonal degeneration; and 3) almost no enlargement, reflecting "burned-out" or "cured" disease without active inflammation. Clinical improvement after 12 months was best in patients with pattern 1 (up to 75% vs up to 43% in pattern 2/3, Fisher's exact test p < 0.05). Nerve ultrasound has additional value not only for diagnosis, but also for classification of disease state and may predict treatment response.

  6. Implicit learning of predictable sound sequences modulates human brain responses at different levels of the auditory hierarchy

    Directory of Open Access Journals (Sweden)

    Françoise eLecaignard

    2015-09-01

    Full Text Available Deviant stimuli, violating regularities in a sensory environment, elicit the Mismatch Negativity (MMN, largely described in the Event-Related Potential literature. While it is widely accepted that the MMN reflects more than basic change detection, a comprehensive description of mental processes modulating this response is still lacking. Within the framework of predictive coding, deviance processing is part of an inference process where prediction errors (the mismatch between incoming sensations and predictions established through experience are minimized. In this view, the MMN is a measure of prediction error, which yields specific expectations regarding its modulations by various experimental factors. In particular, it predicts that the MMN should decrease as the occurrence of a deviance becomes more predictable. We conducted a passive oddball EEG study and manipulated the predictability of sound sequences by means of different temporal structures. Importantly, our design allows comparing mismatch responses elicited by predictable and unpredictable violations of a simple repetition rule and therefore departs from previous studies that investigate violations of different time-scale regularities. We observed a decrease of the MMN with predictability and interestingly, a similar effect at earlier latencies, within 70 ms after deviance onset. Following these pre-attentive responses, a reduced P3a was measured in the case of predictable deviants. We conclude that early and late deviance responses reflect prediction errors, triggering belief updating within the auditory hierarchy. Beside, in this passive study, such perceptual inference appears to be modulated by higher-level implicit learning of sequence statistical structures. Our findings argue for a hierarchical model of auditory processing where predictive coding enables implicit extraction of environmental regularities.

  7. Molecular markers predicting radiotherapy response: Report and recommendations from an International Atomic Energy Agency technical meeting

    International Nuclear Information System (INIS)

    West, Catharine M.L.; McKay, Michael J.; Hoelscher, Tobias; Baumann, Michael; Stratford, Ian J.; Bristow, Robert G.; Iwakawa, Mayumi; Imai, Takashi; Zingde, Surekha M.; Anscher, Mitchell S.; Bourhis, Jean; Begg, Adrian C.; Haustermans, Karin; Bentzen, Soren M.; Hendry, Jolyon H.

    2005-01-01

    Purpose: There is increasing interest in radiogenomics and the characterization of molecular profiles that predict normal tissue and tumor radioresponse. A meeting in Amsterdam was organized by the International Atomic Energy Agency to discuss this topic on an international basis. Methods and Materials: This report is not completely exhaustive, but highlights some of the ongoing studies and new initiatives being carried out worldwide in the banking of tumor and normal tissue samples underpinning the development of molecular marker profiles for predicting patient response to radiotherapy. It is generally considered that these profiles will more accurately define individual or group radiosensitivities compared with the nondefinitive findings from the previous era of cellular-based techniques. However, so far there are only a few robust reports of molecular markers predicting normal tissue or tumor response. Results: Many centers in different countries have initiated tissue and tumor banks to store samples from clinical trials for future molecular profiling analysis, to identify profiles that predict for radiotherapy response. The European Society for Therapeutic Radiology and Oncology GENEtic pathways for the Prediction of the effects of Irradiation (GENEPI) project, to store, document, and analyze sample characteristics vs. response, is the most comprehensive in this regard. Conclusions: The next 5-10 years are likely to see the results of these and other correlative studies, and promising associations of profiles with response should be validated in larger definitive trials

  8. Predictions of the electro-mechanical response of conductive CNT-polymer composites

    Science.gov (United States)

    Matos, Miguel A. S.; Tagarielli, Vito L.; Baiz-Villafranca, Pedro M.; Pinho, Silvestre T.

    2018-05-01

    We present finite element simulations to predict the conductivity, elastic response and strain-sensing capability of conductive composites comprising a polymeric matrix and carbon nanotubes. Realistic representative volume elements (RVE) of the microstructure are generated and both constituents are modelled as linear elastic solids, with resistivity independent of strain; the electrical contact between nanotubes is represented by a new element which accounts for quantum tunnelling effects and captures the sensitivity of conductivity to separation. Monte Carlo simulations are conducted and the sensitivity of the predictions to RVE size is explored. Predictions of modulus and conductivity are found in good agreement with published results. The strain-sensing capability of the material is explored for multiaxial strain states.

  9. Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.

    Directory of Open Access Journals (Sweden)

    Petros-Pavlos Ypsilantis

    Full Text Available Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy. In this article we investigate the challenging problem of predicting a patient's response to neoadjuvant chemotherapy from a single 18F-FDG PET scan taken prior to treatment. We take a "radiomics" approach whereby a large amount of quantitative features is automatically extracted from pretherapy PET images in order to build a comprehensive quantification of the tumor phenotype. While the dominant methodology relies on hand-crafted texture features, we explore the potential of automatically learning low- to high-level features directly from PET scans. We report on a study that compares the performance of two competing radiomics strategies: an approach based on state-of-the-art statistical classifiers using over 100 quantitative imaging descriptors, including texture features as well as standardized uptake values, and a convolutional neural network, 3S-CNN, trained directly from PET scans by taking sets of adjacent intra-tumor slices. Our experimental results, based on a sample of 107 patients with esophageal cancer, provide initial evidence that convolutional neural networks have the potential to extract PET imaging representations that are highly predictive of response to therapy. On this dataset, 3S-CNN achieves an average 80.7% sensitivity and 81.6% specificity in predicting non-responders, and outperforms other competing predictive models.

  10. A mesenchymal-like phenotype and expression of CD44 predict lack of apoptotic response to sorafenib in liver tumor cells.

    Science.gov (United States)

    Fernando, Joan; Malfettone, Andrea; Cepeda, Edgar B; Vilarrasa-Blasi, Roser; Bertran, Esther; Raimondi, Giulia; Fabra, Àngels; Alvarez-Barrientos, Alberto; Fernández-Salguero, Pedro; Fernández-Rodríguez, Conrado M; Giannelli, Gianluigi; Sancho, Patricia; Fabregat, Isabel

    2015-02-15

    The multikinase inhibitor sorafenib is the only effective drug in advanced cases of hepatocellular carcinoma (HCC). However, response differs among patients and effectiveness only implies a delay. We have recently described that sorafenib sensitizes HCC cells to apoptosis. In this work, we have explored the response to this drug of six different liver tumor cell lines to define a phenotypic signature that may predict lack of response in HCC patients. Results have indicated that liver tumor cells that show a mesenchymal-like phenotype, resistance to the suppressor effects of transforming growth factor beta (TGF-β) and high expression of the stem cell marker CD44 were refractory to sorafenib-induced cell death in in vitro studies, which correlated with lack of response to sorafenib in nude mice xenograft models of human HCC. In contrast, epithelial-like cells expressing the stem-related proteins EpCAM or CD133 were sensitive to sorafenib-induced apoptosis both in vitro and in vivo. A cross-talk between the TGF-β pathway and the acquisition of a mesenchymal-like phenotype with up-regulation of CD44 expression was found in the HCC cell lines. Targeted CD44 knock-down in the mesenchymal-like cells indicated that CD44 plays an active role in protecting HCC cells from sorafenib-induced apoptosis. However, CD44 effect requires a TGF-β-induced mesenchymal background, since the only overexpression of CD44 in epithelial-like HCC cells is not sufficient to impair sorafenib-induced cell death. In conclusion, a mesenchymal profile and expression of CD44, linked to activation of the TGF-β pathway, may predict lack of response to sorafenib in HCC patients. © 2014 UICC.

  11. Validation of Quantitative Structure-Activity Relationship (QSAR Model for Photosensitizer Activity Prediction

    Directory of Open Access Journals (Sweden)

    Sharifuddin M. Zain

    2011-11-01

    Full Text Available Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 µM to 7.04 µM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.

  12. Impaired chronotropic response to physical activities in heart failure patients.

    Science.gov (United States)

    Shen, Hong; Zhao, Jianrong; Zhou, Xiaohong; Li, Jingbo; Wan, Qing; Huang, Jing; Li, Hui; Wu, Liqun; Yang, Shungang; Wang, Ping

    2017-05-25

    While exercise-based cardiac rehabilitation has a beneficial effect on heart failure hospitalization and mortality, it is limited by the presence of chronotropic incompetence (CI) in some patients. This study explored the feasibility of using wearable devices to assess impaired chronotropic response in heart failure patients. Forty patients with heart failure (left ventricular ejection fraction, LVEF: 44.6 ± 5.8; age: 54.4 ± 11.7) received ECG Holter and accelerometer to monitor heart rate (HR) and physical activities during symptom-limited treadmill exercise testing, 6-min hall walk (6MHW), and 24-h daily living. CI was defined as maximal HR during peak exercise testing failing to reach 70% of age-predicted maximal HR (APMHR, 220 - age). The correlation between HR and physical activities in Holter-accelerometer recording was analyzed. Of 40 enrolled patients, 26 were able to perform treadmill exercise testing. Based on exercise test reports, 13 (50%) of 26 patients did not achieve at least 70% of APMHR (CI patients). CI patients achieved a lower % APMHR (62.0 ± 6.3%) than non-CI patients who achieved 72.0 ± 1.2% of APMHR (P failure patients who took treadmill exercise testing. The wearable Holter-accelerometer recording could help to identify impaired chronotropic response to physical activities in heart failure patients. ClinicalTrials.gov ID NCT02358603 . Registered 16 May 2014.

  13. Vigorous physical activity predicts higher heart rate variability among younger adults.

    Science.gov (United States)

    May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

    2017-06-14

    Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

  14. Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches.

    Science.gov (United States)

    Memarian, Negar; Torre, Jared B; Haltom, Kate E; Stanton, Annette L; Lieberman, Matthew D

    2017-09-01

    Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. © The Author (2017). Published by Oxford University Press.

  15. Children's biological responsivity to acute stress predicts concurrent cognitive performance.

    Science.gov (United States)

    Roos, Leslie E; Beauchamp, Kathryn G; Giuliano, Ryan; Zalewski, Maureen; Kim, Hyoun K; Fisher, Philip A

    2018-04-10

    Although prior research has characterized stress system reactivity (i.e. hypothalamic-pituitary-adrenal axis, HPAA; autonomic nervous system, ANS) in children, it has yet to examine the extent to which biological reactivity predicts concurrent goal-directed behavior. Here, we employed a stressor paradigm that allowed concurrent assessment of both stress system reactivity and performance on a speeded-response task to investigate the links between biological reactivity and cognitive function under stress. We further investigated gender as a moderator given previous research suggesting that the ANS may be particularly predictive of behavior in males due to gender differences in socialization. In a sociodemographically diverse sample of young children (N = 58, M age = 5.38 yrs; 44% male), individual differences in sociodemographic covariates (age, household income), HPAA (i.e. cortisol), and ANS (i.e. respiratory sinus arrhythmia, RSA, indexing the parasympathetic branch; pre-ejection period, PEP, indexing the sympathetic branch) function were assessed as predictors of cognitive performance under stress. We hypothesized that higher income, older age, and greater cortisol reactivity would be associated with better performance overall, and flexible ANS responsivity (i.e. RSA withdrawal, PEP shortening) would be predictive of performance for males. Overall, females performed better than males. Two-group SEM analyses suggest that, for males, greater RSA withdrawal to the stressor was associated with better performance, while for females, older age, higher income, and greater cortisol reactivity were associated with better performance. Results highlight the relevance of stress system reactivity to cognitive performance under stress. Future research is needed to further elucidate for whom and in what situations biological reactivity predicts goal-directed behavior.

  16. Texture analysis on MR images helps predicting non-response to NAC in breast cancer

    International Nuclear Information System (INIS)

    Michoux, N.; Van den Broeck, S.; Lacoste, L.; Fellah, L.; Galant, C.; Berlière, M.; Leconte, I.

    2015-01-01

    To assess the performance of a predictive model of non-response to neoadjuvant chemotherapy (NAC) in patients with breast cancer based on texture, kinetic, and BI-RADS parameters measured from dynamic MRI. Sixty-nine patients with invasive ductal carcinoma of the breast who underwent pre-treatment MRI were studied. Morphological parameters and biological markers were measured. Pathological complete response was defined as the absence of invasive and in situ cancer in breast and nodes. Pathological non-responders, partial and complete responders were identified. Dynamic imaging was performed at 1.5 T with a 3D axial T1W GRE fat-suppressed sequence. Visual texture, kinetic and BI-RADS parameters were measured in each lesion. ROC analysis and leave-one-out cross-validation were used to assess the performance of individual parameters, then the performance of multi-parametric models in predicting non-response to NAC. A model based on four pre-NAC parameters (inverse difference moment, GLN, LRHGE, wash-in) and k-means clustering as statistical classifier identified non-responders with 84 % sensitivity. BI-RADS mass/non-mass enhancement, biological markers and histological grade did not contribute significantly to the prediction. Pre-NAC texture and kinetic parameters help predicting non-benefit to NAC. Further testing including larger groups of patients with different tumor subtypes is needed to improve the generalization properties and validate the performance of the predictive model

  17. Demonstration of a multiscale modeling technique: prediction of the stress–strain response of light activated shape memory polymers

    International Nuclear Information System (INIS)

    Beblo, Richard V; Weiland, Lisa Mauck

    2010-01-01

    Presented is a multiscale modeling method applied to light activated shape memory polymers (LASMPs). LASMPs are a new class of shape memory polymer (SMPs) being developed for adaptive structures applications where a thermal stimulus is undesirable. LASMP developmental emphasis is placed on optical manipulation of Young's modulus. A multiscale modeling approach is employed to anticipate the soft and hard state moduli solely on the basis of a proposed molecular formulation. Employing such a model shows promise for expediting down-selection of favorable formulations for synthesis and testing, and subsequently accelerating LASMP development. An empirical adaptation of the model is also presented which has applications in system design once a formulation has been identified. The approach employs rotational isomeric state theory to build a molecular scale model of the polymer chain yielding a list of distances between the predicted crosslink locations, or r-values. The r-values are then fitted with Johnson probability density functions and used with Boltzmann statistical mechanics to predict stress as a function of the strain of the phantom polymer network. Empirical adaptation for design adds junction constraint theory to the modeling process. Junction constraint theory includes the effects of neighboring chain interactions. Empirical fitting results in numerically accurate Young's modulus predictions. The system is modular in nature and thus lends itself well to being adapted to other polymer systems and development applications

  18. Characterization of acute-on-chronic liver failure and prediction of mortality in Asian patients with active alcoholism.

    Science.gov (United States)

    Kim, Hwi Young; Chang, Young; Park, Jae Yong; Ahn, Hongkeun; Cho, Hyeki; Han, Seung Jun; Oh, Sohee; Kim, Donghee; Jung, Yong Jin; Kim, Byeong Gwan; Lee, Kook Lae; Kim, Won

    2016-02-01

    Alcoholic liver diseases often evolve to acute-on-chronic liver failure (ACLF), which increases the risk of (multi-)organ failure and death. We investigated the development and characteristics of alcohol-related ACLF and evaluated prognostic scores for prediction of mortality in Asian patients with active alcoholism. A total of 205 patients who were hospitalized with severe alcoholic liver disease were included in this retrospective cohort study, after excluding those with serious cardiovascular diseases, malignancy, or co-existing viral hepatitis. The Chronic Liver Failure (CLIF) Consortium Organ Failure score was used in the diagnosis and grading of ACLF, and the CLIF Consortium ACLF score (CLIF-C ACLFs) was used to predict mortality. Patients with ACLF had higher Maddrey discriminant function, model for end-stage liver disease (MELD), and MELD-sodium scores than those without ACLF. Infections were more frequently documented in patients with ACLF (33.3% vs 53.0%; P = 0.004). Predictive factors for ACLF development were systemic inflammatory response syndrome (odds ratio [OR], 2.239; P alcohol-related ACLF in Asian patients with active alcoholism. The CLIF-C ACLFs may be more useful for predicting mortality in ACLF cases than liver-specific scoring systems. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  19. Vital Signs Predict Rapid-Response Team Activation Within Twelve Hours of Emergency Department Admission.

    Science.gov (United States)

    Walston, James M; Cabrera, Daniel; Bellew, Shawna D; Olive, Marc N; Lohse, Christine M; Bellolio, M Fernanda

    2016-05-01

    Rapid-response teams (RRTs) are interdisciplinary groups created to rapidly assess and treat patients with unexpected clinical deterioration marked by decline in vital signs. Traditionally emergency department (ED) disposition is partially based on the patients' vital signs (VS) at the time of hospital admission. We aimed to identify which patients will have RRT activation within 12 hours of admission based on their ED VS, and if their outcomes differed. We conducted a case-control study of patients presenting from January 2009 to December 2012 to a tertiary ED who subsequently had RRT activations within 12 hours of admission (early RRT activations). The medical records of patients 18 years and older admitted to a non-intensive care unit (ICU) setting were reviewed to obtain VS at the time of ED arrival and departure, age, gender and diagnoses. Controls were matched 1:1 on age, gender, and diagnosis. We evaluated VS using cut points (lowest 10%, middle 80% and highest 10%) based on the distribution of VS for all patients. Our study adheres to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting observational studies. A total of 948 patients were included (474 cases and 474 controls). Patients who had RRT activations were more likely to be tachycardic (odds ratio [OR] 2.02, 95% CI [1.25-3.27]), tachypneic (OR 2.92, 95% CI [1.73-4.92]), and had lower oxygen saturations (OR 2.25, 95% CI [1.42-3.56]) upon arrival to the ED. Patients who had RRT activations were more likely to be tachycardic at the time of disposition from the ED (OR 2.76, 95% CI [1.65-4.60]), more likely to have extremes of systolic blood pressure (BP) (OR 1.72, 95% CI [1.08-2.72] for low BP and OR 1.82, 95% CI [1.19-2.80] for high BP), higher respiratory rate (OR 4.15, 95% CI [2.44-7.07]) and lower oxygen saturation (OR 2.29, 95% CI [1.43-3.67]). Early RRT activation was associated with increased healthcare utilization and worse outcomes including

  20. Footbridge Response Predictions and Their Sensitivity to Stochastic Load Assumptions

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2011-01-01

    Knowledge about footbridges response to actions of walking is important in assessments of vibration serviceability. In a number of design codes for footbridges, the vibration serviceability limit state is assessed using a walking load model in which the walking parameters (step frequency, pedestr......Knowledge about footbridges response to actions of walking is important in assessments of vibration serviceability. In a number of design codes for footbridges, the vibration serviceability limit state is assessed using a walking load model in which the walking parameters (step frequency...... of pedestrians for predicting footbridge response, which is meaningful, and a step forward. Modelling walking parameters stochastically, however, requires decisions to be made in terms of their statistical distribution and the parameters describing the statistical distribution. The paper investigates...... the sensitivity of results of computations of bridge response to some of the decisions to be made in this respect. This is a useful approach placing focus on which decisions (and which information) are important for sound estimation of bridge response. The studies involve estimating footbridge responses using...

  1. Diagnostic accuracy of soluble urokinase plasminogen activator receptor (suPAR) for prediction of bacteremia in patients with systemic inflammatory response syndrome.

    Science.gov (United States)

    Hoenigl, Martin; Raggam, Reinhard B; Wagner, Jasmin; Valentin, Thomas; Leitner, Eva; Seeber, Katharina; Zollner-Schwetz, Ines; Krammer, Werner; Prüller, Florian; Grisold, Andrea J; Krause, Robert

    2013-02-01

    Soluble urokinase plasminogen activator receptor (suPAR) serum concentrations have recently been described to reflect the severity status of systemic inflammation. In this study, the diagnostic accuracy of suPAR, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) to predict bacteremia in patients with systemic inflammatory response syndrome (SIRS) was compared. A total of 132 patients with SIRS were included. In 55 patients blood cultures had resulted positive (study group 1, Gram positive bacteria: Staphylococcus aureus and Streptococcus spp., n=15; study group 2, Gram-negative bacteria, n=40) and 77 patients had negative blood culture results (control group, n=77). Simultaneously with blood cultures suPAR, CRP, PCT, IL-6 and white blood count (WBC) were determined. SuPAR values were significantly higher in study group 1 (median 8.11; IQR 5.78-15.53; p=0.006) and study group 2 (median 9.62; IQR 6.52-11.74; p<0.001) when compared with the control group (median 5.65; IQR 4.30-7.83). ROC curve analysis revealed an AUC of 0.726 for suPAR in differentiating SIRS patients with bacteremia from those without. The biomarkers PCT and IL-6 showed comparable results. Regarding combinations of biomarkers multiplying suPAR, PCT and IL-6 was most promising and resulted in an AUC value of 0.804. Initial suPAR serum concentrations were significantly higher (p=0.028) in patients who died within 28 days than in those who survived. No significant difference was seen for PCT, IL-6 and CRP. In conclusion, suPAR, IL-6 and PCT may contribute to predicting bacteremia in SIRS patients. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  2. Implicit motives predict affective responses to emotional expressions

    Directory of Open Access Journals (Sweden)

    Andreas G. Rösch

    2013-12-01

    Full Text Available We explored the influence of implicit motives and activity inhibition on subjectively experienced affect in response to the presentation of six different facial expressions of emotion (FEEs; anger, disgust, fear, happiness, sadness, and surprise and neutral faces from the NimStim set of facial expressions (Tottenham et al., 2009. Implicit motives and activity inhibition were assessed using a Picture Story Exercise (Schultheiss et al., 2009b. Ratings of subjectively experienced affect (arousal and valence were assessed using Self-Assessment Manikins (Bradley and Lang, 1994 in a sample of 84 participants. We found that people with either a strong implicit power or achievement motive experienced stronger arousal, while people with a strong affiliation motive experienced less aroused and felt more unpleasant across emotions. Additionally, we obtained significant power motive × activity inhibition interactions for arousal ratings in response to FEEs and neutral faces. Participants with a strong power motive and weak activity inhibition experienced stronger arousal after the presentation of neutral faces but no additional increase in arousal after the presentation of FEEs. Participants with a strong power motive and strong activity inhibition (inhibited power motive did not feel aroused by neutral faces. However, their arousal increased in response to all FEEs with the exception of happy faces, for which their subjective arousal decreased. These more differentiated reaction pattern of individuals with an inhibited power motive suggest that they engage in a more socially adaptive manner of responding to different FEEs. Our findings extend established links between implicit motives and affective processes found at the procedural level to declarative reactions to FEEs. Implications are discussed with respect to dual-process models of motivation and research in motive congruence.

  3. Auditory Brainstem Response to Complex Sounds Predicts Self-Reported Speech-in-Noise Performance

    Science.gov (United States)

    Anderson, Samira; Parbery-Clark, Alexandra; White-Schwoch, Travis; Kraus, Nina

    2013-01-01

    Purpose: To compare the ability of the auditory brainstem response to complex sounds (cABR) to predict subjective ratings of speech understanding in noise on the Speech, Spatial, and Qualities of Hearing Scale (SSQ; Gatehouse & Noble, 2004) relative to the predictive ability of the Quick Speech-in-Noise test (QuickSIN; Killion, Niquette,…

  4. Identification of Predictive Response Markers and Novel Treatment Targets for Gliomas

    NARCIS (Netherlands)

    L. Erdem-Eraslan (Lale)

    2016-01-01

    markdownabstractGliomas are the most frequent primary brain tumors in adults. Despite multimodality treatment strategies, the survival of patients with a diffuse glioma remains poor. There has been an increasing use of molecular markers to assist diagnosis and predict prognosis and response to

  5. D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans.

    Science.gov (United States)

    Fazio, Leonardo; Blasi, Giuseppe; Taurisano, Paolo; Papazacharias, Apostolos; Romano, Raffaella; Gelao, Barbara; Ursini, Gianluca; Quarto, Tiziana; Lo Bianco, Luciana; Di Giorgio, Annabella; Mancini, Marina; Popolizio, Teresa; Rubini, Giuseppe; Bertolino, Alessandro

    2011-02-14

    Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 (rs1076560 G>T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [(123)I] FP-CIT SPECT. Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [(123)I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease. Copyright © 2010 Elsevier Inc. All rights reserved.

  6. Emotional Responses to Suicidal Patients: Factor Structure, Construct, and Predictive Validity of the Therapist Response Questionnaire-Suicide Form

    Directory of Open Access Journals (Sweden)

    Shira Barzilay

    2018-04-01

    Full Text Available BackgroundMental health professionals have a pivotal role in suicide prevention. However, they also often have intense emotional responses, or countertransference, during encounters with suicidal patients. Previous studies of the Therapist Response Questionnaire-Suicide Form (TRQ-SF, a brief novel measure aimed at probing a distinct set of suicide-related emotional responses to patients found it to be predictive of near-term suicidal behavior among high suicide-risk inpatients. The purpose of this study was to validate the TRQ-SF in a general outpatient clinic setting.MethodsAdult psychiatric outpatients (N = 346 and their treating mental health professionals (N = 48 completed self-report assessments following their first clinic meeting. Clinician measures included the TRQ-SF, general emotional states and traits, therapeutic alliance, and assessment of patient suicide risk. Patient suicidal outcomes and symptom severity were assessed at intake and one-month follow-up. Following confirmatory factor analysis of the TRQ-SF, factor scores were examined for relationships with clinician and patient measures and suicidal outcomes.ResultsFactor analysis of the TRQ-SF confirmed three dimensions: (1 affiliation, (2 distress, and (3 hope. The three factors also loaded onto a single general factor of negative emotional response toward the patient that demonstrated good internal reliability. The TRQ-SF scores were associated with measures of clinician state anger and anxiety and therapeutic alliance, independently of clinician personality traits after controlling for the state- and patient-specific measures. The total score and three subscales were associated in both concurrent and predictive ways with patient suicidal outcomes, depression severity, and clinicians’ judgment of patient suicide risk, but not with global symptom severity, thus indicating specifically suicide-related responses.ConclusionThe TRQ-SF is a brief and reliable measure with a

  7. Emotional Responses to Suicidal Patients: Factor Structure, Construct, and Predictive Validity of the Therapist Response Questionnaire-Suicide Form.

    Science.gov (United States)

    Barzilay, Shira; Yaseen, Zimri S; Hawes, Mariah; Gorman, Bernard; Altman, Rachel; Foster, Adriana; Apter, Alan; Rosenfield, Paul; Galynker, Igor

    2018-01-01

    Mental health professionals have a pivotal role in suicide prevention. However, they also often have intense emotional responses, or countertransference, during encounters with suicidal patients. Previous studies of the Therapist Response Questionnaire-Suicide Form (TRQ-SF), a brief novel measure aimed at probing a distinct set of suicide-related emotional responses to patients found it to be predictive of near-term suicidal behavior among high suicide-risk inpatients. The purpose of this study was to validate the TRQ-SF in a general outpatient clinic setting. Adult psychiatric outpatients ( N  = 346) and their treating mental health professionals ( N  = 48) completed self-report assessments following their first clinic meeting. Clinician measures included the TRQ-SF, general emotional states and traits, therapeutic alliance, and assessment of patient suicide risk. Patient suicidal outcomes and symptom severity were assessed at intake and one-month follow-up. Following confirmatory factor analysis of the TRQ-SF, factor scores were examined for relationships with clinician and patient measures and suicidal outcomes. Factor analysis of the TRQ-SF confirmed three dimensions: (1) affiliation, (2) distress, and (3) hope. The three factors also loaded onto a single general factor of negative emotional response toward the patient that demonstrated good internal reliability. The TRQ-SF scores were associated with measures of clinician state anger and anxiety and therapeutic alliance, independently of clinician personality traits after controlling for the state- and patient-specific measures. The total score and three subscales were associated in both concurrent and predictive ways with patient suicidal outcomes, depression severity, and clinicians' judgment of patient suicide risk, but not with global symptom severity, thus indicating specifically suicide-related responses. The TRQ-SF is a brief and reliable measure with a 3-factor structure. It demonstrates

  8. Your Brain on the Movies: A Computational Approach for Predicting Box-office Performance from Viewer's Brain Responses to Movie Trailers.

    Science.gov (United States)

    Christoforou, Christoforos; Papadopoulos, Timothy C; Constantinidou, Fofi; Theodorou, Maria

    2017-01-01

    The ability to anticipate the population-wide response of a target audience to a new movie or TV series, before its release, is critical to the film industry. Equally important is the ability to understand the underlying factors that drive or characterize viewer's decision to watch a movie. Traditional approaches (which involve pilot test-screenings, questionnaires, and focus groups) have reached a plateau in their ability to predict the population-wide responses to new movies. In this study, we develop a novel computational approach for extracting neurophysiological electroencephalography (EEG) and eye-gaze based metrics to predict the population-wide behavior of movie goers. We further, explore the connection of the derived metrics to the underlying cognitive processes that might drive moviegoers' decision to watch a movie. Towards that, we recorded neural activity-through the use of EEG-and eye-gaze activity from a group of naive individuals while watching movie trailers of pre-selected movies for which the population-wide preference is captured by the movie's market performance (i.e., box-office ticket sales in the US). Our findings show that the neural based metrics, derived using the proposed methodology, carry predictive information about the broader audience decisions to watch a movie, above and beyond traditional methods. In particular, neural metrics are shown to predict up to 72% of the variance of the films' performance at their premiere and up to 67% of the variance at following weekends; which corresponds to a 23-fold increase in prediction accuracy compared to current neurophysiological or traditional methods. We discuss our findings in the context of existing literature and hypothesize on the possible connection of the derived neurophysiological metrics to cognitive states of focused attention, the encoding of long-term memory, and the synchronization of different components of the brain's rewards network. Beyond the practical implication in

  9. Implicit Learning Abilities Predict Treatment Response in Autism Spectrum Disorders

    Science.gov (United States)

    2015-09-01

    early behavioral interventions are the most effective treatment for Autism Spectrum Disorder (ASD), but almost half of the children do not make...behavioral intervention . 2. KEYWORDS Autism Spectrum Disorder , implicit learning, associative learning, individual differences, functional Magnetic...2 AWARD NUMBER: W81XWH-14-1-0261 TITLE: Implicit Learning Abilities Predict Treatment Response in Autism Spectrum Disorders PRINCIPAL

  10. Fear on the move: predator hunting mode predicts variation in prey mortality and plasticity in prey spatial response.

    Science.gov (United States)

    Miller, Jennifer R B; Ament, Judith M; Schmitz, Oswald J

    2014-01-01

    Ecologists have long searched for a framework of a priori species traits to help predict predator-prey interactions in food webs. Empirical evidence has shown that predator hunting mode and predator and prey habitat domain are useful traits for explaining predator-prey interactions. Yet, individual experiments have yet to replicate predator hunting mode, calling into question whether predator impacts can be attributed to hunting mode or merely species identity. We tested the effects of spider predators with sit-and-wait, sit-and-pursue and active hunting modes on grasshopper habitat domain, activity and mortality in a grassland system. We replicated hunting mode by testing two spider predator species of each hunting mode on the same grasshopper prey species. We observed grasshoppers with and without each spider species in behavioural cages and measured their mortality rates, movements and habitat domains. We likewise measured the movements and habitat domains of spiders to characterize hunting modes. We found that predator hunting mode explained grasshopper mortality and spider and grasshopper movement activity and habitat domain size. Sit-and-wait spider predators covered small distances over a narrow domain space and killed fewer grasshoppers than sit-and-pursue and active predators, which ranged farther distances across broader domains and killed more grasshoppers, respectively. Prey adjusted their activity levels and horizontal habitat domains in response to predator presence and hunting mode: sedentary sit-and-wait predators with narrow domains caused grasshoppers to reduce activity in the same-sized domain space; more mobile sit-and-pursue predators with broader domains caused prey to reduce their activity within a contracted horizontal (but not vertical) domain space; and highly mobile active spiders led grasshoppers to increase their activity across the same domain area. All predators impacted prey activity, and sit-and-pursue predators generated strong

  11. Individual response to ionising radiation: What predictive assay(s) to choose?

    International Nuclear Information System (INIS)

    Granzotto, A.; Viau, M.; Devic, C.; Maalouf, M.; Thomas, Ch.; Vogin, G.; Foray, N.; Granzotto, A.; Vogin, G.; Balosso, J.; Joubert, A.; Maalouf, M.; Vogin, G.; Colin, C.; Malek, K.; Balosso, J.; Colin, C.

    2011-01-01

    Individual response to ionizing radiation is an important information required to apply an efficient radiotherapy treatment against tumour and to avoid any adverse effects in normal tissues. In 1981, Fertil and Malaise have demonstrated that the post-irradiation local tumor control determined in vivo is correlated with clonogenic cell survival assessed in vitro. Furthermore, these authors have reminded the relevance of the concept of intrinsic radiosensitivity that is specific to each individual organ (Fertil and Malaise, 1981) [1]. To date, since clonogenicity assays are too time-consuming and do not provide any other molecular information, a plethora of research groups have attempted to determine the molecular bases of intrinsic radiosensitivity in order to propose reliable and faster predictive assays. To this aim, several approaches have been developed. Notably, the recent revolution in genomic and proteomics technologies is providing a considerable number of data but their link with radiosensitivity still remains to be elucidated. On another hand, the systematic screening of some candidate genes potentially involved in the radiation response is highlighting the complexity of the molecular and cellular mechanisms of DNA damage sensing and signalling and shows that an abnormal radiation response is not necessarily due to the impairment of one single protein. Finally, more modest approaches consisting in focusing some specific functions of DNA repair seem to provide more reliable clues to predict over-acute reactions caused by radiotherapy. In this review, we endeavored to analyse the contributions of these major approaches to predict human radiosensitivity. (authors)

  12. Evaluation of stroke volume variation obtained by arterial pulse contour analysis to predict fluid responsiveness intraoperatively.

    Science.gov (United States)

    Lahner, D; Kabon, B; Marschalek, C; Chiari, A; Pestel, G; Kaider, A; Fleischmann, E; Hetz, H

    2009-09-01

    Fluid management guided by oesophageal Doppler monitor has been reported to improve perioperative outcome. Stroke volume variation (SVV) is considered a reliable clinical predictor of fluid responsiveness. Consequently, the aim of the present trial was to evaluate the accuracy of SVV determined by arterial pulse contour (APCO) analysis, using the FloTrac/Vigileo system, to predict fluid responsiveness as measured by the oesophageal Doppler. Patients undergoing major abdominal surgery received intraoperative fluid management guided by oesophageal Doppler monitoring. Fluid boluses of 250 ml each were administered in case of a decrease in corrected flow time (FTc) to 10%. The ability of SVV to predict fluid responsiveness was assessed by calculation of the area under the receiver operating characteristic (ROC) curve. Twenty patients received 67 fluid boluses. Fifty-two of the 67 fluid boluses administered resulted in fluid responsiveness. SVV achieved an area under the ROC curve of 0.512 [confidence interval (CI) 0.32-0.70]. A cut-off point for fluid responsiveness was found for SVV > or =8.5% (sensitivity: 77%; specificity: 43%; positive predictive value: 84%; and negative predictive value: 33%). This prospective, interventional observer-blinded study demonstrates that SVV obtained by APCO, using the FloTrac/Vigileo system, is not a reliable predictor of fluid responsiveness in the setting of major abdominal surgery.

  13. Perturbation of B Cell Gene Expression Persists in HIV-Infected Children Despite Effective Antiretroviral Therapy and Predicts H1N1 Response.

    Science.gov (United States)

    Cotugno, Nicola; De Armas, Lesley; Pallikkuth, Suresh; Rinaldi, Stefano; Issac, Biju; Cagigi, Alberto; Rossi, Paolo; Palma, Paolo; Pahwa, Savita

    2017-01-01

    Despite effective antiretroviral therapy (ART), HIV-infected individuals with apparently similar clinical and immunological characteristics can vary in responsiveness to vaccinations. However, molecular mechanisms responsible for such impairment, as well as biomarkers able to predict vaccine responsiveness in HIV-infected children, remain unknown. Following the hypothesis that a B cell qualitative impairment persists in HIV-infected children (HIV) despite effective ART and phenotypic B cell immune reconstitution, the aim of the current study was to investigate B cell gene expression of HIV compared to age-matched healthy controls (HCs) and to determine whether distinct gene expression patterns could predict the ability to respond to influenza vaccine. To do so, we analyzed prevaccination transcriptional levels of a 96-gene panel in equal numbers of sort-purified B cell subsets (SPBS) isolated from peripheral blood mononuclear cells using multiplexed RT-PCR. Immune responses to H1N1 antigen were determined by hemaglutination inhibition and memory B cell ELISpot assays following trivalent-inactivated influenza vaccination (TIV) for all study participants. Although there were no differences in terms of cell frequencies of SPBS between HIV and HC, the groups were distinguishable based upon gene expression analyses. Indeed, a 28-gene signature, characterized by higher expression of genes involved in the inflammatory response and immune activation was observed in activated memory B cells (CD27 + CD21 - ) from HIV when compared to HC despite long-term viral control (>24 months). Further analysis, taking into account H1N1 responses after TIV in HIV participants, revealed that a 25-gene signature in resting memory (RM) B cells (CD27 + CD21 + ) was able to distinguish vaccine responders from non-responders (NR). In fact, prevaccination RM B cells of responders showed a higher expression of gene sets involved in B cell adaptive immune responses ( APRIL, BTK, BLIMP1 ) and

  14. Muscle myeloid type I interferon gene expression may predict therapeutic responses to rituximab in myositis patients.

    Science.gov (United States)

    Nagaraju, Kanneboyina; Ghimbovschi, Svetlana; Rayavarapu, Sree; Phadke, Aditi; Rider, Lisa G; Hoffman, Eric P; Miller, Frederick W

    2016-09-01

    To identify muscle gene expression patterns that predict rituximab responses and assess the effects of rituximab on muscle gene expression in PM and DM. In an attempt to understand the molecular mechanism of response and non-response to rituximab therapy, we performed Affymetrix gene expression array analyses on muscle biopsy specimens taken before and after rituximab therapy from eight PM and two DM patients in the Rituximab in Myositis study. We also analysed selected muscle-infiltrating cell phenotypes in these biopsies by immunohistochemical staining. Partek and Ingenuity pathway analyses assessed the gene pathways and networks. Myeloid type I IFN signature genes were expressed at higher levels at baseline in the skeletal muscle of rituximab responders than in non-responders, whereas classic non-myeloid IFN signature genes were expressed at higher levels in non-responders at baseline. Also, rituximab responders have a greater reduction of the myeloid and non-myeloid type I IFN signatures than non-responders. The decrease in the type I IFN signature following administration of rituximab may be associated with the decreases in muscle-infiltrating CD19(+) B cells and CD68(+) macrophages in responders. Our findings suggest that high levels of myeloid type I IFN gene expression in skeletal muscle predict responses to rituximab in PM/DM and that rituximab responders also have a greater decrease in the expression of these genes. These data add further evidence to recent studies defining the type I IFN signature as both a predictor of therapeutic responses and a biomarker of myositis disease activity. Published by Oxford University Press on behalf British Society for Rheumatology 2016. This work is written by US Government employees and is in the public domain in the US.

  15. Predictive equations for lumbar spine loads in load-dependent asymmetric one- and two-handed lifting activities.

    Science.gov (United States)

    Arjmand, N; Plamondon, A; Shirazi-Adl, A; Parnianpour, M; Larivière, C

    2012-07-01

    Asymmetric lifting activities are associated with low back pain. A finite element biomechanical model is used to estimate spinal loads during one- and two-handed asymmetric static lifting activities. Model input variables are thorax flexion angle, load magnitude as well as load sagittal and lateral positions while response variables are L4-L5 and L5-S1 disc compression and shear forces. A number of levels are considered for each input variable and all their possible combinations are introduced into the model. Robust yet user-friendly predictive equations that relate model responses to its inputs are established. Predictive equations with adequate goodness-of-fit (R(2) ranged from ~94% to 99%, P≤0.001) that relate spinal loads to task (input) variables are established. Contour plots are used to identify combinations of task variable levels that yield spine loads beyond the recommended limits. The effect of uncertainties in the measurements of asymmetry-related inputs on spinal loads is studied. A number of issues regarding the NIOSH asymmetry multiplier are discussed and it is concluded that this multiplier should depend on the trunk posture and be defined in terms of the load vertical and horizontal positions. Due to an imprecise adjustment of the handled load magnitude this multiplier inadequately controls the biomechanical loading of the spine. Ergonomists and bioengineers, faced with the dilemma of using either complex but more accurate models on one hand or less accurate but simple models on the other hand, have hereby easy-to-use predictive equations that quantify spinal loads under various occupational tasks. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Self-reported Physical Activity Predicts Pain Inhibitory and Facilitatory Function

    Science.gov (United States)

    Naugle, Kelly M.; Riley, Joseph L.

    2013-01-01

    Considerable evidence suggests regular physical activity can reduce chronic pain symptoms. Dysfunction of endogenous facilitatory and inhibitory systems has been implicated in multiple chronic pain conditions. However, few studies have investigated the relationship between levels of physical activity and descending pain modulatory function. Purpose This study’s purpose was to determine whether self-reported levels of physical activity in healthy adults predicted 1) pain sensitivity to heat and cold stimuli, 2) pain facilitatory function as tested by temporal summation of pain (TS), and 3) pain inhibitory function as tested by conditioned pain modulation (CPM) and offset analgesia. Methods Forty-eight healthy adults (age range 18–76) completed the International Physical Activity Questionnaire (IPAQ) and the following pain tests: heat pain thresholds (HPT), heat pain suprathresholds, cold pressor pain (CPP), temporal summation of heat pain, conditioned pain modulation, and offset analgesia. The IPAQ measured levels of walking, moderate, vigorous and total physical activity over the past seven days. Hierarchical linear regressions were conducted to determine the relationship between each pain test and self-reported levels of physical activity, while controlling for age, sex and psychological variables. Results Self-reported total and vigorous physical activity predicted TS and CPM (p’s pain and greater CPM. The IPAQ measures did not predict any of the other pain measures. Conclusion Thus, these results suggest that healthy older and younger adults who self-report greater levels of vigorous and total physical activity exhibit enhanced descending pain modulatory function. Improved descending pain modulation may be a mechanism through which exercise reduces or prevents chronic pain symptoms. PMID:23899890

  17. Quantitative modeling of the ionospheric response to geomagnetic activity

    Directory of Open Access Journals (Sweden)

    T. J. Fuller-Rowell

    Full Text Available A physical model of the coupled thermosphere and ionosphere has been used to determine the accuracy of model predictions of the ionospheric response to geomagnetic activity, and assess our understanding of the physical processes. The physical model is driven by empirical descriptions of the high-latitude electric field and auroral precipitation, as measures of the strength of the magnetospheric sources of energy and momentum to the upper atmosphere. Both sources are keyed to the time-dependent TIROS/NOAA auroral power index. The output of the model is the departure of the ionospheric F region from the normal climatological mean. A 50-day interval towards the end of 1997 has been simulated with the model for two cases. The first simulation uses only the electric fields and auroral forcing from the empirical models, and the second has an additional source of random electric field variability. In both cases, output from the physical model is compared with F-region data from ionosonde stations. Quantitative model/data comparisons have been performed to move beyond the conventional "visual" scientific assessment, in order to determine the value of the predictions for operational use. For this study, the ionosphere at two ionosonde stations has been studied in depth, one each from the northern and southern mid-latitudes. The model clearly captures the seasonal dependence in the ionospheric response to geomagnetic activity at mid-latitude, reproducing the tendency for decreased ion density in the summer hemisphere and increased densities in winter. In contrast to the "visual" success of the model, the detailed quantitative comparisons, which are necessary for space weather applications, are less impressive. The accuracy, or value, of the model has been quantified by evaluating the daily standard deviation, the root-mean-square error, and the correlation coefficient between the data and model predictions. The modeled quiet-time variability, or standard

  18. Quantitative modeling of the ionospheric response to geomagnetic activity

    Directory of Open Access Journals (Sweden)

    T. J. Fuller-Rowell

    2000-07-01

    Full Text Available A physical model of the coupled thermosphere and ionosphere has been used to determine the accuracy of model predictions of the ionospheric response to geomagnetic activity, and assess our understanding of the physical processes. The physical model is driven by empirical descriptions of the high-latitude electric field and auroral precipitation, as measures of the strength of the magnetospheric sources of energy and momentum to the upper atmosphere. Both sources are keyed to the time-dependent TIROS/NOAA auroral power index. The output of the model is the departure of the ionospheric F region from the normal climatological mean. A 50-day interval towards the end of 1997 has been simulated with the model for two cases. The first simulation uses only the electric fields and auroral forcing from the empirical models, and the second has an additional source of random electric field variability. In both cases, output from the physical model is compared with F-region data from ionosonde stations. Quantitative model/data comparisons have been performed to move beyond the conventional "visual" scientific assessment, in order to determine the value of the predictions for operational use. For this study, the ionosphere at two ionosonde stations has been studied in depth, one each from the northern and southern mid-latitudes. The model clearly captures the seasonal dependence in the ionospheric response to geomagnetic activity at mid-latitude, reproducing the tendency for decreased ion density in the summer hemisphere and increased densities in winter. In contrast to the "visual" success of the model, the detailed quantitative comparisons, which are necessary for space weather applications, are less impressive. The accuracy, or value, of the model has been quantified by evaluating the daily standard deviation, the root-mean-square error, and the correlation coefficient between the data and model predictions. The modeled quiet-time variability, or standard

  19. Stock price change rate prediction by utilizing social network activities.

    Science.gov (United States)

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  20. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    Directory of Open Access Journals (Sweden)

    Shangkun Deng

    2014-01-01

    Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

  1. Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

    Science.gov (United States)

    Lymperopoulos, Ilias N

    2017-10-01

    The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Vital Signs Predict Rapid-Response Team Activation within Twelve Hours of Emergency Department Admission

    Directory of Open Access Journals (Sweden)

    James M. Walston

    2016-05-01

    Full Text Available Introduction: Rapid-response teams (RRTs are interdisciplinary groups created to rapidly assess and treat patients with unexpected clinical deterioration marked by decline in vital signs. Traditionally emergency department (ED disposition is partially based on the patients’ vital signs (VS at the time of hospital admission. We aimed to identify which patients will have RRT activation within 12 hours of admission based on their ED VS, and if their outcomes differed. Methods: We conducted a case-control study of patients presenting from January 2009 to December 2012 to a tertiary ED who subsequently had RRT activations within 12 hours of admission (early RRT activations. The medical records of patients 18 years and older admitted to a non-intensive care unit (ICU setting were reviewed to obtain VS at the time of ED arrival and departure, age, gender and diagnoses. Controls were matched 1:1 on age, gender, and diagnosis. We evaluated VS using cut points (lowest 10%, middle 80% and highest 10% based on the distribution of VS for all patients. Our study adheres to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting observational studies. Results: A total of 948 patients were included (474 cases and 474 controls. Patients who had RRT activations were more likely to be tachycardic (odds ratio [OR] 2.02, 95% CI [1.25-3.27], tachypneic (OR 2.92, 95% CI [1.73-4.92], and had lower oxygen saturations (OR 2.25, 95% CI [1.42-3.56] upon arrival to the ED. Patients who had RRT activations were more likely to be tachycardic at the time of disposition from the ED (OR 2.76, 95% CI [1.65-4.60], more likely to have extremes of systolic blood pressure (BP (OR 1.72, 95% CI [1.08-2.72] for low BP and OR 1.82, 95% CI [1.19-2.80] for high BP, higher respiratory rate (OR 4.15, 95% CI [2.44-7.07] and lower oxygen saturation (OR 2.29, 95% CI [1.43-3.67]. Early RRT activation was associated with increased healthcare

  3. Dissociation predicts poor response to Dialectial Behavioral Therapy in female patients with Borderline Personality Disorder.

    Science.gov (United States)

    Kleindienst, Nikolaus; Limberger, Matthias F; Ebner-Priemer, Ulrich W; Keibel-Mauchnik, Jana; Dyer, Anne; Berger, Mathias; Schmahl, Christian; Bohus, Martin

    2011-08-01

    A substantial proportion of Borderline Personality Disorder (BPD) patients respond by a marked decrease of psychopathology when treated with Dialectical Behavioral Therapy (DBT). To further enhance the rate of DBT-response, it is useful to identify characteristics related to unsatisfactory response. As DBT relies on emotional learning, we explored whether dissociation-which is known to interfere with learning- predicts poor response to DBT. Fifty-seven Borderline Personality Disorder (BPD) patients (DSM-IV) were prospectively observed during a three-month inpatient DBT program. Pre-post improvements in general psychopathology (SCL-90-R) were predicted from baseline scores of the Dissociative Experiences Scale (DES) by regression models accounting for baseline psychopathology. High DES-scores were related to poor pre-post improvement (β = -0.017 ± 0.006, p = 0.008). The data yielded no evidence that some facets of dissociation are more important in predicting DBT-response than others. The results suggest that dissociation in borderline-patients should be closely monitored and targeted during DBT. At this stage, research on treatment of dissociation (e.g., specific skills training) is warranted.

  4. Baseline 18F-FDG PET image-derived parameters for therapy response prediction in oesophageal cancer

    International Nuclear Information System (INIS)

    Hatt, Mathieu; Visvikis, Dimitris; Cheze-le Rest, Catherine; Pradier, Olivier

    2011-01-01

    The objectives of this study were to investigate the predictive value of tumour measurements on 2-deoxy-2-[ 18 F]fluoro-D-glucose ( 18 F-FDG) positron emission tomography (PET) pretreatment scan regarding therapy response in oesophageal cancer and to evaluate the impact of tumour delineation strategies. Fifty patients with oesophageal cancer treated with concomitant radiochemotherapy between 2004 and 2008 were retrospectively considered and classified as complete, partial or non-responders (including stable and progressive disease) according to Response Evaluation Criteria in Solid Tumors (RECIST). The classification of partial and complete responders was confirmed by biopsy. Tumours were delineated on the 18 F-FDG pretreatment scan using an adaptive threshold and the automatic fuzzy locally adaptive Bayesian (FLAB) methodologies. Several parameters were then extracted: maximum and peak standardized uptake value (SUV), tumour longitudinal length (TL) and volume (TV), SUV mean , and total lesion glycolysis (TLG = TV x SUV mean ). The correlation between each parameter and response was investigated using Kruskal-Wallis tests, and receiver-operating characteristic methodology was used to assess performance of the parameters to differentiate patients. Whereas commonly used parameters such as SUV measurements were not significant predictive factors of the response, parameters related to tumour functional spatial extent (TL, TV, TLG) allowed significant differentiation of all three groups of patients, independently of the delineation strategy, and could identify complete and non-responders with sensitivity above 75% and specificity above 85%. A systematic although not statistically significant trend was observed regarding the hierarchy of the delineation methodologies and the parameters considered, with slightly higher predictive value obtained with FLAB over adaptive thresholding, and TLG over TV and TL. TLG is a promising predictive factor of concomitant

  5. Reading a suspenseful literary text activates brain areas related to social cognition and predictive inference.

    Directory of Open Access Journals (Sweden)

    Moritz Lehne

    Full Text Available Stories can elicit powerful emotions. A key emotional response to narrative plots (e.g., novels, movies, etc. is suspense. Suspense appears to build on basic aspects of human cognition such as processes of expectation, anticipation, and prediction. However, the neural processes underlying emotional experiences of suspense have not been previously investigated. We acquired functional magnetic resonance imaging (fMRI data while participants read a suspenseful literary text (E.T.A. Hoffmann's "The Sandman" subdivided into short text passages. Individual ratings of experienced suspense obtained after each text passage were found to be related to activation in the medial frontal cortex, bilateral frontal regions (along the inferior frontal sulcus, lateral premotor cortex, as well as posterior temporal and temporo-parietal areas. The results indicate that the emotional experience of suspense depends on brain areas associated with social cognition and predictive inference.

  6. Observed Parent-Child Relationship Quality Predicts Antibody Response to Vaccination in Children

    Science.gov (United States)

    O'Connor, Thomas G; Wang, Hongyue; Moynihan, Jan A; Wyman, Peter A.; Carnahan, Jennifer; Lofthus, Gerry; Quataert, Sally A.; Bowman, Melissa; Burke, Anne S.; Caserta, Mary T

    2015-01-01

    Background Quality of the parent-child relationship is a robust predictor of behavioral and emotional health for children and adolescents; the application to physical health is less clear. Methods We investigated the links between observed parent-child relationship quality in an interaction task and antibody response to meningococcal conjugate vaccine in a longitudinal study of 164 ambulatory 10-11 year-old children; additional analyses examine associations with cortisol reactivity, BMI, and somatic illness. Results Observed negative/conflict behavior in the interaction task predicted a less robust antibody response to meningococcal serotype C vaccine in the child over a 6 month-period, after controlling for socio-economic and other covariates. Observer rated interaction conflict also predicted increased cortisol reactivity following the interaction task and higher BMI, but these factors did not account for the link between relationship quality and antibody response. Conclusions The results begin to document the degree to which a major source of child stress exposure, parent-child relationship conflict, is associated with altered immune system development in children, and may constitute an important public health consideration. PMID:25862953

  7. Predicting activities after stroke : what is clinically relevant?

    NARCIS (Netherlands)

    Kwakkel, G.; Kollen, B. J.

    Knowledge about factors that determine the final outcome after stroke is important for early stroke management, rehabilitation goals, and discharge planning. This narrative review provides an overview of current knowledge about the prediction of activities after stroke. We reviewed the pattern of

  8. AAA gunnermodel based on observer theory. [predicting a gunner's tracking response

    Science.gov (United States)

    Kou, R. S.; Glass, B. C.; Day, C. N.; Vikmanis, M. M.

    1978-01-01

    The Luenberger observer theory is used to develop a predictive model of a gunner's tracking response in antiaircraft artillery systems. This model is composed of an observer, a feedback controller and a remnant element. An important feature of the model is that the structure is simple, hence a computer simulation requires only a short execution time. A parameter identification program based on the least squares curve fitting method and the Gauss Newton gradient algorithm is developed to determine the parameter values of the gunner model. Thus, a systematic procedure exists for identifying model parameters for a given antiaircraft tracking task. Model predictions of tracking errors are compared with human tracking data obtained from manned simulation experiments. Model predictions are in excellent agreement with the empirical data for several flyby and maneuvering target trajectories.

  9. Demographic and phenotypic responses of juvenile steelhead trout to spatial predictability of food resources

    Science.gov (United States)

    Matthew R. Sloat; Gordon H. Reeves

    2014-01-01

    We manipulated food inputs among patches within experimental streams to determine how variation in foraging behavior influenced demographic and phenotypic responses of juvenile steelhead trout (Oncorhynchus mykiss) to the spatial predictability of food resources. Demographic responses included compensatory adjustments in fish abundance, mean fish...

  10. Identifying a predictive model for response to atypical antipsychotic monotherapy treatment in south Indian schizophrenia patients.

    Science.gov (United States)

    Gupta, Meenal; Moily, Nagaraj S; Kaur, Harpreet; Jajodia, Ajay; Jain, Sanjeev; Kukreti, Ritushree

    2013-08-01

    Atypical antipsychotic (AAP) drugs are the preferred choice of treatment for schizophrenia patients. Patients who do not show favorable response to AAP monotherapy are subjected to random prolonged therapeutic treatment with AAP multitherapy, typical antipsychotics or a combination of both. Therefore, prior identification of patients' response to drugs can be an important step in providing efficacious and safe therapeutic treatment. We thus attempted to elucidate a genetic signature which could predict patients' response to AAP monotherapy. Our logistic regression analyses indicated the probability that 76% patients carrying combination of four SNPs will not show favorable response to AAP therapy. The robustness of this prediction model was assessed using repeated 10-fold cross validation method, and the results across n-fold cross-validations (mean accuracy=71.91%; 95%CI=71.47-72.35) suggest high accuracy and reliability of the prediction model. Further validations of these results in large sample sets are likely to establish their clinical applicability. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Early perception of medication benefit predicts subsequent antipsychotic response in schizophrenia: "the consumer has a point" revisited.

    Science.gov (United States)

    Ascher-Svanum, Haya; Weiden, Peter; Nyhuis, Allen W; Faries, Douglas E; Stauffer, Virginia; Kollack-Walker, Sara; Kinon, Bruce J

    2014-07-01

    An easy-to-administer tool for predicting response to antipsychotic treatment could improve the acute management of patients with schizophrenia. We assessed whether a patient's perception of medication benefit early in treatment could predict subsequent response or nonresponse to continued use of the same treatment. This post hoc analysis used data from a randomized, open-label trial of antipsychotics for treatment of schizophrenia in which attitudes about medication adherence were assessed after two weeks of antipsychotic treatment using the Rating of Medication Influences (ROMI) scale. The analysis included 439 patients who had Positive and Negative Syndrome Scale (PANSS) and ROMI scale data at Weeks 2 and 8. Scores on the ROMI subscale Perceived Medication Benefit factor were used to predict subsequent antipsychotic response at Week 8, defined as a .20% reduction from baseline on the PANSS. Logistic regression was used to identify a cut-off score for the Perceived Medication Benefit factor that could accurately identify antipsychotic responders vs. nonresponders at Week 8. A score of .2.75 (equal to a mean subscale score of .11.00) on the ROMI scale Perceived Medication Benefit factor at Week 2 predicted response at Week 8 with high specificity (72%) and negative predictive value (70%), moderate sensitivity (44%) and positive predictive value (47%), and with a 38% misclassification rate. A brief assessment of the patient's perception of medication benefit at two weeks into treatment appears to be a good predictor of subsequent response and nonresponse after eight weeks of treatment with the same antipsychotic.

  12. Genetic polymorphisms in 5-Fluorouracil-related enzymes predict pathologic response after neoadjuvant chemoradiation for rectal cancer.

    Science.gov (United States)

    Nelson, Bailey; Carter, Jane V; Eichenberger, Maurice R; Netz, Uri; Galandiuk, Susan

    2016-11-01

    Many patients with rectal cancer undergo preoperative neoadjuvant chemoradiation, with approximately 70% exhibiting pathologic downstaging in response to treatment. Currently, there is no accurate test to predict patients who are likely to be complete responders to therapy. 5-Fluorouracil is used regularly in the neoadjuvant treatment of rectal cancer. Genetic polymorphisms affect the activity of thymidylate synthase, an enzyme involved in 5-Fluorouracil metabolism, which may account for observed differences in response to neoadjuvant treatment between patients. Detection of genetic polymorphisms might identify patients who are likely to have a complete response to neoadjuvant therapy and perhaps allow them to avoid operation. DNA was isolated from whole blood taken from patients with newly diagnosed rectal cancer who received neoadjuvant therapy (n = 50). Response to therapy was calculated with a tumor regression score based on histology from the time of operation. Polymerase chain reaction was performed targeting the promoter region of thymidylate synthase. Polymerase chain reaction products were separated using electrophoresis to determine whether patients were homozygous for a double-tandem repeat (2R), a triple-tandem repeat (3R), or were heterozygous (2R/3R). A single nucleotide polymorphism, 3G or 3C, also may be present in the second repeat unit of the triple-tandem repeat allele. Restriction fragment length polymorphism assays were performed in patients with at least one 3R allele using HaeIII. Patients with at least 1 thymidylate synthase 3G allele were more likely to have a complete or partial pathologic response to 5-Fluorouracil neoadjuvant therapy (odds ratio 10.4; 95% confidence interval, 1.3-81.6; P = .01) than those without at least one 3G allele. Identification of rectal cancer patients with specific genetic polymorphisms in enzymes involved in 5-Fluorouracil metabolism seems to predict the likelihood of complete or partial pathologic response

  13. Evaluate the capability and accuracy of response-2000 program in prediction of the shear capacities of reinforced and prestressed concrete members

    Directory of Open Access Journals (Sweden)

    Ibrahim M. Metwally

    2012-08-01

    Member response analysis and sectional analysis were both used in Response-2000 to predict the behavior of the beams. Member response calculates the full member behavior including the deflection and curvature along the member length, as well as predicted failure modes. The analysis was performed by specifying the length subjected to shear and any constant moment region. Response-2000 provided a very good prediction of experimental behavior when compared to a database of 534 beams tested in shear. These include prestressed and reinforced sections, very large footing-like sections, sections made with very high strength concrete and elements with unusual geometry. All are predicted well. The results include that Response-2000 can predict the failure shear with an average experimental over predicted shear ratio of 1.05 with a coefficient of variation of 12%. This compares favorably to the ACI 318-08 [2] Code prediction ratios that have an average of 1.20 and a coefficient of variation of 32%.

  14. Brain activity elicited by viewing pictures of the own virtually amputated body predicts xenomelia.

    Science.gov (United States)

    Oddo-Sommerfeld, Silvia; Hänggi, Jürgen; Coletta, Ludovico; Skoruppa, Silke; Thiel, Aylin; Stirn, Aglaja V

    2018-01-08

    Xenomelia is a rare condition characterized by the persistent desire for the amputation of physically healthy limbs. Prior studies highlighted the importance of superior and inferior parietal lobuli (SPL/IPL) and other sensorimotor regions as key brain structures associated with xenomelia. We expected activity differences in these areas in response to pictures showing the desired body state, i.e. that of an amputee in xenomelia. Functional magnetic resonance images were acquired in 12 xenomelia individuals and 11 controls while they viewed pictures of their own real and virtually amputated body. Pictures were rated on several dimensions. Multivariate statistics using machine learning was performed on imaging data. Brain activity when viewing pictures of one's own virtually amputated body predicted group membership accurately with a balanced accuracy of 82.58% (p = 0.002), sensitivity of 83.33% (p = 0.018), specificity of 81.82% (p = 0.015) and an area under the ROC curve of 0.77. Among the highest predictive brain regions were bilateral SPL, IPL, and caudate nucleus, other limb representing areas, but also occipital regions. Pleasantness and attractiveness ratings were higher for amputated bodies in xenomelia. Findings show that neuronal processing in response to pictures of one's own desired body state is different in xenomelia compared with controls and might represent a neuronal substrate of the xenomelia complaints that become behaviourally relevant, at least when rating the pleasantness and attractiveness of one's own body. Our findings converge with structural peculiarities reported in xenomelia and partially overlap in task and results with that of anorexia and transgender research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Species’ traits help predict small mammal responses to habitat homogenization by an invasive grass

    Science.gov (United States)

    Ceradini, Joseph P.; Chalfoun, Anna D.

    2017-01-01

    Invasive plants can negatively affect native species, however, the strength, direction, and shape of responses may vary depending on the type of habitat alteration and the natural history of native species. To prioritize conservation of vulnerable species, it is therefore critical to effectively predict species’ responses to invasive plants, which may be facilitated by a framework based on species’ traits. We studied the population and community responses of small mammals and changes in habitat heterogeneity across a gradient of cheatgrass (Bromus tectorum) cover, a widespread invasive plant in North America. We live-trapped small mammals over two summers and assessed the effect of cheatgrass on native small mammal abundance, richness, and species-specific and trait-based occupancy, while accounting for detection probability and other key habitat elements. Abundance was only estimated for the most common species, deer mice (Peromyscus maniculatus). All species were pooled for the trait-based occupancy analysis to quantify the ability of small mammal traits (habitat association, mode of locomotion, and diet) to predict responses to cheatgrass invasion. Habitat heterogeneity decreased with cheatgrass cover. Deer mouse abundance increased marginally with cheatgrass. Species richness did not vary with cheatgrass, however, pocket mouse (Perognathus spp.) and harvest mouse (Reithrodontomys spp.) occupancy tended to decrease and increase, respectively, with cheatgrass cover, suggesting a shift in community composition. Cheatgrass had little effect on occupancy for deer mice, 13-lined ground squirrels (Spermophilus tridecemlineatus), and Ord's kangaroo rat (Dipodomys ordii). Species’ responses to cheatgrass primarily corresponded with our a priori predictions based on species’ traits. The probability of occupancy varied significantly with a species’ habitat association but not with diet or mode of locomotion. When considered within the context of a rapid

  16. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    DEFF Research Database (Denmark)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara

    2017-01-01

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity ...

  17. Resting alpha activity predicts learning ability in alpha neurofeedback

    Directory of Open Access Journals (Sweden)

    Wenya eNan

    2014-07-01

    Full Text Available Individuals differ in their ability to learn how to regulate the alpha activity by neurofeedback. This study aimed to investigate whether the resting alpha activity is related to the learning ability of alpha enhancement in neurofeedback and could be used as a predictor. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback in order to learn how to enhance activity in the alpha frequency band. The learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.

  18. Ohmyungsamycins promote antimicrobial responses through autophagy activation via AMP-activated protein kinase pathway.

    Science.gov (United States)

    Kim, Tae Sung; Shin, Yern-Hyerk; Lee, Hye-Mi; Kim, Jin Kyung; Choe, Jin Ho; Jang, Ji-Chan; Um, Soohyun; Jin, Hyo Sun; Komatsu, Masaaki; Cha, Guang-Ho; Chae, Han-Jung; Oh, Dong-Chan; Jo, Eun-Kyeong

    2017-06-13

    The induction of host cell autophagy by various autophagy inducers contributes to the antimicrobial host defense against Mycobacterium tuberculosis (Mtb), a major pathogenic strain that causes human tuberculosis. In this study, we present a role for the newly identified cyclic peptides ohmyungsamycins (OMS) A and B in the antimicrobial responses against Mtb infections by activating autophagy in murine bone marrow-derived macrophages (BMDMs). OMS robustly activated autophagy, which was essentially required for the colocalization of LC3 autophagosomes with bacterial phagosomes and antimicrobial responses against Mtb in BMDMs. Using a Drosophila melanogaster-Mycobacterium marinum infection model, we showed that OMS-A-induced autophagy contributed to the increased survival of infected flies and the limitation of bacterial load. We further showed that OMS triggered AMP-activated protein kinase (AMPK) activation, which was required for OMS-mediated phagosome maturation and antimicrobial responses against Mtb. Moreover, treating BMDMs with OMS led to dose-dependent inhibition of macrophage inflammatory responses, which was also dependent on AMPK activation. Collectively, these data show that OMS is a promising candidate for new anti-mycobacterial therapeutics by activating antibacterial autophagy via AMPK-dependent signaling and suppressing excessive inflammation during Mtb infections.

  19. Predicting for activity of second-line trastuzumab-based therapy in her2-positive advanced breast cancer

    Directory of Open Access Journals (Sweden)

    Rottenfusser Andrea

    2009-10-01

    Full Text Available Abstract Background In Her2-positive advanced breast cancer, the upfront use of trastuzumab is well established. Upon progression on first-line therapy, patients may be switched to lapatinib. Others however remain candidates for continued antibody treatment (treatment beyond progression. Here, we aimed to identify factors predicting for activity of second-line trastuzumab-based therapy. Methods Ninety-seven patients treated with > 1 line of trastuzumab-containing therapy were available for this analysis. Her2-status was determined by immunohistochemistry and re-analyzed by FISH if a score of 2+ was gained. Time to progression (TTP on second-line therapy was defined as primary study endpoint. TTP and overall survival (OS were estimated using the Kaplan-Meier product limit method. Multivariate analyses (Cox proportional hazards model, multinomial logistic regression were applied in order to identify factors associated with TTP, response, OS, and incidence of brain metastases. p values Results Median TTP on second-line trastuzumab-based therapy was 7 months (95% CI 5.74-8.26, and 8 months (95% CI 6.25-9.74 on first-line, respectively (n.s.. In the multivariate models, none of the clinical or histopthological features could reliably predict for activity of second-line trastuzumab-based treatment. OS was 43 months suggesting improved survival in patients treated with trastuzumab in multiple-lines. A significant deterioration of cardiac function was observed in three patients; 40.2% developed brain metastases while on second-line trastuzumab or thereafter. Conclusion Trastuzumab beyond progression showed considerable activity. None of the variables investigated correlated with activity of second-line therapy. In order to predict for activity of second-line trastuzumab, it appears necessary to evaluate factors known to confer trastuzumab-resistance.

  20. Parental overcontrol x OPRM1 genotype interaction predicts school-aged children's sympathetic nervous system activation in response to performance challenge.

    Science.gov (United States)

    Partington, Lindsey C; Borelli, Jessica L; Smiley, Patricia; Jarvik, Ella; Rasmussen, Hannah F; Seaman, Lauren C; Nurmi, Erika L

    2018-04-26

    Parental overcontrol (OC), the excessive regulation of a child's behavior, cognition, and emotion, is associated with the development of child anxiety. While studies have shown that genetic factors may increase sensitivity to stress, genetic vulnerability to parental OC has not been examined in anxiety etiology. A functional polymorphism in the mu opioid receptor OPRM1 (A118G, rs1799971) has been shown to impact stress reactivity. Using a community sample of children (N = 85, 9-12 years old), we examined the main and interactive effects of maternal OC and child OPRM1 genotype in predicting children's sympathetic nervous system reactivity during a performance stressor. Neither OC nor genotype predicted children's electrodermal activity (EDA); however, the interaction between OC and child genotype significantly predicted stress reactivity, as indexed by EDA, during the challenging task. Among children with the minor G-allele, higher maternal OC was associated with higher reactivity. In A homozygotes, maternal OC was not associated with EDA, suggesting a diathesis-stress pattern of gene x environment interaction. We discuss implications for anxiety etiology and intervention. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Prediction of inflammatory responses induced by biomaterials in contact with human blood using protein fingerprint from plasma.

    Science.gov (United States)

    Engberg, Anna E; Nilsson, Per H; Huang, Shan; Fromell, Karin; Hamad, Osama A; Mollnes, Tom Eirik; Rosengren-Holmberg, Jenny P; Sandholm, Kerstin; Teramura, Yuji; Nicholls, Ian A; Nilsson, Bo; Ekdahl, Kristina N

    2015-01-01

    Inappropriate complement activation is often responsible for incompatibility reactions that occur when biomaterials are used. Complement activation is therefore a criterion included in legislation regarding biomaterials testing. However, no consensus is yet available regarding appropriate complement-activation-related test parameters. We examined protein adsorption in plasma and complement activation/cytokine release in whole blood incubated with well-characterized polymers. Strong correlations were found between the ratio of C4 to its inhibitor C4BP and generation of 10 (mainly pro-inflammatory) cytokines, including IL-17, IFN-γ, and IL-6. The levels of complement activation products correlated weakly (C3a) or not at all (C5a, sC5b-9), confirming their poor predictive values. We have demonstrated a direct correlation between downstream biological effects and the proteins initially adhering to an artificial surface after contact with blood. Consequently, we propose the C4/C4BP ratio as a robust, predictor of biocompatibility with superior specificity and sensitivity over the current gold standard. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    NARCIS (Netherlands)

    Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Alhusseini, Tamera I; Bedford, Felicity E; Bennett, Dominic J; Booth, Hollie; Burton, Victoria J; Chng, Charlotte W T; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Emerson, Susan R; Gao, Di; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; Pask-Hale, Gwilym D; Pynegar, Edwin L; Robinson, Alexandra N; Sanchez-Ortiz, Katia; Senior, Rebecca A; Simmons, Benno I; White, Hannah J; Zhang, Hanbin; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Albertos, Belén; Alcala, E L; Del Mar Alguacil, Maria; Alignier, Audrey; Ancrenaz, Marc; Andersen, Alan N; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Arroyo-Rodríguez, Víctor; Aumann, Tom; Axmacher, Jan C; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Bakayoko, Adama; Báldi, András; Banks, John E; Baral, Sharad K; Barlow, Jos; Barratt, Barbara I P; Barrico, Lurdes; Bartolommei, Paola; Barton, Diane M; Basset, Yves; Batáry, Péter; Bates, Adam J; Baur, Bruno; Bayne, Erin M; Beja, Pedro; Benedick, Suzan; Berg, Åke; Bernard, Henry; Berry, Nicholas J; Bhatt, Dinesh; Bicknell, Jake E; Bihn, Jochen H; Blake, Robin J; Bobo, Kadiri S; Bóçon, Roberto; Boekhout, Teun; Böhning-Gaese, Katrin; Bonham, Kevin J; Borges, Paulo A V; Borges, Sérgio H; Boutin, Céline; Bouyer, Jérémy; Bragagnolo, Cibele; Brandt, Jodi S; Brearley, Francis Q; Brito, Isabel; Bros, Vicenç; Brunet, Jörg; Buczkowski, Grzegorz; Buddle, Christopher M; Bugter, Rob; Buscardo, Erika; Buse, Jörn; Cabra-García, Jimmy; Cáceres, Nilton C; Cagle, Nicolette L; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Caparrós, Rut; Cardoso, Pedro; Carpenter, Dan; Carrijo, Tiago F; Carvalho, Anelena L; Cassano, Camila R; Castro, Helena; Castro-Luna, Alejandro A; Rolando, Cerda B; Cerezo, Alexis; Chapman, Kim Alan; Chauvat, Matthieu; Christensen, Morten; Clarke, Francis M; Cleary, Daniel F R; Colombo, Giorgio; Connop, Stuart P; Craig, Michael D; Cruz-López, Leopoldo; Cunningham, Saul A; D'Aniello, Biagio; D'Cruze, Neil; da Silva, Pedro Giovâni; Dallimer, Martin; Danquah, Emmanuel; Darvill, Ben; Dauber, Jens; Davis, Adrian L V; Dawson, Jeff; de Sassi, Claudio; de Thoisy, Benoit; Deheuvels, Olivier; Dejean, Alain; Devineau, Jean-Louis; Diekötter, Tim; Dolia, Jignasu V; Domínguez, Erwin; Dominguez-Haydar, Yamileth; Dorn, Silvia; Draper, Isabel; Dreber, Niels; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Eggleton, Paul; Eigenbrod, Felix; Elek, Zoltán; Entling, Martin H; Esler, Karen J; de Lima, Ricardo F; Faruk, Aisyah; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Fensham, Roderick J; Fernandez, Ignacio C; Ferreira, Catarina C; Ficetola, Gentile F; Fiera, Cristina; Filgueiras, Bruno K C; Fırıncıoğlu, Hüseyin K; Flaspohler, David; Floren, Andreas; Fonte, Steven J; Fournier, Anne; Fowler, Robert E; Franzén, Markus; Fraser, Lauchlan H; Fredriksson, Gabriella M; Freire, Geraldo B; Frizzo, Tiago L M; Fukuda, Daisuke; Furlani, Dario; Gaigher, René; Ganzhorn, Jörg U; García, Karla P; Garcia-R, Juan C; Garden, Jenni G; Garilleti, Ricardo; Ge, Bao-Ming; Gendreau-Berthiaume, Benoit; Gerard, Philippa J; Gheler-Costa, Carla; Gilbert, Benjamin; Giordani, Paolo; Giordano, Simonetta; Golodets, Carly; Gomes, Laurens G L; Gould, Rachelle K; Goulson, Dave; Gove, Aaron D; Granjon, Laurent; Grass, Ingo; Gray, Claudia L; Grogan, James; Gu, Weibin; Guardiola, Moisès; Gunawardene, Nihara R; Gutierrez, Alvaro G; Gutiérrez-Lamus, Doris L; Haarmeyer, Daniela H; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hassan, Shombe N; Hatfield, Richard G; Hawes, Joseph E; Hayward, Matt W; Hébert, Christian; Helden, Alvin J; Henden, John-André; Henschel, Philipp; Hernández, Lionel; Herrera, James P; Herrmann, Farina; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Höfer, Hubert; Hoffmann, Anke; Horgan, Finbarr G; Hornung, Elisabeth; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishida, Hiroaki; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Hernández, F Jiménez; Johnson, McKenzie F; Jolli, Virat; Jonsell, Mats; Juliani, S Nur; Jung, Thomas S; Kapoor, Vena; Kappes, Heike; Kati, Vassiliki; Katovai, Eric; Kellner, Klaus; Kessler, Michael; Kirby, Kathryn R; Kittle, Andrew M; Knight, Mairi E; Knop, Eva; Kohler, Florian; Koivula, Matti; Kolb, Annette; Kone, Mouhamadou; Kőrösi, Ádám; Krauss, Jochen; Kumar, Ajith; Kumar, Raman; Kurz, David J; Kutt, Alex S; Lachat, Thibault; Lantschner, Victoria; Lara, Francisco; Lasky, Jesse R; Latta, Steven C; Laurance, William F; Lavelle, Patrick; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Lehouck, Valérie; Lencinas, María V; Lentini, Pia E; Letcher, Susan G; Li, Qi; Litchwark, Simon A; Littlewood, Nick A; Liu, Yunhui; Lo-Man-Hung, Nancy; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Luskin, Matthew S; MacSwiney G, M Cristina; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Malone, Louise A; Malonza, Patrick K; Malumbres-Olarte, Jagoba; Mandujano, Salvador; Måren, Inger E; Marin-Spiotta, Erika; Marsh, Charles J; Marshall, E J P; Martínez, Eliana; Martínez Pastur, Guillermo; Moreno Mateos, David; Mayfield, Margaret M; Mazimpaka, Vicente; McCarthy, Jennifer L; McCarthy, Kyle P; McFrederick, Quinn S; McNamara, Sean; Medina, Nagore G; Medina, Rafael; Mena, Jose L; Mico, Estefania; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Miranda-Esquivel, Daniel R; Moir, Melinda L; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Mudri-Stojnic, Sonja; Munira, A Nur; Muoñz-Alonso, Antonio; Munyekenye, B F; Naidoo, Robin; Naithani, A; Nakagawa, Michiko; Nakamura, Akihiro; Nakashima, Yoshihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Navarro-Iriarte, Luis; Ndang'ang'a, Paul K; Neuschulz, Eike L; Ngai, Jacqueline T; Nicolas, Violaine; Nilsson, Sven G; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Norton, David A; Nöske, Nicole M; Nowakowski, A Justin; Numa, Catherine; O'Dea, Niall; O'Farrell, Patrick J; Oduro, William; Oertli, Sabine; Ofori-Boateng, Caleb; Oke, Christopher Omamoke; Oostra, Vicencio; Osgathorpe, Lynne M; Otavo, Samuel Eduardo; Page, Navendu V; Paritsis, Juan; Parra-H, Alejandro; Parry, Luke; Pe'er, Guy; Pearman, Peter B; Pelegrin, Nicolás; Pélissier, Raphaël; Peres, Carlos A; Peri, Pablo L; Persson, Anna S; Petanidou, Theodora; Peters, Marcell K; Pethiyagoda, Rohan S; Phalan, Ben; Philips, T Keith; Pillsbury, Finn C; Pincheira-Ulbrich, Jimmy; Pineda, Eduardo; Pino, Joan; Pizarro-Araya, Jaime; Plumptre, A J; Poggio, Santiago L; Politi, Natalia; Pons, Pere; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Rader, Romina; Ramesh, B R; Ramirez-Pinilla, Martha P; Ranganathan, Jai; Rasmussen, Claus; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Rey Benayas, José M; Rey-Velasco, Juan Carlos; Reynolds, Chevonne; Ribeiro, Danilo Bandini; Richards, Miriam H; Richardson, Barbara A; Richardson, Michael J; Ríos, Rodrigo Macip; Robinson, Richard; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rös, Matthias; Rosselli, Loreta; Rossiter, Stephen J; Roth, Dana S; Roulston, T'ai H; Rousseau, Laurent; Rubio, André V; Ruel, Jean-Claude; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Sam, Katerina; Samnegård, Ulrika; Santana, Joana; Santos, Xavier; Savage, Jade; Schellhorn, Nancy A; Schilthuizen, Menno; Schmiedel, Ute; Schmitt, Christine B; Schon, Nicole L; Schüepp, Christof; Schumann, Katharina; Schweiger, Oliver; Scott, Dawn M; Scott, Kenneth A; Sedlock, Jodi L; Seefeldt, Steven S; Shahabuddin, Ghazala; Shannon, Graeme; Sheil, Douglas; Sheldon, Frederick H; Shochat, Eyal; Siebert, Stefan J; Silva, Fernando A B; Simonetti, Javier A; Slade, Eleanor M; Smith, Jo; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Soto Quiroga, Grimaldo; St-Laurent, Martin-Hugues; Starzomski, Brian M; Stefanescu, Constanti; Steffan-Dewenter, Ingolf; Stouffer, Philip C; Stout, Jane C; Strauch, Ayron M; Struebig, Matthew J; Su, Zhimin; Suarez-Rubio, Marcela; Sugiura, Shinji; Summerville, Keith S; Sung, Yik-Hei; Sutrisno, Hari; Svenning, Jens-Christian; Teder, Tiit; Threlfall, Caragh G; Tiitsaar, Anu; Todd, Jacqui H; Tonietto, Rebecca K; Torre, Ignasi; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Uehara-Prado, Marcio; Urbina-Cardona, Nicolas; Vallan, Denis; Vanbergen, Adam J; Vasconcelos, Heraldo L; Vassilev, Kiril; Verboven, Hans A F; Verdasca, Maria João; Verdú, José R; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Virgilio, Massimiliano; Vu, Lien Van; Waite, Edward M; Walker, Tony R; Wang, Hua-Feng; Wang, Yanping; Watling, James I; Weller, Britta; Wells, Konstans; Westphal, Catrin; Wiafe, Edward D; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Wolters, Volkmar; Woodcock, Ben A; Wu, Jihua; Wunderle, Joseph M; Yamaura, Yuichi; Yoshikura, Satoko; Yu, Douglas W; Zaitsev, Andrey S; Zeidler, Juliane; Zou, Fasheng; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

    The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of

  3. Dynamic preload indicators fail to predict fluid responsiveness in open-chest conditions

    NARCIS (Netherlands)

    de Waal, Eric E. C.; Rex, Steffen; Kruitwagen, Cas L. J. J.; Kalkman, Cor J.; Buhre, Wolfgang F.

    Objective: Dynamic preload indicators like pulse pressure variation (PPV) and stroke volume variation (SVV) are increasingly being used for optimizing cardiac preload since they have been demonstrated to predict fluid responsiveness in a variety of perioperative settings. However, in open-chest

  4. Dexamethasone-suppressed cortisol awakening response predicts treatment outcome in posttraumatic stress disorder

    NARCIS (Netherlands)

    Nijdam, M. J.; van Amsterdam, J. G. C.; Gersons, B. P. R.; Olff, M.

    2015-01-01

    Posttraumatic stress disorder (PTSD) has been associated with several alterations in the neuroendocrine system, including enhanced cortisol suppression in response to the dexamethasone suppression test. The aim of this study was to examine whether specific biomarkers of PTSD predict treatment

  5. Predicting Dynamic Response of Structures under Earthquake Loads Using Logical Analysis of Data

    Directory of Open Access Journals (Sweden)

    Ayman Abd-Elhamed

    2018-04-01

    Full Text Available In this paper, logical analysis of data (LAD is used to predict the seismic response of building structures employing the captured dynamic responses. In order to prepare the data, computational simulations using a single degree of freedom (SDOF building model under different ground motion records are carried out. The selected excitation records are real and of different peak ground accelerations (PGA. The sensitivity of the seismic response in terms of displacements of floors to the variation in earthquake characteristics, such as soil class, characteristic period, and time step of records, peak ground displacement, and peak ground velocity, have also been considered. The dynamic equation of motion describing the building model and the applied earthquake load are presented and solved incrementally using the Runge-Kutta method. LAD then finds the characteristic patterns which lead to forecast the seismic response of building structures. The accuracy of LAD is compared to that of an artificial neural network (ANN, since the latter is the most known machine learning technique. Based on the conducted study, the proposed LAD model has been proven to be an efficient technique to learn, simulate, and blindly predict the dynamic response behaviour of building structures subjected to earthquake loads.

  6. Fluoride therapy for osteoporosis: characterization of the skeletal response by serial measurements of serum alkaline phosphatase activity.

    Science.gov (United States)

    Farley, S M; Wergedal, J E; Smith, L C; Lundy, M W; Farley, J R; Baylink, D J

    1987-03-01

    Optimum use of fluoride therapy for osteoporosis requires a sensitive and convenient index of the skeletal response to fluoride. Since previous studies had shown that serum alkaline phosphatase activity (SALP) was increased in response to fluoride therapy, we examined serial measurements of SALP in 53 osteoporotics treated with 66 to 110 mg of sodium fluoride (NaF) for 12 to 91 months. SALP was increased in 87% of the subjects during therapy with fluoride. The increase in SALP was thought to reflect the osteogenic action of fluoride based on the findings that SALP correlated with both trabecular bone area (r = .81, P less than .001) and osteoid length (r = .67, P less than .01) in iliac crest biopsies, predicted increased bone density on spinal radiographs in response to fluoride therapy with an 87% accuracy, and predicted decreased back pain in response to fluoride with a 91% accuracy. In addition, the SALP response to fluoride was seen earlier than other therapeutic responses as indicated by the findings that the tau 1/2 for the SALP response (ie, time for 1/2 of the patients to show a significant response) was significantly less (1.2 +/- 0.3 yr) than that for the pain response (1.6 +/- 0.3 yr, P less than .05) or that for the radiographic response (3.7 +/- 0.5 yr, P less than .001). Although most patients responded to fluoride with an increase in SALP, evaluation of the kinetics of the SALP response to fluoride revealed marked interpatient variation.(ABSTRACT TRUNCATED AT 250 WORDS)

  7. Clinical application of a systems model of apoptosis execution for the prediction of colorectal cancer therapy responses and personalisation of therapy

    LENUS (Irish Health Repository)

    Hector, S.

    2012-06-15

    Objective Key to the clinical management of colorectal cancer is identifying tools which aid in assessing patient prognosis and determining more effective and personalised treatment strategies. We evaluated whether an experimental systems biology strategy which analyses the susceptibility of cancer cells to undergo caspase activation can be exploited to predict patient responses to 5-fluorouracil-based chemotherapy and to case-specifically identify potential alternative targeted treatments to reactivate apoptosis. \\r\

  8. Getting the Most out of Audience Response Systems: Predicting Student Reactions

    Science.gov (United States)

    Trew, Jennifer L.; Nelsen, Jacqueline L.

    2012-01-01

    Audience response systems (ARS) are effective tools for improving learning outcomes and student engagement in large undergraduate classes. However, if students do not accept ARS and do not find them to be useful, ARS may be less effective. Predicting and improving student perceptions of ARS may help to ensure positive outcomes. The present study…

  9. Predicting Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer with Textural Features Derived from Pretreatment F-18-FDG PET/CT Imaging

    NARCIS (Netherlands)

    Beukinga, Roelof J.; Hulshoff, Jan B.; van Dijk, Lisanne V.; Muijs, Christina T.; Burgerhof, Johannes G. M.; Kats-Ugurlu, Gursah; Slart, Riemer H. J. A.; Slump, Cornelis H.; Mul, Veronique E. M.; Plukker, John Th. M.

    Adequate prediction of tumor response to neoadjuvant chemoradiotherapy (nCRT) in esophageal cancer (EC) patients is important in a more personalized treatment. The current best clinical method to predict pathologic complete response is SUVmax in F-18-FDG PET/ CT imaging. To improve the prediction of

  10. MR Imaging in Monitoring and Predicting Treatment Response in Multiple Sclerosis.

    Science.gov (United States)

    Río, Jordi; Auger, Cristina; Rovira, Àlex

    2017-05-01

    MR imaging is the most sensitive tool for identifying lesions in patients with multiple sclerosis (MS). MR imaging has also acquired an essential role in the detection of complications arising from these treatments and in the assessment and prediction of efficacy. In the future, other radiological measures that have shown prognostic value may be incorporated within the models for predicting treatment response. This article examines the role of MR imaging as a prognostic tool in patients with MS and the recommendations that have been proposed in recent years to monitor patients who are treated with disease-modifying drugs. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Fourier and non-Fourier bio-heat transfer models to predict ex vivo temperature response to focused ultrasound heating

    Science.gov (United States)

    Li, Chenghai; Miao, Jiaming; Yang, Kexin; Guo, Xiasheng; Tu, Juan; Huang, Pintong; Zhang, Dong

    2018-05-01

    Although predicting temperature variation is important for designing treatment plans for thermal therapies, research in this area is yet to investigate the applicability of prevalent thermal conduction models, such as the Pennes equation, the thermal wave model of bio-heat transfer, and the dual phase lag (DPL) model. To address this shortcoming, we heated a tissue phantom and ex vivo bovine liver tissues with focused ultrasound (FU), measured the temperature response, and compared the results with those predicted by these models. The findings show that, for a homogeneous-tissue phantom, the initial temperature increase is accurately predicted by the Pennes equation at the onset of FU irradiation, although the prediction deviates from the measured temperature with increasing FU irradiation time. For heterogeneous liver tissues, the predicted response is closer to the measured temperature for the non-Fourier models, especially the DPL model. Furthermore, the DPL model accurately predicts the temperature response in biological tissues because it increases the phase lag, which characterizes microstructural thermal interactions. These findings should help to establish more precise clinical treatment plans for thermal therapies.

  12. Thermally activated post-glitch response of the neutron star inner crust and core. I. Theory

    Energy Technology Data Exchange (ETDEWEB)

    Link, Bennett, E-mail: link@physics.montana.edu [Department of Physics, Montana State University, Bozeman, MT 59717 (United States)

    2014-07-10

    Pinning of superfluid vortices is predicted to prevail throughout much of a neutron star. Based on the idea of Alpar et al., I develop a description of the coupling between the solid and liquid components of a neutron star through thermally activated vortex slippage, and calculate the response to a spin glitch. The treatment begins with a derivation of the vortex velocity from the vorticity equations of motion. The activation energy for vortex slippage is obtained from a detailed study of the mechanics and energetics of vortex motion. I show that the 'linear creep' regime introduced by Alpar et al. and invoked in fits to post-glitch response is not realized for physically reasonable parameters, a conclusion that strongly constrains the physics of a post-glitch response through thermal activation. Moreover, a regime of 'superweak pinning', crucial to the theory of Alpar et al. and its extensions, is probably precluded by thermal fluctuations. The theory given here has a robust conclusion that can be tested by observations: for a glitch in the spin rate of magnitude Δν, pinning introduces a delay in the post-glitch response time. The delay time is t{sub d} = 7(t{sub sd}/10{sup 4} yr)((Δν/ν)/10{sup –6}) d, where t{sub sd} is the spin-down age; t{sub d} is typically weeks for the Vela pulsar and months in older pulsars, and is independent of the details of vortex pinning. Post-glitch response through thermal activation cannot occur more quickly than this timescale. Quicker components of post-glitch response, as have been observed in some pulsars, notably, the Vela pulsar, cannot be due to thermally activated vortex motion but must represent a different process, such as drag on vortices in regions where there is no pinning. I also derive the mutual friction force for a pinned superfluid at finite temperature for use in other studies of neutron star hydrodynamics.

  13. Parametric response mapping of dynamic CT for predicting intrahepatic recurrence of hepatocellular carcinoma after conventional transcatheter arterial chemoembolization

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Seung Joon; Kim, Hyung Sik [Gachon University Gil Hospital, Department of Radiology, Incheon (Korea, Republic of); Kim, Jonghoon [Sungkyunkwan University, Department of Electronic Electrical and Computer Engineering, Suwon (Korea, Republic of); Seo, Jongbum [Yonsei University, Department of Biomedical Engineering, Wonju (Korea, Republic of); Lee, Jong-min [Hanyang University, Department of Biomedical Engineering, Seoul (Korea, Republic of); Park, Hyunjin [Sungkyunwkan University, School of Electronic and Electrical Engineering, Suwon (Korea, Republic of)

    2016-01-15

    The aim of our study was to determine the diagnostic value of a novel image analysis method called parametric response mapping (PRM) for prediction of intrahepatic recurrence of hepatocellular carcinoma (HCC) treated with conventional transcatheter arterial chemoembolization (TACE). This retrospective study was approved by the IRB. We recruited 55 HCC patients who achieved complete remission (CR) after TACE and received longitudinal multiphasic liver computed tomography (CT). The patients fell into two groups: the recurrent tumour group (n = 29) and the non-recurrent tumour group (n = 26). We applied the PRM analysis to see if this technique could distinguish between the two groups. The results of the PRM analysis were incorporated into a prediction algorithm. We retrospectively removed data from the last time point and attempted to predict the response to therapy of the removed data. The PRM analysis was able to distinguish between the non-recurrent and recurrent groups successfully. The prediction algorithm detected response to therapy with an area under the curve (AUC) of 0.76, while the manual approach had AUC 0.64. Adopting PRM analysis can potentially distinguish between recurrent and non-recurrent HCCs and allow for prediction of response to therapy after TACE. (orig.)

  14. Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction.

    Science.gov (United States)

    Baker, Christopher M; Gordon, Ascelin; Bode, Michael

    2017-04-01

    Introducing a new or extirpated species to an ecosystem is risky, and managers need quantitative methods that can predict the consequences for the recipient ecosystem. Proponents of keystone predator reintroductions commonly argue that the presence of the predator will restore ecosystem function, but this has not always been the case, and mathematical modeling has an important role to play in predicting how reintroductions will likely play out. We devised an ensemble modeling method that integrates species interaction networks and dynamic community simulations and used it to describe the range of plausible consequences of 2 keystone-predator reintroductions: wolves (Canis lupus) to Yellowstone National Park and dingoes (Canis dingo) to a national park in Australia. Although previous methods for predicting ecosystem responses to such interventions focused on predicting changes around a given equilibrium, we used Lotka-Volterra equations to predict changing abundances through time. We applied our method to interaction networks for wolves in Yellowstone National Park and for dingoes in Australia. Our model replicated the observed dynamics in Yellowstone National Park and produced a larger range of potential outcomes for the dingo network. However, we also found that changes in small vertebrates or invertebrates gave a good indication about the potential future state of the system. Our method allowed us to predict when the systems were far from equilibrium. Our results showed that the method can also be used to predict which species may increase or decrease following a reintroduction and can identify species that are important to monitor (i.e., species whose changes in abundance give extra insight into broad changes in the system). Ensemble ecosystem modeling can also be applied to assess the ecosystem-wide implications of other types of interventions including assisted migration, biocontrol, and invasive species eradication. © 2016 Society for Conservation Biology.

  15. Does early response to intravenous glucocorticoids predict the final outcome in patients with moderate-to-severe and active Graves' orbitopathy?

    NARCIS (Netherlands)

    Bartalena, L.; Veronesi, G.; Krassas, G. E.; Wiersinga, W. M.; Marcocci, C.; Marinò, M.; Salvi, M.; Daumerie, C.; Bournaud, C.; Stahl, M.; Sassi, L.; Azzolini, C.; Boboridis, K. G.; Mourits, M. P.; Soeters, M. R.; Baldeschi, L.; Nardi, M.; Currò, N.; Boschi, A.; Bernard, M.; von Arx, G.; Perros, P.; Kahaly, G. J.

    2017-01-01

    Intravenous glucocorticoids (ivGCs) given as 12-weekly infusions are the first-line treatment for moderate-to-severe and active Graves' orbitopathy (GO), but they are not always effective. In this study, we evaluated whether response at 6 weeks correlated with outcomes at 12 (end of intervention)

  16. Activity limitations predict health care expenditures in the general population in Belgium.

    Science.gov (United States)

    Van der Heyden, Johan; Van Oyen, Herman; Berger, Nicolas; De Bacquer, Dirk; Van Herck, Koen

    2015-03-19

    Disability and chronic conditions both have an impact on health expenditures and although they are conceptually related, they present different dimensions of ill-health. Recent concepts of disability combine a biological understanding of impairment with the social dimension of activity limitation and resulted in the development of the Global Activity Limitation Indicator (GALI). This paper reports on the predictive value of the GALI on health care expenditures in relation to the presence of chronic conditions. Data from the Belgian Health Interview Survey 2008 were linked with data from the compulsory national health insurance (n = 7,286). The effect of activity limitation on health care expenditures was assessed via cost ratios from multivariate linear regression models. To study the factors contributing to the difference in health expenditure between persons with and without activity limitations, the Blinder-Oaxaca decomposition method was used. Activity limitations are a strong determinant of health care expenditures. People with severe activity limitations (5.1%) accounted for 16.9% of the total health expenditure, whereas those without activity limitations (79.0%), were responsible for 51.5% of the total health expenditure. These observed differences in health care expenditures can to some extent be explained by chronic conditions, but activity limitations also contribute substantially to higher health care expenditures in the absence of chronic conditions (cost ratio 2.46; 95% CI 1.74-3.48 for moderate and 4.45; 95% CI 2.47-8.02 for severe activity limitations). The association between activity limitation and health care expenditures is stronger for reimbursed health care costs than for out-of-pocket payments. In the absence of chronic conditions, activity limitations appear to be an important determinant of health care expenditures. To make projections on health care expenditures, routine data on activity limitations are essential and complementary to data

  17. Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries

    NARCIS (Netherlands)

    Nistor, Nicolae; Dascalu, Mihai; Stavarache, Lucia Larise; Serafin, Yvonne; Trausan-Matu, Stefan

    2016-01-01

    Nistor, N., Dascalu, M., Stavarache, L.L., Serafin, Y., & Trausan-Matu, S. (2015). Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries. In G. Conole, T. Klobucar, C. Rensing, J. Konert & É. Lavoué (Eds.), 10th European Conf. on Technology Enhanced

  18. Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases.

    Science.gov (United States)

    Liang, He-Yue; Huang, Ya-Qin; Yang, Zhao-Xia; Ying-Ding; Zeng, Meng-Su; Rao, Sheng-Xiang

    2016-07-01

    To determine if magnetic resonance imaging (MRI) histogram analyses can help predict response to chemotherapy in patients with colorectal hepatic metastases by using response evaluation criteria in solid tumours (RECIST1.1) as the reference standard. Standard MRI including diffusion-weighted imaging (b=0, 500 s/mm(2)) was performed before chemotherapy in 53 patients with colorectal hepatic metastases. Histograms were performed for apparent diffusion coefficient (ADC) maps, arterial, and portal venous phase images; thereafter, mean, percentiles (1st, 10th, 50th, 90th, 99th), skewness, kurtosis, and variance were generated. Quantitative histogram parameters were compared between responders (partial and complete response, n=15) and non-responders (progressive and stable disease, n=38). Receiver operator characteristics (ROC) analyses were further analyzed for the significant parameters. The mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, 99th percentile of the ADC maps were significantly lower in responding group than that in non-responding group (p=0.000-0.002) with area under the ROC curve (AUCs) of 0.76-0.82. The histogram parameters of arterial and portal venous phase showed no significant difference (p>0.05) between the two groups. Histogram-derived parameters for ADC maps seem to be a promising tool for predicting response to chemotherapy in patients with colorectal hepatic metastases. • ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases. • Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response. • MR enhancement histogram analyses are not reliable to predict response.

  19. Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities

    International Nuclear Information System (INIS)

    Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

    2016-01-01

    Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM_1_0) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM_1_0-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM_1_0-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM_1_0 concentration and green space per capita could best explain the heterogeneity in PM_1_0-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. - Highlights: • The heterogeneity was examined in PM_1_0-mortality associations among Chinese cities. • Temperature, PM_1_0 and green space could best explain the heterogeneity. • PM_1_0-mortality associations were predicted for 73 Chinese cities. - This study provides a practical way to assess exposure-response associations and evaluate the burden of mortality in areas with insufficient data.

  20. Baseline {sup 18}F-FDG PET image-derived parameters for therapy response prediction in oesophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Hatt, Mathieu; Visvikis, Dimitris; Cheze-le Rest, Catherine [CHU Morvan, LaTIM, INSERM U650, Brest (France); Pradier, Olivier [CHU Morvan, LaTIM, INSERM U650, Brest (France); CHU Morvan, Department of Radiotherapy, Brest (France)

    2011-09-15

    The objectives of this study were to investigate the predictive value of tumour measurements on 2-deoxy-2-[{sup 18}F]fluoro-D-glucose ({sup 18}F-FDG) positron emission tomography (PET) pretreatment scan regarding therapy response in oesophageal cancer and to evaluate the impact of tumour delineation strategies. Fifty patients with oesophageal cancer treated with concomitant radiochemotherapy between 2004 and 2008 were retrospectively considered and classified as complete, partial or non-responders (including stable and progressive disease) according to Response Evaluation Criteria in Solid Tumors (RECIST). The classification of partial and complete responders was confirmed by biopsy. Tumours were delineated on the {sup 18}F-FDG pretreatment scan using an adaptive threshold and the automatic fuzzy locally adaptive Bayesian (FLAB) methodologies. Several parameters were then extracted: maximum and peak standardized uptake value (SUV), tumour longitudinal length (TL) and volume (TV), SUV{sub mean}, and total lesion glycolysis (TLG = TV x SUV{sub mean}). The correlation between each parameter and response was investigated using Kruskal-Wallis tests, and receiver-operating characteristic methodology was used to assess performance of the parameters to differentiate patients. Whereas commonly used parameters such as SUV measurements were not significant predictive factors of the response, parameters related to tumour functional spatial extent (TL, TV, TLG) allowed significant differentiation of all three groups of patients, independently of the delineation strategy, and could identify complete and non-responders with sensitivity above 75% and specificity above 85%. A systematic although not statistically significant trend was observed regarding the hierarchy of the delineation methodologies and the parameters considered, with slightly higher predictive value obtained with FLAB over adaptive thresholding, and TLG over TV and TL. TLG is a promising predictive factor of

  1. The effects of incidentally learned temporal and spatial predictability on response times and visual fixations during target detection and discrimination.

    Directory of Open Access Journals (Sweden)

    Melissa R Beck

    Full Text Available Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1 different time intervals between a response and the next target; and 2 possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1 and target discrimination (Experiment 2 were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations.

  2. Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.

    Science.gov (United States)

    Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

    2015-01-01

    Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature - integrin β4 (ITGB4) - was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.

  3. Sexual selection predicts advancement of avian spring migration in response to climate change

    DEFF Research Database (Denmark)

    Spottiswoode, Claire N; Tøttrup, Anders P; Coppack, Timothy

    2006-01-01

    Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We...... suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species...... in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting...

  4. Implicit activation of the aging stereotype influences effort-related cardiovascular response: The role of incentive.

    Science.gov (United States)

    Zafeiriou, Athina; Gendolla, Guido H E

    2017-09-01

    Based on previous research on implicit effects on effort-related cardiovascular response and evidence that aging is associated with cognitive difficulties, we tested whether the mere activation of the aging stereotype can systematically influence young individuals' effort-mobilization during cognitive performance. Young participants performed an objectively difficult short-term memory task during which they processed elderly vs. youth primes and expected low vs. high incentive for success. When participants processed elderly primes during the task, we expected cardiovascular response to be weak in the low-incentive condition and strong in the high-incentive condition. Unaffected by incentive, effort in the youth-prime condition should fall in between the two elderly-prime cells. Effects on cardiac pre-ejection period (PEP) and heart rate (HR) largely supported these predictions. The present findings show for the first time that the mere activation of the aging stereotype can systematically influence effort mobilization during cognitive performance-even in young adults. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Can biomass responses to warming at plant to ecosystem levels be predicted by leaf-level responses?

    Science.gov (United States)

    Xia, J.; Shao, J.; Zhou, X.; Yan, W.; Lu, M.

    2015-12-01

    Global warming has the profound impacts on terrestrial C processes from leaf to ecosystem scales, potentially feeding back to climate dynamics. Although numerous studies had investigated the effects of warming on C processes from leaf to plant and ecosystem levels, how leaf-level responses to warming scale up to biomass responses at plant, population, and community levels are largely unknown. In this study, we compiled a dataset from 468 papers at 300 experimental sites and synthesized the warming effects on leaf-level parameters, and plant, population and ecosystem biomass. Our results showed that responses of plant biomass to warming mainly resulted from the changed leaf area rather than the altered photosynthetic capacity. The response of ecosystem biomass to warming was weaker than those of leaf area and plant biomass. However, the scaling functions from responses of leaf area to plant biomass to warming were different in diverse forest types, but functions were similar in non-forested biomes. In addition, it is challenging to scale the biomass responses from plant up to ecosystem. These results indicated that leaf area might be the appropriate index for plant biomass response to warming, and the interspecific competition might hamper the scaling of the warming effects on plant and ecosystem levels, suggesting that the acclimation capacity of plant community should be incorporated into land surface models to improve the prediction of climate-C cycle feedback.

  6. Neural activity in the hippocampus predicts individual visual short-term memory capacity.

    Science.gov (United States)

    von Allmen, David Yoh; Wurmitzer, Karoline; Martin, Ernst; Klaver, Peter

    2013-07-01

    Although the hippocampus had been traditionally thought to be exclusively involved in long-term memory, recent studies raised controversial explanations why hippocampal activity emerged during short-term memory tasks. For example, it has been argued that long-term memory processes might contribute to performance within a short-term memory paradigm when memory capacity has been exceeded. It is still unclear, though, whether neural activity in the hippocampus predicts visual short-term memory (VSTM) performance. To investigate this question, we measured BOLD activity in 21 healthy adults (age range 19-27 yr, nine males) while they performed a match-to-sample task requiring processing of object-location associations (delay period  =  900 ms; set size conditions 1, 2, 4, and 6). Based on individual memory capacity (estimated by Cowan's K-formula), two performance groups were formed (high and low performers). Within whole brain analyses, we found a robust main effect of "set size" in the posterior parietal cortex (PPC). In line with a "set size × group" interaction in the hippocampus, a subsequent Finite Impulse Response (FIR) analysis revealed divergent hippocampal activation patterns between performance groups: Low performers (mean capacity  =  3.63) elicited increased neural activity at set size two, followed by a drop in activity at set sizes four and six, whereas high performers (mean capacity  =  5.19) showed an incremental activity increase with larger set size (maximal activation at set size six). Our data demonstrated that performance-related neural activity in the hippocampus emerged below capacity limit. In conclusion, we suggest that hippocampal activity reflected successful processing of object-location associations in VSTM. Neural activity in the PPC might have been involved in attentional updating. Copyright © 2013 Wiley Periodicals, Inc.

  7. A rapid method of predicting radiocaesium concentrations in sheep from activity levels in faeces

    International Nuclear Information System (INIS)

    McGee, E.J.; Synnott, H.J.; Colgan, P.A.; Keatinge, M.J.

    1994-01-01

    The use of faecal samples taken from sheep flocks as a means of predicting radiocaesium concentrations in live animals was studied. Radiocaesium levels in 1726 sheep from 29 flocks were measured using in vivo techniques and a single faecal sample taken from each flock was also analysed. A highly significant relationship was found to exist between mean flock activity and activity in the corresponding faecal samples. Least-square regression yielded a simple model for predicting mean flock radiocaesium concentrations based on activity levels in faecal samples. A similar analysis of flock maxima and activity levels in faeces provides an alternative model for predicting the expected within-flock maximum radiocaesium concentration. (Author)

  8. HSP60 may predict good pathological response to neoadjuvant chemoradiotherapy in bladder cancer

    International Nuclear Information System (INIS)

    Urushibara, Masayasu; Kageyama, Yukio; Akashi, Takumi; Otsuka, Yukihiro; Takizawa, Touichiro; Koike, Morio; Kihara, Kazunori

    2007-01-01

    Heat shock proteins (HSPs) play crucial roles in cellular responses to stressful conditions. Expression of HSPs in invasive or high-risk superficial bladder cancer was investigated to identify whether HSPs predict pathological response to neoadjuvant chemoradiotherapy (CRT). Immunohistochemistry was used to assess expression levels of HSP27, HSP60, HSP70, HSP90 and p53 in 54 patients with invasive or high-risk superficial bladder cancer, prior to low-dose neoadjuvant CRT, followed by radical or partial cystectomy. Patients were classified into two groups (good or poor responders) depending on pathological response to CRT, which was defined as the proportion of morphological therapeutic changes in surgical specimens. Good responders showed morphological therapeutic changes in two-thirds or more of tumor tissues. In contrast, poor responders showed changes in less than two-thirds of tumor tissues. Using a multivariate analysis, positive HSP60 expression prior to CRT was found to be marginally associated with good pathological response to CRT (P=0.0564). None of clinicopathological factors was associated with HSP60 expression level. In the good pathological responders, the 5-year cause-specific survival was 88%, which was significantly better than survival in the poor responders (51%) (P=0.0373). Positive HSP60 expression prior to CRT may predict good pathological response to low-dose neoadjuvant CRT in invasive or high-risk superficial bladder cancer. (author)

  9. Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils.

    Science.gov (United States)

    Daynac, Mathieu; Cortes-Cabrera, Alvaro; Prieto, Jose M

    2015-01-01

    Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity. Methods. The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extracted from NCCLS compliant works. The fast artificial neural networks (FANN) software was used and the output data reflected the antimicrobial activity of these EOs against four common pathogens: Staphylococcus aureus, Escherichia coli, Candida albicans, and Clostridium perfringens as measured by standardised disk diffusion assays. Results. ANNs were able to predict >70% of the antimicrobial activities within a 10 mm maximum error range. Similarly, ANNs were able to predict 2 or 3 different bioactivities at the same time. The accuracy of the prediction was only limited by the inherent errors of the popular antimicrobial disk susceptibility test and the nature of the pathogens. Conclusions. ANNs can be reliable, fast, and cheap tools for the prediction of the antimicrobial activity of EOs thus improving their use in CAM.

  10. Prediction of Vertical-Plane Wave Loading and Ship Responses in High Seas

    DEFF Research Database (Denmark)

    Wang, Z.; Xia, J.; Jensen, Jørgen Juncher

    2000-01-01

    The non-linearities in wave- and slamming-induced rigid-body motions and structural responses of ships such as heave, pitch and vertical bending moments are consistently investigated based on a rational time-domain strip method. A hydrodynamic model for predicting sectional green water force is a...

  11. A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions.

    Directory of Open Access Journals (Sweden)

    Francesco Iorio

    Full Text Available We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound. This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells-consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel.

  12. Role of MRI in osteosarcoma for evaluation and prediction of chemotherapy response: correlation with histological necrosis

    Energy Technology Data Exchange (ETDEWEB)

    Bajpai, Jyoti; Bakhshi, Sameer [Dr. B. R. A. Institute Rotary Cancer Hospital, Department of Medical Oncology, All India Institute of Medical Sciences, New Delhi (India); Gamnagatti, Shivanand [All India Institute of Medical Sciences, Department of Radiodiagnosis, New Delhi (India); Kumar, Rakesh; Malhotra, Arun [All India Institute of Medical Sciences, Department of Nuclear Medicine, New Delhi (India); Sreenivas, Vishnubhatla [All India Institute of Medical Sciences, Department of Biostatistics, New Delhi (India); Sharma, Mehar Chand; Safaya, Rajni [All India Institute of Medical Sciences, Department of Pathology, New Delhi (India); Khan, Shah Alam; Rastogi, Shishir [All India Institute of Medical Sciences, Department of Orthopedics, New Delhi (India)

    2011-04-15

    Histological necrosis, the current standard for response evaluation in osteosarcoma, is attainable after neoadjuvant chemotherapy. To establish the role of surrogate markers of response prediction and evaluation using MRI in the early phases of the disease. Thirty-one treatment-naive osteosarcoma patients received three cycles of neoadjuvant chemotherapy followed by surgery during 2006-2008. All patients underwent baseline and post-chemotherapy conventional, diffusion-weighted and dynamic contrast-enhanced MRI. Taking histological response (good response {>=}90% necrosis) as the reference standard, various parameters of MRI were compared to it. A tumor was considered ellipsoidal; volume, average tumor plane and its relative value (average tumor plane relative/body surface area) was calculated using the standard formula for ellipse. Receiver operating characteristic curves were generated to assess best threshold and predictability. After deriving thresholds for each parameter in univariable analysis, multivariable analysis was carried out. Both pre-and post-chemotherapy absolute and relative-size parameters correlated well with necrosis. Apparent diffusion coefficient did not correlate with necrosis; however, on adjusting for volume, significant correlation was found. Thus, we could derive a new parameter: diffusion per unit volume. In osteosarcoma, chemotherapy response can be predicted and evaluated by conventional and diffusion-weighted MRI early in the disease course and it correlates well with necrosis. Further, newly derived parameter diffusion per unit volume appears to be a sensitive substitute for response evaluation in osteosarcoma. (orig.)

  13. Role of MRI in osteosarcoma for evaluation and prediction of chemotherapy response: correlation with histological necrosis

    International Nuclear Information System (INIS)

    Bajpai, Jyoti; Bakhshi, Sameer; Gamnagatti, Shivanand; Kumar, Rakesh; Malhotra, Arun; Sreenivas, Vishnubhatla; Sharma, Mehar Chand; Safaya, Rajni; Khan, Shah Alam; Rastogi, Shishir

    2011-01-01

    Histological necrosis, the current standard for response evaluation in osteosarcoma, is attainable after neoadjuvant chemotherapy. To establish the role of surrogate markers of response prediction and evaluation using MRI in the early phases of the disease. Thirty-one treatment-naive osteosarcoma patients received three cycles of neoadjuvant chemotherapy followed by surgery during 2006-2008. All patients underwent baseline and post-chemotherapy conventional, diffusion-weighted and dynamic contrast-enhanced MRI. Taking histological response (good response ≥90% necrosis) as the reference standard, various parameters of MRI were compared to it. A tumor was considered ellipsoidal; volume, average tumor plane and its relative value (average tumor plane relative/body surface area) was calculated using the standard formula for ellipse. Receiver operating characteristic curves were generated to assess best threshold and predictability. After deriving thresholds for each parameter in univariable analysis, multivariable analysis was carried out. Both pre-and post-chemotherapy absolute and relative-size parameters correlated well with necrosis. Apparent diffusion coefficient did not correlate with necrosis; however, on adjusting for volume, significant correlation was found. Thus, we could derive a new parameter: diffusion per unit volume. In osteosarcoma, chemotherapy response can be predicted and evaluated by conventional and diffusion-weighted MRI early in the disease course and it correlates well with necrosis. Further, newly derived parameter diffusion per unit volume appears to be a sensitive substitute for response evaluation in osteosarcoma. (orig.)

  14. Visual-induced expectations modulate auditory cortical responses

    Directory of Open Access Journals (Sweden)

    Virginie evan Wassenhove

    2015-02-01

    Full Text Available Active sensing has important consequences on multisensory processing (Schroeder et al. 2010. Here, we asked whether in the absence of saccades, the position of the eyes and the timing of transient colour changes of visual stimuli could selectively affect the excitability of auditory cortex by predicting the where and the when of a sound, respectively. Human participants were recorded with magnetoencephalography (MEG while maintaining the position of their eyes on the left, right, or centre of the screen. Participants counted colour changes of the fixation cross while neglecting sounds which could be presented to the left, right or both ears. First, clear alpha power increases were observed in auditory cortices, consistent with participants’ attention directed to visual inputs. Second, colour changes elicited robust modulations of auditory cortex responses (when prediction seen as ramping activity, early alpha phase-locked responses, and enhanced high-gamma band responses in the contralateral side of sound presentation. Third, no modulations of auditory evoked or oscillatory activity were found to be specific to eye position. Altogether, our results suggest that visual transience can automatically elicit a prediction of when a sound will occur by changing the excitability of auditory cortices irrespective of the attended modality, eye position or spatial congruency of auditory and visual events. To the contrary, auditory cortical responses were not significantly affected by eye position suggesting that where predictions may require active sensing or saccadic reset to modulate auditory cortex responses, notably in the absence of spatial orientation to sounds.

  15. Immunological tumor status may predict response to neoadjuvant chemotherapy and outcome after radical cystectomy in bladder cancer.

    Science.gov (United States)

    Tervahartiala, Minna; Taimen, Pekka; Mirtti, Tuomas; Koskinen, Ilmari; Ecke, Thorsten; Jalkanen, Sirpa; Boström, Peter J

    2017-10-04

    Bladder cancer (BC) is the ninth most common cancer worldwide. Radical cystectomy (RC) with neoadjuvant chemotherapy (NAC) is recommended for muscle-invasive BC. The challenge of the neoadjuvant approach relates to challenges in selection of patients to chemotherapy that are likely to respond to the treatment. To date, there are no validated molecular markers or baseline clinical characteristics to identify these patients. Different inflammatory markers, including tumor associated macrophages with their plastic pro-tumorigenic and anti-tumorigenic functions, have extensively been under interests as potential prognostic and predictive biomarkers in different cancer types. In this immunohistochemical study we evaluated the predictive roles of three immunological markers, CD68, MAC387, and CLEVER-1, in response to NAC and outcome of BC. 41% of the patients had a complete response (pT0N0) to NAC. Basic clinicopathological variables did not predict response to NAC. In contrast, MAC387 + cells and CLEVER-1 + macrophages associated with poor NAC response, while CLEVER-1 + vessels associated with more favourable response to NAC. Higher counts of CLEVER-1 + macrophages associated with poorer overall survival and CD68 + macrophages seem to have an independent prognostic value in BC patients treated with NAC. Our findings point out that CD68, MAC387, and CLEVER-1 may be useful prognostic and predictive markers in BC.

  16. Discrimination of amygdala response predicts future separation anxiety in youth with early deprivation.

    Science.gov (United States)

    Green, Shulamite A; Goff, Bonnie; Gee, Dylan G; Gabard-Durnam, Laurel; Flannery, Jessica; Telzer, Eva H; Humphreys, Kathryn L; Louie, Jennifer; Tottenham, Nim

    2016-10-01

    Significant disruption in caregiving is associated with increased internalizing symptoms, most notably heightened separation anxiety symptoms during childhood. It is also associated with altered functional development of the amygdala, a neurobiological correlate of anxious behavior. However, much less is known about how functional alterations of amygdala predict individual differences in anxiety. Here, we probed amygdala function following institutional caregiving using very subtle social-affective stimuli (trustworthy and untrustworthy faces), which typically result in large differences in amygdala signal, and change in separation anxiety behaviors over a 2-year period. We hypothesized that the degree of differentiation of amygdala signal to trustworthy versus untrustworthy face stimuli would predict separation anxiety symptoms. Seventy-four youths mean (SD) age = 9.7 years (2.64) with and without previous institutional care, who were all living in families at the time of testing, participated in an fMRI task designed to examine differential amygdala response to trustworthy versus untrustworthy faces. Parents reported on their children's separation anxiety symptoms at the time of scan and again 2 years later. Previous institutional care was associated with diminished amygdala signal differences and behavioral differences to the contrast of untrustworthy and trustworthy faces. Diminished differentiation of these stimuli types predicted more severe separation anxiety symptoms 2 years later. Older age at adoption was associated with diminished differentiation of amygdala responses. A history of institutional care is associated with reduced differential amygdala responses to social-affective cues of trustworthiness that are typically exhibited by comparison samples. Individual differences in the degree of amygdala differential responding to these cues predict the severity of separation anxiety symptoms over a 2-year period. These findings provide a biological

  17. Self-responsibility predicts the successful outcome of coronary artery bypass surgery

    Directory of Open Access Journals (Sweden)

    C. J. Eales

    2004-01-01

    and their spouses/care-givers had a greater knowledge about the disease and the risk factor modification (p=0.01; p<0.01, and twelve months after the operation the patients are satisfied with the outcome of the operation (p<0.01. Conclusions: A stepwise logistic regression established that the acceptance of self-responsibility was the strongest  factor predicting an improved quality of life after CABG surgery. Patients who did not accept responsibility did not have an improved quality of life irrespective of the impact of all other parameters. Patients' satisfaction with the outcome of the operative procedure is an important predictor of the acceptance of self-responsibility. Realistic expectations of the outcome of CABG surgery will improve patients' satisfaction with the outcome. The knowledge of the spouse is a significant factor in the patients' acceptance of self-responsibility. Knowledge of the chronic nature of their disease as well as risk factor modification and realistic expectations of the outcome of CABG surgery influences patientsacceptance of self-responsibility.

  18. Linear response approach to active Brownian particles in time-varying activity fields

    Science.gov (United States)

    Merlitz, Holger; Vuijk, Hidde D.; Brader, Joseph; Sharma, Abhinav; Sommer, Jens-Uwe

    2018-05-01

    In a theoretical and simulation study, active Brownian particles (ABPs) in three-dimensional bulk systems are exposed to time-varying sinusoidal activity waves that are running through the system. A linear response (Green-Kubo) formalism is applied to derive fully analytical expressions for the torque-free polarization profiles of non-interacting particles. The activity waves induce fluxes that strongly depend on the particle size and may be employed to de-mix mixtures of ABPs or to drive the particles into selected areas of the system. Three-dimensional Langevin dynamics simulations are carried out to verify the accuracy of the linear response formalism, which is shown to work best when the particles are small (i.e., highly Brownian) or operating at low activity levels.

  19. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

  20. Electrophysiological indices of response inhibition in a Go/NoGo task predict self-control in a social context.

    Directory of Open Access Journals (Sweden)

    Kyle Nash

    Full Text Available Recent research demonstrates that response inhibition-a core executive function-may subserve self-regulation and self-control. However, it is unclear whether response inhibition also predicts self-control in the multifaceted, high-level phenomena of social decision-making. Here we examined whether electrophysiological indices of response inhibition would predict self-control in a social context. Electroencephalography was recorded as participants completed a widely used Go/NoGo task (the cued Continuous Performance Test. Participants then interacted with a partner in an economic exchange game that requires self-control. Results demonstrated that greater NoGo-Anteriorization and larger NoGo-P300 peak amplitudes-two established electrophysiological indices of response inhibition-both predicted more self-control in this social game. These findings support continued integration of executive function and self-regulation and help extend prior research into social decision-making processes.

  1. Regional brain activity during early-stage intense romantic love predicted relationship outcomes after 40 months: an fMRI assessment.

    Science.gov (United States)

    Xu, Xiaomeng; Brown, Lucy; Aron, Arthur; Cao, Guikang; Feng, Tingyong; Acevedo, Bianca; Weng, Xuchu

    2012-09-20

    Early-stage romantic love is associated with activation in reward and motivation systems of the brain. Can these localized activations, or others, predict long-term relationship stability? We contacted participants from a previous fMRI study of early-stage love by Xu et al. [34] after 40 months from initial assessments. We compared brain activation during the initial assessment at early-stage love for those who were still together at 40 months and those who were apart, and surveyed those still together about their relationship happiness and commitment at 40 months. Six participants who were still with their partners at 40 months (compared to six who had broken up) showed less activation during early-stage love in the medial orbitofrontal cortex, right subcallosal cingulate and right accumbens, regions implicated in long-term love and relationship satisfaction [1,2]. These regions of deactivation at the early stage of love were also negatively correlated with relationship happiness scores collected at 40 months. Other areas involved were the caudate tail, and temporal and parietal lobes. These data are preliminary evidence that neural responses in the early stages of romantic love can predict relationship stability and quality up to 40 months later in the relationship. The brain regions involved suggest that forebrain reward functions may be predictive for relationship stability, as well as regions involved in social evaluation, emotional regulation, and mood. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  2. Mycobacteria-specific cytokine responses as correlates of treatment response in active and latent tuberculosis.

    Science.gov (United States)

    Clifford, Vanessa; Tebruegge, Marc; Zufferey, Christel; Germano, Susie; Forbes, Ben; Cosentino, Lucy; McBryde, Emma; Eisen, Damon; Robins-Browne, Roy; Street, Alan; Denholm, Justin; Curtis, Nigel

    2017-08-01

    A biomarker indicating successful tuberculosis (TB) therapy would assist in determining appropriate length of treatment. This study aimed to determine changes in mycobacteria-specific antigen-induced cytokine biomarkers in patients receiving therapy for latent or active TB, to identify biomarkers potentially correlating with treatment success. A total of 33 adults with active TB and 36 with latent TB were followed longitudinally over therapy. Whole blood stimulation assays using mycobacteria-specific antigens (CFP-10, ESAT-6, PPD) were done on samples obtained at 0, 1, 3, 6 and 9 months. Cytokine responses (IFN-γ, IL-1ra, IL-2, IL-10, IL-13, IP-10, MIP-1β, and TNF-α) in supernatants were measured by Luminex xMAP immunoassay. In active TB cases, median IL-1ra (with CFP-10 and with PPD stimulation), IP-10 (CFP-10, ESAT-6), MIP-1β (ESAT-6, PPD), and TNF-α (ESAT-6) responses declined significantly over the course of therapy. In latent TB cases, median IL-1ra (CFP-10, ESAT-6, PPD), IL-2 (CFP-10, ESAT-6), and IP-10 (CFP-10, ESAT-6) responses declined significantly. Mycobacteria-specific cytokine responses change significantly over the course of therapy, and their kinetics in active TB differ from those observed in latent TB. In particular, mycobacteria-specific IL-1ra responses are potential correlates of successful therapy in both active and latent TB. Copyright © 2017 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

  3. Successful emotion regulation is predicted by amygdala activity and aspects of personality: A latent variable approach.

    Science.gov (United States)

    Morawetz, Carmen; Alexandrowicz, Rainer W; Heekeren, Hauke R

    2017-04-01

    The experience of emotions and their cognitive control are based upon neural responses in prefrontal and subcortical regions and could be affected by personality and temperamental traits. Previous studies established an association between activity in reappraisal-related brain regions (e.g., inferior frontal gyrus and amygdala) and emotion regulation success. Given these relationships, we aimed to further elucidate how individual differences in emotion regulation skills relate to brain activity within the emotion regulation network on the one hand, and personality/temperamental traits on the other. We directly examined the relationship between personality and temperamental traits, emotion regulation success and its underlying neuronal network in a large sample (N = 82) using an explicit emotion regulation task and functional MRI (fMRI). We applied a multimethodological analysis approach, combing standard activation-based analyses with structural equation modeling. First, we found that successful downregulation is predicted by activity in key regions related to emotion processing. Second, the individual ability to successfully upregulate emotions is strongly associated with the ability to identify feelings, conscientiousness, and neuroticism. Third, the successful downregulation of emotion is modulated by openness to experience and habitual use of reappraisal. Fourth, the ability to regulate emotions is best predicted by a combination of brain activity and personality as well temperamental traits. Using a multimethodological analysis approach, we provide a first step toward a causal model of individual differences in emotion regulation ability by linking biological systems underlying emotion regulation with descriptive constructs. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. Modulation of blood pressure response to exercise by physical activity and relationship with resting blood pressure during pregnancy.

    Science.gov (United States)

    Bisson, Michèle; Rhéaume, Caroline; Bujold, Emmanuel; Tremblay, Angelo; Marc, Isabelle

    2014-07-01

    To determine whether physical activity and blood pressure (BP) response to exercise in early pregnancy are related to resting BP at the end of pregnancy. Understanding physiological BP responses to exercise during pregnancy will help in improving BP profile and guiding exercise recommendations in pregnant women. Maternal physical activity, cardiorespiratory fitness (VO2peak) and BP (systolic and diastolic) at rest and during exercise (submaximal and relative response) were assessed at 16 weeks of gestation in 61 normotensive pregnant women. BP at 36 weeks of gestation and obstetrical outcomes were collected from maternal charts. Related to resting DBP at 16 weeks (r =  -0.28, P = 0.028), total energy expenditure spend at any physical activity in early pregnancy was also associated with resting SBP at 36 weeks (r =  -0.27, P = 0.038). On the contrary, although related to VO2peak (r =  -0.57, P sports and exercise (r =  -0.29, P = 0.024), the relative SBP response to exercise at 16 weeks was not associated with resting BP at 36 weeks. Strongly associated with resting BP at 16 weeks and also with total energy expenditure, submaximal BP response to exercise at 16 weeks was related to resting SBP and DBP at 36 weeks (r = 0.41, P = 0.001 and r = 0.26, P = 0.051, respectively). In normotensive women, physical activity performed in early pregnancy appears to slightly modulate resting BP in early and late pregnancy. However, further investigations are needed to determine which physical activity-related parameter in response to exercise best predicts BP variations during pregnancy.

  5. Predicting Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer with Textural Features Derived from Pretreatment 18F-FDG PET/CT Imaging.

    Science.gov (United States)

    Beukinga, Roelof J; Hulshoff, Jan B; van Dijk, Lisanne V; Muijs, Christina T; Burgerhof, Johannes G M; Kats-Ugurlu, Gursah; Slart, Riemer H J A; Slump, Cornelis H; Mul, Véronique E M; Plukker, John Th M

    2017-05-01

    Adequate prediction of tumor response to neoadjuvant chemoradiotherapy (nCRT) in esophageal cancer (EC) patients is important in a more personalized treatment. The current best clinical method to predict pathologic complete response is SUV max in 18 F-FDG PET/CT imaging. To improve the prediction of response, we constructed a model to predict complete response to nCRT in EC based on pretreatment clinical parameters and 18 F-FDG PET/CT-derived textural features. Methods: From a prospectively maintained single-institution database, we reviewed 97 consecutive patients with locally advanced EC and a pretreatment 18 F-FDG PET/CT scan between 2009 and 2015. All patients were treated with nCRT (carboplatin/paclitaxel/41.4 Gy) followed by esophagectomy. We analyzed clinical, geometric, and pretreatment textural features extracted from both 18 F-FDG PET and CT. The current most accurate prediction model with SUV max as a predictor variable was compared with 6 different response prediction models constructed using least absolute shrinkage and selection operator regularized logistic regression. Internal validation was performed to estimate the model's performances. Pathologic response was defined as complete versus incomplete response (Mandard tumor regression grade system 1 vs. 2-5). Results: Pathologic examination revealed 19 (19.6%) complete and 78 (80.4%) incomplete responders. Least absolute shrinkage and selection operator regularization selected the clinical parameters: histologic type and clinical T stage, the 18 F-FDG PET-derived textural feature long run low gray level emphasis, and the CT-derived textural feature run percentage. Introducing these variables to a logistic regression analysis showed areas under the receiver-operating-characteristic curve (AUCs) of 0.78 compared with 0.58 in the SUV max model. The discrimination slopes were 0.17 compared with 0.01, respectively. After internal validation, the AUCs decreased to 0.74 and 0.54, respectively. Conclusion

  6. Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

    Science.gov (United States)

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

    Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. Copyright 2010 APA, all rights reserved.

  7. Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

    Science.gov (United States)

    Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

    2017-08-03

    Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

  8. Establishing Esri ArcGIS Enterprise Platform Capabilities to Support Response Activities of the NASA Earth Science Disasters Program

    Science.gov (United States)

    Molthan, A.; Seepersad, J.; Shute, J.; Carriere, L.; Duffy, D.; Tisdale, B.; Kirschbaum, D.; Green, D. S.; Schwizer, L.

    2017-12-01

    NASA's Earth Science Disasters Program promotes the use of Earth observations to improve the prediction of, preparation for, response to, and recovery from natural and technological disasters. NASA Earth observations and those of domestic and international partners are combined with in situ observations and models by NASA scientists and partners to develop products supporting disaster mitigation, response, and recovery activities among several end-user partners. These products are accompanied by training to ensure proper integration and use of these materials in their organizations. Many products are integrated along with other observations available from other sources in GIS-capable formats to improve situational awareness and response efforts before, during and after a disaster. Large volumes of NASA observations support the generation of disaster response products by NASA field center scientists, partners in academia, and other institutions. For example, a prediction of high streamflows and inundation from a NASA-supported model may provide spatial detail of flood extent that can be combined with GIS information on population density, infrastructure, and land value to facilitate a prediction of who will be affected, and the economic impact. To facilitate the sharing of these outputs in a common framework that can be easily ingested by downstream partners, the NASA Earth Science Disasters Program partnered with Esri and the NASA Center for Climate Simulation (NCCS) to establish a suite of Esri/ArcGIS services to support the dissemination of routine and event-specific products to end users. This capability has been demonstrated to key partners including the Federal Emergency Management Agency using a case-study example of Hurricane Matthew, and will also help to support future domestic and international disaster events. The Earth Science Disasters Program has also established a longer-term vision to leverage scientists' expertise in the development and delivery of

  9. Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI

    Directory of Open Access Journals (Sweden)

    Alina Tudorica

    2016-02-01

    Full Text Available The purpose is to compare quantitative dynamic contrast-enhanced (DCE magnetic resonance imaging (MRI metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT and evaluation of residual cancer burden (RCB. Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM. After one NACT cycle the percent changes of DCE-MRI parameters Ktrans (contrast agent plasma/interstitium transfer rate constant, ve (extravascular and extracellular volume fraction, kep (intravasation rate constant, and SSM-unique τi (mean intracellular water lifetime are good to excellent early predictors of pathologic complete response (pCR vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. ve values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT Ktrans, τi, and RECIST LD show statistically significant (P < .05 correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τi parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism.

  10. Cortical Response Similarities Predict which Audiovisual Clips Individuals Viewed, but Are Unrelated to Clip Preference.

    Directory of Open Access Journals (Sweden)

    David A Bridwell

    Full Text Available Cortical responses to complex natural stimuli can be isolated by examining the relationship between neural measures obtained while multiple individuals view the same stimuli. These inter-subject correlation's (ISC's emerge from similarities in individual's cortical response to the shared audiovisual inputs, which may be related to their emergent cognitive and perceptual experience. Within the present study, our goal is to examine the utility of using ISC's for predicting which audiovisual clips individuals viewed, and to examine the relationship between neural responses to natural stimuli and subjective reports. The ability to predict which clips individuals viewed depends on the relationship of the EEG response across subjects and the nature in which this information is aggregated. We conceived of three approaches for aggregating responses, i.e. three assignment algorithms, which we evaluated in Experiment 1A. The aggregate correlations algorithm generated the highest assignment accuracy (70.83% chance = 33.33% and was selected as the assignment algorithm for the larger sample of individuals and clips within Experiment 1B. The overall assignment accuracy was 33.46% within Experiment 1B (chance = 06.25%, with accuracies ranging from 52.9% (Silver Linings Playbook to 11.75% (Seinfeld within individual clips. ISC's were significantly greater than zero for 15 out of 16 clips, and fluctuations within the delta frequency band (i.e. 0-4 Hz primarily contributed to response similarities across subjects. Interestingly, there was insufficient evidence to indicate that individuals with greater similarities in clip preference demonstrate greater similarities in cortical responses, suggesting a lack of association between ISC and clip preference. Overall these results demonstrate the utility of using ISC's for prediction, and further characterize the relationship between ISC magnitudes and subjective reports.

  11. Cortical Response Similarities Predict which Audiovisual Clips Individuals Viewed, but Are Unrelated to Clip Preference.

    Science.gov (United States)

    Bridwell, David A; Roth, Cullen; Gupta, Cota Navin; Calhoun, Vince D

    2015-01-01

    Cortical responses to complex natural stimuli can be isolated by examining the relationship between neural measures obtained while multiple individuals view the same stimuli. These inter-subject correlation's (ISC's) emerge from similarities in individual's cortical response to the shared audiovisual inputs, which may be related to their emergent cognitive and perceptual experience. Within the present study, our goal is to examine the utility of using ISC's for predicting which audiovisual clips individuals viewed, and to examine the relationship between neural responses to natural stimuli and subjective reports. The ability to predict which clips individuals viewed depends on the relationship of the EEG response across subjects and the nature in which this information is aggregated. We conceived of three approaches for aggregating responses, i.e. three assignment algorithms, which we evaluated in Experiment 1A. The aggregate correlations algorithm generated the highest assignment accuracy (70.83% chance = 33.33%) and was selected as the assignment algorithm for the larger sample of individuals and clips within Experiment 1B. The overall assignment accuracy was 33.46% within Experiment 1B (chance = 06.25%), with accuracies ranging from 52.9% (Silver Linings Playbook) to 11.75% (Seinfeld) within individual clips. ISC's were significantly greater than zero for 15 out of 16 clips, and fluctuations within the delta frequency band (i.e. 0-4 Hz) primarily contributed to response similarities across subjects. Interestingly, there was insufficient evidence to indicate that individuals with greater similarities in clip preference demonstrate greater similarities in cortical responses, suggesting a lack of association between ISC and clip preference. Overall these results demonstrate the utility of using ISC's for prediction, and further characterize the relationship between ISC magnitudes and subjective reports.

  12. Stathmin protein level, a potential predictive marker for taxane treatment response in endometrial cancer.

    Directory of Open Access Journals (Sweden)

    Henrica M J Werner

    Full Text Available Stathmin is a prognostic marker in many cancers, including endometrial cancer. Preclinical studies, predominantly in breast cancer, have suggested that stathmin may additionally be a predictive marker for response to paclitaxel. We first evaluated the response to paclitaxel in endometrial cancer cell lines before and after stathmin knock-down. Subsequently we investigated the clinical response to paclitaxel containing chemotherapy in metastatic endometrial cancer in relation to stathmin protein level in tumors. Stathmin level was also determined in metastatic lesions, analyzing changes in biomarker status on disease progression. Knock-down of stathmin improved sensitivity to paclitaxel in endometrial carcinoma cell lines with both naturally higher and lower sensitivity to paclitaxel. In clinical samples, high stathmin level was demonstrated to be associated with poor response to paclitaxel containing chemotherapy and to reduced disease specific survival only in patients treated with such combination. Stathmin level increased significantly from primary to metastatic lesions. This study suggests, supported by both preclinical and clinical data, that stathmin could be a predictive biomarker for response to paclitaxel treatment in endometrial cancer. Re-assessment of stathmin level in metastatic lesions prior to treatment start may be relevant. Also, validation in a randomized clinical trial will be important.

  13. Glucocorticoid exposure in preterm babies predicts saliva cortisol response to immunization at 4 months.

    Science.gov (United States)

    Glover, Vivette; Miles, Rachel; Matta, Simon; Modi, Neena; Stevenson, James

    2005-12-01

    Preterm babies are exposed to multiple stressors and this may have long-term effects. In particular, high levels of endogenous cortisol might have a programming effect on the hypothalamic-pituitary-adrenal axis as may administered glucocorticoids. In this study, we aimed to test the hypothesis that the level of endogenous and exogenous glucocorticoid exposure during the neonatal period predicts the saliva cortisol response to immunization at 4 mo of age. We followed 45 babies born below 32 wk gestation. We showed that their concentration of plasma cortisol during the first 4 wk was 358, 314, 231, and 195 nmol/L cortisol, respectively (geometric mean). This is four to seven times higher than fetal levels at the same gestational age range. We used routine immunization at 4 mo and 12 mo as a stressor and measured the change in saliva cortisol as the stress response. Mean circulating cortisol in the first 4 wk predicted the cortisol response at 4 but not at 12 mo. Path analysis showed that birthweight for gestational age, therapeutic antenatal steroids, and therapeutic postnatal steroids also contributed to the magnitude of the saliva cortisol response at 4 mo. This provides evidence that the magnitude of glucocorticoid exposure, both endogenous and exogenous, may have an effect on later stress responses.

  14. Translating crustacean biological responses from CO2 bubbling experiments into population-level predictions

    Science.gov (United States)

    Many studies of animal responses to ocean acidification focus on uniformly conditioned age cohorts that lack complexities typically found in wild populations. These studies have become the primary data source for predicting higher level ecological effects, but the roles of intras...

  15. Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data.

    Science.gov (United States)

    Redlich, Ronny; Opel, Nils; Grotegerd, Dominik; Dohm, Katharina; Zaremba, Dario; Bürger, Christian; Münker, Sandra; Mühlmann, Lisa; Wahl, Patricia; Heindel, Walter; Arolt, Volker; Alferink, Judith; Zwanzger, Peter; Zavorotnyy, Maxim; Kugel, Harald; Dannlowski, Udo

    2016-06-01

    Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depression. However, biomarkers that accurately predict a response to ECT remain unidentified. To investigate whether certain factors identified by structural magnetic resonance imaging (MRI) techniques are able to predict ECT response. In this nonrandomized prospective study, gray matter structure was assessed twice at approximately 6 weeks apart using 3-T MRI and voxel-based morphometry. Patients were recruited through the inpatient service of the Department of Psychiatry, University of Muenster, from March 11, 2010, to March 27, 2015. Two patient groups with acute major depressive disorder were included. One group received an ECT series in addition to antidepressants (n = 24); a comparison sample was treated solely with antidepressants (n = 23). Both groups were compared with a sample of healthy control participants (n = 21). Binary pattern classification was used to predict ECT response by structural MRI that was performed before treatment. In addition, univariate analysis was conducted to predict reduction of the Hamilton Depression Rating Scale score by pretreatment gray matter volumes and to investigate ECT-related structural changes. One participant in the ECT sample was excluded from the analysis, leaving 67 participants (27 men and 40 women; mean [SD] age, 43.7 [10.6] years). The binary pattern classification yielded a successful prediction of ECT response, with accuracy rates of 78.3% (18 of 23 patients in the ECT sample) and sensitivity rates of 100% (13 of 13 who responded to ECT). Furthermore, a support vector regression yielded a significant prediction of relative reduction in the Hamilton Depression Rating Scale score. The principal findings of the univariate model indicated a positive association between pretreatment subgenual cingulate volume and individual ECT response (Montreal Neurological Institute [MNI] coordinates x = 8, y = 21, z = -18

  16. Myopodin methylation is a prognostic biomarker and predicts antiangiogenic response in advanced kidney cancer.

    Science.gov (United States)

    Pompas-Veganzones, N; Sandonis, V; Perez-Lanzac, Alberto; Beltran, M; Beardo, P; Juárez, A; Vazquez, F; Cozar, J M; Alvarez-Ossorio, J L; Sanchez-Carbayo, Marta

    2016-10-01

    Myopodin is a cytoskeleton protein that shuttles to the nucleus depending on the cellular differentiation and stress. It has shown tumor suppressor functions. Myopodin methylation status was useful for staging bladder and colon tumors and predicting clinical outcome. To our knowledge, myopodin has not been tested in kidney cancer to date. The purpose of this study was to evaluate whether myopodin methylation status could be clinically useful in renal cancer (1) as a prognostic biomarker and 2) as a predictive factor of response to antiangiogenic therapy in patients with metastatic disease. Methylation-specific polymerase chain reactions (MS-PCR) were used to evaluate myopodin methylation in 88 kidney tumors. These belonged to patients with localized disease and no evidence of disease during follow-up (n = 25) (group 1), and 63 patients under antiangiogenic therapy (sunitinib, sorafenib, pazopanib, and temsirolimus), from which group 2 had non-metastatic disease at diagnosis (n = 32), and group 3 showed metastatic disease at diagnosis (n = 31). Univariate and multivariate Cox analyses were utilized to assess outcome and response to antiangiogenic agents taking progression, disease-specific survival, and overall survival as clinical endpoints. Myopodin was methylated in 50 out of the 88 kidney tumors (56.8 %). Among the 88 cases analyzed, 10 of them recurred (11.4 %), 51 progressed (57.9 %), and 40 died of disease (45.4 %). Myopodin methylation status correlated to MSKCC Risk score (p = 0.050) and the presence of distant metastasis (p = 0.039). Taking all patients, an unmethylated myopodin identified patients with shorter progression-free survival, disease-specific survival, and overall survival. Using also in univariate and multivariate models, an unmethylated myopodin predicted response to antiangiogenic therapy (groups 2 and 3) using progression-free survival, disease-specific, and overall survival as clinical endpoints. Myopodin was revealed

  17. Differential activation behavior of dermal dendritic cells underlies the strain-specific Th1 responses to single epicutaneous immunization.

    Science.gov (United States)

    Lee, Chih-Hung; Chen, Jau-Shiuh; Chiu, Hsien-Ching; Hong, Chien-Hui; Liu, Ching-Yi; Ta, Yng-Cun; Wang, Li-Fang

    2016-12-01

    Epicutaneous immunization with allergens is an important sensitization route for atopic dermatitis. We recently showed in addition to the Th2 response following single epicutaneous immunization, a remarkable Th1 response is induced in B6 mice, but not in BALB/c mice, mimicking the immune response to allergens in human non-atopics and atopics. We investigated the underlying mechanisms driving this differential Th1 response between BALB/c and B6 mice. We characterized dermal dendritic cells by flow cytometric analysis. We measured the induced Th1/Th2 responses by measuring the IFN-γ/IL-13 contents of supernatants of antigen reactivation cultures of lymph node cells. We demonstrate that more dermal dendritic cells with higher activation status migrate into draining lymph nodes of B6 mice compared to BALB/c mice. Dermal dendritic cells of B6 mice have a greater ability to capture protein antigen than those of BALB/c mice. Moreover, increasing the activation status or amount of captured antigen in dermal dendritic cells induced a Th1 response in BALB/c mice. Further, differential activation behavior, but not antigen-capturing ability of dermal dendritic cells between BALB/c and B6 mice is dendritic cell-intrinsic. These results show that the differential activation behavior of dermal dendritic cells underlies the strain-specific Th1 responses following single epicutaneous immunization. Furthermore, our findings highlight the potential differences between human atopics and non-atopics and provide useful information for the prediction and prevention of atopic diseases. Copyright © 2016 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

  18. A prospective study on personality and the cortisol awakening response to predict posttraumatic stress symptoms in response to military deployment

    NARCIS (Netherlands)

    van Zuiden, Mirjam; Kavelaars, Annemieke; Rademaker, Arthur R.; Vermetten, Eric; Heijnen, Cobi J.; Geuze, Elbert

    2011-01-01

    Few prospective studies on pre-trauma predictors for subsequent development of posttraumatic stress disorder (PTSD) have been conducted. In this study we prospectively investigated whether pre-deployment personality and the cortisol awakening response (CAR) predicted development of PTSD symptoms in

  19. Fungistatic activity of heat-treated flaxseed determined by response surface methodology.

    Science.gov (United States)

    Xu, Y; Hall, C; Wolf-Hall, C

    2008-08-01

    The objective of this study was to evaluate the effect of heat treatment on the fungistatic activity of flaxseed (Linum usitatissimum) in potato dextrose agar (PDA) medium and a fresh noodle system. The radial growth of Penicilliumn chrysogenum, Aspergillus flavus, and a Penicillium sp. isolated from moldy noodles, as well as the mold count of fresh noodle enriched with heat treated flaxseed, were used to assess antifungal activity. A central composite design in the response surface methodology was used to predict the effect of heating temperature and time on antifungal activity of flaxseed flour (FF). Statistical analysis determined that the linear terms of both variables (that is, heating temperature and time) and the quadratic terms of the heating temperature had significant (P<0.05) effects on the radial growth of all 3 test fungi and the mold count log-cycle reduction of fresh noodle. The interactions between the temperature and time were significant for all dependent variables (P<0.05). Significant reductions in antifungal activities were found when FF was subjected to high temperatures, regardless of heating time. In contrast, prolonging the heating time did not substantially affect the antifungal activities of FF at low temperature. However, 60% of the antifungal activity was retained after FF was heated at 100 degrees C for 15 min, which suggests a potential use of FF as an antifungal additive in food products subjected to low to mild heat treatments.

  20. Predictive and prognostic factors associated with soft tissue sarcoma response to chemotherapy

    DEFF Research Database (Denmark)

    Young, Robin J; Litière, Saskia; Lia, Michela

    2017-01-01

    BACKGROUND: The European Organization for Research and Treatment of Cancer (EORTC) 62012 study was a Phase III trial of doxorubicin versus doxorubicin-ifosfamide chemotherapy in 455 patients with advanced soft tissue sarcoma (STS). Analysis of the main study showed that combination chemotherapy...... improved tumor response and progression-free survival, but differences in overall survival (OS) were not statistically significant. We analyzed factors prognostic for tumor response and OS, and assessed histological subgroup and tumor grade as predictive factors to identify patients more likely to benefit...... patients had improved tumor response compared to other histological subgroups, whilst patients with metastases other than lung, liver or bone had a poorer response [odds ratio (OR) 0.42, 95% confidence interval (CI) 0.23-0.78; p = 0.006]. Patients with bone metastases had reduced OS [hazard ratio (HR) 1...

  1. Predicting the Responses of Soil Nitrite-Oxidizers to Multi-Factorial Global Change: A Trait-Based Approach

    DEFF Research Database (Denmark)

    Le Roux, Xavier; Bouskill, Nicholas J.; Niboyet, Audrey

    2016-01-01

    Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil...... functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global...

  2. An Assessment of the Model of Concentration Addition for Predicting the Estrogenic Activity of Chemical Mixtures in Wastewater Treatment Works Effluents

    Science.gov (United States)

    Thorpe, Karen L.; Gross-Sorokin, Melanie; Johnson, Ian; Brighty, Geoff; Tyler, Charles R.

    2006-01-01

    The effects of simple mixtures of chemicals, with similar mechanisms of action, can be predicted using the concentration addition model (CA). The ability of this model to predict the estrogenic effects of more complex mixtures such as effluent discharges, however, has yet to be established. Effluents from 43 U.K. wastewater treatment works were analyzed for the presence of the principal estrogenic chemical contaminants, estradiol, estrone, ethinylestradiol, and nonylphenol. The measured concentrations were used to predict the estrogenic activity of each effluent, employing the model of CA, based on the relative potencies of the individual chemicals in an in vitro recombinant yeast estrogen screen (rYES) and a short-term (14-day) in vivo rainbow trout vitellogenin induction assay. Based on the measured concentrations of the four chemicals in the effluents and their relative potencies in each assay, the calculated in vitro and in vivo responses compared well and ranged between 3.5 and 87 ng/L of estradiol equivalents (E2 EQ) for the different effluents. In the rYES, however, the measured E2 EQ concentrations in the effluents ranged between 0.65 and 43 ng E2 EQ/L, and they varied against those predicted by the CA model. Deviations in the estimation of the estrogenic potency of the effluents by the CA model, compared with the measured responses in the rYES, are likely to have resulted from inaccuracies associated with the measurement of the chemicals in the extracts derived from the complex effluents. Such deviations could also result as a consequence of interactions between chemicals present in the extracts that disrupted the activation of the estrogen response elements in the rYES. E2 EQ concentrations derived from the vitellogenic response in fathead minnows exposed to a series of effluent dilutions were highly comparable with the E2 EQ concentrations derived from assessments of the estrogenic potency of these dilutions in the rYES. Together these data support the

  3. Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

    Directory of Open Access Journals (Sweden)

    Devin W McBride

    Full Text Available The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

  4. Responsiveness of performance and morphological traits to experimental submergence predicts field distribution pattern of wetland plants

    NARCIS (Netherlands)

    Luo, Fang-Li; Huang, Lin; Lei, Ting; Xue, Wei; Li, Hong-Li; Yu, Fei-Hai; Cornelissen, J.H.C.

    2016-01-01

    Question: Plant trait mean values and trait responsiveness to different environmental regimes are both important determinants of plant field distribution, but the degree to which plant trait means vs trait responsiveness predict plant distribution has rarely been compared quantitatively. Because

  5. Predictive capabilities of the specific activity hypothesis for Cs and Zn in freshwater systems

    International Nuclear Information System (INIS)

    Seelye, J.G.

    1975-01-01

    Predictions of radioisotope concentrations in components of aquatic systems have been attempted using the specific activity concept, an approach that seems theoretically sound. A comprehensive examination of the specific activities of 134 Cs and 65 Zn in the components of a freshwater system, over a 10 month period, was conducted to evaluate the specific activity hypothesis under applied conditions. This study was designed to provide comparisons of predicted and observed specific activities and to test the equivalence of specific activities between all components of the system. One dose of radioisotopes was added to the system in this study and even after 10 months these radioisotopes were not distributed similarly to the stable isotopes. This suggests that the time necessary to reach a specific activity equilibrium might be a matter of years rather than months. More importantly, in natural systems, where the radioisotope addition is continuous a specific activity equilibrium may never be achieved. These things plus the non-conservative nature of the 134 Cs and 65 Zn predicted concentrations indicates that the use of the specific activity concept for predicting radioisotope concentrations of Cs and Zn in freshwater systems is questionable. A more rigorous approach must be used, considering isotope transfer rates between components and the complexity of the system. Problems with statistical comparisons of derived variables, such as specific activities, are discussed and were considered in interpreting the results of this study

  6. Prediction of Support Reaction Forces of ITA via Response Spectrum Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, Jin Sung; Jeong, Joon Ho; Lee, Sang Jin; Oh, Jin Ho; Lee, Jong Min [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    The irradiation targets are transferred along pipes between TTS (Target Transfer Station) and ITA (Irradiation Tube Assembly) by hydraulic forces. The ITA corresponds to the vertical guide tube for irradiation targets inside a reactor, and it penetrates the reactor structure. Because the ITA is classified into seismic category II, its structural integrity must be evaluated by the seismic analysis. To approach more realistic problem, the interaction between the ITA and the reactor structure must be considered. However, this paper is focused on the preliminary analysis, and it is simplified that only the response of the ITA caused by earthquake affects the reactor structure. The response of the ITA is predicted by the spectrum response analysis based on the FDRS (Floor Design Response Spectra) of KJRR. Finally, the reaction forces corresponding to the load transfer into the reactor structure are estimated by using ANSYS. In this study, the reaction forces due to the earthquake are estimated by the response spectrum analysis. For the saving computational time and resource required, the FE model with beam element is constructed, and it is confirmed that the accuracy of the solution is acceptable by comparing the results of the solid model.

  7. Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities.

    Science.gov (United States)

    Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

    2016-01-01

    Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Consumers' evaluations of socially responsible activities in retailing

    NARCIS (Netherlands)

    Herpen, van E.; Pennings, J.M.E.; Meulenberg, M.T.G.

    2003-01-01

    The authors approached Corporate Social Responsibility (CSR) as a process in which particular CSR activities impact on consumers’ store evaluation and trust. They hypothesized that consumers classify CSR activities along two dimensions: (1) the beneficiary of the activity and (2) the intrinsic

  9. An overview of the Environmental Response Team's air surveillance procedures at emergency response activities

    Energy Technology Data Exchange (ETDEWEB)

    Turpin, R.D.; Campagna, P.R. (U.S. Environmental Protection Agency, Edison, NJ (USA))

    The Safety and Air Surveillance Section of the United States Environmental Protection Agency's Environmental Response Team responds to emergency air releases such as tire fires and explosions. The air surveillance equipment and procedures used by the organization are described, and case studies demonstrating the various emergency response activities are presented. Air response activities include emergency air responses, occupational and human health air responses and remedial air responses. Monitoring and sampling equipment includes photoionization detectors, combustible gas meters, real-time aerosol monitors, personal sampling pumps, and high flow pumps. Case histories presented include disposal of dioxane from a cotton plant, response to oil well fires in Kuwait, disposal of high pressure cylinders in American Samoa, and response to hurricane Hugo. 3 refs., 1 tab.

  10. A cluster expansion model for predicting activation barrier of atomic processes

    International Nuclear Information System (INIS)

    Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit

    2013-01-01

    We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog

  11. Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets.

    Science.gov (United States)

    Ajitha, M; Sundar, K; Arul Mugilan, S; Arumugam, S

    2018-03-01

    The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques. © 2017 Wiley Periodicals, Inc.

  12. Generation of human auditory steady-state responses (SSRs). II: Addition of responses to individual stimuli.

    Science.gov (United States)

    Santarelli, R; Maurizi, M; Conti, G; Ottaviani, F; Paludetti, G; Pettorossi, V E

    1995-03-01

    In order to investigate the generation of the 40 Hz steady-state response (SSR), auditory potentials evoked by clicks were recorded in 16 healthy subjects in two stimulating conditions. Firstly, repetition rates of 7.9 and 40 Hz were used to obtain individual middle latency responses (MLRs) and 40 Hz-SSRs, respectively. In the second condition, eight click trains were presented at a 40 Hz repetition rate and an inter-train interval of 126 ms. We extracted from the whole train response: (1) the response-segment taking place after the last click of the train (last click response, LCR), (2) a modified LCR (mLCR) obtained by clearing the LCR from the amplitude enhancement due to the overlapping of the responses to the clicks preceding the last within the stimulus train. In comparison to MLRs, the most relevant feature of the evoked activity following the last click of the train (LCRs, mLCRs) was the appearance in the 50-110 ms latency range of one (in 11 subjects) or two (in 2 subjects) additional positive-negative deflections having the same periodicity as that of MLR waves. The grand average (GA) of the 40 Hz-SSRs was compared with three predictions synthesized by superimposing: (1) the GA of MLRs, (2) the GA of LCRs, (3) the GA of mLCRs. Both the MLR and mLCR predictions reproduced the recorded signal in amplitude while the LCR prediction amplitude resulted almost twice that of the 40 Hz-SSR. With regard to the phase, the MLR, LCR and mLCR closely predicted the recorded signal. Our findings confirm the effectiveness of the linear addition mechanism in the generation of the 40 Hz-SSR. However the responses to individual stimuli within the 40 Hz-SSR differ from MLRs because of additional periodic activity. These results suggest that phenomena related to the resonant frequency of the activated system may play a role in the mechanisms which interact to generate the 40 Hz-SSR.

  13. Predicting active school travel: The role of planned behavior and habit strength

    Science.gov (United States)

    2012-01-01

    Background Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model’s predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children’s active school travel. Method Participants (N = 126 children aged 8–9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. Results The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. Conclusions The TPB significantly predicts children’s active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children’s intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these

  14. Stroke volume variation compared with pulse pressure variation and cardiac index changes for prediction of fluid responsiveness in mechanically ventilated patients

    Directory of Open Access Journals (Sweden)

    Randa Aly Soliman

    2015-04-01

    Conclusions: Baseline stroke volume variation ⩾8.15% predicted fluid responsiveness in mechanically ventilated patients with acute circulatory failure. The study also confirmed the ability of pulse pressure variation to predict fluid responsiveness.

  15. Human V4 Activity Patterns Predict Behavioral Performance in Imagery of Object Color.

    Science.gov (United States)

    Bannert, Michael M; Bartels, Andreas

    2018-04-11

    Color is special among basic visual features in that it can form a defining part of objects that are engrained in our memory. Whereas most neuroimaging research on human color vision has focused on responses related to external stimulation, the present study investigated how sensory-driven color vision is linked to subjective color perception induced by object imagery. We recorded fMRI activity in male and female volunteers during viewing of abstract color stimuli that were red, green, or yellow in half of the runs. In the other half we asked them to produce mental images of colored, meaningful objects (such as tomato, grapes, banana) corresponding to the same three color categories. Although physically presented color could be decoded from all retinotopically mapped visual areas, only hV4 allowed predicting colors of imagined objects when classifiers were trained on responses to physical colors. Importantly, only neural signal in hV4 was predictive of behavioral performance in the color judgment task on a trial-by-trial basis. The commonality between neural representations of sensory-driven and imagined object color and the behavioral link to neural representations in hV4 identifies area hV4 as a perceptual hub linking externally triggered color vision with color in self-generated object imagery. SIGNIFICANCE STATEMENT Humans experience color not only when visually exploring the outside world, but also in the absence of visual input, for example when remembering, dreaming, and during imagery. It is not known where neural codes for sensory-driven and internally generated hue converge. In the current study we evoked matching subjective color percepts, one driven by physically presented color stimuli, the other by internally generated color imagery. This allowed us to identify area hV4 as the only site where neural codes of corresponding subjective color perception converged regardless of its origin. Color codes in hV4 also predicted behavioral performance in an

  16. 18F-fluorodeoxyglucose positron emission tomography for predicting tumor response to radiochemotherapy in nasopharyngeal carcinoma

    International Nuclear Information System (INIS)

    Su, Meng; Wei, Hangping; Lin, Ruifang; Zhang, Xuebang; Zou, Changlin; Zhao, Liang

    2015-01-01

    The aim of this study was to evaluate the value of 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in predicting tumor response to radiochemotherapy in nasopharyngeal carcinoma (NPC). From July 2012 to March 2014, 46 NPC patients who had undergone PET scanning before receiving definitive intensity-modulated radiotherapy (IMRT) treatment in our hospital were enrolled. Factors potentially affecting tumor response to treatment were studied by multiple logistic regression analysis. After radiochemotherapy, 32 patients had a clinical complete response (CR), making the CR rate 69.6 %. Multiple logistic regression analysis demonstrated that the maximal standard uptake value (SUV max ) of the primary tumor was the only factor related to tumor response (p = 0.001), and that the logistic model had a high positive predictive value (90.6 %). The area under the receiver operating characteristic (ROC) curve was 0.809, with a best cutoff threshold at 10.05. Patients with SUV max ≤ 10 had a higher CR rate than those with SUV max > 10 (p < 0.001). The SUV max of the primary tumor before treatment is an independent predictor of tumor response in NPC. (orig.) [de

  17. The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

    Science.gov (United States)

    Lawrence N. Hudson; Joseph Wunderle M.; And Others

    2016-01-01

    The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to...

  18. Auditory prediction during speaking and listening.

    Science.gov (United States)

    Sato, Marc; Shiller, Douglas M

    2018-02-02

    In the present EEG study, the role of auditory prediction in speech was explored through the comparison of auditory cortical responses during active speaking and passive listening to the same acoustic speech signals. Two manipulations of sensory prediction accuracy were used during the speaking task: (1) a real-time change in vowel F1 feedback (reducing prediction accuracy relative to unaltered feedback) and (2) presenting a stable auditory target rather than a visual cue to speak (enhancing auditory prediction accuracy during baseline productions, and potentially enhancing the perturbing effect of altered feedback). While subjects compensated for the F1 manipulation, no difference between the auditory-cue and visual-cue conditions were found. Under visually-cued conditions, reduced N1/P2 amplitude was observed during speaking vs. listening, reflecting a motor-to-sensory prediction. In addition, a significant correlation was observed between the magnitude of behavioral compensatory F1 response and the magnitude of this speaking induced suppression (SIS) for P2 during the altered auditory feedback phase, where a stronger compensatory decrease in F1 was associated with a stronger the SIS effect. Finally, under the auditory-cued condition, an auditory repetition-suppression effect was observed in N1/P2 amplitude during the listening task but not active speaking, suggesting that auditory predictive processes during speaking and passive listening are functionally distinct. Copyright © 2018 Elsevier Inc. All rights reserved.

  19. Serum Adiponectin, Vitamin D, and Alpha-Fetoprotein in Children with Chronic Hepatitis C: Can They Predict Treatment Response?

    Science.gov (United States)

    Khedr, Mohamed Ahmed; Sira, Ahmad Mohamed; Saber, Magdy Anwar; Raia, Gamal Yousef

    2015-01-01

    Background & Aims. The currently available treatment for chronic hepatitis C (CHC) in children is costly and with much toxicity. So, predicting the likelihood of response before starting therapy is important. Methods. Serum adiponectin, vitamin D, and alpha-fetoprotein (AFP) were measured before starting pegylated-interferon/ribavirin therapy for 50 children with CHC. Another 21 healthy children were recruited as controls. Results. Serum adiponectin, vitamin D, and AFP were higher in the CHC group than healthy controls (p < 0.0001, p = 0.071, and p = 0.87, resp.). In univariate analysis, serum adiponectin was significantly higher in responders than nonresponders (p < 0.0001) and at a cutoff value ≥8.04 ng/mL it can predict treatment response by 77.8% sensitivity and 92.9% specificity, while both AFP and viremia were significantly lower in responders than nonresponders, p < 0.0001 and p = 0.0003, respectively, and at cutoff values ≤3.265 ng/mL and ≤235,384 IU/mL, respectively, they can predict treatment response with a sensitivity of 83.3% for both and specificity of 85.7% and 78.6%, respectively. In multivariate analysis, adiponectin was found to be the only independent predictor of treatment response (p = 0.044). Conclusions. The pretreatment serum level of adiponectin can predict the likelihood of treatment response, thus avoiding toxicities for those unlikely to respond to therapy.

  20. Merlin : microsimulation system for predicting leisure activity-travel patterns

    NARCIS (Netherlands)

    Middelkoop, van M.; Borgers, A.W.J.; Timmermans, H.J.P.

    2004-01-01

    Development of a model of annual activity-travel patterns of leisure and vacation travel is reported. The simulation system, called Merlin, is a hybrid model system consisting of discrete choice models and rule-based models. It predicts the annual number of day trips and vacations, and the profile

  1. The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil.

    Science.gov (United States)

    Sánchez-Aragó, María; Cuezva, José M

    2011-02-08

    Metabolic reprogramming resulting in enhanced glycolysis is a phenotypic trait of cancer cells, which is imposed by the tumor microenvironment and is linked to the down-regulation of the catalytic subunit of the mitochondrial H+-ATPase (β-F1-ATPase). The bioenergetic signature is a protein ratio (β-F1-ATPase/GAPDH), which provides an estimate of glucose metabolism in tumors and serves as a prognostic indicator for cancer patients. Targeting energetic metabolism could be a viable alternative to conventional anticancer chemotherapies. Herein, we document that the bioenergetic signature of isogenic colon cancer cells provides a gauge to predict the cell-death response to the metabolic inhibitors, 3-bromopyruvate (3BrP) and iodoacetate (IA), and the anti-metabolite, 5-fluorouracil (5-FU). The bioenergetic signature of the cells was determined by western blotting. Aerobic glycolysis was determined from lactate production rates. The cell death was analyzed by fluorescence microscopy and flow cytometry. Cellular ATP concentrations were determined using bioluminiscence. Pearson's correlation coefficient was applied to assess the relationship between the bioenergetic signature and the cell death response. In vivo tumor regression activities of the compounds were assessed using a xenograft mouse model injected with the highly glycolytic HCT116 colocarcinoma cells. We demonstrate that the bioenergetic signature of isogenic HCT116 cancer cells inversely correlates with the potential to execute necrosis in response to 3BrP or IA treatment. Conversely, the bioenergetic signature directly correlates with the potential to execute apoptosis in response to 5-FU treatment in the same cells. However, despite the large differences observed in the in vitro cell-death responses associated with 3BrP, IA and 5-FU, the in vivo tumor regression activities of these agents were comparable. Overall, we suggest that the determination of the bioenergetic signature of colon carcinomas could

  2. The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil

    Directory of Open Access Journals (Sweden)

    Cuezva José M

    2011-02-01

    Full Text Available Abstract Background Metabolic reprogramming resulting in enhanced glycolysis is a phenotypic trait of cancer cells, which is imposed by the tumor microenvironment and is linked to the down-regulation of the catalytic subunit of the mitochondrial H+-ATPase (β-F1-ATPase. The bioenergetic signature is a protein ratio (β-F1-ATPase/GAPDH, which provides an estimate of glucose metabolism in tumors and serves as a prognostic indicator for cancer patients. Targeting energetic metabolism could be a viable alternative to conventional anticancer chemotherapies. Herein, we document that the bioenergetic signature of isogenic colon cancer cells provides a gauge to predict the cell-death response to the metabolic inhibitors, 3-bromopyruvate (3BrP and iodoacetate (IA, and the anti-metabolite, 5-fluorouracil (5-FU. Methods The bioenergetic signature of the cells was determined by western blotting. Aerobic glycolysis was determined from lactate production rates. The cell death was analyzed by fluorescence microscopy and flow cytometry. Cellular ATP concentrations were determined using bioluminiscence. Pearson's correlation coefficient was applied to assess the relationship between the bioenergetic signature and the cell death response. In vivo tumor regression activities of the compounds were assessed using a xenograft mouse model injected with the highly glycolytic HCT116 colocarcinoma cells. Results We demonstrate that the bioenergetic signature of isogenic HCT116 cancer cells inversely correlates with the potential to execute necrosis in response to 3BrP or IA treatment. Conversely, the bioenergetic signature directly correlates with the potential to execute apoptosis in response to 5-FU treatment in the same cells. However, despite the large differences observed in the in vitro cell-death responses associated with 3BrP, IA and 5-FU, the in vivo tumor regression activities of these agents were comparable. Conclusions Overall, we suggest that the

  3. On the same wavelength: predictable language enhances speaker-listener brain-to-brain synchrony in posterior superior temporal gyrus.

    Science.gov (United States)

    Dikker, Suzanne; Silbert, Lauren J; Hasson, Uri; Zevin, Jason D

    2014-04-30

    Recent research has shown that the degree to which speakers and listeners exhibit similar brain activity patterns during human linguistic interaction is correlated with communicative success. Here, we used an intersubject correlation approach in fMRI to test the hypothesis that a listener's ability to predict a speaker's utterance increases such neural coupling between speakers and listeners. Nine subjects listened to recordings of a speaker describing visual scenes that varied in the degree to which they permitted specific linguistic predictions. In line with our hypothesis, the temporal profile of listeners' brain activity was significantly more synchronous with the speaker's brain activity for highly predictive contexts in left posterior superior temporal gyrus (pSTG), an area previously associated with predictive auditory language processing. In this region, predictability differentially affected the temporal profiles of brain responses in the speaker and listeners respectively, in turn affecting correlated activity between the two: whereas pSTG activation increased with predictability in the speaker, listeners' pSTG activity instead decreased for more predictable sentences. Listeners additionally showed stronger BOLD responses for predictive images before sentence onset, suggesting that highly predictable contexts lead comprehenders to preactivate predicted words.

  4. Response-predictive gene expression profiling of glioma progenitor cells in vitro.

    Directory of Open Access Journals (Sweden)

    Sylvia Moeckel

    Full Text Available High-grade gliomas are amongst the most deadly human tumors. Treatment results are disappointing. Still, in several trials around 20% of patients respond to therapy. To date, diagnostic strategies to identify patients that will profit from a specific therapy do not exist.In this study, we used serum-free short-term treated in vitro cell cultures to predict treatment response in vitro. This approach allowed us (a to enrich specimens for brain tumor initiating cells and (b to confront cells with a therapeutic agent before expression profiling.As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed to predict therapy-induced impairment of proliferation in vitro.For the tyrosine kinase inhibitor Sunitinib used in this dataset, the approach revealed additional predictive information in comparison to the evaluation of classical signaling analysis.

  5. Skin conductance response to the pain of others predicts later costly helping.

    Directory of Open Access Journals (Sweden)

    Grit Hein

    Full Text Available People show autonomic responses when they empathize with the suffering of another person. However, little is known about how these autonomic changes are related to prosocial behavior. We measured skin conductance responses (SCRs and affect ratings in participants while either receiving painful stimulation themselves, or observing pain being inflicted on another person. In a later session, they could prevent the infliction of pain in the other by choosing to endure pain themselves. Our results show that the strength of empathy-related vicarious skin conductance responses predicts later costly helping. Moreover, the higher the match between SCR magnitudes during the observation of pain in others and SCR magnitude during self pain, the more likely a person is to engage in costly helping. We conclude that prosocial motivation is fostered by the strength of the vicarious autonomic response as well as its match with first-hand autonomic experience.

  6. NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

    Directory of Open Access Journals (Sweden)

    Shunichi Kosugi

    2014-09-01

    Full Text Available The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS. Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

  7. Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

    Science.gov (United States)

    Naik, P K; Singh, T; Singh, H

    2009-07-01

    Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

  8. Volumetric PET/CT parameters predict local response of head and neck squamous cell carcinoma to chemoradiotherapy

    International Nuclear Information System (INIS)

    Hanamoto, Atsushi; Tatsumi, Mitsuaki; Takenaka, Yukinori; Hamasaki, Toshimitsu; Yasui, Toshimichi; Nakahara, Susumu; Yamamoto, Yoshifumi; Seo, Yuji; Isohashi, Fumiaki; Ogawa, Kazuhiko; Hatazawa, Jun; Inohara, Hidenori

    2014-01-01

    It is not well established whether pretreatment 18 F-FDG PET/CT can predict local response of head and neck squamous cell carcinoma (HNSCC) to chemoradiotherapy (CRT). We examined 118 patients: 11 with nasopharyngeal cancer (NPC), 30 with oropharyngeal cancer (OPC), and 77 with laryngohypopharyngeal cancer (LHC) who had completed CRT. PET/CT parameters of primary tumor, including metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum and mean standardized uptake value (SUV max and SUV mean ), were correlated with local response, according to primary site and human papillomavirus (HPV) status. Receiver-operating characteristic analyses were made to access predictive values of the PET/CT parameters, while logistic regression analyses were used to identify independent predictors. Area under the curve (AUC) of the PET/CT parameters ranged from 0.53 to 0.63 in NPC and from 0.50 to 0.54 in OPC. HPV-negative OPC showed AUC ranging from 0.51 to 0.58, while all of HPV-positive OPCs showed complete response. In contrast, AUC ranged from 0.71 to 0.90 in LHC. Moreover, AUCs of MTV and TLG were significantly higher than those of SUV max and SUV mean (P < 0.01). After multivariate analysis, high MTV >25.0 mL and high TLG >144.8 g remained as independent, significant predictors of incomplete response compared with low MTV (odds ratio [OR], 13.4; 95% confidence interval [CI], 2.5–72.9; P = 0.003) and low TLG (OR, 12.8; 95% CI, 2.4–67.9; P = 0.003), respectively. In conclusion, predictive efficacy of pretreatment 18 F-FDG PET/CT varies with different primary sites and chosen parameters. Local response of LHC is highly predictable by volume-based PET/CT parameters

  9. Anthropometry and physical activity level in the prediction of metabolic syndrome in children.

    Science.gov (United States)

    Andaki, Alynne Christian Ribeiro; Tinôco, Adelson Luiz Araújo; Mendes, Edmar Lacerda; Andaki Júnior, Roberto; Hills, Andrew P; Amorim, Paulo Roberto S

    2014-10-01

    To evaluate the effectiveness of anthropometric measures and physical activity level in the prediction of metabolic syndrome (MetS) in children. Cross-sectional study with children from public and private schools. Children underwent an anthropometric assessment, blood pressure measurement and biochemical evaluation of serum for determination of TAG, HDL-cholesterol and glucose. Physical activity level was calculated and number of steps per day obtained using a pedometer for seven consecutive days. Viçosa, south-eastern Brazil. Boys and girls (n 187), mean age 9·90 (SD 0·7) years. Conicity index, sum of four skinfolds, physical activity level and number of steps per day were accurate in predicting MetS in boys. Anthropometric indicators were accurate in predicting MetS for girls, specifically BMI, waist circumference measured at the narrowest point and at the level of the umbilicus, four skinfold thickness measures evaluated separately, the sum of subscapular and triceps skinfold thickness, the sum of four skinfolds and body fat percentage. The sum of four skinfolds was the most accurate method in predicting MetS in both genders.

  10. Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

    Science.gov (United States)

    Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

    2017-09-01

    We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Elevation in inflammatory serum biomarkers predicts response to trastuzumab-containing therapy.

    Directory of Open Access Journals (Sweden)

    Ahmed A Alkhateeb

    Full Text Available Approximately half of all HER2/neu-overexpressing breast cancer patients do not respond to trastuzumab-containing therapy. Therefore, there remains an urgent and unmet clinical need for the development of predictive biomarkers for trastuzumab response. Recently, several lines of evidence have demonstrated that the inflammatory tumor microenvironment is a major contributor to therapy resistance in breast cancer. In order to explore the predictive value of inflammation in breast cancer patients, we measured the inflammatory biomarkers serum ferritin and C-reactive protein (CRP in 66 patients immediately before undergoing trastuzumab-containing therapy and evaluated their progression-free and overall survival. The elevation in pre-treatment serum ferritin (>250 ng/ml or CRP (>7.25 mg/l was a significant predictor of reduced progression-free survival and shorter overall survival. When patients were stratified based on their serum ferritin and CRP levels, patients with elevation in both inflammatory biomarkers had a markedly poorer response to trastuzumab-containing therapy. Therefore, the elevation in inflammatory serum biomarkers may reflect a pathological state that decreases the clinical efficacy of this therapy. Anti-inflammatory drugs and life-style changes to decrease inflammation in cancer patients should be explored as possible strategies to sensitize patients to anti-cancer therapeutics.

  12. DRD2 genotype predicts prefrontal activity during working memory after stimulation of D2 receptors with bromocriptine.

    Science.gov (United States)

    Gelao, Barbara; Fazio, Leonardo; Selvaggi, Pierluigi; Di Giorgio, Annabella; Taurisano, Paolo; Quarto, Tiziana; Romano, Raffaella; Porcelli, Annamaria; Mancini, Marina; Masellis, Rita; Ursini, Gianluca; De Simeis, Giuseppe; Caforio, Grazia; Ferranti, Laura; Lo Bianco, Luciana; Rampino, Antonio; Todarello, Orlando; Popolizio, Teresa; Blasi, Giuseppe; Bertolino, Alessandro

    2014-06-01

    Pharmacological stimulation of D2 receptors modulates prefrontal neural activity associated with working memory (WM) processing. The T allele of a functional single-nucleotide polymorphism (SNP) within DRD2 (rs1076560 G > T) predicts reduced relative expression of the D2S receptor isoform and less efficient neural cortical responses during WM tasks. We used functional MRI to test the hypothesis that DRD2 rs1076560 genotype interacts with pharmacological stimulation of D2 receptors with bromocriptine on prefrontal responses during different loads of a spatial WM task (N-Back). Fifty-three healthy subjects (38 GG and 15 GT) underwent two 3-T functional MRI scans while performing the 1-, 2- and 3-Back versions of the N-Back WM task. Before the imaging sessions, either bromocriptine or placebo was administered to all subjects in a counterbalanced order. A factorial repeated-measures ANOVA within SPM8 (p < 0.05, family-wise error corrected) was used. On bromocriptine, GG subjects had reduced prefrontal activity at 3-Back together with a significant decrement in performance, compared with placebo. On the other hand, GT subjects had lower activity for the same level of performance at 1-Back but a trend for reduced behavioral performance in the face of unchanged activity at 2-Back. These results indicate that bromocriptine stimulation modulates prefrontal activity in terms of disengagement or of efficiency depending on DRD2 genotype and working memory load.

  13. Spontaneous brain activity predicts learning ability of foreign sounds.

    Science.gov (United States)

    Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

    2013-05-29

    Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

  14. A Personalized Approach to Biological Therapy Using Prediction of Clinical Response Based on MRP8/14 Serum Complex Levels in Rheumatoid Arthritis Patients.

    Directory of Open Access Journals (Sweden)

    S C Nair

    Full Text Available Measurement of MRP8/14 serum levels has shown potential in predicting clinical response to different biological agents in rheumatoid arthritis (RA. We aimed to develop a treatment algorithm based on a prediction score using MRP8/14 measurements and clinical parameters predictive for response to different biological agents.Baseline serum levels of MRP8/14 were measured in 170 patients starting treatment with infliximab, adalimumab or rituximab. We used logistic regression analysis to develop a predictive score for clinical response at 16 weeks. MRP8/14 levels along with clinical variables at baseline were investigated. We also investigated how the predictive effect of MRP8/14 was modified by drug type. A treatment algorithm was developed based on categorizing the expected response per drug type as high, intermediate or low for each patient and optimal treatment was defined. Finally, we present the utility of using this treatment algorithm in clinical practice.The probability of response increased with higher baseline MRP8/14 complex levels (OR = 1.39, differentially between the TNF-blockers and rituximab (OR of interaction term = 0.78, and also increased with higher DAS28 at baseline (OR = 1.28. Rheumatoid factor positivity, functional disability (a higher HAQ, and previous use of a TNF-inhibitor decreased the probability of response. Based on the treatment algorithm 80 patients would have been recommended for anti-TNF treatment, 8 for rituximab, 13 for another biological treatment (other than TNFi or rituximab and for 69 no recommendation was made. The predicted response rates matched the observed response in the cohort well. On group level the predicted response based on the algorithm resulted in a modest 10% higher response rate in our cohort with much higher differences in response probability in individual patients treated contrary to treatment recommendation.Prediction of response using MRP8/14 levels along with clinical predictors has

  15. Epigenetic Regulation of KLHL34 Predictive of Pathologic Response to Preoperative Chemoradiation Therapy in Rectal Cancer Patients

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Ye J. [Department of Surgery, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Institute of Innovative Cancer Research and Asan Institute for Life Sciences, Asan Medical Center, Seoul (Korea, Republic of); Kim, Chan W. [Department of Surgery, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Roh, Seon A. [Department of Surgery, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Institute of Innovative Cancer Research and Asan Institute for Life Sciences, Asan Medical Center, Seoul (Korea, Republic of); Cho, Dong H. [Institute of Innovative Cancer Research and Asan Institute for Life Sciences, Asan Medical Center, Seoul (Korea, Republic of); Graduate School of East-West Medical Science, Kyung Hee University, Gyeonggi-do (Korea, Republic of); Park, Jong L.; Kim, Seon Y. [Medical Genomics Research Center, Korea Research Institute of Bioscience & Biotechnology, Daejeon (Korea, Republic of); Kim, Jong H. [Department of Radiation Oncology, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Choi, Eun K. [Department of Radiation Oncology, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Institute of Innovative Cancer Research and Asan Institute for Life Sciences, Asan Medical Center, Seoul (Korea, Republic of); Kim, Yong S., E-mail: yongsung@kribb.re.kr [Medical Genomics Research Center, Korea Research Institute of Bioscience & Biotechnology, Daejeon (Korea, Republic of); Institute of Innovative Cancer Research and Asan Institute for Life Sciences, Asan Medical Center, Seoul (Korea, Republic of); Kim, Jin C., E-mail: jckim@amc.seoul.kr [Department of Surgery, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Institute of Innovative Cancer Research and Asan Institute for Life Sciences, Asan Medical Center, Seoul (Korea, Republic of)

    2015-03-01

    Purpose: Prediction of individual responsiveness to preoperative chemoradiation therapy (CRT) is urgently needed in patients with poorly responsive locally advanced rectal cancer (LARC). Methods and Materials: Candidate methylation genes associated with radiosensitivity were identified using a 3-step process. In the first step, genome-wide screening of methylation genes was performed in correlation with histopathologic tumor regression grade in 45 patients with LARC. In the second step, the methylation status of selected sites was analyzed by pyrosequencing in 67 LARC patients, including 24 patients analyzed in the first step. Finally, colorectal cancer cell clones with stable KLHL34 knockdown were generated and tested for cellular sensitivity to radiation. Results: Genome-wide screening identified 7 hypermethylated CpG sites (DZIP1 cg24107021, DZIP1 cg26886381, ZEB1 cg04430381, DKK3 cg041006961, STL cg00991794, KLHL34 cg01828474, and ARHGAP6 cg07828380) associated with preoperative CRT responses. Radiosensitivity in patients with hypermethylated KLHL34 cg14232291 was confirmed by pyrosequencing in additional cohorts. Knockdown of KLHL34 significantly reduced colony formation (KLHL34 sh#1: 20.1%, P=.0001 and KLHL34 sh#2: 15.8%, P=.0002), increased the cytotoxicity (KLHL34 sh#1: 14.8%, P=.019 and KLHL34 sh#2: 17.9%, P=.007) in LoVo cells, and increased radiation-induced caspase-3 activity and the sub-G1 population of cells. Conclusions: The methylation status of KLHL34 cg14232291 may be a predictive candidate of sensitivity to preoperative CRT, although further validation is needed in large cohorts using various cell types.

  16. Epigenetic Regulation of KLHL34 Predictive of Pathologic Response to Preoperative Chemoradiation Therapy in Rectal Cancer Patients

    International Nuclear Information System (INIS)

    Ha, Ye J.; Kim, Chan W.; Roh, Seon A.; Cho, Dong H.; Park, Jong L.; Kim, Seon Y.; Kim, Jong H.; Choi, Eun K.; Kim, Yong S.; Kim, Jin C.

    2015-01-01

    Purpose: Prediction of individual responsiveness to preoperative chemoradiation therapy (CRT) is urgently needed in patients with poorly responsive locally advanced rectal cancer (LARC). Methods and Materials: Candidate methylation genes associated with radiosensitivity were identified using a 3-step process. In the first step, genome-wide screening of methylation genes was performed in correlation with histopathologic tumor regression grade in 45 patients with LARC. In the second step, the methylation status of selected sites was analyzed by pyrosequencing in 67 LARC patients, including 24 patients analyzed in the first step. Finally, colorectal cancer cell clones with stable KLHL34 knockdown were generated and tested for cellular sensitivity to radiation. Results: Genome-wide screening identified 7 hypermethylated CpG sites (DZIP1 cg24107021, DZIP1 cg26886381, ZEB1 cg04430381, DKK3 cg041006961, STL cg00991794, KLHL34 cg01828474, and ARHGAP6 cg07828380) associated with preoperative CRT responses. Radiosensitivity in patients with hypermethylated KLHL34 cg14232291 was confirmed by pyrosequencing in additional cohorts. Knockdown of KLHL34 significantly reduced colony formation (KLHL34 sh#1: 20.1%, P=.0001 and KLHL34 sh#2: 15.8%, P=.0002), increased the cytotoxicity (KLHL34 sh#1: 14.8%, P=.019 and KLHL34 sh#2: 17.9%, P=.007) in LoVo cells, and increased radiation-induced caspase-3 activity and the sub-G1 population of cells. Conclusions: The methylation status of KLHL34 cg14232291 may be a predictive candidate of sensitivity to preoperative CRT, although further validation is needed in large cohorts using various cell types

  17. Nurse-Administered, Gut-Directed Hypnotherapy in IBS: Efficacy and Factors Predicting a Positive Response.

    Science.gov (United States)

    Lövdahl, Jenny; Ringström, Gisela; Agerforz, Pia; Törnblom, Hans; Simrén, Magnus

    2015-07-01

    Hypnotherapy is an effective treatment in irritable bowel syndrome (IBS). It is often delivered by a psychotherapist and is costly and time consuming. Nurse-administered hypnotherapy could increase availability and reduce costs. In this study the authors evaluate the effectiveness of nurse-administered, gut-directed hypnotherapy and identify factors predicting treatment outcome. Eighty-five patients were included in the study. Participants received hypnotherapy by a nurse once/week for 12 weeks. Patients reported marked improvement in gastrointestinal (GI) and extra-colonic symptoms after treatment, as well as a reduction in GI-specific anxiety, general anxiety, and depression. Fifty-eight percent were responders after the 12 weeks treatment period, and of these 82% had a favorable clinical response already at week 6. Women were more likely than men to respond favorably to the treatment. Nurse-administered hypnotherapy is an effective treatment for IBS. Being female and reporting a favorable response to treatment by week 6 predicted a positive treatment response at the end of the 12 weeks treatment period.

  18. Predicting response to incretin-based therapy

    Directory of Open Access Journals (Sweden)

    Agrawal N

    2011-04-01

    Full Text Available Sanjay Kalra1, Bharti Kalra2, Rakesh Sahay3, Navneet Agrawal41Department of Endocrinology, 2Department of Diabetology, Bharti Hospital, Karnal, India; 3Department of Endocrinology, Osmania Medical College, Hyderabad, India; 4Department of Medicine, GR Medical College, Gwalior, IndiaAbstract: There are two important incretin hormones, glucose-dependent insulin tropic polypeptide (GIP and glucagon-like peptide-1 (GLP-1. The biological activities of GLP-1 include stimulation of glucose-dependent insulin secretion and insulin biosynthesis, inhibition of glucagon secretion and gastric emptying, and inhibition of food intake. GLP-1 appears to have a number of additional effects in the gastrointestinal tract and central nervous system. Incretin based therapy includes GLP-1 receptor agonists like human GLP-1 analogs (liraglutide and exendin-4 based molecules (exenatide, as well as DPP-4 inhibitors like sitagliptin, vildagliptin and saxagliptin. Most of the published studies showed a significant reduction in HbA1c using these drugs. A critical analysis of reported data shows that the response rate in terms of target achievers of these drugs is average. One of the first actions identified for GLP-1 was the glucose-dependent stimulation of insulin secretion from islet cell lines. Following the detection of GLP-1 receptors on islet beta cells, a large body of evidence has accumulated illustrating that GLP-1 exerts multiple actions on various signaling pathways and gene products in the ß cell. GLP-1 controls glucose homeostasis through well-defined actions on the islet ß cell via stimulation of insulin secretion and preservation and expansion of ß cell mass. In summary, there are several factors determining the response rate to incretin therapy. Currently minimal clinical data is available to make a conclusion. Key factors appear to be duration of diabetes, obesity, presence of autonomic neuropathy, resting energy expenditure, plasma glucagon levels and

  19. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    Energy Technology Data Exchange (ETDEWEB)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A [Duke University Medical Center, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States)

    2014-06-15

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

  20. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    International Nuclear Information System (INIS)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

    2014-01-01

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

  1. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    Energy Technology Data Exchange (ETDEWEB)

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  2. Reassessment of the thermospheric response to geomagnetic activity at low latitudes

    International Nuclear Information System (INIS)

    Berger, C.; Barlier, F.; Ill, M.

    1988-01-01

    The present study takes advantage of measurements made at low latitudes by the Cactus accelerometer. From such measurements the response of several thermospheric parameters to geomagnetic activity can be simultaneously and reliably retrieved: total density, density scale height, vertical density scale height gradient, temperature, O/N 2 ratio and mean molecular mass. On investigation their behaviour exhibits a diurnal variation, some features of which have not been described, especially in the case of strong geomagnetic storms. In particular, the night scale height response appears to be stronger than the day one while its vertical gradients increase by day and slightly decrease at night. The temperature increase is higher by day while the O/N 2 ratio decreases by day, and increases at night at constant pressure level as well as at fixed height. By day, significant vertical temperature gradients are also found. These results as well as others are analysed in the light of existing theories and compared to the predictions of existing thermospheric models. Strong meridional winds at night, heat transport through thermal conductivity as well as wave dissipation during the day might be factors helping to account for such a behaviour

  3. Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

    Science.gov (United States)

    Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

    2012-01-01

    Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

  4. Matrix Metalloproteinase-9/Neutrophil Gelatinase-Associated Lipocalin Complex Activity in Human Glioma Samples Predicts Tumor Presence and Clinical Prognosis

    Directory of Open Access Journals (Sweden)

    Ming-Fa Liu

    2015-01-01

    Full Text Available Matrix metalloproteinase-9/neutrophil gelatinase-associated lipocalin (MMP-9/NGAL complex activity is elevated in brain tumors and may serve as a molecular marker for brain tumors. However, the relationship between MMP-9/NGAL activity in brain tumors and patient prognosis and treatment response remains unclear. Here, we compared the clinical characteristics of glioma patients with the MMP-9/NGAL activity measured in their respective tumor and urine samples. Using gelatin zymography assays, we found that MMP-9/NGAL activity was significantly increased in tumor tissues (TT and preoperative urine samples (Preop-1d urine. Activity was reduced by seven days after surgery (Postop-1w urine and elevated again in cases of tumor recurrence. The MMP-9/NGAL status correlated well with MRI-based tumor assessments. These findings suggest that MMP-9/NGAL activity could be a novel marker to detect gliomas and predict the clinical outcome of patients.

  5. Mirror neuron activation as a function of explicit learning: changes in mu-event-related power after learning novel responses to ideomotor compatible, partially compatible, and non-compatible stimuli.

    Science.gov (United States)

    Behmer, Lawrence P; Fournier, Lisa R

    2016-11-01

    Questions regarding the malleability of the mirror neuron system (MNS) continue to be debated. MNS activation has been reported when people observe another person performing biological goal-directed behaviors, such as grasping a cup. These findings support the importance of mapping goal-directed biological behavior onto one's motor repertoire as a means of understanding the actions of others. Still, other evidence supports the Associative Sequence Learning (ASL) model which predicts that the MNS responds to a variety of stimuli after sensorimotor learning, not simply biological behavior. MNS activity develops as a consequence of developing stimulus-response associations between a stimulus and its motor outcome. Findings from the ideomotor literature indicate that stimuli that are more ideomotor compatible with a response are accompanied by an increase in response activation compared to less compatible stimuli; however, non-compatible stimuli robustly activate a constituent response after sensorimotor learning. Here, we measured changes in the mu-rhythm, an EEG marker thought to index MNS activity, predicting that stimuli that differ along dimensions of ideomotor compatibility should show changes in mirror neuron activation as participants learn the respective stimulus-response associations. We observed robust mu-suppression for ideomotor-compatible hand actions and partially compatible dot animations prior to learning; however, compatible stimuli showed greater mu-suppression than partially or non-compatible stimuli after explicit learning. Additionally, non-compatible abstract stimuli exceeded baseline only after participants explicitly learned the motor responses associated with the stimuli. We conclude that the empirical differences between the biological and ASL accounts of the MNS can be explained by Ideomotor Theory. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  6. Posterior superior temporal sulcus responses predict perceived pleasantness of skin stroking

    Directory of Open Access Journals (Sweden)

    Monika Davidovic

    2016-09-01

    Full Text Available Love and affection is expressed through a range of physically intimate gestures, including caresses. Recent studies suggest that posterior temporal lobe areas typically associated with visual processing of social cues also respond to interpersonal touch. Here, we asked whether these areas are selective to caress-like skin stroking. We collected functional magnetic resonance imaging (fMRI data from 23 healthy participants and compared brain responses to skin stroking and vibration. We did not find any significant differences between stroking and vibration in the posterior temporal lobe; however, right posterior superior temporal sulcus (pSTS responses predicted healthy participant's perceived pleasantness of skin stroking, but not vibration. These findings link right pSTS responses to individual variability in perceived pleasantness of caress-like tactile stimuli. We speculate that the right pSTS may play a role in the translation of tactile stimuli into positively valenced, socially relevant interpersonal touch and that this system may be affected in disorders associated with impaired attachment.

  7. Uncertainty in Predicting CCN Activity of Aged and Primary Aerosols

    Science.gov (United States)

    Zhang, Fang; Wang, Yuying; Peng, Jianfei; Ren, Jingye; Collins, Don; Zhang, Renyi; Sun, Yele; Yang, Xin; Li, Zhanqing

    2017-11-01

    Understanding particle CCN activity in diverse atmospheres is crucial when evaluating aerosol indirect effects. Here aerosols measured at three sites in China were categorized as different types for attributing uncertainties in CCN prediction in terms of a comprehensive data set including size-resolved CCN activity, size-resolved hygroscopic growth factor, and chemical composition. We show that CCN activity for aged aerosols is unexpectedly underestimated 22% at a supersaturation (S) of 0.2% when using κ-Kohler theory with an assumption of an internal mixture with measured bulk composition that has typically resulted in an overestimate of the CCN activity in previous studies. We conclude that the underestimation stems from neglect of the effect of aging/coating on particle hygroscopicity, which is not considered properly in most current models. This effect enhanced the hygroscopicity parameter (κ) by between 11% (polluted conditions) and 30% (clean days), as indicated in diurnal cycles of κ based on measurements by different instruments. In the urban Beijing atmosphere heavily influenced by fresh emissions, the CCN activity was overestimated by 45% at S = 0.2%, likely because of inaccurate assumptions of particle mixing state and because of variability of chemical composition over the particle size range. For both fresh and aged aerosols, CCN prediction exhibits very limited sensitivity to κSOA, implying a critical role of other factors like mixing of aerosol components within and between particles in regulating CCN activity. Our findings could help improving CCN parameterization in climate models.

  8. Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

    Science.gov (United States)

    Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

    2015-10-01

    Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley

  9. Finite element predictions of active buckling control of stiffened panels

    Science.gov (United States)

    Thompson, Danniella M.; Griffin, O. H., Jr.

    1993-04-01

    Materials systems and structures that can respond 'intelligently' to their environment are currently being proposed and investigated. A series of finite element analyses was performed to investigate the potential for active buckling control of two different stiffened panels by embedded shape memory alloy (SMA) rods. Changes in the predicted buckling load increased with the magnitude of the actuation level for a given structural concept. Increasing the number of actuators for a given concept yielded greater predicted increases in buckling load. Considerable control authority was generated with a small number of actuators, with greater authority demonstrated for those structural concepts where the activated SMA rods could develop greater forces and moments on the structure. Relatively simple and inexpensive analyses were performed with standard finite elements to determine such information, indicating the viability of these types of models for design purposes.

  10. The Features of the Normative-Legal Provision of Socially Responsible Activity

    Directory of Open Access Journals (Sweden)

    Pavlykivska Olha I.

    2018-01-01

    Full Text Available The article is aimed at researching the features of the normative-legal provision of socially responsible activity and providing recommendations for its improvement. As a result of the analysis of the world tendencies of standardization of socially responsible activity the scientific classification of standards has been suggested, which will allow to structure more effectively and use their information in the process of economic activity. The opinion is expressed that for a comprehensive assessment of socially responsible activity it is necessary to use several standards in combination, taking into consideration specifics of the activity of a particular enterprise. The most applied among them are: standards of social reporting series AA 1000, standard of social responsibility SA 8000, standard for reporting in the field of sustainable development GRI; Standard ISO 26000 «Guide to Social Responsibility». The author’s own definition of social responsibility has been formulated as an activity in which enterprise adheres to the principles of the social doing business, takes account first of all of the needs of stakeholders, has a positive impact on society, facilitates growth of reputation capital, reduces non-financial risks, which, as a result, contributes to maximizing profits for shareholders.

  11. Evaluation of In-111 DTPA-paclitaxel scintigraphy to predict response on murine tumors to paclitaxel

    International Nuclear Information System (INIS)

    Inoue, Tomio; Li, C.; Yang, D.J.

    1999-01-01

    Our goal was to determine whether scintigraphy with 111 In-DTPA-paclitaxel could predict the response to chemotherapy with paclitaxel. Ovarian carcinoma (OCA 1), mammary carcinoma (MCA-4), fibrosarcoma (FSA) and squamous cell carcinoma (SCC VII) were inoculated into the thighs of female C3Hf/Kam mice. Mice bearing 8 mm tumors were treated with paclitaxel (40 mg/kg). The growth delay, which was defined as the time in days for tumors in the treated groups to grow from 8 to 12 mm in diameter minus the time in days for tumors in the untreated control group to reach the same size, was measured to determine the effect of paclitaxel on the tumors. Sequential scintigraphy in mice bearing 10 to 14 mm tumors was conducted at 5, 30, 60, 120, 240 min and 24 hrs postinjection of 111 In-DTPA-paclitaxel (3.7 MBq) or 111 In-DTPA as a control tracer. The tumor uptakes (% injection dose/pixel) were determined. The growth delay of OCA 1, MCA-4, FSA and SCC VII tumors was 13.6, 4.0, -0.02 and -0.28 days, respectively. In other words, OCA 1 and MCA-4 were paclitaxel-sensitive tumors, whereas FSA and SCC VII were paclitaxel-resistant tumors. The tumor uptakes at 24 hrs postinjection of In-111 DTPA paclitaxel of OCA 1, MCA-4, FSA and SCC VII were 1.0 x 10 -3 , 1.6 x 10 -3 , 2.2 x 10 -3 and 9.0 x 10 -3 % injection dose/pixel, respectively. There was no correlation between the response to chemotherapy with paclitaxel and the tumor uptakes of 111 In-DTPA-paclitaxel. Scintigraphy with 111 In-DTPA-paclitaxel could not predict the response to paclitaxel chemotherapy. Although there was significant accumulation of the paclitaxel in the tumor cells, additional mechanisms must be operative for the agent to be effective against the neoplasm. 111 In-DTPA-paclitaxel activity is apparently different from that of paclitaxel with Cremophor. (author)

  12. Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

    Science.gov (United States)

    Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

    2016-02-19

    Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

  13. Prediction of placebo responses: A systematic review of the literature

    Directory of Open Access Journals (Sweden)

    Bjoern eHoring

    2014-10-01

    Full Text Available Objective: Predicting who responds to placebo treatment – and under which circumstances – has been a question of interest and investigation for generations. However, the literature is disparate and inconclusive. This review aims to identify publications that provide high quality data on the topic of placebo response (PR prediction. Methods: To identify studies concerned with PR prediction, independent searches were performed in an expert database (for all symptom modalities and in PubMed (for pain only. Articles were selected when a they assessed putative predictors prior to placebo treatment and b an adequate control group was included when the association of predictors and PRs were analyzed. Results: Twenty-one studies were identified, most with pain as dependent variable. Most predictors of PRs were psychological constructs related to actions, expected outcomes and the emotional valence attached to these events (goal-seeking, self-efficacy/-esteem, locus of control, optimism. Other predictors involved behavioural control (desire for control, eating restraint, personality variables (fun seeking, sensation seeking, neuroticism, biological markers (sex, a single nucleotide polymorphism related to dopamine metabolism. Finally, suggestibility and beliefs in expectation biases, body consciousness and baseline symptom severity were found to be predictive. Conclusions: While results are heterogeneous, some congruence of predictors can be identified. PRs mainly appear to be moderated by expectations of how the symptom might change after treatment, or the expectation of how symptom repetition can be coped with. It is suggested to include the listed constructs in future research. Furthermore, a closer look at variables moderating symptom change in control groups seems warranted.

  14. Predictive event modelling in multicenter clinical trials with waiting time to response.

    Science.gov (United States)

    Anisimov, Vladimir V

    2011-01-01

    A new analytic statistical technique for predictive event modeling in ongoing multicenter clinical trials with waiting time to response is developed. It allows for the predictive mean and predictive bounds for the number of events to be constructed over time, accounting for the newly recruited patients and patients already at risk in the trial, and for different recruitment scenarios. For modeling patient recruitment, an advanced Poisson-gamma model is used, which accounts for the variation in recruitment over time, the variation in recruitment rates between different centers and the opening or closing of some centers in the future. A few models for event appearance allowing for 'recurrence', 'death' and 'lost-to-follow-up' events and using finite Markov chains in continuous time are considered. To predict the number of future events over time for an ongoing trial at some interim time, the parameters of the recruitment and event models are estimated using current data and then the predictive recruitment rates in each center are adjusted using individual data and Bayesian re-estimation. For a typical scenario (continue to recruit during some time interval, then stop recruitment and wait until a particular number of events happens), the closed-form expressions for the predictive mean and predictive bounds of the number of events at any future time point are derived under the assumptions of Markovian behavior of the event progression. The technique is efficiently applied to modeling different scenarios for some ongoing oncology trials. Case studies are considered. Copyright © 2011 John Wiley & Sons, Ltd.

  15. Nomograms Predicting Response to Therapy and Outcomes After Bladder-Preserving Trimodality Therapy for Muscle-Invasive Bladder Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Coen, John J., E-mail: jcoen@harthosp.org [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Paly, Jonathan J.; Niemierko, Andrzej [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Kaufman, Donald S. [Department of Medical Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Heney, Niall M. [Department of Urology, Massachusetts General Hospital, Boston, Massachusetts (United States); Spiegel, Daphne Y.; Efstathiou, Jason A.; Zietman, Anthony L.; Shipley, William U. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)

    2013-06-01

    Purpose: Selective bladder preservation by use of trimodality therapy is an established management strategy for muscle-invasive bladder cancer. Individual disease features have been associated with response to therapy, likelihood of bladder preservation, and disease-free survival. We developed prognostic nomograms to predict the complete response rate, disease-specific survival, and likelihood of remaining free of recurrent bladder cancer or cystectomy. Methods and Materials: From 1986 to 2009, 325 patients were managed with selective bladder preservation at Massachusetts General Hospital (MGH) and had complete data adequate for nomogram development. Treatment consisted of a transurethral resection of bladder tumor followed by split-course chemoradiation. Patients with a complete response at midtreatment cystoscopic assessment completed radiation, whereas those with a lesser response underwent a prompt cystectomy. Prognostic nomograms were constructed predicting complete response (CR), disease-specific survival (DSS), and bladder-intact disease-free survival (BI-DFS). BI-DFS was defined as the absence of local invasive or regional recurrence, distant metastasis, bladder cancer-related death, or radical cystectomy. Results: The final nomograms included information on clinical T stage, presence of hydronephrosis, whether a visibly complete transurethral resection of bladder tumor was performed, age, sex, and tumor grade. The predictive accuracy of these nomograms was assessed. For complete response, the area under the receiving operating characteristic curve was 0.69. The Harrell concordance index was 0.61 for both DSS and BI-DFS. Conclusions: Our nomograms allow individualized estimates of complete response, DSS, and BI-DFS. They may assist patients and clinicians making important treatment decisions.

  16. Serum Adiponectin, Vitamin D, and Alpha-Fetoprotein in Children with Chronic Hepatitis C: Can They Predict Treatment Response?

    Directory of Open Access Journals (Sweden)

    Mohamed Ahmed Khedr

    2015-01-01

    Full Text Available Background & Aims. The currently available treatment for chronic hepatitis C (CHC in children is costly and with much toxicity. So, predicting the likelihood of response before starting therapy is important. Methods. Serum adiponectin, vitamin D, and alpha-fetoprotein (AFP were measured before starting pegylated-interferon/ribavirin therapy for 50 children with CHC. Another 21 healthy children were recruited as controls. Results. Serum adiponectin, vitamin D, and AFP were higher in the CHC group than healthy controls (p<0.0001, p=0.071, and p=0.87, resp.. In univariate analysis, serum adiponectin was significantly higher in responders than nonresponders (p<0.0001 and at a cutoff value ≥8.04 ng/mL it can predict treatment response by 77.8% sensitivity and 92.9% specificity, while both AFP and viremia were significantly lower in responders than nonresponders, p<0.0001 and p=0.0003, respectively, and at cutoff values ≤3.265 ng/mL and ≤235,384 IU/mL, respectively, they can predict treatment response with a sensitivity of 83.3% for both and specificity of 85.7% and 78.6%, respectively. In multivariate analysis, adiponectin was found to be the only independent predictor of treatment response (p=0.044. Conclusions. The pretreatment serum level of adiponectin can predict the likelihood of treatment response, thus avoiding toxicities for those unlikely to respond to therapy.

  17. Metabolic activity in the insular cortex and hypothalamus predicts hot flashes: an FDG-PET study.

    Science.gov (United States)

    Joffe, Hadine; Deckersbach, Thilo; Lin, Nancy U; Makris, Nikos; Skaar, Todd C; Rauch, Scott L; Dougherty, Darin D; Hall, Janet E

    2012-09-01

    Hot flashes are a common side effect of adjuvant endocrine therapies (AET; leuprolide, tamoxifen, aromatase inhibitors) that reduce quality of life and treatment adherence in breast cancer patients. Because hot flashes affect only some women, preexisting neurobiological traits might predispose to their development. Previous studies have implicated the insula during the perception of hot flashes and the hypothalamus in thermoregulatory dysfunction. The aim of the study was to understand whether neurobiological factors predict hot flashes. [18F]-Fluorodeoxyglucose (FDG) positron emission tomography (PET) brain scans coregistered with structural magnetic resonance imaging were used to determine whether metabolic activity in the insula and hypothalamic thermoregulatory and estrogen-feedback regions measured before and in response to AET predict hot flashes. Findings were correlated with CYP2D6 genotype because of CYP2D6 polymorphism associations with tamoxifen-induced hot flashes. We measured regional cerebral metabolic rate of glucose uptake (rCMRglu) in the insula and hypothalamus on FDG-PET. Of 18 women without hot flashes who began AET, new-onset hot flashes were reported by 10 (55.6%) and were detected objectively in nine (50%) participants. Prior to the use of all AET, rCMRglu in the insula (P ≤ 0.01) and hypothalamic thermoregulatory (P = 0.045) and estrogen-feedback (P = 0.007) regions was lower in women who reported developing hot flashes. In response to AET, rCMRglu was further reduced in the insula in women developing hot flashes (P ≤ 0.02). Insular and hypothalamic rCMRglu levels were lower in intermediate than extensive CYP2D6 metabolizers. Trait neurobiological characteristics predict hot flashes. Genetic variability in CYP2D6 may underlie the neurobiological predisposition to hot flashes induced by AET.

  18. Identifying predictive features in drug response using machine learning: opportunities and challenges.

    Science.gov (United States)

    Vidyasagar, Mathukumalli

    2015-01-01

    This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

  19. Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes.

    Science.gov (United States)

    Lenka, Sangram K; Lohia, Bikash; Kumar, Abhay; Chinnusamy, Viswanathan; Bansal, Kailash C

    2009-02-01

    Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

  20. A study on the predictability of acute lymphoblastic leukaemia response to treatment using a hybrid oncosimulator.

    Science.gov (United States)

    Ouzounoglou, Eleftherios; Kolokotroni, Eleni; Stanulla, Martin; Stamatakos, Georgios S

    2018-02-06

    Efficient use of Virtual Physiological Human (VPH)-type models for personalized treatment response prediction purposes requires a precise model parameterization. In the case where the available personalized data are not sufficient to fully determine the parameter values, an appropriate prediction task may be followed. This study, a hybrid combination of computational optimization and machine learning methods with an already developed mechanistic model called the acute lymphoblastic leukaemia (ALL) Oncosimulator which simulates ALL progression and treatment response is presented. These methods are used in order for the parameters of the model to be estimated for retrospective cases and to be predicted for prospective ones. The parameter value prediction is based on a regression model trained on retrospective cases. The proposed Hybrid ALL Oncosimulator system has been evaluated when predicting the pre-phase treatment outcome in ALL. This has been correctly achieved for a significant percentage of patient cases tested (approx. 70% of patients). Moreover, the system is capable of denying the classification of cases for which the results are not trustworthy enough. In that case, potentially misleading predictions for a number of patients are avoided, while the classification accuracy for the remaining patient cases further increases. The results obtained are particularly encouraging regarding the soundness of the proposed methodologies and their relevance to the process of achieving clinical applicability of the proposed Hybrid ALL Oncosimulator system and VPH models in general.

  1. Dissociating action-effect activation and effect-based response selection.

    Science.gov (United States)

    Schwarz, Katharina A; Pfister, Roland; Wirth, Robert; Kunde, Wilfried

    2018-05-25

    Anticipated action effects have been shown to govern action selection and initiation, as described in ideomotor theory, and they have also been demonstrated to determine crosstalk between different tasks in multitasking studies. Such effect-based crosstalk was observed not only in a forward manner (with a first task influencing performance in a following second task) but also in a backward manner (the second task influencing the preceding first task), suggesting that action effect codes can become activated prior to a capacity-limited processing stage often denoted as response selection. The process of effect-based response production, by contrast, has been proposed to be capacity-limited. These observations jointly suggest that effect code activation can occur independently of effect-based response production, though this theoretical implication has not been tested directly at present. We tested this hypothesis by employing a dual-task set-up in which we manipulated the ease of effect-based response production (via response-effect compatibility) in an experimental design that allows for observing forward and backward crosstalk. We observed robust crosstalk effects and response-effect compatibility effects alike, but no interaction between both effects. These results indicate that effect activation can occur in parallel for several tasks, independently of effect-based response production, which is confined to one task at a time. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Predicting Treatment