WorldWideScience

Sample records for species-related diseases model

  1. Ameliorative effects of low dose/low dose-rate irradiation on reactive oxygen species-related diseases model mice

    International Nuclear Information System (INIS)

    Nomura, Takaharu

    2008-01-01

    Living organisms have developed complex biological system which protects themselves against environmental radiation, and irradiation with proper dose, dose-rate and irradiation time can stimulate their biological responses against oxidative stress evoked by the irradiation. Because reactive oxygen species are involved in various human diseases, non-toxic low dose/low dose-rate radiation can be utilized for the amelioration of such diseases. In this study, we used mouse experimental models for fatty liver, nephritis, diabetes, and ageing to elucidate the ameliorative effect of low dose/low dose-rate radiation in relation to endogenous antioxidant activity. Single irradiation at 0.5 Gy ameliorates carbon tetrachloride-induced fatty liver. The irradiation increases hepatic anti-oxidative system involving glutathione and glutathione peroxidase, suggesting that endogenous radical scavenger is essential for the ameliorative effect of low dose radiation on carbon tetrachloride-induced fatty liver. Single irradiation at 0.5 Gy ameliorates ferric nitrilotriacetate-induced nephritis. The irradiation increases catalase and decreases superoxide dismutase in kidney. The result suggests that low dose radiation reduced generation of hydroxide radical generation by reducing cellular hydroperoxide level. Single irradiation at 0.5 Gy at 12 week of age ameliorates incidence of type I diabetes in non-obese diabetic (NOD) mice through the suppression of inflammatory activity of splenocytes, and resultant apoptosis of β-cells in pancreas. The irradiation activities of superoxide dismutase and catalase, which coordinately diminish intracellular reactive oxygen species. Continuous irradiation at 0.70 mGy/hr from 10 week of age elongates life span, and suppresses alopecia in type II diabetesmice. The irradiation improved glucose clearance without affecting insulin-resistance, and increased pancreatic catalase activity. The results suggest that continuous low dose-rate irradiation protect

  2. Animal Models of Cardiovascular Diseases

    Directory of Open Access Journals (Sweden)

    Carlos Zaragoza

    2011-01-01

    Full Text Available Cardiovascular diseases are the first leading cause of death and morbidity in developed countries. The use of animal models have contributed to increase our knowledge, providing new approaches focused to improve the diagnostic and the treatment of these pathologies. Several models have been developed to address cardiovascular complications, including atherothrombotic and cardiac diseases, and the same pathology have been successfully recreated in different species, including small and big animal models of disease. However, genetic and environmental factors play a significant role in cardiovascular pathophysiology, making difficult to match a particular disease, with a single experimental model. Therefore, no exclusive method perfectly recreates the human complication, and depending on the model, additional considerations of cost, infrastructure, and the requirement for specialized personnel, should also have in mind. Considering all these facts, and depending on the budgets available, models should be selected that best reproduce the disease being investigated. Here we will describe models of atherothrombotic diseases, including expanding and occlusive animal models, as well as models of heart failure. Given the wide range of models available, today it is possible to devise the best strategy, which may help us to find more efficient and reliable solutions against human cardiovascular diseases.

  3. Animal models of cardiovascular diseases.

    Science.gov (United States)

    Zaragoza, Carlos; Gomez-Guerrero, Carmen; Martin-Ventura, Jose Luis; Blanco-Colio, Luis; Lavin, Begoña; Mallavia, Beñat; Tarin, Carlos; Mas, Sebastian; Ortiz, Alberto; Egido, Jesus

    2011-01-01

    Cardiovascular diseases are the first leading cause of death and morbidity in developed countries. The use of animal models have contributed to increase our knowledge, providing new approaches focused to improve the diagnostic and the treatment of these pathologies. Several models have been developed to address cardiovascular complications, including atherothrombotic and cardiac diseases, and the same pathology have been successfully recreated in different species, including small and big animal models of disease. However, genetic and environmental factors play a significant role in cardiovascular pathophysiology, making difficult to match a particular disease, with a single experimental model. Therefore, no exclusive method perfectly recreates the human complication, and depending on the model, additional considerations of cost, infrastructure, and the requirement for specialized personnel, should also have in mind. Considering all these facts, and depending on the budgets available, models should be selected that best reproduce the disease being investigated. Here we will describe models of atherothrombotic diseases, including expanding and occlusive animal models, as well as models of heart failure. Given the wide range of models available, today it is possible to devise the best strategy, which may help us to find more efficient and reliable solutions against human cardiovascular diseases.

  4. Disease modeling in genetic kidney diseases: zebrafish.

    Science.gov (United States)

    Schenk, Heiko; Müller-Deile, Janina; Kinast, Mark; Schiffer, Mario

    2017-07-01

    Growing numbers of translational genomics studies are based on the highly efficient and versatile zebrafish (Danio rerio) vertebrate model. The increasing types of zebrafish models have improved our understanding of inherited kidney diseases, since they not only display pathophysiological changes but also give us the opportunity to develop and test novel treatment options in a high-throughput manner. New paradigms in inherited kidney diseases have been developed on the basis of the distinct genome conservation of approximately 70 % between zebrafish and humans in terms of existing gene orthologs. Several options are available to determine the functional role of a specific gene or gene sets. Permanent genome editing can be induced via complete gene knockout by using the CRISPR/Cas-system, among others, or via transient modification by using various morpholino techniques. Cross-species rescues succeeding knockdown techniques are employed to determine the functional significance of a target gene or a specific mutation. This article summarizes the current techniques and discusses their perspectives.

  5. Animal Models of Allergic Diseases

    Directory of Open Access Journals (Sweden)

    Domenico Santoro

    2014-12-01

    Full Text Available Allergic diseases have great impact on the quality of life of both people and domestic animals. They are increasing in prevalence in both animals and humans, possibly due to the changed lifestyle conditions and the decreased exposure to beneficial microorganisms. Dogs, in particular, suffer from environmental skin allergies and develop a clinical presentation which is very similar to the one of children with eczema. Thus, dogs are a very useful species to improve our understanding on the mechanisms involved in people’s allergies and a natural model to study eczema. Animal models are frequently used to elucidate mechanisms of disease and to control for confounding factors which are present in studies with patients with spontaneously occurring disease and to test new therapies that can be beneficial in both species. It has been found that drugs useful in one species can also have benefits in other species highlighting the importance of a comprehensive understanding of diseases across species and the value of comparative studies. The purpose of the current article is to review allergic diseases across species and to focus on how these diseases compare to the counterpart in people.

  6. Animal Models for Periodontal Disease

    Directory of Open Access Journals (Sweden)

    Helieh S. Oz

    2011-01-01

    Full Text Available Animal models and cell cultures have contributed new knowledge in biological sciences, including periodontology. Although cultured cells can be used to study physiological processes that occur during the pathogenesis of periodontitis, the complex host response fundamentally responsible for this disease cannot be reproduced in vitro. Among the animal kingdom, rodents, rabbits, pigs, dogs, and nonhuman primates have been used to model human periodontitis, each with advantages and disadvantages. Periodontitis commonly has been induced by placing a bacterial plaque retentive ligature in the gingival sulcus around the molar teeth. In addition, alveolar bone loss has been induced by inoculation or injection of human oral bacteria (e.g., Porphyromonas gingivalis in different animal models. While animal models have provided a wide range of important data, it is sometimes difficult to determine whether the findings are applicable to humans. In addition, variability in host responses to bacterial infection among individuals contributes significantly to the expression of periodontal diseases. A practical and highly reproducible model that truly mimics the natural pathogenesis of human periodontal disease has yet to be developed.

  7. Animal Models for Periodontal Disease

    Science.gov (United States)

    Oz, Helieh S.; Puleo, David A.

    2011-01-01

    Animal models and cell cultures have contributed new knowledge in biological sciences, including periodontology. Although cultured cells can be used to study physiological processes that occur during the pathogenesis of periodontitis, the complex host response fundamentally responsible for this disease cannot be reproduced in vitro. Among the animal kingdom, rodents, rabbits, pigs, dogs, and nonhuman primates have been used to model human periodontitis, each with advantages and disadvantages. Periodontitis commonly has been induced by placing a bacterial plaque retentive ligature in the gingival sulcus around the molar teeth. In addition, alveolar bone loss has been induced by inoculation or injection of human oral bacteria (e.g., Porphyromonas gingivalis) in different animal models. While animal models have provided a wide range of important data, it is sometimes difficult to determine whether the findings are applicable to humans. In addition, variability in host responses to bacterial infection among individuals contributes significantly to the expression of periodontal diseases. A practical and highly reproducible model that truly mimics the natural pathogenesis of human periodontal disease has yet to be developed. PMID:21331345

  8. Mathematical model on Alzheimer's disease.

    Science.gov (United States)

    Hao, Wenrui; Friedman, Avner

    2016-11-18

    Alzheimer disease (AD) is a progressive neurodegenerative disease that destroys memory and cognitive skills. AD is characterized by the presence of two types of neuropathological hallmarks: extracellular plaques consisting of amyloid β-peptides and intracellular neurofibrillary tangles of hyperphosphorylated tau proteins. The disease affects 5 million people in the United States and 44 million world-wide. Currently there is no drug that can cure, stop or even slow the progression of the disease. If no cure is found, by 2050 the number of alzheimer's patients in the U.S. will reach 15 million and the cost of caring for them will exceed $ 1 trillion annually. The present paper develops a mathematical model of AD that includes neurons, astrocytes, microglias and peripheral macrophages, as well as amyloid β aggregation and hyperphosphorylated tau proteins. The model is represented by a system of partial differential equations. The model is used to simulate the effect of drugs that either failed in clinical trials, or are currently in clinical trials. Based on these simulations it is suggested that combined therapy with TNF- α inhibitor and anti amyloid β could yield significant efficacy in slowing the progression of AD.

  9. Bioprinting technologies for disease modeling.

    Science.gov (United States)

    Memic, Adnan; Navaei, Ali; Mirani, Bahram; Cordova, Julio Alvin Vacacela; Aldhahri, Musab; Dolatshahi-Pirouz, Alireza; Akbari, Mohsen; Nikkhah, Mehdi

    2017-09-01

    There is a great need for the development of biomimetic human tissue models that allow elucidation of the pathophysiological conditions involved in disease initiation and progression. Conventional two-dimensional (2D) in vitro assays and animal models have been unable to fully recapitulate the critical characteristics of human physiology. Alternatively, three-dimensional (3D) tissue models are often developed in a low-throughput manner and lack crucial native-like architecture. The recent emergence of bioprinting technologies has enabled creating 3D tissue models that address the critical challenges of conventional in vitro assays through the development of custom bioinks and patient derived cells coupled with well-defined arrangements of biomaterials. Here, we provide an overview on the technological aspects of 3D bioprinting technique and discuss how the development of bioprinted tissue models have propelled our understanding of diseases' characteristics (i.e. initiation and progression). The future perspectives on the use of bioprinted 3D tissue models for drug discovery application are also highlighted.

  10. Mouse Models of Graves' Disease

    OpenAIRE

    Nagayama, Yuji

    2005-01-01

    Graves' disease is characterized by overstimulation of the thyroid gland with agonistic autoantibodies against the thyrotropin (TSH) receptor, leading to hyperthyroidism and diffuse hyperplasia of the thyroid gland. Our and other laboratories have recently established several animal models of Graves' hyperthyroidism with novel immunization approaches, i.e., in vivo expression of the TSH receptor by injection of syngeneic living cells co-expressing the TSH receptor and major histocompatibility...

  11. Bioprinting technologies for disease modeling

    DEFF Research Database (Denmark)

    Memic, Adnan; Navaei, Ali; Mirani, Bahram

    2017-01-01

    the critical characteristics of human physiology. Alternatively, three-dimensional (3D) tissue models are often developed in a low-throughput manner and lack crucial native-like architecture. The recent emergence of bioprinting technologies has enabled creating 3D tissue models that address the critical...... challenges of conventional in vitro assays through the development of custom bioinks and patient derived cells coupled with well-defined arrangements of biomaterials. Here, we provide an overview on the technological aspects of 3D bioprinting technique and discuss how the development of bioprinted tissue...... models have propelled our understanding of diseases’ characteristics (i.e. initiation and progression). The future perspectives on the use of bioprinted 3D tissue models for drug discovery application are also highlighted....

  12. Parathyroid diseases and animal models.

    Science.gov (United States)

    Imanishi, Yasuo; Nagata, Yuki; Inaba, Masaaki

    2012-01-01

    CIRCULATING CALCIUM AND PHOSPHATE ARE TIGHTLY REGULATED BY THREE HORMONES: the active form of vitamin D (1,25-dihydroxyvitamin D), fibroblast growth factor (FGF)-23, and parathyroid hormone (PTH). PTH acts to stimulate a rapid increment in serum calcium and has a crucial role in calcium homeostasis. Major target organs of PTH are kidney and bone. The oversecretion of the hormone results in hypercalcemia, caused by increased intestinal calcium absorption, reduced renal calcium clearance, and mobilization of calcium from bone in primary hyperparathyroidism. In chronic kidney disease, secondary hyperparathyroidism of uremia is observed in its early stages, and this finally develops into the autonomous secretion of PTH during maintenance hemodialysis. Receptors in parathyroid cells, such as the calcium-sensing receptor, vitamin D receptor, and FGF receptor (FGFR)-Klotho complex have crucial roles in the regulation of PTH secretion. Genes such as Cyclin D1, RET, MEN1, HRPT2, and CDKN1B have been identified in parathyroid diseases. Genetically engineered animals with these receptors and the associated genes have provided us with valuable information on the patho-physiology of parathyroid diseases. The application of these animal models is significant for the development of new therapies.

  13. Organoids: Modelling polycystic kidney disease

    Science.gov (United States)

    Romagnani, Paola

    2017-11-01

    Cysts were generated from organoids in vitro and the removal of adherent cues was shown to play a key role in polycystic kidney disease progression. These cysts resembled those of diseased tissue phenotypically and were capable of remodelling their microenvironment.

  14. Modeling human disease using organotypic cultures

    DEFF Research Database (Denmark)

    Schweiger, Pawel J; Jensen, Kim B

    2016-01-01

    animal models and in vitro cell culture systems. However, it has been exceedingly difficult to model disease at the tissue level. Since recently, the gap between cell line studies and in vivo modeling has been narrowing thanks to progress in biomaterials and stem cell research. Development of reliable 3D...... culture systems has enabled a rapid expansion of sophisticated in vitro models. Here we focus on some of the latest advances and future perspectives in 3D organoids for human disease modeling....

  15. Animal models of chronic obstructive pulmonary disease.

    Science.gov (United States)

    Pérez-Rial, Sandra; Girón-Martínez, Álvaro; Peces-Barba, Germán

    2015-03-01

    Animal models of disease have always been welcomed by the scientific community because they provide an approach to the investigation of certain aspects of the disease in question. Animal models of COPD cannot reproduce the heterogeneity of the disease and usually only manage to represent the disease in its milder stages. Moreover, airflow obstruction, the variable that determines patient diagnosis, not always taken into account in the models. For this reason, models have focused on the development of emphysema, easily detectable by lung morphometry, and have disregarded other components of the disease, such as airway injury or associated vascular changes. Continuous, long-term exposure to cigarette smoke is considered the main risk factor for this disease, justifying the fact that the cigarette smoke exposure model is the most widely used. Some variations on this basic model, related to exposure time, the association of other inducers or inhibitors, exacerbations or the use of transgenic animals to facilitate the identification of pathogenic pathways have been developed. Some variations or heterogeneity of this disease, then, can be reproduced and models can be designed for resolving researchers' questions on disease identification or treatment responses. Copyright © 2014 SEPAR. Published by Elsevier Espana. All rights reserved.

  16. Eight challenges in modelling infectious livestock diseases

    Directory of Open Access Journals (Sweden)

    E. Brooks-Pollock

    2015-03-01

    Full Text Available The transmission of infectious diseases of livestock does not differ in principle from disease transmission in any other animals, apart from that the aim of control is ultimately economic, with the influence of social, political and welfare constraints often poorly defined. Modelling of livestock diseases suffers simultaneously from a wealth and a lack of data. On the one hand, the ability to conduct transmission experiments, detailed within-host studies and track individual animals between geocoded locations make livestock diseases a particularly rich potential source of realistic data for illuminating biological mechanisms of transmission and conducting explicit analyses of contact networks. On the other hand, scarcity of funding, as compared to human diseases, often results in incomplete and partial data for many livestock diseases and regions of the world. In this overview of challenges in livestock disease modelling, we highlight eight areas unique to livestock that, if addressed, would mark major progress in the area.

  17. Huntington disease: Experimental models and therapeutic perspectives

    International Nuclear Information System (INIS)

    Serrano Sanchez, Teresa; Blanco Lezcano, Lisette; Garcia Minet, Rocio; Alberti Amador, Esteban; Diaz Armesto, Ivan and others

    2011-01-01

    Huntington's disease (HD) is a degenerative dysfunction of hereditary origin. Up to date there is not, an effective treatment to the disease which having lapsed 15 or 20 years advances inexorably, in a slow form, toward the total inability or death. This paper reviews the clinical and morphological characteristics of Huntington's disease as well as the experimental models more commonly used to study this disease, having as source the articles indexed in Medline data base, published in the last 20 years. Advantages and disadvantages of all experimental models to reproduce the disease as well as the perspectives to therapeutic assay have been also considered. the consent of outline reported about the toxic models, those induced by neurotoxins such as quinolinic acid, appears to be the most appropriate to reproduce the neuropathologic characteristic of the disease, an genetic models contributing with more evidence to the knowledge of the disease etiology. Numerous treatments ameliorate clinical manifestations, but none of them has been able to stop or diminish the affectations derived from neuronal loss. At present time it is possible to reproduce, at least partially, the characteristics of the disease in experimentation animals that allow therapy evaluation in HD. from the treatment view point, the more promissory seems to be transplantation of no neuronal cells, taking into account ethical issues and factibility. On the other hand the new technology of interference RNA emerges as a potential therapeutic tool for treatment in HD, and to respond basic questions on the development of the disease.

  18. Osteosarcoma models : understanding complex disease

    NARCIS (Netherlands)

    Mohseny, Alexander Behzad

    2012-01-01

    A mesenchymal stem cell (MSC) based osteosarcoma model was established. The model provided evidence for a MSC origin of osteosarcoma. Normal MSCs transformed spontaneously to osteosarcoma-like cells which was always accompanied by genomic instability and loss of the Cdkn2a locus. Accordingly loss of

  19. Animal models for human genetic diseases

    African Journals Online (AJOL)

    Sharif Sons

    The study of human genetic diseases can be greatly aided by animal models because of their similarity .... and gene targeting in embryonic stem cells) has been a powerful tool in .... endonucleases that are designed to make a doublestrand.

  20. Deterministic SLIR model for tuberculosis disease mapping

    Science.gov (United States)

    Aziz, Nazrina; Diah, Ijlal Mohd; Ahmad, Nazihah; Kasim, Maznah Mat

    2017-11-01

    Tuberculosis (TB) occurs worldwide. It can be transmitted to others directly through air when active TB persons sneeze, cough or spit. In Malaysia, it was reported that TB cases had been recognized as one of the most infectious disease that lead to death. Disease mapping is one of the methods that can be used as the prevention strategies since it can displays clear picture for the high-low risk areas. Important thing that need to be considered when studying the disease occurrence is relative risk estimation. The transmission of TB disease is studied through mathematical model. Therefore, in this study, deterministic SLIR models are used to estimate relative risk for TB disease transmission.

  1. Polycystic ovarian disease: animal models.

    Science.gov (United States)

    Mahajan, D K

    1988-12-01

    The reproductive systems of human beings and other vertebrates are grossly similar. In the ovary particularly, the biochemical and physiologic processes are identical not only in the formation of germ cells, the development of primordial follicles and their subsequent growth to Graafian follicles, and eventual ovulation but also in anatomic structure. In a noncarcinogenic human ovary, hypersecretion of androgen causes PCOD. Such hypersecretion may result from a nonpulsatile, constant elevated level of circulating LH or a disturbance in the action of neurotransmitters in the hypothalamus. In studying the pathophysiology of PCOD in humans, one must be aware of the limitations for manipulating the hypothalamic-pituitary axis. Although the rat is a polytocous rodent, the female has a regular ovarian cyclicity of 4 or 5 days, with distinct proestrus, estrus, and diestrus phases. Inasmuch as PCOD can be experimentally produced in the rat, that species is a good model for studying the pathophysiology of human PCOD. These PCOD models and their validity have been described: (1) estradiol-valerate, (2) DHA, (3) constant-light (LL), and (4) neonatally androgenized. Among these, the LL model is noninvasive and seems superior to the others for study of the pathophysiology of PCOD. The production of the polycystic ovarian condition in the rat by the injection of estrogens or androgens in neonate animals, or estradiol or DHA in adult rats, or the administration of antigonadotropins to these animals all cause a sudden appearance of the persistent estrus state by disturbing the metabolic and physiologic processes, whereas exposure of the adult rat to LL causes polycystic ovaries gradually, similar to what is seen in human idiopathic PCOD. After about 50 days of LL, the rat becomes anovulatory and the ovaries contain thickened tunica albuginea and many atretic follicles, and the tertiary follicles are considerably distended and cystic. The granulosa and theca cells appear normal

  2. A nonlocal spatial model for Lyme disease

    Science.gov (United States)

    Yu, Xiao; Zhao, Xiao-Qiang

    2016-07-01

    This paper is devoted to the study of a nonlocal and time-delayed reaction-diffusion model for Lyme disease with a spatially heterogeneous structure. In the case of a bounded domain, we first prove the existence of the positive steady state and a threshold type result for the disease-free system, and then establish the global dynamics for the model system in terms of the basic reproduction number. In the case of an unbound domain, we obtain the existence of the disease spreading speed and its coincidence with the minimal wave speed. At last, we use numerical simulations to verify our analytic results and investigate the influence of model parameters and spatial heterogeneity on the disease infection risk.

  3. Reproduction numbers of infectious disease models

    Directory of Open Access Journals (Sweden)

    Pauline van den Driessche

    2017-08-01

    Full Text Available This primer article focuses on the basic reproduction number, ℛ0, for infectious diseases, and other reproduction numbers related to ℛ0 that are useful in guiding control strategies. Beginning with a simple population model, the concept is developed for a threshold value of ℛ0 determining whether or not the disease dies out. The next generation matrix method of calculating ℛ0 in a compartmental model is described and illustrated. To address control strategies, type and target reproduction numbers are defined, as well as sensitivity and elasticity indices. These theoretical ideas are then applied to models that are formulated for West Nile virus in birds (a vector-borne disease, cholera in humans (a disease with two transmission pathways, anthrax in animals (a disease that can be spread by dead carcasses and spores, and Zika in humans (spread by mosquitoes and sexual contacts. Some parameter values from literature data are used to illustrate the results. Finally, references for other ways to calculate ℛ0 are given. These are useful for more complicated models that, for example, take account of variations in environmental fluctuation or stochasticity. Keywords: Basic reproduction number, Disease control, West Nile virus, Cholera, Anthrax, Zika virus

  4. Animal Models of Calcific Aortic Valve Disease

    Directory of Open Access Journals (Sweden)

    Krista L. Sider

    2011-01-01

    Full Text Available Calcific aortic valve disease (CAVD, once thought to be a degenerative disease, is now recognized to be an active pathobiological process, with chronic inflammation emerging as a predominant, and possibly driving, factor. However, many details of the pathobiological mechanisms of CAVD remain to be described, and new approaches to treat CAVD need to be identified. Animal models are emerging as vital tools to this end, facilitated by the advent of new models and improved understanding of the utility of existing models. In this paper, we summarize and critically appraise current small and large animal models of CAVD, discuss the utility of animal models for priority CAVD research areas, and provide recommendations for future animal model studies of CAVD.

  5. Seven challenges in modeling vaccine preventable diseases

    Directory of Open Access Journals (Sweden)

    C.J.E. Metcalf

    2015-03-01

    Full Text Available Vaccination has been one of the most successful public health measures since the introduction of basic sanitation. Substantial mortality and morbidity reductions have been achieved via vaccination against many infections, and the list of diseases that are potentially controllable by vaccines is growing steadily. We introduce key challenges for modeling in shaping our understanding and guiding policy decisions related to vaccine preventable diseases.

  6. Neurophysiology of Drosophila Models of Parkinson's Disease

    OpenAIRE

    West, Ryan J. H.; Furmston, Rebecca; Williams, Charles A. C.; Elliott, Christopher J. H.

    2015-01-01

    We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson's disease- (PD-) related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson's ...

  7. Humanized mouse models: Application to human diseases.

    Science.gov (United States)

    Ito, Ryoji; Takahashi, Takeshi; Ito, Mamoru

    2018-05-01

    Humanized mice are superior to rodents for preclinical evaluation of the efficacy and safety of drug candidates using human cells or tissues. During the past decade, humanized mouse technology has been greatly advanced by the establishment of novel platforms of genetically modified immunodeficient mice. Several human diseases can be recapitulated using humanized mice due to the improved engraftment and differentiation capacity of human cells or tissues. In this review, we discuss current advanced humanized mouse models that recapitulate human diseases including cancer, allergy, and graft-versus-host disease. © 2017 Wiley Periodicals, Inc.

  8. A mathematical model of Chagas disease transmission

    Science.gov (United States)

    Hidayat, Dayat; Nugraha, Edwin Setiawan; Nuraini, Nuning

    2018-03-01

    Chagas disease is a parasitic infection caused by protozoan Trypanosoma cruzi which is transmitted to human by insects of the subfamily Triatominae, including Rhodnius prolixus. This disease is a major problem in several countries of Latin America. A mathematical model of Chagas disease with separate vector reservoir and a neighboring human resident is constructed. The basic reproductive ratio is obtained and stability analysis of the equilibria is shown. We also performed sensitivity populations dynamics of infected humans and infected insects based on migration rate, carrying capacity, and infection rate parameters. Our findings showed that the dynamics of the infected human and insect is mostly affected by carrying capacity insect in the settlement.

  9. Large Mammalian Animal Models of Heart Disease

    Directory of Open Access Journals (Sweden)

    Paula Camacho

    2016-10-01

    Full Text Available Due to the biological complexity of the cardiovascular system, the animal model is an urgent pre-clinical need to advance our knowledge of cardiovascular disease and to explore new drugs to repair the damaged heart. Ideally, a model system should be inexpensive, easily manipulated, reproducible, a biological representative of human disease, and ethically sound. Although a larger animal model is more expensive and difficult to manipulate, its genetic, structural, functional, and even disease similarities to humans make it an ideal model to first consider. This review presents the commonly-used large animals—dog, sheep, pig, and non-human primates—while the less-used other large animals—cows, horses—are excluded. The review attempts to introduce unique points for each species regarding its biological property, degrees of susceptibility to develop certain types of heart diseases, and methodology of induced conditions. For example, dogs barely develop myocardial infarction, while dilated cardiomyopathy is developed quite often. Based on the similarities of each species to the human, the model selection may first consider non-human primates—pig, sheep, then dog—but it also depends on other factors, for example, purposes, funding, ethics, and policy. We hope this review can serve as a basic outline of large animal models for cardiovascular researchers and clinicians.

  10. Animal models for Gaucher disease research.

    Science.gov (United States)

    Farfel-Becker, Tamar; Vitner, Einat B; Futerman, Anthony H

    2011-11-01

    Gaucher disease (GD), the most common lysosomal storage disorder (LSD), is caused by the defective activity of the lysosomal hydrolase glucocerebrosidase, which is encoded by the GBA gene. Generation of animal models that faithfully recapitulate the three clinical subtypes of GD has proved to be more of a challenge than first anticipated. The first mouse to be produced died within hours after birth owing to skin permeability problems, and mice with point mutations in Gba did not display symptoms correlating with human disease and also died soon after birth. Recently, conditional knockout mice that mimic some features of the human disease have become available. Here, we review the contribution of all currently available animal models to examining pathological pathways underlying GD and to testing the efficacy of new treatment modalities, and propose a number of criteria for the generation of more appropriate animal models of GD.

  11. Animal models for Gaucher disease research

    Directory of Open Access Journals (Sweden)

    Tamar Farfel-Becker

    2011-11-01

    Full Text Available Gaucher disease (GD, the most common lysosomal storage disorder (LSD, is caused by the defective activity of the lysosomal hydrolase glucocerebrosidase, which is encoded by the GBA gene. Generation of animal models that faithfully recapitulate the three clinical subtypes of GD has proved to be more of a challenge than first anticipated. The first mouse to be produced died within hours after birth owing to skin permeability problems, and mice with point mutations in Gba did not display symptoms correlating with human disease and also died soon after birth. Recently, conditional knockout mice that mimic some features of the human disease have become available. Here, we review the contribution of all currently available animal models to examining pathological pathways underlying GD and to testing the efficacy of new treatment modalities, and propose a number of criteria for the generation of more appropriate animal models of GD.

  12. Economic Modeling Considerations for Rare Diseases.

    Science.gov (United States)

    Pearson, Isobel; Rothwell, Ben; Olaye, Andrew; Knight, Christopher

    2018-05-01

    To identify challenges that affect the feasibility and rigor of economic models in rare diseases and strategies that manufacturers have employed in health technology assessment submissions to demonstrate the value of new orphan products that have limited study data. Targeted reviews of PubMed, the National Institute for Health and Care Excellence's (NICE's) Highly Specialised Technologies (HST), and the Scottish Medicines Consortium's (SMC's) ultra-orphan submissions were performed. A total of 19 PubMed studies, 3 published NICE HSTs, and 11 ultra-orphan SMC submissions were eligible for inclusion. In rare diseases, a number of different factors may affect the model's ability to comply with good practice recommendations. Many products for the treatment of rare diseases have an incomplete efficacy and safety profile at product launch. In addition, there is often limited available natural history and epidemiology data. Information on the direct and indirect cost burden of an orphan disease also may be limited, making it difficult to estimate the potential economic benefit of treatment. These challenges can prevent accurate estimation of a new product's benefits in relation to costs. Approaches that can address such challenges include using patient and/or clinician feedback to inform model assumptions; data from disease analogues; epidemiological techniques, such as matching-adjusted indirect comparison; and long-term data collection. Modeling in rare diseases is often challenging; however, a number of approaches are available to support the development of model structures and the collation of input parameters and to manage uncertainty. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  13. Infectious disease modeling a hybrid system approach

    CERN Document Server

    Liu, Xinzhi

    2017-01-01

    This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.

  14. Ideal Experimental Rat Models for Liver Diseases

    OpenAIRE

    Lee, Sang Woo; Kim, Sung Hoon; Min, Seon Ok; Kim, Kyung Sik

    2011-01-01

    There are many limitations for conducting liver disease research in human beings due to the high cost and potential ethical issues. For this reason, conducting a study that is difficult to perform in humans using appropriate animal models, can be beneficial in ascertaining the pathological physiology, and in developing new treatment modalities. However, it is difficult to determine the appropriate animal model which is suitable for research purposes, since every patient has different and dive...

  15. Computational disease modeling – fact or fiction?

    Directory of Open Access Journals (Sweden)

    Stephan Klaas

    2009-06-01

    Full Text Available Abstract Background Biomedical research is changing due to the rapid accumulation of experimental data at an unprecedented scale, revealing increasing degrees of complexity of biological processes. Life Sciences are facing a transition from a descriptive to a mechanistic approach that reveals principles of cells, cellular networks, organs, and their interactions across several spatial and temporal scales. There are two conceptual traditions in biological computational-modeling. The bottom-up approach emphasizes complex intracellular molecular models and is well represented within the systems biology community. On the other hand, the physics-inspired top-down modeling strategy identifies and selects features of (presumably essential relevance to the phenomena of interest and combines available data in models of modest complexity. Results The workshop, "ESF Exploratory Workshop on Computational disease Modeling", examined the challenges that computational modeling faces in contributing to the understanding and treatment of complex multi-factorial diseases. Participants at the meeting agreed on two general conclusions. First, we identified the critical importance of developing analytical tools for dealing with model and parameter uncertainty. Second, the development of predictive hierarchical models spanning several scales beyond intracellular molecular networks was identified as a major objective. This contrasts with the current focus within the systems biology community on complex molecular modeling. Conclusion During the workshop it became obvious that diverse scientific modeling cultures (from computational neuroscience, theory, data-driven machine-learning approaches, agent-based modeling, network modeling and stochastic-molecular simulations would benefit from intense cross-talk on shared theoretical issues in order to make progress on clinically relevant problems.

  16. Experimental models of autoimmune inflammatory ocular diseases

    Directory of Open Access Journals (Sweden)

    Fabio Gasparin

    2012-04-01

    Full Text Available Ocular inflammation is one of the leading causes of blindness and loss of vision. Human uveitis is a complex and heterogeneous group of diseases characterized by inflammation of intraocular tissues. The eye may be the only organ involved, or uveitis may be part of a systemic disease. A significant number of cases are of unknown etiology and are labeled idiopathic. Animal models have been developed to the study of the physiopathogenesis of autoimmune uveitis due to the difficulty in obtaining human eye inflamed tissues for experiments. Most of those models are induced by injection of specific photoreceptors proteins (e.g., S-antigen, interphotoreceptor retinoid-binding protein, rhodopsin, recoverin, phosducin. Non-retinal antigens, including melanin-associated proteins and myelin basic protein, are also good inducers of uveitis in animals. Understanding the basic mechanisms and pathogenesis of autoimmune ocular diseases are essential for the development of new treatment approaches and therapeutic agents. The present review describes the main experimental models of autoimmune ocular inflammatory diseases.

  17. Neurophysiology of Drosophila models of Parkinson's disease.

    Science.gov (United States)

    West, Ryan J H; Furmston, Rebecca; Williams, Charles A C; Elliott, Christopher J H

    2015-01-01

    We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson's disease- (PD-) related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson's disease. Firstly, Drosophila models are instrumental in exploring the mechanisms of neurodegeneration, with several PD-related mutations eliciting related phenotypes including sensitivity to energy supply and vesicular deformities. These are leading to the identification of plausible cellular mechanisms, which may be specific to (dopaminergic) neurons and synapses rather than general cellular phenotypes. Secondly, models show noncell autonomous signalling within the nervous system, offering the opportunity to develop our understanding of the way pathogenic signalling propagates, resembling Braak's scheme of spreading pathology in PD. Thirdly, the models link physiological deficits to changes in synaptic structure. While the structure-function relationship is complex, the genetic tractability of Drosophila offers the chance to separate fundamental changes from downstream consequences. Finally, the strong neuronal phenotypes permit relevant first in vivo drug testing.

  18. Mathematical Model of Cytomegalovirus (CMV) Disease

    Science.gov (United States)

    Sriningsih, R.; Subhan, M.; Nasution, M. L.

    2018-04-01

    The article formed the mathematical model of cytomegalovirus (CMV) disease. Cytomegalovirus (CMV) is a type of herpes virus. This virus is actually not dangerous, but if the body's immune weakens the virus can cause serious problems for health and even can cause death. This virus is also susceptible to infect pregnant women. In addition, the baby may also be infected through the placenta. If this is experienced early in pregnancy, it will increase the risk of miscarriage. If the baby is born, it can cause disability in the baby. The model is formed by determining its variables and parameters based on assumptions. The goal is to analyze the dynamics of cytomegalovirus (CMV) disease spread.

  19. Animal models for Gaucher disease research

    OpenAIRE

    Farfel-Becker, Tamar; Vitner, Einat B.; Futerman, Anthony H.

    2011-01-01

    Gaucher disease (GD), the most common lysosomal storage disorder (LSD), is caused by the defective activity of the lysosomal hydrolase glucocerebrosidase, which is encoded by the GBA gene. Generation of animal models that faithfully recapitulate the three clinical subtypes of GD has proved to be more of a challenge than first anticipated. The first mouse to be produced died within hours after birth owing to skin permeability problems, and mice with point mutations in Gba did not display sympt...

  20. The new disease model of alcoholism.

    OpenAIRE

    Wallace, J

    1990-01-01

    The new biopsychosocial disease model of alcoholism is examined from the perspective of recent biologic research. Studies of animal and human genetic predispositions suggest the presence of genetic influences over drinking behavior as well as biologic risk factors related to deficiencies in various neurochemicals. Ethanol affects the fluidity of cell membrane lipids, eventually causing membrane dysfunction. It also adversely affects the activity of two enzymes, monoamine oxidase and adenylate...

  1. Mouse Chromosome Engineering for Modeling Human Disease

    OpenAIRE

    van der Weyden, Louise; Bradley, Allan

    2006-01-01

    Chromosomal rearrangements occur frequently in humans and can be disease-associated or phenotypically neutral. Recent technological advances have led to the discovery of copy-number changes previously undetected by cytogenetic techniques. To understand the genetic consequences of such genomic changes, these mutations need to be modeled in experimentally tractable systems. The mouse is an excellent organism for this analysis because of its biological and genetic similarity to humans, and the e...

  2. Novel in Vitro Model for Keratoconus Disease

    Directory of Open Access Journals (Sweden)

    James D. Zieske

    2012-11-01

    Full Text Available Keratoconus is a disease where the cornea becomes cone-like due to structural thinning and ultimately leads to compromised corneal integrity and loss of vision. Currently, the therapeutic options are corrective lenses for early stages and surgery for advanced cases with no in vitro model available. In this study, we used human corneal fibroblasts (HCFs and compared them to human Keratoconus fibroblasts (HKCs cultured in a 3-dimensional (3D model, in order to compare the expression and secretion of specific extracellular matrix (ECM components. For four weeks, the cells were stimulated with a stable Vitamin C (VitC derivative ± TGF-β1 or TGF-β3 (T1 and T3, respectively. After four weeks, HKCs stimulated with T1 and T3 were significantly thicker compared with Control (VitC only; however, HCF constructs were significantly thicker than HKCs under all conditions. Both cell types secreted copious amounts of type I and V collagens in their assembled, aligned collagen fibrils, which increased in the degree of alignment upon T3 stimulation. In contrast, only HKCs expressed high levels of corneal scarring markers, such as type III collagen, which was dramatically reduced with T3. HKCs expressed α-smooth muscle actin (SMA under all conditions in contrast to HCFs, where T3 minimized SMA expression. Fast Fourier transform (FFT data indicated that HKCs were more aligned when compared to HCFs, independent of treatments; however, HKC’s ECM showed the least degree of rotation. HKCs also secreted the most aligned type I collagen under T3 treatment, when compared to any condition and cell type. Overall, our model for Keratoconus disease studies is the first 3D in vitro tissue engineered model that can mimic the Keratoconus disease in vivo and may be a breakthrough in efforts to understand the progression of this disease.

  3. Ideal Experimental Rat Models for Liver Diseases.

    Science.gov (United States)

    Lee, Sang Woo; Kim, Sung Hoon; Min, Seon Ok; Kim, Kyung Sik

    2011-05-01

    There are many limitations for conducting liver disease research in human beings due to the high cost and potential ethical issues. For this reason, conducting a study that is difficult to perform in humans using appropriate animal models, can be beneficial in ascertaining the pathological physiology, and in developing new treatment modalities. However, it is difficult to determine the appropriate animal model which is suitable for research purposes, since every patient has different and diverse clinical symptoms, adverse reactions, and complications due to the pathological physiology. Also, it is not easy to reproduce identically various clinical situations in animal models. Recently, the Guide for the Care and Use of Laboratory Animals has tightened up the regulations, and therefore it is advisable to select the appropriate animals and decide upon the appropriate quantities through scientific and systemic considerations before conducting animal testing. Therefore, in this review article the authors examined various white rat animal testing models and determined the appropriate usable rat model, and the pros and cons of its application in liver disease research. The authors believe that this review will be beneficial in selecting proper laboratory animals for research purposes.

  4. Mathematical modeling of infectious disease dynamics

    Science.gov (United States)

    Siettos, Constantinos I.; Russo, Lucia

    2013-01-01

    Over the last years, an intensive worldwide effort is speeding up the developments in the establishment of a global surveillance network for combating pandemics of emergent and re-emergent infectious diseases. Scientists from different fields extending from medicine and molecular biology to computer science and applied mathematics have teamed up for rapid assessment of potentially urgent situations. Toward this aim mathematical modeling plays an important role in efforts that focus on predicting, assessing, and controlling potential outbreaks. To better understand and model the contagious dynamics the impact of numerous variables ranging from the micro host–pathogen level to host-to-host interactions, as well as prevailing ecological, social, economic, and demographic factors across the globe have to be analyzed and thoroughly studied. Here, we present and discuss the main approaches that are used for the surveillance and modeling of infectious disease dynamics. We present the basic concepts underpinning their implementation and practice and for each category we give an annotated list of representative works. PMID:23552814

  5. Models of chronic obstructive pulmonary disease

    Directory of Open Access Journals (Sweden)

    Chung K Fan

    2004-11-01

    Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major global health problem and is predicted to become the third most common cause of death by 2020. Apart from the important preventive steps of smoking cessation, there are no other specific treatments for COPD that are as effective in reversing the condition, and therefore there is a need to understand the pathophysiological mechanisms that could lead to new therapeutic strategies. The development of experimental models will help to dissect these mechanisms at the cellular and molecular level. COPD is a disease characterized by progressive airflow obstruction of the peripheral airways, associated with lung inflammation, emphysema and mucus hypersecretion. Different approaches to mimic COPD have been developed but are limited in comparison to models of allergic asthma. COPD models usually do not mimic the major features of human COPD and are commonly based on the induction of COPD-like lesions in the lungs and airways using noxious inhalants such as tobacco smoke, nitrogen dioxide, or sulfur dioxide. Depending on the duration and intensity of exposure, these noxious stimuli induce signs of chronic inflammation and airway remodelling. Emphysema can be achieved by combining such exposure with instillation of tissue-degrading enzymes. Other approaches are based on genetically-targeted mice which develop COPD-like lesions with emphysema, and such mice provide deep insights into pathophysiological mechanisms. Future approaches should aim to mimic irreversible airflow obstruction, associated with cough and sputum production, with the possibility of inducing exacerbations.

  6. Modeling rapidly disseminating infectious disease during mass gatherings

    Directory of Open Access Journals (Sweden)

    Chowell Gerardo

    2012-12-01

    Full Text Available Abstract We discuss models for rapidly disseminating infectious diseases during mass gatherings (MGs, using influenza as a case study. Recent innovations in modeling and forecasting influenza transmission dynamics at local, regional, and global scales have made influenza a particularly attractive model scenario for MG. We discuss the behavioral, medical, and population factors for modeling MG disease transmission, review existing model formulations, and highlight key data and modeling gaps related to modeling MG disease transmission. We argue that the proposed improvements will help integrate infectious-disease models in MG health contingency plans in the near future, echoing modeling efforts that have helped shape influenza pandemic preparedness plans in recent years.

  7. Poisson Mixture Regression Models for Heart Disease Prediction.

    Science.gov (United States)

    Mufudza, Chipo; Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

  8. Poisson-generalized gamma empirical Bayes model for disease ...

    African Journals Online (AJOL)

    In spatial disease mapping, the use of Bayesian models of estimation technique is becoming popular for smoothing relative risks estimates for disease mapping. The most common Bayesian conjugate model for disease mapping is the Poisson-Gamma Model (PG). To explore further the activity of smoothing of relative risk ...

  9. A surface hydrology model for regional vector borne disease models

    Science.gov (United States)

    Tompkins, Adrian; Asare, Ernest; Bomblies, Arne; Amekudzi, Leonard

    2016-04-01

    Small, sun-lit temporary pools that form during the rainy season are important breeding sites for many key mosquito vectors responsible for the transmission of malaria and other diseases. The representation of this surface hydrology in mathematical disease models is challenging, due to their small-scale, dependence on the terrain and the difficulty of setting soil parameters. Here we introduce a model that represents the temporal evolution of the aggregate statistics of breeding sites in a single pond fractional coverage parameter. The model is based on a simple, geometrical assumption concerning the terrain, and accounts for the processes of surface runoff, pond overflow, infiltration and evaporation. Soil moisture, soil properties and large-scale terrain slope are accounted for using a calibration parameter that sets the equivalent catchment fraction. The model is calibrated and then evaluated using in situ pond measurements in Ghana and ultra-high (10m) resolution explicit simulations for a village in Niger. Despite the model's simplicity, it is shown to reproduce the variability and mean of the pond aggregate water coverage well for both locations and validation techniques. Example malaria simulations for Uganda will be shown using this new scheme with a generic calibration setting, evaluated using district malaria case data. Possible methods for implementing regional calibration will be briefly discussed.

  10. Modeling proteasome dynamics in Parkinson's disease

    International Nuclear Information System (INIS)

    Sneppen, Kim; Lizana, Ludvig; Jensen, Mogens H; Pigolotti, Simone; Otzen, Daniel

    2009-01-01

    In Parkinson's disease (PD), there is evidence that α-synuclein (αSN) aggregation is coupled to dysfunctional or overburdened protein quality control systems, in particular the ubiquitin–proteasome system. Here, we develop a simple dynamical model for the on-going conflict between αSN aggregation and the maintenance of a functional proteasome in the healthy cell, based on the premise that proteasomal activity can be titrated out by mature αSN fibrils and their protofilament precursors. In the presence of excess proteasomes the cell easily maintains homeostasis. However, when the ratio between the available proteasome and the αSN protofilaments is reduced below a threshold level, we predict a collapse of homeostasis and onset of oscillations in the proteasome concentration. Depleted proteasome opens for accumulation of oligomers. Our analysis suggests that the onset of PD is associated with a proteasome population that becomes occupied in periodic degradation of aggregates. This behavior is found to be the general state of a proteasome/chaperone system under pressure, and suggests new interpretations of other diseases where protein aggregation could stress elements of the protein quality control system

  11. A complete categorization of multiscale models of infectious disease systems.

    Science.gov (United States)

    Garira, Winston

    2017-12-01

    Modelling of infectious disease systems has entered a new era in which disease modellers are increasingly turning to multiscale modelling to extend traditional modelling frameworks into new application areas and to achieve higher levels of detail and accuracy in characterizing infectious disease systems. In this paper we present a categorization framework for categorizing multiscale models of infectious disease systems. The categorization framework consists of five integration frameworks and five criteria. We use the categorization framework to give a complete categorization of host-level immuno-epidemiological models (HL-IEMs). This categorization framework is also shown to be applicable in categorizing other types of multiscale models of infectious diseases beyond HL-IEMs through modifying the initial categorization framework presented in this study. Categorization of multiscale models of infectious disease systems in this way is useful in bringing some order to the discussion on the structure of these multiscale models.

  12. Animal models for bone tissue engineering and modelling disease

    Science.gov (United States)

    Griffin, Michelle

    2018-01-01

    ABSTRACT Tissue engineering and its clinical application, regenerative medicine, are instructing multiple approaches to aid in replacing bone loss after defects caused by trauma or cancer. In such cases, bone formation can be guided by engineered biodegradable and nonbiodegradable scaffolds with clearly defined architectural and mechanical properties informed by evidence-based research. With the ever-increasing expansion of bone tissue engineering and the pioneering research conducted to date, preclinical models are becoming a necessity to allow the engineered products to be translated to the clinic. In addition to creating smart bone scaffolds to mitigate bone loss, the field of tissue engineering and regenerative medicine is exploring methods to treat primary and secondary bone malignancies by creating models that mimic the clinical disease manifestation. This Review gives an overview of the preclinical testing in animal models used to evaluate bone regeneration concepts. Immunosuppressed rodent models have shown to be successful in mimicking bone malignancy via the implantation of human-derived cancer cells, whereas large animal models, including pigs, sheep and goats, are being used to provide an insight into bone formation and the effectiveness of scaffolds in induced tibial or femoral defects, providing clinically relevant similarity to human cases. Despite the recent progress, the successful translation of bone regeneration concepts from the bench to the bedside is rooted in the efforts of different research groups to standardise and validate the preclinical models for bone tissue engineering approaches. PMID:29685995

  13. The Chronic Kidney Disease Model: A General Purpose Model of Disease Progression and Treatment

    Directory of Open Access Journals (Sweden)

    Patel Uptal D

    2011-06-01

    Full Text Available Abstract Background Chronic kidney disease (CKD is the focus of recent national policy efforts; however, decision makers must account for multiple therapeutic options, comorbidities and complications. The objective of the Chronic Kidney Disease model is to provide guidance to decision makers. We describe this model and give an example of how it can inform clinical and policy decisions. Methods Monte Carlo simulation of CKD natural history and treatment. Health states include myocardial infarction, stroke with and without disability, congestive heart failure, CKD stages 1-5, bone disease, dialysis, transplant and death. Each cycle is 1 month. Projections account for race, age, gender, diabetes, proteinuria, hypertension, cardiac disease, and CKD stage. Treatment strategies include hypertension control, diabetes control, use of HMG-CoA reductase inhibitors, use of angiotensin converting enzyme inhibitors, nephrology specialty care, CKD screening, and a combination of these. The model architecture is flexible permitting updates as new data become available. The primary outcome is quality adjusted life years (QALYs. Secondary outcomes include health state events and CKD progression rate. Results The model was validated for GFR change/year -3.0 ± 1.9 vs. -1.7 ± 3.4 (in the AASK trial, and annual myocardial infarction and mortality rates 3.6 ± 0.9% and 1.6 ± 0.5% vs. 4.4% and 1.6% in the Go study. To illustrate the model's utility we estimated lifetime impact of a hypothetical treatment for primary prevention of vascular disease. As vascular risk declined, QALY improved but risk of dialysis increased. At baseline, 20% and 60% reduction: QALYs = 17.6, 18.2, and 19.0 and dialysis = 7.7%, 8.1%, and 10.4%, respectively. Conclusions The CKD Model is a valid, general purpose model intended as a resource to inform clinical and policy decisions improving CKD care. Its value as a tool is illustrated in our example which projects a relationship between

  14. TOWARDS MODELING DISEASE OUTBREAK NOTIFICATION SYSTEMS

    OpenAIRE

    Farag Azzedin; Jaweed Yazdani,; Salahadin Adam; Mustafa Ghaleb

    2014-01-01

    Disease outbreak detection, monitoring and notification systems play an important role in assessing threats to public health since disease outbreaks are becoming increasingly common world-wide. There are several systems in use around the world, with coverage of national, international and global disease outbreaks. These systems use different taxonomies and classifications for the detection and prioritization of potential disease outbreaks. In this paper, we study and analyze th...

  15. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

    .... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...

  16. Predictive modeling of coral disease distribution within a reef system.

    Directory of Open Access Journals (Sweden)

    Gareth J Williams

    2010-02-01

    Full Text Available Diseases often display complex and distinct associations with their environment due to differences in etiology, modes of transmission between hosts, and the shifting balance between pathogen virulence and host resistance. Statistical modeling has been underutilized in coral disease research to explore the spatial patterns that result from this triad of interactions. We tested the hypotheses that: 1 coral diseases show distinct associations with multiple environmental factors, 2 incorporating interactions (synergistic collinearities among environmental variables is important when predicting coral disease spatial patterns, and 3 modeling overall coral disease prevalence (the prevalence of multiple diseases as a single proportion value will increase predictive error relative to modeling the same diseases independently. Four coral diseases: Porites growth anomalies (PorGA, Porites tissue loss (PorTL, Porites trematodiasis (PorTrem, and Montipora white syndrome (MWS, and their interactions with 17 predictor variables were modeled using boosted regression trees (BRT within a reef system in Hawaii. Each disease showed distinct associations with the predictors. Environmental predictors showing the strongest overall associations with the coral diseases were both biotic and abiotic. PorGA was optimally predicted by a negative association with turbidity, PorTL and MWS by declines in butterflyfish and juvenile parrotfish abundance respectively, and PorTrem by a modal relationship with Porites host cover. Incorporating interactions among predictor variables contributed to the predictive power of our models, particularly for PorTrem. Combining diseases (using overall disease prevalence as the model response, led to an average six-fold increase in cross-validation predictive deviance over modeling the diseases individually. We therefore recommend coral diseases to be modeled separately, unless known to have etiologies that respond in a similar manner to

  17. Models of marine molluscan diseases: Trends and challenges.

    Science.gov (United States)

    Powell, Eric N; Hofmann, Eileen E

    2015-10-01

    Disease effects on host population dynamics and the transmission of pathogens between hosts are two important challenges for understanding how epizootics wax and wane and how disease influences host population dynamics. For the management of marine shellfish resources, marine diseases pose additional challenges in early intervention after the appearance of disease, management of the diseased population to limit a decline in host abundance, and application of measures to restrain that decline once it occurs. Mathematical models provide one approach for quantifying these effects and addressing the competing goals of managing the diseased population versus managing the disease. The majority of models for molluscan diseases fall into three categories distinguished by these competing goals. (1) Models that consider disease effects on the host population tend to focus on pathogen proliferation within the host. Many of the well-known molluscan diseases are pandemic, in that they routinely reach high prevalence rapidly over large geographic expanses, are characterized by transmission that does not depend upon a local source, and exert a significant influence on host population dynamics. Models focused on disease proliferation examine the influence of environmental change on host population metrics and provide a basis to better manage diseased stocks. Such models are readily adapted to questions of fishery management and habitat restoration. (2) Transmission models are designed to understand the mechanisms triggering epizootics, identify factors impeding epizootic development, and evaluate controls on the rate of disease spread over the host's range. Transmission models have been used extensively to study terrestrial diseases, yet little attention has been given to their potential for understanding the epidemiology of marine molluscan diseases. For management of diseases of wild stocks, transmission models open up a range of options, including the application of area

  18. A model to evaluate quality and effectiveness of disease management.

    Science.gov (United States)

    Lemmens, K M M; Nieboer, A P; van Schayck, C P; Asin, J D; Huijsman, R

    2008-12-01

    Disease management has emerged as a new strategy to enhance quality of care for patients suffering from chronic conditions, and to control healthcare costs. So far, however, the effects of this strategy remain unclear. Although current models define the concept of disease management, they do not provide a systematic development or an explanatory theory of how disease management affects the outcomes of care. The objective of this paper is to present a framework for valid evaluation of disease-management initiatives. The evaluation model is built on two pillars of disease management: patient-related and professional-directed interventions. The effectiveness of these interventions is thought to be affected by the organisational design of the healthcare system. Disease management requires a multifaceted approach; hence disease-management programme evaluations should focus on the effects of multiple interventions, namely patient-related, professional-directed and organisational interventions. The framework has been built upon the conceptualisation of these disease-management interventions. Analysis of the underlying mechanisms of these interventions revealed that learning and behavioural theories support the core assumptions of disease management. The evaluation model can be used to identify the components of disease-management programmes and the mechanisms behind them, making valid comparison feasible. In addition, this model links the programme interventions to indicators that can be used to evaluate the disease-management programme. Consistent use of this framework will enable comparisons among disease-management programmes and outcomes in evaluation research.

  19. Mathematical models in medicine: Diseases and epidemics

    International Nuclear Information System (INIS)

    Witten, M.

    1987-01-01

    This volume presents the numerous applications of mathematics in the life sciences and medicine, and demonstrates how mathematics and computers have taken root in these fields. The work covers a variety of techniques and applications including mathematical and modelling methodology, modelling/simulation technology, and philosophical issues in model formulation, leading to speciality medical modelling, artificial intelligence, psychiatric models, medical decision making, and molecular modelling

  20. Modelling Neurodegenerative Diseases Using Human Pluripotent Stem Cells

    DEFF Research Database (Denmark)

    Hall, Vanessa Jane

    2016-01-01

    Neurodegenerative diseases are being modelled in-vitro using human patient-specific, induced pluripotent stem cells and transgenic embryonic stem cells to determine more about disease mechanisms, as well as to discover new treatments for patients. Current research in modelling Alzheimer’s disease......, frontotemporal dementia and Parkinson’s disease using pluripotent stem cells is described, along with the advent of gene-editing, which has been the complimentary tool for the field. Current methods used to model these diseases are predominantly dependent on 2D cell culture methods. Outcomes reveal that only...... that includes studying more complex 3D cell cultures, as well as accelerating aging of the neurons, may help to yield stronger phenotypes in the cultured cells. Thus, the use and application of pluripotent stem cells for modelling disease have already shown to be a powerful approach for discovering more about...

  1. Primary skin fibroblasts as a model of Parkinson's disease

    NARCIS (Netherlands)

    Auburger, G.; Klinkenberg, M.; Droste, J.A.H.; Marcus, K.; Morales-Gordo, B.; Kunz, W.S.; Brandt, U.; Broccoli, V.; Reichmann, H.; Gispert, S.; Jendrach, M.

    2012-01-01

    Parkinson's disease is the second most frequent neurodegenerative disorder. While most cases occur sporadic mutations in a growing number of genes including Parkin (PARK2) and PINK1 (PARK6) have been associated with the disease. Different animal models and cell models like patient skin fibroblasts

  2. Concise Review: Cardiac Disease Modeling Using Induced Pluripotent Stem Cells.

    Science.gov (United States)

    Yang, Chunbo; Al-Aama, Jumana; Stojkovic, Miodrag; Keavney, Bernard; Trafford, Andrew; Lako, Majlinda; Armstrong, Lyle

    2015-09-01

    Genetic cardiac diseases are major causes of morbidity and mortality. Although animal models have been created to provide some useful insights into the pathogenesis of genetic cardiac diseases, the significant species differences and the lack of genetic information for complex genetic diseases markedly attenuate the application values of such data. Generation of induced pluripotent stem cells (iPSCs) from patient-specific specimens and subsequent derivation of cardiomyocytes offer novel avenues to study the mechanisms underlying cardiac diseases, to identify new causative genes, and to provide insights into the disease aetiology. In recent years, the list of human iPSC-based models for genetic cardiac diseases has been expanding rapidly, although there are still remaining concerns on the level of functionality of iPSC-derived cardiomyocytes and their ability to be used for modeling complex cardiac diseases in adults. This review focuses on the development of cardiomyocyte induction from pluripotent stem cells, the recent progress in heart disease modeling using iPSC-derived cardiomyocytes, and the challenges associated with understanding complex genetic diseases. To address these issues, we examine the similarity between iPSC-derived cardiomyocytes and their ex vivo counterparts and how this relates to the method used to differentiate the pluripotent stem cells into a cardiomyocyte phenotype. We progress to examine categories of congenital cardiac abnormalities that are suitable for iPSC-based disease modeling. © AlphaMed Press.

  3. Poisson Mixture Regression Models for Heart Disease Prediction

    Science.gov (United States)

    Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

  4. A Robust Mathematical Model On Infectious Diseases | Omorogbe ...

    African Journals Online (AJOL)

    The paper presents a robust epidemiological compartment model on infectious diseases. The model obviates the limitations of the classical epidemiological model by accommodating different levels of vulnerability and susceptibility to infections within different social class and spatial structures. Unlike the classical model ...

  5. Genome engineering of stem cell organoids for disease modeling.

    Science.gov (United States)

    Sun, Yingmin; Ding, Qiurong

    2017-05-01

    Precision medicine emerges as a new approach that takes into account individual variability. Successful realization of precision medicine requires disease models that are able to incorporate personalized disease information and recapitulate disease development processes at the molecular, cellular and organ levels. With recent development in stem cell field, a variety of tissue organoids can be derived from patient specific pluripotent stem cells and adult stem cells. In combination with the state-of-the-art genome editing tools, organoids can be further engineered to mimic disease-relevant genetic and epigenetic status of a patient. This has therefore enabled a rapid expansion of sophisticated in vitro disease models, offering a unique system for fundamental and biomedical research as well as the development of personalized medicine. Here we summarize some of the latest advances and future perspectives in engineering stem cell organoids for human disease modeling.

  6. Deterministic and stochastic CTMC models from Zika disease transmission

    Science.gov (United States)

    Zevika, Mona; Soewono, Edy

    2018-03-01

    Zika infection is one of the most important mosquito-borne diseases in the world. Zika virus (ZIKV) is transmitted by many Aedes-type mosquitoes including Aedes aegypti. Pregnant women with the Zika virus are at risk of having a fetus or infant with a congenital defect and suffering from microcephaly. Here, we formulate a Zika disease transmission model using two approaches, a deterministic model and a continuous-time Markov chain stochastic model. The basic reproduction ratio is constructed from a deterministic model. Meanwhile, the CTMC stochastic model yields an estimate of the probability of extinction and outbreaks of Zika disease. Dynamical simulations and analysis of the disease transmission are shown for the deterministic and stochastic models.

  7. Evaluation of models of Parkinson’s Disease

    Directory of Open Access Journals (Sweden)

    Shail Adrian Jagmag

    2016-01-01

    Full Text Available Parkinson’s disease is one of the most common neurodegenerative diseases. Animal models have contributed a large part to our understanding and therapeutics developed for treatment of PD. There are several more exhaustive reviews of literature that provide the initiated insights into the specific models; however a novel synthesis of the basic advantages and disadvantages of different models is much needed. Here we compare both neurotoxin based and genetic models while suggesting some novel avenues in PD modelling. We also highlight the problems faced and promises of all the mammalian models with the hope of providing a framework for comparison of various systems.

  8. Advances and Limitations of Disease Biogeography Using Ecological Niche Modeling.

    Science.gov (United States)

    Escobar, Luis E; Craft, Meggan E

    2016-01-01

    Mapping disease transmission risk is crucial in public and animal health for evidence based decision-making. Ecology and epidemiology are highly related disciplines that may contribute to improvements in mapping disease, which can be used to answer health related questions. Ecological niche modeling is increasingly used for understanding the biogeography of diseases in plants, animals, and humans. However, epidemiological applications of niche modeling approaches for disease mapping can fail to generate robust study designs, producing incomplete or incorrect inferences. This manuscript is an overview of the history and conceptual bases behind ecological niche modeling, specifically as applied to epidemiology and public health; it does not pretend to be an exhaustive and detailed description of ecological niche modeling literature and methods. Instead, this review includes selected state-of-the-science approaches and tools, providing a short guide to designing studies incorporating information on the type and quality of the input data (i.e., occurrences and environmental variables), identification and justification of the extent of the study area, and encourages users to explore and test diverse algorithms for more informed conclusions. We provide a friendly introduction to the field of disease biogeography presenting an updated guide for researchers looking to use ecological niche modeling for disease mapping. We anticipate that ecological niche modeling will soon be a critical tool for epidemiologists aiming to map disease transmission risk, forecast disease distribution under climate change scenarios, and identify landscape factors triggering outbreaks.

  9. Disease Extinction Versus Persistence in Discrete-Time Epidemic Models.

    Science.gov (United States)

    van den Driessche, P; Yakubu, Abdul-Aziz

    2018-04-12

    We focus on discrete-time infectious disease models in populations that are governed by constant, geometric, Beverton-Holt or Ricker demographic equations, and give a method for computing the basic reproduction number, [Formula: see text]. When [Formula: see text] and the demographic population dynamics are asymptotically constant or under geometric growth (non-oscillatory), we prove global asymptotic stability of the disease-free equilibrium of the disease models. Under the same demographic assumption, when [Formula: see text], we prove uniform persistence of the disease. We apply our theoretical results to specific discrete-time epidemic models that are formulated for SEIR infections, cholera in humans and anthrax in animals. Our simulations show that a unique endemic equilibrium of each of the three specific disease models is asymptotically stable whenever [Formula: see text].

  10. The cost of simplifying air travel when modeling disease spread.

    Directory of Open Access Journals (Sweden)

    Justin Lessler

    Full Text Available BACKGROUND: Air travel plays a key role in the spread of many pathogens. Modeling the long distance spread of infectious disease in these cases requires an air travel model. Highly detailed air transportation models can be over determined and computationally problematic. We compared the predictions of a simplified air transport model with those of a model of all routes and assessed the impact of differences on models of infectious disease. METHODOLOGY/PRINCIPAL FINDINGS: Using U.S. ticket data from 2007, we compared a simplified "pipe" model, in which individuals flow in and out of the air transport system based on the number of arrivals and departures from a given airport, to a fully saturated model where all routes are modeled individually. We also compared the pipe model to a "gravity" model where the probability of travel is scaled by physical distance; the gravity model did not differ significantly from the pipe model. The pipe model roughly approximated actual air travel, but tended to overestimate the number of trips between small airports and underestimate travel between major east and west coast airports. For most routes, the maximum number of false (or missed introductions of disease is small (<1 per day but for a few routes this rate is greatly underestimated by the pipe model. CONCLUSIONS/SIGNIFICANCE: If our interest is in large scale regional and national effects of disease, the simplified pipe model may be adequate. If we are interested in specific effects of interventions on particular air routes or the time for the disease to reach a particular location, a more complex point-to-point model will be more accurate. For many problems a hybrid model that independently models some frequently traveled routes may be the best choice. Regardless of the model used, the effect of simplifications and sensitivity to errors in parameter estimation should be analyzed.

  11. Research progress on animal models of Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Wen DONG

    2015-08-01

    Full Text Available Alzheimer's disease (AD is a degenerative disease of the central nervous system, and its pathogenesis is complex. Animal models play an important role in study on pathogenesis and treatment of AD. This paper summarized methods of building models, observation on animal models and evaluation index in recent years, so as to provide related evidence for basic and clinical research in future. DOI: 10.3969/j.issn.1672-6731.2015.08.003

  12. Modelling the impacts of pests and diseases on agricultural systems.

    Science.gov (United States)

    Donatelli, M; Magarey, R D; Bregaglio, S; Willocquet, L; Whish, J P M; Savary, S

    2017-07-01

    The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.

  13. Stem Cells as In Vitro Model of Parkinson's Disease

    Directory of Open Access Journals (Sweden)

    Patricia L. Martínez-Morales

    2012-01-01

    Full Text Available Progress in understanding neurodegenerative cell biology in Parkinson's disease (PD has been hampered by a lack of predictive and relevant cellular models. In addition, the lack of an adequate in vitro human neuron cell-based model has been an obstacle for the uncover of new drugs for treating PD. The ability to generate induced pluripotent stem cells (iPSCs from PD patients and a refined capacity to differentiate these iPSCs into DA neurons, the relevant disease cell type, promises a new paradigm in drug development that positions human disease pathophysiology at the core of preclinical drug discovery. Disease models derived from iPSC that manifest cellular disease phenotypes have been established for several monogenic diseases, but iPSC can likewise be used for phenotype-based drug screens in complex diseases for which the underlying genetic mechanism is unknown. Here, we highlight recent advances as well as limitations in the use of iPSC technology for modelling PD “in a dish” and for testing compounds against human disease phenotypes in vitro. We discuss how iPSCs are being exploited to illuminate disease pathophysiology, identify novel drug targets, and enhance the probability of clinical success of new drugs.

  14. Genetic engineering in nonhuman primates for human disease modeling.

    Science.gov (United States)

    Sato, Kenya; Sasaki, Erika

    2018-02-01

    Nonhuman primate (NHP) experimental models have contributed greatly to human health research by assessing the safety and efficacy of newly developed drugs, due to their physiological and anatomical similarities to humans. To generate NHP disease models, drug-inducible methods, and surgical treatment methods have been employed. Recent developments in genetic and developmental engineering in NHPs offer new options for producing genetically modified disease models. Moreover, in recent years, genome-editing technology has emerged to further promote this trend and the generation of disease model NHPs has entered a new era. In this review, we summarize the generation of conventional disease model NHPs and discuss new solutions to the problem of mosaicism in genome-editing technology.

  15. Development of a Conceptual Model of Disease Progression for Use in Economic Modeling of Chronic Obstructive Pulmonary Disease.

    Science.gov (United States)

    Tabberer, Maggie; Gonzalez-McQuire, Sebastian; Muellerova, Hana; Briggs, Andrew H; Rutten-van Mölken, Maureen P M H; Chambers, Mike; Lomas, David A

    2017-05-01

    To develop and validate a new conceptual model (CM) of chronic obstructive pulmonary disease (COPD) for use in disease progression and economic modeling. The CM identifies and describes qualitative associations between disease attributes, progression and outcomes. A literature review was performed to identify any published CMs or literature reporting the impact and association of COPD disease attributes with outcomes. After critical analysis of the literature, a Steering Group of experts from the disciplines of health economics, epidemiology and clinical medicine was convened to develop a draft CM, which was refined using a Delphi process. The refined CM was validated by testing for associations between attributes using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). Disease progression attributes included in the final CM were history and occurrence of exacerbations, lung function, exercise capacity, signs and symptoms (cough, sputum, dyspnea), cardiovascular disease comorbidities, 'other' comorbidities (including depression), body composition (body mass index), fibrinogen as a biomarker, smoking and demographic characteristics (age, gender). Mortality and health-related quality of life were determined to be the most relevant final outcome measures for this model, intended to be the foundation of an economic model of COPD. The CM is being used as the foundation for developing a new COPD model of disease progression and to provide a framework for the analysis of patient-level data. The CM is available as a reference for the implementation of further disease progression and economic models.

  16. An introduction to mathematical modeling of infectious diseases

    CERN Document Server

    Li, Michael Y

    2018-01-01

    This text provides essential modeling skills and methodology for the study of infectious diseases through a one-semester modeling course or directed individual studies.  The book includes mathematical descriptions of epidemiological concepts, and uses classic epidemic models to introduce different mathematical methods in model analysis.  Matlab codes are also included for numerical implementations. It is primarily written for upper undergraduate and beginning graduate students in mathematical sciences who have an interest in mathematical modeling of infectious diseases.  Although written in a rigorous mathematical manner, the style is not unfriendly to non-mathematicians.

  17. Modeling seasonal behavior changes and disease transmission with application to chronic wasting disease.

    Science.gov (United States)

    Oraby, Tamer; Vasilyeva, Olga; Krewski, Daniel; Lutscher, Frithjof

    2014-01-07

    Behavior and habitat of wildlife animals change seasonally according to environmental conditions. Mathematical models need to represent this seasonality to be able to make realistic predictions about the future of a population and the effectiveness of human interventions. Managing and modeling disease in wild animal populations requires particular care in that disease transmission dynamics is a critical consideration in the etiology of both human and animal diseases, with different transmission paradigms requiring different disease risk management strategies. Since transmission of infectious diseases among wildlife depends strongly on social behavior, mechanisms of disease transmission could also change seasonally. A specific consideration in this regard confronted by modellers is whether the contact rate between individuals is density-dependent or frequency-dependent. We argue that seasonal behavior changes could lead to a seasonal shift between density and frequency dependence. This hypothesis is explored in the case of chronic wasting disease (CWD), a fatal disease that affects deer, elk and moose in many areas of North America. Specifically, we introduce a strategic CWD risk model based on direct disease transmission that accounts for the seasonal change in the transmission dynamics and habitats occupied, guided by information derived from cervid ecology. The model is composed of summer and winter susceptible-infected (SI) equations, with frequency-dependent and density-dependent transmission dynamics, respectively. The model includes impulsive birth events with density-dependent birth rate. We determine the basic reproduction number as a weighted average of two seasonal reproduction numbers. We parameterize the model from data derived from the scientific literature on CWD and deer ecology, and conduct global and local sensitivity analyses of the basic reproduction number. We explore the effectiveness of different culling strategies for the management of CWD

  18. A Mouse Model of Chronic West Nile Virus Disease.

    Directory of Open Access Journals (Sweden)

    Jessica B Graham

    2016-11-01

    Full Text Available Infection with West Nile virus (WNV leads to a range of disease outcomes, including chronic infection, though lack of a robust mouse model of chronic WNV infection has precluded identification of the immune events contributing to persistent infection. Using the Collaborative Cross, a population of recombinant inbred mouse strains with high levels of standing genetic variation, we have identified a mouse model of persistent WNV disease, with persistence of viral loads within the brain. Compared to lines exhibiting no disease or marked disease, the F1 cross CC(032x013F1 displays a strong immunoregulatory signature upon infection that correlates with restraint of the WNV-directed cytolytic response. We hypothesize that this regulatory T cell response sufficiently restrains the immune response such that a chronic infection can be maintained in the CNS. Use of this new mouse model of chronic neuroinvasive virus will be critical in developing improved strategies to prevent prolonged disease in humans.

  19. Stargardt disease: towards developing a model to predict phenotype

    OpenAIRE

    Heathfield, Laura; Lacerda, Miguel; Nossek, Christel; Roberts, Lisa; Ramesar, Rajkumar S

    2013-01-01

    Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype–phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual...

  20. Model-based economic evaluation in Alzheimer's disease: a review of the methods available to model Alzheimer's disease progression.

    Science.gov (United States)

    Green, Colin; Shearer, James; Ritchie, Craig W; Zajicek, John P

    2011-01-01

    To consider the methods available to model Alzheimer's disease (AD) progression over time to inform on the structure and development of model-based evaluations, and the future direction of modelling methods in AD. A systematic search of the health care literature was undertaken to identify methods to model disease progression in AD. Modelling methods are presented in a descriptive review. The literature search identified 42 studies presenting methods or applications of methods to model AD progression over time. The review identified 10 general modelling frameworks available to empirically model the progression of AD as part of a model-based evaluation. Seven of these general models are statistical models predicting progression of AD using a measure of cognitive function. The main concerns with models are on model structure, around the limited characterization of disease progression, and on the use of a limited number of health states to capture events related to disease progression over time. None of the available models have been able to present a comprehensive model of the natural history of AD. Although helpful, there are serious limitations in the methods available to model progression of AD over time. Advances are needed to better model the progression of AD and the effects of the disease on peoples' lives. Recent evidence supports the need for a multivariable approach to the modelling of AD progression, and indicates that a latent variable analytic approach to characterising AD progression is a promising avenue for advances in the statistical development of modelling methods. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  1. A murine model of human myeloma bone disease

    NARCIS (Netherlands)

    Garrett, I.R.; Dallas, S.; Radl, J.; Mundy, G.R.

    1997-01-01

    Myeloma causes a devastating and unique form of osteolytic bone disease. Although osteoclast activation is responsible for bone destruction, the precise mechanisms by which myeloma cells increase osteoclast activity have not been defined. An animal model of human myeloma bone disease mould help in

  2. Animal models of human respiratory syncytial virus disease

    NARCIS (Netherlands)

    Bem, Reinout A.; Domachowske, Joseph B.; Rosenberg, Helene F.

    2011-01-01

    Infection with the human pneumovirus pathogen, respiratory syncytial virus (hRSV), causes a wide spectrum of respiratory disease, notably among infants and the elderly. Laboratory animal studies permit detailed experimental modeling of hRSV disease and are therefore indispensable in the search for

  3. Macrophage models of Gaucher disease for evaluating disease pathogenesis and candidate drugs.

    Science.gov (United States)

    Aflaki, Elma; Stubblefield, Barbara K; Maniwang, Emerson; Lopez, Grisel; Moaven, Nima; Goldin, Ehud; Marugan, Juan; Patnaik, Samarjit; Dutra, Amalia; Southall, Noel; Zheng, Wei; Tayebi, Nahid; Sidransky, Ellen

    2014-06-11

    Gaucher disease is caused by an inherited deficiency of glucocerebrosidase that manifests with storage of glycolipids in lysosomes, particularly in macrophages. Available cell lines modeling Gaucher disease do not demonstrate lysosomal storage of glycolipids; therefore, we set out to develop two macrophage models of Gaucher disease that exhibit appropriate substrate accumulation. We used these cellular models both to investigate altered macrophage biology in Gaucher disease and to evaluate candidate drugs for its treatment. We generated and characterized monocyte-derived macrophages from 20 patients carrying different Gaucher disease mutations. In addition, we created induced pluripotent stem cell (iPSC)-derived macrophages from five fibroblast lines taken from patients with type 1 or type 2 Gaucher disease. Macrophages derived from patient monocytes or iPSCs showed reduced glucocerebrosidase activity and increased storage of glucocerebroside and glucosylsphingosine in lysosomes. These macrophages showed efficient phagocytosis of bacteria but reduced production of intracellular reactive oxygen species and impaired chemotaxis. The disease phenotype was reversed with a noninhibitory small-molecule chaperone drug that enhanced glucocerebrosidase activity in the macrophages, reduced glycolipid storage, and normalized chemotaxis and production of reactive oxygen species. Macrophages differentiated from patient monocytes or patient-derived iPSCs provide cellular models that can be used to investigate disease pathogenesis and facilitate drug development. Copyright © 2014, American Association for the Advancement of Science.

  4. Disease Modeling and Gene Therapy of Copper Storage Disease in Canine Hepatic Organoids

    NARCIS (Netherlands)

    Nantasanti, Sathidpak; Spee, Bart; Kruitwagen, Hedwig S.; Chen, Chen; Geijsen, Niels; Oosterhoff, Loes A.; van Wolferen, Monique E.; Pelaez, Nicolas; Fieten, Hille; Wubbolts, Richard W.; Grinwis, Guy C.; Chan, Jefferson; Huch, Meritxell; Vries, Robert R. G.; Clevers, Hans; de Bruin, Alain; Rothuizen, Jan; Penning, Louis C.; Schotanus, Baukje A.

    2015-01-01

    The recent development of 3D-liver stem cell cultures (hepatic organoids) opens up new avenues for gene and/or stem cell therapy to treat liver disease. To test safety and efficacy, a relevant large animal model is essential but not yet established. Because of its shared pathologies and disease

  5. Vitiligo: A Possible Model of Degenerative Diseases

    Science.gov (United States)

    Bellei, Barbara; Pitisci, Angela; Ottaviani, Monica; Ludovici, Matteo; Cota, Carlo; Luzi, Fabiola; Dell'Anna, Maria Lucia; Picardo, Mauro

    2013-01-01

    Vitiligo is characterized by the progressive disappearance of pigment cells from skin and hair follicle. Several in vitro and in vivo studies show evidence of an altered redox status, suggesting that loss of cellular redox equilibrium might be the pathogenic mechanism in vitiligo. However, despite the numerous data supporting a pathogenic role of oxidative stress, there is still no consensus explanation underlying the oxidative stress-driven disappear of melanocytes from the epidermis. In this study, in vitro characterization of melanocytes cultures from non-lesional vitiligo skin revealed at the cellular level aberrant function of signal transduction pathways common with neurodegenerative diseases including modification of lipid metabolism, hyperactivation of mitogen-activated protein kinase (MAPK) and cAMP response element-binding protein (CREB), constitutive p53-dependent stress signal transduction cascades, and enhanced sensibility to pro-apoptotic stimuli. Notably, these long-term effects of subcytotoxic oxidative stress are also biomarkers of pre-senescent cellular phenotype. Consistent with this, vitiligo cells showed a significant increase in p16 that did not correlate with the chronological age of the donor. Moreover, vitiligo melanocytes produced many biologically active proteins among the senescence-associated secretory phenotype (SAPS), such as interleukin-6 (IL-6), matrix metallo proteinase-3 (MMP3), cyclooxygenase-2 (Cox-2), insulin-like growth factor-binding protein-3 and 7 (IGFBP3, IGFBP7). Together, these data argue for a complicated pathophysiologic puzzle underlying melanocytes degeneration resembling, from the biological point of view, neurodegenerative diseases. Our results suggest new possible targets for intervention that in combination with current therapies could correct melanocytes intrinsic defects. PMID:23555779

  6. A mathematical model of insulin resistance in Parkinson's disease.

    Science.gov (United States)

    Braatz, Elise M; Coleman, Randolph A

    2015-06-01

    This paper introduces a mathematical model representing the biochemical interactions between insulin signaling and Parkinson's disease. The model can be used to examine the changes that occur over the course of the disease as well as identify which processes would be the most effective targets for treatment. The model is mathematized using biochemical systems theory (BST). It incorporates a treatment strategy that includes several experimental drugs along with current treatments. In the past, BST models of neurodegeneration have used power law analysis and simulation (PLAS) to model the system. This paper recommends the use of MATLAB instead. MATLAB allows for more flexibility in both the model itself and in data analysis. Previous BST analyses of neurodegeneration began treatment at disease onset. As shown in this model, the outcomes of delayed, realistic treatment and full treatment at disease onset are significantly different. The delayed treatment strategy is an important development in BST modeling of neurodegeneration. It emphasizes the importance of early diagnosis, and allows for a more accurate representation of disease and treatment interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Modelling and controlling infectious diseases | IDRC - International ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The research team is exploring the potential of mathematical modelling to ... to China's health system and improvements to its medical research capacity. ... and on the scientific board of the Gates Foundation's Global Health program. ... He has published more than 400 research papers in national and international journals.

  8. Animal model of human disease. Multiple myeloma

    NARCIS (Netherlands)

    Radl, J.; Croese, J.W.; Zurcher, C.; Enden-Vieveen, M.H.M. van den; Leeuw, A.M. de

    1988-01-01

    Animal models of spontaneous and induced plasmacytomas in some inbred strains of mice have proven to be useful tools for different studies on tumorigenesis and immunoregulation. Their wide applicability and the fact that after their intravenous transplantation, the recipient mice developed bone

  9. Murine nephrotoxic nephritis as a model of chronic kidney disease

    DEFF Research Database (Denmark)

    Ougaard, M. K.E.; Kvist, P. H.; Jensen, H. E.

    2018-01-01

    Using the nonaccelerated murine nephrotoxic nephritis (NTN) as a model of chronic kidney disease (CKD) could provide an easily inducible model that enables a rapid test of treatments. Originally, the NTN model was developed as an acute model of glomerulonephritis, but in this study we evaluate...... progressive mesangial expansion and significant renal fibrosis within three weeks suggesting CKD development. CD1 and C57BL/6 females showed a similar disease progression, but female mice seemed more susceptible to NTS compared to male mice. The presence of albuminuria, GFR decline, mesangial expansion...

  10. Classic and New Animal Models of Parkinson's Disease

    Directory of Open Access Journals (Sweden)

    Javier Blesa

    2012-01-01

    Full Text Available Neurological disorders can be modeled in animals so as to recreate specific pathogenic events and behavioral outcomes. Parkinson’s Disease (PD is the second most common neurodegenerative disease of an aging population, and although there have been several significant findings about the PD disease process, much of this process still remains a mystery. Breakthroughs in the last two decades using animal models have offered insights into the understanding of the PD disease process, its etiology, pathology, and molecular mechanisms. Furthermore, while cellular models have helped to identify specific events, animal models, both toxic and genetic, have replicated almost all of the hallmarks of PD and are useful for testing new neuroprotective or neurorestorative strategies. Moreover, significant advances in the modeling of additional PD features have come to light in both classic and newer models. In this review, we try to provide an updated summary of the main characteristics of these models as well as the strengths and weaknesses of what we believe to be the most popular PD animal models. These models include those produced by 6-hydroxydopamine (6-OHDA, 1-methyl-1,2,3,6-tetrahydropiridine (MPTP, rotenone, and paraquat, as well as several genetic models like those related to alpha-synuclein, PINK1, Parkin and LRRK2 alterations.

  11. Interprofessional Collaborative Practice Models in Chronic Disease Management.

    Science.gov (United States)

    Southerland, Janet H; Webster-Cyriaque, Jennifer; Bednarsh, Helene; Mouton, Charles P

    2016-10-01

    Interprofessional collaboration in health has become essential to providing high-quality care, decreased costs, and improved outcomes. Patient-centered care requires synthesis of all the components of primary and specialty medicine to address patient needs. For individuals living with chronic diseases, this model is even more critical to obtain better health outcomes. Studies have shown shown that oral health and systemic disease are correlated as it relates to disease development and progression. Thus, inclusion of oral health in many of the existing and new collaborative models could result in better management of chronic illnesses and improve overall health outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Modeling human gastrointestinal inflammatory diseases using microphysiological culture systems.

    Science.gov (United States)

    Hartman, Kira G; Bortner, James D; Falk, Gary W; Ginsberg, Gregory G; Jhala, Nirag; Yu, Jian; Martín, Martín G; Rustgi, Anil K; Lynch, John P

    2014-09-01

    Gastrointestinal illnesses are a significant health burden for the US population, with 40 million office visits each year for gastrointestinal complaints and nearly 250,000 deaths. Acute and chronic inflammations are a common element of many gastrointestinal diseases. Inflammatory processes may be initiated by a chemical injury (acid reflux in the esophagus), an infectious agent (Helicobacter pylori infection in the stomach), autoimmune processes (graft versus host disease after bone marrow transplantation), or idiopathic (as in the case of inflammatory bowel diseases). Inflammation in these settings can contribute to acute complaints (pain, bleeding, obstruction, and diarrhea) as well as chronic sequelae including strictures and cancer. Research into the pathophysiology of these conditions has been limited by the availability of primary human tissues or appropriate animal models that attempt to physiologically model the human disease. With the many recent advances in tissue engineering and primary human cell culture systems, it is conceivable that these approaches can be adapted to develop novel human ex vivo systems that incorporate many human cell types to recapitulate in vivo growth and differentiation in inflammatory microphysiological environments. Such an advance in technology would improve our understanding of human disease progression and enhance our ability to test for disease prevention strategies and novel therapeutics. We will review current models for the inflammatory and immunological aspects of Barrett's esophagus, acute graft versus host disease, and inflammatory bowel disease and explore recent advances in culture methodologies that make these novel microphysiological research systems possible. © 2014 by the Society for Experimental Biology and Medicine.

  13. Disease-specific induced pluripotent stem cells: a platform for human disease modeling and drug discovery.

    Science.gov (United States)

    Jang, Jiho; Yoo, Jeong-Eun; Lee, Jeong-Ah; Lee, Dongjin R; Kim, Ji Young; Huh, Yong Jun; Kim, Dae-Sung; Park, Chul-Yong; Hwang, Dong-Youn; Kim, Han-Soo; Kang, Hoon-Chul; Kim, Dong-Wook

    2012-03-31

    The generation of disease-specific induced pluripotent stem cell (iPSC) lines from patients with incurable diseases is a promising approach for studying disease mechanisms and drug screening. Such innovation enables to obtain autologous cell sources in regenerative medicine. Herein, we report the generation and characterization of iPSCs from fibroblasts of patients with sporadic or familial diseases, including Parkinson's disease (PD), Alzheimer's disease (AD), juvenile-onset, type I diabetes mellitus (JDM), and Duchenne type muscular dystrophy (DMD), as well as from normal human fibroblasts (WT). As an example to modeling disease using disease-specific iPSCs, we also discuss the previously established childhood cerebral adrenoleukodystrophy (CCALD)- and adrenomyeloneuropathy (AMN)-iPSCs by our group. Through DNA fingerprinting analysis, the origins of generated disease-specific iPSC lines were identified. Each iPSC line exhibited an intense alkaline phosphatase activity, expression of pluripotent markers, and the potential to differentiate into all three embryonic germ layers: the ectoderm, endoderm, and mesoderm. Expression of endogenous pluripotent markers and downregulation of retrovirus-delivered transgenes [OCT4 (POU5F1), SOX2, KLF4, and c-MYC] were observed in the generated iPSCs. Collectively, our results demonstrated that disease-specific iPSC lines characteristically resembled hESC lines. Furthermore, we were able to differentiate PD-iPSCs, one of the disease-specific-iPSC lines we generated, into dopaminergic (DA) neurons, the cell type mostly affected by PD. These PD-specific DA neurons along with other examples of cell models derived from disease-specific iPSCs would provide a powerful platform for examining the pathophysiology of relevant diseases at the cellular and molecular levels and for developing new drugs and therapeutic regimens.

  14. Using Human Induced Pluripotent Stem Cells to Model Skeletal Diseases.

    Science.gov (United States)

    Barruet, Emilie; Hsiao, Edward C

    2016-01-01

    Musculoskeletal disorders affecting the bones and joints are major health problems among children and adults. Major challenges such as the genetic origins or poor diagnostics of severe skeletal disease hinder our understanding of human skeletal diseases. The recent advent of human induced pluripotent stem cells (human iPS cells) provides an unparalleled opportunity to create human-specific models of human skeletal diseases. iPS cells have the ability to self-renew, allowing us to obtain large amounts of starting material, and have the potential to differentiate into any cell types in the body. In addition, they can carry one or more mutations responsible for the disease of interest or be genetically corrected to create isogenic controls. Our work has focused on modeling rare musculoskeletal disorders including fibrodysplasia ossificans progressive (FOP), a congenital disease of increased heterotopic ossification. In this review, we will discuss our experiences and protocols differentiating human iPS cells toward the osteogenic lineage and their application to model skeletal diseases. A number of critical challenges and exciting new approaches are also discussed, which will allow the skeletal biology field to harness the potential of human iPS cells as a critical model system for understanding diseases of abnormal skeletal formation and bone regeneration.

  15. Glycogen storage disease type Ia in canines: a model for human metabolic and genetic liver disease.

    Science.gov (United States)

    Specht, Andrew; Fiske, Laurie; Erger, Kirsten; Cossette, Travis; Verstegen, John; Campbell-Thompson, Martha; Struck, Maggie B; Lee, Young Mok; Chou, Janice Y; Byrne, Barry J; Correia, Catherine E; Mah, Cathryn S; Weinstein, David A; Conlon, Thomas J

    2011-01-01

    A canine model of Glycogen storage disease type Ia (GSDIa) is described. Affected dogs are homozygous for a previously described M121I mutation resulting in a deficiency of glucose-6-phosphatase-α. Metabolic, clinicopathologic, pathologic, and clinical manifestations of GSDIa observed in this model are described and compared to those observed in humans. The canine model shows more complete recapitulation of the clinical manifestations seen in humans including "lactic acidosis", larger size, and longer lifespan compared to other animal models. Use of this model in preclinical trials of gene therapy is described and briefly compared to the murine model. Although the canine model offers a number of advantages for evaluating potential therapies for GSDIa, there are also some significant challenges involved in its use. Despite these challenges, the canine model of GSDIa should continue to provide valuable information about the potential for generating curative therapies for GSDIa as well as other genetic hepatic diseases.

  16. Glycogen Storage Disease Type Ia in Canines: A Model for Human Metabolic and Genetic Liver Disease

    Directory of Open Access Journals (Sweden)

    Andrew Specht

    2011-01-01

    Full Text Available A canine model of Glycogen storage disease type Ia (GSDIa is described. Affected dogs are homozygous for a previously described M121I mutation resulting in a deficiency of glucose-6-phosphatase-α. Metabolic, clinicopathologic, pathologic, and clinical manifestations of GSDIa observed in this model are described and compared to those observed in humans. The canine model shows more complete recapitulation of the clinical manifestations seen in humans including “lactic acidosis”, larger size, and longer lifespan compared to other animal models. Use of this model in preclinical trials of gene therapy is described and briefly compared to the murine model. Although the canine model offers a number of advantages for evaluating potential therapies for GSDIa, there are also some significant challenges involved in its use. Despite these challenges, the canine model of GSDIa should continue to provide valuable information about the potential for generating curative therapies for GSDIa as well as other genetic hepatic diseases.

  17. Genetic enhancement of macroautophagy in vertebrate models of neurodegenerative diseases.

    Science.gov (United States)

    Ejlerskov, Patrick; Ashkenazi, Avraham; Rubinsztein, David C

    2018-04-03

    Most of the neurodegenerative diseases that afflict humans manifest with the intraneuronal accumulation of toxic proteins that are aggregate-prone. Extensive data in cell and neuronal models support the concept that such proteins, like mutant huntingtin or alpha-synuclein, are substrates for macroautophagy (hereafter autophagy). Furthermore, autophagy-inducing compounds lower the levels of such proteins and ameliorate their toxicity in diverse animal models of neurodegenerative diseases. However, most of these compounds also have autophagy-independent effects and it is important to understand if similar benefits are seen with genetic strategies that upregulate autophagy, as this strengthens the validity of this strategy in such diseases. Here we review studies in vertebrate models using genetic manipulations of core autophagy genes and describe how these improve pathology and neurodegeneration, supporting the validity of autophagy upregulation as a target for certain neurodegenerative diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Drosophila as an In Vivo Model for Human Neurodegenerative Disease

    Science.gov (United States)

    McGurk, Leeanne; Berson, Amit; Bonini, Nancy M.

    2015-01-01

    With the increase in the ageing population, neurodegenerative disease is devastating to families and poses a huge burden on society. The brain and spinal cord are extraordinarily complex: they consist of a highly organized network of neuronal and support cells that communicate in a highly specialized manner. One approach to tackling problems of such complexity is to address the scientific questions in simpler, yet analogous, systems. The fruit fly, Drosophila melanogaster, has been proven tremendously valuable as a model organism, enabling many major discoveries in neuroscientific disease research. The plethora of genetic tools available in Drosophila allows for exquisite targeted manipulation of the genome. Due to its relatively short lifespan, complex questions of brain function can be addressed more rapidly than in other model organisms, such as the mouse. Here we discuss features of the fly as a model for human neurodegenerative disease. There are many distinct fly models for a range of neurodegenerative diseases; we focus on select studies from models of polyglutamine disease and amyotrophic lateral sclerosis that illustrate the type and range of insights that can be gleaned. In discussion of these models, we underscore strengths of the fly in providing understanding into mechanisms and pathways, as a foundation for translational and therapeutic research. PMID:26447127

  19. Towards a characterization of behavior-disease models.

    Directory of Open Access Journals (Sweden)

    Nicola Perra

    Full Text Available The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself. While models lacking this coupling can be extremely successful in mild epidemics, they obviously will be of limited use in situations where social disruption or behavioral alterations are induced in the population by knowledge of the disease. Here we propose a characterization of a set of prototypical mechanisms for self-initiated social distancing induced by local and non-local prevalence-based information available to individuals in the population. We characterize the effects of these mechanisms in the framework of a compartmental scheme that enlarges the basic SIR model by considering separate behavioral classes within the population. The transition of individuals in/out of behavioral classes is coupled with the spreading of the disease and provides a rich phase space with multiple epidemic peaks and tipping points. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.

  20. Gene therapy in nonhuman primate models of human autoimmune disease

    NARCIS (Netherlands)

    t'Hart, B. A.; Vervoordeldonk, M.; Heeney, J. L.; Tak, P. P.

    2003-01-01

    Before autoimmune diseases in humans can be treated with gene therapy, the safety and efficacy of the used vectors must be tested in valid experimental models. Monkeys, such as the rhesus macaque or the common marmoset, provide such models. This publication reviews the state of the art in monkey

  1. Animal models for human genetic diseases | Sharif | African Journal ...

    African Journals Online (AJOL)

    The study of human genetic diseases can be greatly aided by animal models because of their similarity to humans in terms of genetics. In addition to understand diverse aspects of basic biology, model organisms are extensively used in applied research in agriculture, industry, and also in medicine, where they are used to ...

  2. PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain.

    Science.gov (United States)

    Younesi, Erfan; Malhotra, Ashutosh; Gündel, Michaela; Scordis, Phil; Kodamullil, Alpha Tom; Page, Matt; Müller, Bernd; Springstubbe, Stephan; Wüllner, Ullrich; Scheller, Dieter; Hofmann-Apitius, Martin

    2015-09-22

    Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson's disease. In the area of Parkinson's research, there is a pressing need to integrate various pieces of information into a meaningful context of presumed disease mechanism(s). Disease ontologies provide a novel means for organizing, integrating, and standardizing the knowledge domains specific to disease in a compact, formalized and computer-readable form and serve as a reference for knowledge exchange or systems modeling of disease mechanism. The Parkinson's disease ontology was built according to the life cycle of ontology building. Structural, functional, and expert evaluation of the ontology was performed to ensure the quality and usability of the ontology. A novelty metric has been introduced to measure the gain of new knowledge using the ontology. Finally, a cause-and-effect model was built around PINK1 and two gene expression studies from the Gene Expression Omnibus database were re-annotated to demonstrate the usability of the ontology. The Parkinson's disease ontology with a subclass-based taxonomic hierarchy covers the broad spectrum of major biomedical concepts from molecular to clinical features of the disease, and also reflects different views on disease features held by molecular biologists, clinicians and drug developers. The current version of the ontology contains 632 concepts, which are organized under nine views. The structural evaluation showed the balanced dispersion of concept classes throughout the ontology. The functional evaluation demonstrated that the ontology-driven literature search could gain novel knowledge not present in the reference Parkinson's knowledge map. The ontology was able to answer specific questions related to Parkinson's when evaluated by experts. Finally, the added value of the Parkinson's disease ontology is demonstrated by ontology-driven modeling of PINK1

  3. Research advances in animal models of nonalcoholic fatty liver disease

    Directory of Open Access Journals (Sweden)

    HUANG Haiyan

    2014-09-01

    Full Text Available In recent years, the incidence of nonalcoholic fatty liver disease (NAFLD has increased gradually along with the rising prevalence of obesity, type 2 diabetes, and hyperlipidemia, and NAFLD has become one of the most common chronic liver diseases in the world and the second major liver disease after chronic viral hepatitis in China. However, its pathogenesis has not yet been clarified. Animal models are playing an important role in researches on NAFLD due to the facts that the development and progression of NAFLD require a long period of time, and ethical limitations exist in conducting drug trials in patients or collecting liver tissues from patients. The animal models with histopathology similar to that of NAFLD patients are reviewed, and their modeling principle, as well as the advantages and disadvantages, are compared. Animal models provide a powerful tool for further studies of NAFLD pathogenesis and drug screening for prevention and treatment of NAFLD.

  4. Skin Diseases Modeling using Combined Tissue Engineering and Microfluidic Technologies.

    Science.gov (United States)

    Mohammadi, Mohammad Hossein; Heidary Araghi, Behnaz; Beydaghi, Vahid; Geraili, Armin; Moradi, Farshid; Jafari, Parya; Janmaleki, Mohsen; Valente, Karolina Papera; Akbari, Mohsen; Sanati-Nezhad, Amir

    2016-10-01

    In recent years, both tissue engineering and microfluidics have significantly contributed in engineering of in vitro skin substitutes to test the penetration of chemicals or to replace damaged skins. Organ-on-chip platforms have been recently inspired by the integration of microfluidics and biomaterials in order to develop physiologically relevant disease models. However, the application of organ-on-chip on the development of skin disease models is still limited and needs to be further developed. The impact of tissue engineering, biomaterials and microfluidic platforms on the development of skin grafts and biomimetic in vitro skin models is reviewed. The integration of tissue engineering and microfluidics for the development of biomimetic skin-on-chip platforms is further discussed, not only to improve the performance of present skin models, but also for the development of novel skin disease platforms for drug screening processes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Disease models of chronic inflammatory airway disease : applications and requirements for clinical trials

    NARCIS (Netherlands)

    Diamant, Zuzana; Clarke, Graham W.; Pieterse, Herman; Gispert, Juan

    Purpose of reviewThis review will discuss methodologies and applicability of key inflammatory models of respiratory disease in proof of concept or proof of efficacy clinical studies. In close relationship with these models, induced sputum and inflammatory cell counts will be addressed for

  6. Neurodegeneration and Epilepsy in a Zebrafish Model of CLN3 Disease (Batten Disease.

    Directory of Open Access Journals (Sweden)

    Kim Wager

    Full Text Available The neuronal ceroid lipofuscinoses are a group of lysosomal storage disorders that comprise the most common, genetically heterogeneous, fatal neurodegenerative disorders of children. They are characterised by childhood onset, visual failure, epileptic seizures, psychomotor retardation and dementia. CLN3 disease, also known as Batten disease, is caused by autosomal recessive mutations in the CLN3 gene, 80-85% of which are a ~1 kb deletion. Currently no treatments exist, and after much suffering, the disease inevitably results in premature death. The aim of this study was to generate a zebrafish model of CLN3 disease using antisense morpholino injection, and characterise the pathological and functional consequences of Cln3 deficiency, thereby providing a tool for future drug discovery. The model was shown to faithfully recapitulate the pathological signs of CLN3 disease, including reduced survival, neuronal loss, retinopathy, axonopathy, loss of motor function, lysosomal storage of subunit c of mitochondrial ATP synthase, and epileptic seizures, albeit with an earlier onset and faster progression than the human disease. Our study provides proof of principle that the advantages of the zebrafish over other model systems can be utilised to further our understanding of the pathogenesis of CLN3 disease and accelerate drug discovery.

  7. Current Knowledge of Leishmania Vectors in Mexico: How Geographic Distributions of Species Relate to Transmission Areas

    Science.gov (United States)

    González, Camila; Rebollar-Téllez, Eduardo A.; Ibáñez-Bernal, Sergio; Becker-Fauser, Ingeborg; Martínez-Meyer, Enrique; Peterson, A. Townsend; Sánchez-Cordero, Víctor

    2011-01-01

    Leishmaniases are a group of vector-borne diseases with different clinical manifestations caused by parasites transmitted by sand fly vectors. In Mexico, the sand fly Lutzomyia olmeca olmeca is the only vector proven to transmit the parasite Leishmania mexicana to humans, which causes leishmaniasis. Other vector species with potential medical importance have been obtained, but their geographic distributions and relation to transmission areas have never been assessed. We modeled the ecological niches of nine sand fly species and projected niches to estimate potential distributions by using known occurrences, environmental coverages, and the algorithms GARP and Maxent. All vector species were distributed in areas with known recurrent transmission, except for Lu. diabolica, which appeared to be related only to areas of occasional transmission in northern Mexico. The distribution of Lu. o. olmeca does not overlap with all reported cutaneous leishmaniasis cases, suggesting that Lu. cruciata and Lu. shannoni are likely also involved as primary vectors in those areas. Our study provides useful information of potential risk areas of leishmaniasis transmission in Mexico. PMID:22049037

  8. Primary immunodeficiency disease: a model for case management of chronic diseases.

    Science.gov (United States)

    Burton, Janet; Murphy, Elyse; Riley, Patty

    2010-01-01

    Patient-centered chronic care management is a new model for the management of rare chronic diseases such as primary immunodeficiency disease (PIDD). This approach emphasizes helping patients become experts on the management of their disease as informed, involved, and interactive partners in healthcare decisions with providers. Because only a few patients are affected by rare illnesses, these patients are forced to become knowledgeable about their disease and therapies and to seek treatment from a healthcare team, which includes physicians and nurse specialists who are equipped to manage the complexity of the disease and its comorbidities. Importantly, therapy for PIDD can be self-administered at home, which has encouraged the transition toward a proactive stance that is at the heart of patient-centered chronic care management. We discuss the evolution of therapy, the issues with the disease, and challenges with its management within the framework of other chronic disease management programs. Suggestions and rationale to move case management of PIDD forward are presented with the intent that sharing our experiences will improve process and better manage outcomes in this patient population. The patient-centered model for the management of PIDD is applicable to the primary care settings, where nurse case managers assist patients through education, support them and their families, and facilitate access to community resources in an approach, which has been described as "guided care." The model also applies specifically to immunology centers where patients receive treatment or instruction on its self-administration at home. Patient-centered management of PIDD, with its emphasis on full involvement of patients in their treatment, has the potential to improve compliance with treatment, and thus patient outcomes, as well as patients' quality of life. The patient-centered model expands the traditional model of chronic disease management, which relies on evidence

  9. Modelling Alzheimer’s disease: from past to future

    Directory of Open Access Journals (Sweden)

    Claudia eSaraceno

    2013-06-01

    Full Text Available Alzheimer’s disease (AD is emerging as the most prevalent and socially disruptive illness of aging populations, as more people live long enough to become affected. Although AD is placing a considerable and increasing burden on society, it represents the largest unmet medical need in neurology, because current drugs improve symptoms, but do not have profound disease-modifying effects.Although AD pathogenesis is multifaceted and difficult to pinpoint, genetic and cell biological studies led to the amyloid hypothesis, which posits that Aβ plays a pivotal role in AD pathogenesis. Amyloid precursor protein (APP, as well as β- and γ-secretases are the principal players involved in Aβ production, while α-secretase cleavage on APP prevents Aβ deposition. The association of early onset familial AD with mutations in the APP and γ-secretase components provided a potential tool of generating animal models of the disease. However, a model that recapitulates all the aspects of AD has not yet been produced.Here, we face the problem of modelling AD pathology describing several models, which have played a major role in defining critical disease-related mechanisms and in exploring novel potential therapeutic approaches. In particular, we will provide an extensive overview on the distinct features and pros and contras of different AD models, ranging from invertebrate to rodent models and finally dealing with computational models and induced pluripotent stem cells.

  10. Airborne spread of foot-and-mouth disease - model intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Gloster, J; Jones, A; Redington, A; Burgin, L; Sorensen, J H; Turner, R; Dillon, M; Hullinger, P; Simpson, M; Astrup, P; Garner, G; Stewart, P; D' Amours, R; Sellers, R; Paton, D

    2008-09-04

    Foot-and-mouth disease is a highly infectious vesicular disease of cloven-hoofed animals caused by foot-and-mouth disease virus. It spreads by direct contact between animals, by animal products (milk, meat and semen), by mechanical transfer on people or fomites and by the airborne route - with the relative importance of each mechanism depending on the particular outbreak characteristics. Over the years a number of workers have developed or adapted atmospheric dispersion models to assess the risk of foot-and-mouth disease virus spread through the air. Six of these models were compared at a workshop hosted by the Institute for Animal Health/Met Office during 2008. A number of key issues emerged from the workshop and subsequent modelling work: (1) in general all of the models predicted similar directions for 'at risk' livestock with much of the remaining differences strongly related to differences in the meteorological data used; (2) determination of an accurate sequence of events is highly important, especially if the meteorological conditions vary substantially during the virus emission period; and (3) differences in assumptions made about virus release, environmental fate, and subsequent infection can substantially modify the size and location of the downwind risk area. Close relationships have now been established between participants, which in the event of an outbreak of disease could be readily activated to supply advice or modelling support.

  11. Experimental Models of Inherited PrP Prion Diseases.

    Science.gov (United States)

    Watts, Joel C; Prusiner, Stanley B

    2017-11-01

    The inherited prion protein (PrP) prion disorders, which include familial Creutzfeldt-Jakob disease, Gerstmann-Sträussler-Scheinker disease, and fatal familial insomnia, constitute ∼10%-15% of all PrP prion disease cases in humans. Attempts to generate animal models of these disorders using transgenic mice expressing mutant PrP have produced variable results. Although many lines of mice develop spontaneous signs of neurological illness with accompanying prion disease-specific neuropathological changes, others do not. Furthermore, demonstrating the presence of protease-resistant PrP species and prion infectivity-two of the hallmarks of the PrP prion disorders-in the brains of spontaneously sick mice has proven particularly challenging. Here, we review the progress that has been made toward developing accurate mouse models of the inherited PrP prion disorders. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

  12. Mottled Mice and Non-Mammalian Models of Menkes Disease

    DEFF Research Database (Denmark)

    Lenartowicz, Małgorzata; Krzeptowski, Wojciech; Lipiński, Paweł

    2015-01-01

    Menkes disease is a multi-systemic copper metabolism disorder caused by mutations in the X-linked ATP7A gene and characterized by progressive neurodegeneration and severe connective tissue defects. The ATP7A protein is a copper (Cu)-transporting ATPase expressed in all tissues and plays a critica......-mammalian models of Menkes disease, Drosophila melanogaster and Danio rerio mutants were used in experiments which would be technically difficult to carry out in mammals....

  13. Big Data for Infectious Disease Surveillance and Modeling

    OpenAIRE

    Bansal, Shweta; Chowell, Gerardo; Simonsen, Lone; Vespignani, Alessandro; Viboud, Cécile

    2016-01-01

    We devote a special issue of the Journal of Infectious Diseases to review the recent advances of big data in strengthening disease surveillance, monitoring medical adverse events, informing transmission models, and tracking patient sentiments and mobility. We consider a broad definition of big data for public health, one encompassing patient information gathered from high-volume electronic health records and participatory surveillance systems, as well as mining of digital traces such as socia...

  14. Modelling the distribution of pig production and diseases in Thailand

    OpenAIRE

    Thanapongtharm, Weerapong

    2015-01-01

    This thesis, entitled “Modelling the distribution of pig production and diseases in Thailand”, presents many aspects of pig production in Thailand including the characteristics of pig farming system, distribution of pig population and pig farms, spatio-temporal distribution and risk of most important diseases in pig at present, and the suitability area for pig farming. Spatial distribution and characteristics of pig farming in Thailand were studied using time-series pig population data to des...

  15. Disease Modeling and Gene Therapy of Copper Storage Disease in Canine Hepatic Organoids

    Directory of Open Access Journals (Sweden)

    Sathidpak Nantasanti

    2015-11-01

    Full Text Available The recent development of 3D-liver stem cell cultures (hepatic organoids opens up new avenues for gene and/or stem cell therapy to treat liver disease. To test safety and efficacy, a relevant large animal model is essential but not yet established. Because of its shared pathologies and disease pathways, the dog is considered the best model for human liver disease. Here we report the establishment of a long-term canine hepatic organoid culture allowing undifferentiated expansion of progenitor cells that can be differentiated toward functional hepatocytes. We show that cultures can be initiated from fresh and frozen liver tissues using Tru-Cut or fine-needle biopsies. The use of Wnt agonists proved important for canine organoid proliferation and inhibition of differentiation. Finally, we demonstrate that successful gene supplementation in hepatic organoids of COMMD1-deficient dogs restores function and can be an effective means to cure copper storage disease.

  16. Glycogen Storage Disease Type Ia in Canines: A Model for Human Metabolic and Genetic Liver Disease

    OpenAIRE

    Specht, Andrew; Fiske, Laurie; Erger, Kirsten; Cossette, Travis; Verstegen, John; Campbell-Thompson, Martha; Struck, Maggie B.; Lee, Young Mok; Chou, Janice Y.; Byrne, Barry J.; Correia, Catherine E.; Mah, Cathryn S.; Weinstein, David A.; Conlon, Thomas J.

    2011-01-01

    A canine model of Glycogen storage disease type Ia (GSDIa) is described. Affected dogs are homozygous for a previously described M121I mutation resulting in a deficiency of glucose-6-phosphatase-α. Metabolic, clinicopathologic, pathologic, and clinical manifestations of GSDIa observed in this model are described and compared to those observed in humans. The canine model shows more complete recapitulation of the clinical manifestations seen in humans including “lactic acidosis”, larger size,...

  17. A Customizable Model for Chronic Disease Coordination: Lessons Learned From the Coordinated Chronic Disease Program.

    Science.gov (United States)

    Voetsch, Karen; Sequeira, Sonia; Chavez, Amy Holmes

    2016-03-31

    In 2012, the Centers for Disease Control and Prevention provided funding and technical assistance to all states and territories to implement the Coordinated Chronic Disease Program, marking the first time that all state health departments had federal resources to coordinate chronic disease prevention and control programs. This article describes lessons learned from this initiative and identifies key elements of a coordinated approach. We analyzed 80 programmatic documents from 21 states and conducted semistructured interviews with 7 chronic disease directors. Six overarching themes emerged: 1) focused agenda, 2) identification of functions, 3) comprehensive planning, 4) collaborative leadership and expertise, 5) managed resources, and 6) relationship building. These elements supported 4 essential activities: 1) evidence-based interventions, 2) strategic use of staff, 3) consistent communication, and 4) strong program infrastructure. On the basis of these elements and activities, we propose a conceptual model that frames overarching concepts, skills, and strategies needed to coordinate state chronic disease prevention and control programs.

  18. An architecture model for multiple disease management information systems.

    Science.gov (United States)

    Chen, Lichin; Yu, Hui-Chu; Li, Hao-Chun; Wang, Yi-Van; Chen, Huang-Jen; Wang, I-Ching; Wang, Chiou-Shiang; Peng, Hui-Yu; Hsu, Yu-Ling; Chen, Chi-Huang; Chuang, Lee-Ming; Lee, Hung-Chang; Chung, Yufang; Lai, Feipei

    2013-04-01

    Disease management is a program which attempts to overcome the fragmentation of healthcare system and improve the quality of care. Many studies have proven the effectiveness of disease management. However, the case managers were spending the majority of time in documentation, coordinating the members of the care team. They need a tool to support them with daily practice and optimizing the inefficient workflow. Several discussions have indicated that information technology plays an important role in the era of disease management. Whereas applications have been developed, it is inefficient to develop information system for each disease management program individually. The aim of this research is to support the work of disease management, reform the inefficient workflow, and propose an architecture model that enhance on the reusability and time saving of information system development. The proposed architecture model had been successfully implemented into two disease management information system, and the result was evaluated through reusability analysis, time consumed analysis, pre- and post-implement workflow analysis, and user questionnaire survey. The reusability of the proposed model was high, less than half of the time was consumed, and the workflow had been improved. The overall user aspect is positive. The supportiveness during daily workflow is high. The system empowers the case managers with better information and leads to better decision making.

  19. Use of rodents as models of human diseases

    Directory of Open Access Journals (Sweden)

    Thierry F Vandamme

    2014-01-01

    Full Text Available Advances in molecular biology have significantly increased the understanding of the biology of different diseases. However, these discoveries have not yet been fully translated into improved treatments for patients with diseases such as cancers. One of the factors limiting the translation of knowledge from preclinical studies to the clinic has been the limitations of in vivo diseases models. In this brief review, we will discuss the advantages and disadvantages of rodent models that have been developed to simulate human pathologies, focusing in models that employ xenografts and genetic modification. Within the framework of genetically engineered mouse (GEM models, we will review some of the current genetic strategies for modeling diseases in the mouse and the preclinical studies that have already been undertaken. We will also discuss how recent improvements in imaging technologies may increase the information derived from using these GEMs during early assessments of potential therapeutic pathways. Furthermore, it is interesting to note that one of the values of using a mouse model is the very rapid turnover rate of the animal, going through the process of birth to death in a very short timeframe relative to that of larger mammalian species.

  20. Simple model systems: a challenge for Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Di Carlo Marta

    2012-04-01

    Full Text Available Abstract The success of biomedical researches has led to improvement in human health and increased life expectancy. An unexpected consequence has been an increase of age-related diseases and, in particular, neurodegenerative diseases. These disorders are generally late onset and exhibit complex pathologies including memory loss, cognitive defects, movement disorders and death. Here, it is described as the use of simple animal models such as worms, fishes, flies, Ascidians and sea urchins, have facilitated the understanding of several biochemical mechanisms underlying Alzheimer's disease (AD, one of the most diffuse neurodegenerative pathologies. The discovery of specific genes and proteins associated with AD, and the development of new technologies for the production of transgenic animals, has helped researchers to overcome the lack of natural models. Moreover, simple model systems of AD have been utilized to obtain key information for evaluating potential therapeutic interventions and for testing efficacy of putative neuroprotective compounds.

  1. A Framework for Modeling Emerging Diseases to Inform Management.

    Science.gov (United States)

    Russell, Robin E; Katz, Rachel A; Richgels, Katherine L D; Walsh, Daniel P; Grant, Evan H C

    2017-01-01

    The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

  2. New Insights from Rodent Models of Fatty Liver Disease

    Science.gov (United States)

    2011-01-01

    Abstract Rodent models of fatty liver disease are essential research tools that provide a window into disease pathogenesis and a testing ground for prevention and treatment. Models come in many varieties involving dietary and genetic manipulations, and sometimes both. High-energy diets that induce obesity do not uniformly cause fatty liver disease; this has prompted close scrutiny of specific macronutrients and nutrient combinations to determine which have the greatest potential for hepatotoxicity. At the same time, diets that do not cause obesity or the metabolic syndrome but do cause severe steatohepatitis have been exploited to study factors important to progressive liver injury, including cell death, oxidative stress, and immune activation. Rodents with a genetic predisposition to overeating offer yet another model in which to explore the evolution of fatty liver disease. In some animals that overeat, steatohepatitis can develop even without resorting to a high-energy diet. Importantly, these models and others have been used to document that aerobic exercise can prevent or reduce fatty liver disease. This review focuses primarily on lessons learned about steatohepatitis from manipulations of diet and eating behavior. Numerous additional insights about hepatic lipid metabolism, which have been gained from genetically engineered mice, are also mentioned. Antioxid. Redox Signal. 15, 535–550. PMID:21126212

  3. Disease management with ARIMA model in time series.

    Science.gov (United States)

    Sato, Renato Cesar

    2013-01-01

    The evaluation of infectious and noninfectious disease management can be done through the use of a time series analysis. In this study, we expect to measure the results and prevent intervention effects on the disease. Clinical studies have benefited from the use of these techniques, particularly for the wide applicability of the ARIMA model. This study briefly presents the process of using the ARIMA model. This analytical tool offers a great contribution for researchers and healthcare managers in the evaluation of healthcare interventions in specific populations.

  4. Multiple sclerosis care: an integrated disease-management model.

    Science.gov (United States)

    Burks, J

    1998-04-01

    A disease-management model must be integrated, comprehensive, individual patient focused and outcome driven. In addition to high quality care, the successful model must reduce variations in care and costs. MS specialists need to be intimately involved in the long-term care of MS patients, while not neglecting primary care issues. A nurse care manager is the "glue" between the managed care company, health care providers and the patient/family. Disease management focuses on education and prevention, and can be cost effective as well as patient specific. To implement a successful program, managed care companies and health care providers must work together.

  5. Landscape epidemiology: An emerging perspective in the mapping and modelling of disease and disease risk factors

    Directory of Open Access Journals (Sweden)

    Nnadi Nnaemeka Emmanuel

    2011-09-01

    Full Text Available Landscape epidemiology describes how the temporal dynamics of host, vector, and pathogen populations interact spatially within a permissive environment to enable transmission. It also aims at understanding the vegetation and geologic conditions that are necessary for the maintenance and transmission of a particular pathogen. The current review describes the evolution of landscape epidemiology. As a science, it also highlights the various methods of mapping and modeling diseases and disease risk factors. The key tool to characterize landscape is satellite remote sensing and these data are used as inputs to drive spatial models of transmission risk.

  6. Computational modeling and engineering in pediatric and congenital heart disease.

    Science.gov (United States)

    Marsden, Alison L; Feinstein, Jeffrey A

    2015-10-01

    Recent methodological advances in computational simulations are enabling increasingly realistic simulations of hemodynamics and physiology, driving increased clinical utility. We review recent developments in the use of computational simulations in pediatric and congenital heart disease, describe the clinical impact in modeling in single-ventricle patients, and provide an overview of emerging areas. Multiscale modeling combining patient-specific hemodynamics with reduced order (i.e., mathematically and computationally simplified) circulatory models has become the de-facto standard for modeling local hemodynamics and 'global' circulatory physiology. We review recent advances that have enabled faster solutions, discuss new methods (e.g., fluid structure interaction and uncertainty quantification), which lend realism both computationally and clinically to results, highlight novel computationally derived surgical methods for single-ventricle patients, and discuss areas in which modeling has begun to exert its influence including Kawasaki disease, fetal circulation, tetralogy of Fallot (and pulmonary tree), and circulatory support. Computational modeling is emerging as a crucial tool for clinical decision-making and evaluation of novel surgical methods and interventions in pediatric cardiology and beyond. Continued development of modeling methods, with an eye towards clinical needs, will enable clinical adoption in a wide range of pediatric and congenital heart diseases.

  7. Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model

    Directory of Open Access Journals (Sweden)

    Xue Feng Hu

    2017-01-01

    Full Text Available Abstract Background Disease incidence and prevalence are both core indicators of population health. Incidence is generally not as readily accessible as prevalence. Cohort studies and electronic health record systems are two major way to estimate disease incidence. The former is time-consuming and expensive; the latter is not available in most developing countries. Alternatively, mathematical models could be used to estimate disease incidence from prevalence. Methods We proposed and validated a method to estimate the age-standardized incidence of cardiovascular disease (CVD, with prevalence data from successive surveys and mortality data from empirical studies. Hallett’s method designed for estimating HIV infections in Africa was modified to estimate the incidence of myocardial infarction (MI in the U.S. population and incidence of heart disease in the Canadian population. Results Model-derived estimates were in close agreement with observed incidence from cohort studies and population surveillance systems. This method correctly captured the trend in incidence given sufficient waves of cross-sectional surveys. The estimated MI declining rate in the U.S. population was in accordance with the literature. This method was superior to closed cohort, in terms of the estimating trend of population cardiovascular disease incidence. Conclusion It is possible to estimate CVD incidence accurately at the population level from cross-sectional prevalence data. This method has the potential to be used for age- and sex- specific incidence estimates, or to be expanded to other chronic conditions.

  8. Preclinical murine models of Chronic Obstructive Pulmonary Disease.

    Science.gov (United States)

    Vlahos, Ross; Bozinovski, Steven

    2015-07-15

    Chronic Obstructive Pulmonary Disease (COPD) is a major incurable global health burden and is the 4th leading cause of death worldwide. It is believed that an exaggerated inflammatory response to cigarette smoke causes progressive airflow limitation. This inflammation, where macrophages, neutrophils and T lymphocytes are prominent, leads to oxidative stress, emphysema, small airway fibrosis and mucus hypersecretion. Much of the disease burden and health care utilisation in COPD is associated with the management of its comorbidities and infectious (viral and bacterial) exacerbations (AECOPD). Comorbidities, defined as other chronic medical conditions, in particular skeletal muscle wasting and cardiovascular disease markedly impact on disease morbidity, progression and mortality. The mechanisms and mediators underlying COPD and its comorbidities are poorly understood and current COPD therapy is relatively ineffective. Thus, there is an obvious need for new therapies that can prevent the induction and progression of COPD and effectively treat AECOPD and comorbidities of COPD. Given that access to COPD patients can be difficult and that clinical samples often represent a "snapshot" at a particular time in the disease process, many researchers have used animal modelling systems to explore the mechanisms underlying COPD, AECOPD and comorbidities of COPD with the goal of identifying novel therapeutic targets. This review highlights the mouse models used to define the cellular, molecular and pathological consequences of cigarette smoke exposure and the recent advances in modelling infectious exacerbations and comorbidities of COPD. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. MeCP2-Related Diseases and Animal Models

    Directory of Open Access Journals (Sweden)

    Chinelo D. Ezeonwuka

    2014-01-01

    Full Text Available The role of epigenetics in human disease has become an area of increased research interest. Collaborative efforts from scientists and clinicians have led to a better understanding of the molecular mechanisms by which epigenetic regulation is involved in the pathogenesis of many human diseases. Several neurological and non-neurological disorders are associated with mutations in genes that encode for epigenetic factors. One of the most studied proteins that impacts human disease and is associated with deregulation of epigenetic processes is Methyl CpG binding protein 2 (MeCP2. MeCP2 is an epigenetic regulator that modulates gene expression by translating epigenetic DNA methylation marks into appropriate cellular responses. In order to highlight the importance of epigenetics to development and disease, we will discuss how MeCP2 emerges as a key epigenetic player in human neurodevelopmental, neurological, and non-neurological disorders. We will review our current knowledge on MeCP2-related diseases, including Rett Syndrome, Angelman Syndrome, Fetal Alcohol Spectrum Disorder, Hirschsprung disease, and Cancer. Additionally, we will briefly discuss about the existing MeCP2 animal models that have been generated for a better understanding of how MeCP2 impacts certain human diseases.

  10. Optimizing agent-based transmission models for infectious diseases.

    Science.gov (United States)

    Willem, Lander; Stijven, Sean; Tijskens, Engelbert; Beutels, Philippe; Hens, Niel; Broeckhove, Jan

    2015-06-02

    Infectious disease modeling and computational power have evolved such that large-scale agent-based models (ABMs) have become feasible. However, the increasing hardware complexity requires adapted software designs to achieve the full potential of current high-performance workstations. We have found large performance differences with a discrete-time ABM for close-contact disease transmission due to data locality. Sorting the population according to the social contact clusters reduced simulation time by a factor of two. Data locality and model performance can also be improved by storing person attributes separately instead of using person objects. Next, decreasing the number of operations by sorting people by health status before processing disease transmission has also a large impact on model performance. Depending of the clinical attack rate, target population and computer hardware, the introduction of the sort phase decreased the run time from 26% up to more than 70%. We have investigated the application of parallel programming techniques and found that the speedup is significant but it drops quickly with the number of cores. We observed that the effect of scheduling and workload chunk size is model specific and can make a large difference. Investment in performance optimization of ABM simulator code can lead to significant run time reductions. The key steps are straightforward: the data structure for the population and sorting people on health status before effecting disease propagation. We believe these conclusions to be valid for a wide range of infectious disease ABMs. We recommend that future studies evaluate the impact of data management, algorithmic procedures and parallelization on model performance.

  11. Time series regression model for infectious disease and weather.

    Science.gov (United States)

    Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

    2015-10-01

    Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  12. Numerical Analysis of Fractional Order Epidemic Model of Childhood Diseases

    Directory of Open Access Journals (Sweden)

    Fazal Haq

    2017-01-01

    Full Text Available The fractional order Susceptible-Infected-Recovered (SIR epidemic model of childhood disease is considered. Laplace–Adomian Decomposition Method is used to compute an approximate solution of the system of nonlinear fractional differential equations. We obtain the solutions of fractional differential equations in the form of infinite series. The series solution of the proposed model converges rapidly to its exact value. The obtained results are compared with the classical case.

  13. Lyapunov functions for a dengue disease transmission model

    International Nuclear Information System (INIS)

    Tewa, Jean Jules; Dimi, Jean Luc; Bowong, Samuel

    2009-01-01

    In this paper, we study a model for the dynamics of dengue fever when only one type of virus is present. For this model, Lyapunov functions are used to show that when the basic reproduction ratio is less than or equal to one, the disease-free equilibrium is globally asymptotically stable, and when it is greater than one there is an endemic equilibrium which is also globally asymptotically stable.

  14. Lyapunov functions for a dengue disease transmission model

    Energy Technology Data Exchange (ETDEWEB)

    Tewa, Jean Jules [Department of Mathematics, Faculty of Science, University of Yaounde I, P.O. Box 812, Yaounde (Cameroon)], E-mail: tewa@univ-metz.fr; Dimi, Jean Luc [Department of Mathematics, Faculty of Science, University Marien Ngouabi, P.O. Box 69, Brazzaville (Congo, The Democratic Republic of the)], E-mail: jldimi@yahoo.fr; Bowong, Samuel [Department of Mathematics and Computer Science, Faculty of Science, University of Douala, P.O. Box 24157, Douala (Cameroon)], E-mail: samuelbowong@yahoo.fr

    2009-01-30

    In this paper, we study a model for the dynamics of dengue fever when only one type of virus is present. For this model, Lyapunov functions are used to show that when the basic reproduction ratio is less than or equal to one, the disease-free equilibrium is globally asymptotically stable, and when it is greater than one there is an endemic equilibrium which is also globally asymptotically stable.

  15. A small nonhuman primate model for filovirus-induced disease.

    Science.gov (United States)

    Carrion, Ricardo; Ro, Youngtae; Hoosien, Kareema; Ticer, Anysha; Brasky, Kathy; de la Garza, Melissa; Mansfield, Keith; Patterson, Jean L

    2011-11-25

    Ebolavirus and Marburgvirus are members of the filovirus family and induce a fatal hemorrhagic disease in humans and nonhuman primates with 90% case fatality. To develop a small nonhuman primate model for filovirus disease, common marmosets (Callithrix jacchus) were intramuscularly inoculated with wild type Marburgvirus Musoke or Ebolavirus Zaire. The infection resulted in a systemic fatal disease with clinical and morphological features closely resembling human infection. Animals experienced weight loss, fever, high virus titers in tissue, thrombocytopenia, neutrophilia, high liver transaminases and phosphatases and disseminated intravascular coagulation. Evidence of a severe disseminated viral infection characterized principally by multifocal to coalescing hepatic necrosis was seen in EBOV animals. MARV-infected animals displayed only moderate fibrin deposition in the spleen. Lymphoid necrosis and lymphocytic depletion observed in spleen. These findings provide support for the use of the common marmoset as a small nonhuman primate model for filovirus induced hemorrhagic fever. Copyright © 2011 Elsevier Inc. All rights reserved.

  16. A model for ubiquitous care of noncommunicable diseases.

    Science.gov (United States)

    Vianna, Henrique Damasceno; Barbosa, Jorge Luis Victória

    2014-09-01

    The ubiquitous computing, or ubicomp, is a promising technology to help chronic diseases patients managing activities, offering support to them anytime, anywhere. Hence, ubicomp can aid community and health organizations to continuously communicate with patients and to offer useful resources for their self-management activities. Communication is prioritized in works of ubiquitous health for noncommunicable diseases care, but the management of resources is not commonly employed. We propose the UDuctor, a model for ubiquitous care of noncommunicable diseases. UDuctor focuses the resources offering, without losing self-management and communication supports. We implemented a system and applied it in two practical experiments. First, ten chronic patients tried the system and filled out a questionnaire based on the technology acceptance model. After this initial evaluation, an alpha test was done. The system was used daily for one month and a half by a chronic patient. The results were encouraging and show potential for implementing UDuctor in real-life situations.

  17. Mathematical models for therapeutic approaches to control HIV disease transmission

    CERN Document Server

    Roy, Priti Kumar

    2015-01-01

    The book discusses different therapeutic approaches based on different mathematical models to control the HIV/AIDS disease transmission. It uses clinical data, collected from different cited sources, to formulate the deterministic as well as stochastic mathematical models of HIV/AIDS. It provides complementary approaches, from deterministic and stochastic points of view, to optimal control strategy with perfect drug adherence and also tries to seek viewpoints of the same issue from different angles with various mathematical models to computer simulations. The book presents essential methods and techniques for students who are interested in designing epidemiological models on HIV/AIDS. It also guides research scientists, working in the periphery of mathematical modeling, and helps them to explore a hypothetical method by examining its consequences in the form of a mathematical modelling and making some scientific predictions. The model equations, mathematical analysis and several numerical simulations that are...

  18. Modeling Kidney Disease with iPS Cells

    Science.gov (United States)

    Freedman, Benjamin S.

    2015-01-01

    Induced pluripotent stem cells (iPSCs) are somatic cells that have been transcriptionally reprogrammed to an embryonic stem cell (ESC)-like state. iPSCs are a renewable source of diverse somatic cell types and tissues matching the original patient, including nephron-like kidney organoids. iPSCs have been derived representing several kidney disorders, such as ADPKD, ARPKD, Alport syndrome, and lupus nephritis, with the goals of generating replacement tissue and ‘disease in a dish’ laboratory models. Cellular defects in iPSCs and derived kidney organoids provide functional, personalized biomarkers, which can be correlated with genetic and clinical information. In proof of principle, disease-specific phenotypes have been described in iPSCs and ESCs with mutations linked to polycystic kidney disease or focal segmental glomerulosclerosis. In addition, these cells can be used to model nephrotoxic chemical injury. Recent advances in directed differentiation and CRISPR genome editing enable more specific iPSC models and present new possibilities for diagnostics, disease modeling, therapeutic screens, and tissue regeneration using human cells. This review outlines growth opportunities and design strategies for this rapidly expanding and evolving field. PMID:26740740

  19. Stargardt disease: towards developing a model to predict phenotype.

    Science.gov (United States)

    Heathfield, Laura; Lacerda, Miguel; Nossek, Christel; Roberts, Lisa; Ramesar, Rajkumar S

    2013-10-01

    Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype-phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual loss and the age of onset. It has, however, been difficult to verify this model statistically in observational studies, as the number of individuals sharing any particular mutation combination is typically low. Seven founder mutations have been identified in a large number of Caucasian Afrikaner patients in South Africa, making it possible to test the genotype-phenotype model. A generalised linear model was developed to predict and assess the relative pathogenic contribution of the seven mutations to the age of onset of Stargardt disease. It is shown that the pathogenicity of an individual mutation can differ significantly depending on the genetic context in which it occurs. The results reported here may be used to identify suitable candidates for inclusion in clinical trials, as well as guide the genetic counselling of affected individuals and families.

  20. A transgenic minipig model of Hungtington´s disease

    Czech Academy of Sciences Publication Activity Database

    Baxa, Monika; Hruška-Plocháň, Marian; Juhás, Štefan; Vodička, Petr; Pavlok, Antonín; Juhásová, Jana; Miyanohara, A.; Nejime, T.; Klíma, Jiří; Mačáková, Monika; Marsala, S.; Weiss, A.; Kubíčková, S.; Musilová, P.; Vrtel, R.; Sontag, E. M.; Thompson, L.M.; Schier, Jan; Hansíková, H.; Howland, D. S.; Cattaneo, E.; DiFiglia, M.; Marsala, M.; Motlík, Jan

    2013-01-01

    Roč. 2, č. 1 (2013), s. 47-68 ISSN 1879-6397 R&D Projects: GA TA ČR TA01011466; GA MŠk ED2.1.00/03.0124 Institutional support: RVO:67985904 ; RVO:67985556 Keywords : Huntington´s disease * mutant huntingtin * minipigs * large animal model Subject RIV: EB - Genetics ; Molecular Biology

  1. Infectious diseases among animals : combining models with data

    NARCIS (Netherlands)

    Koeijer, A.A. de

    2003-01-01

    To eradicate or control the spread of infectious diseases, knowledge on the spread of the infection between (groups of) animals is necessary. Models can include such information and can subsequently be used to observe the efficacy of various control measures in fighting the infection. However, the

  2. Multivariate time series modeling of selected childhood diseases in ...

    African Journals Online (AJOL)

    This paper is focused on modeling the five most prevalent childhood diseases in Akwa Ibom State using a multivariate approach to time series. An aggregate of 78,839 reported cases of malaria, upper respiratory tract infection (URTI), Pneumonia, anaemia and tetanus were extracted from five randomly selected hospitals in ...

  3. Statistics Based Models for the Dynamics of Chernivtsi Children Disease

    Directory of Open Access Journals (Sweden)

    Igor G. Nesteruk

    2017-10-01

    Full Text Available Background. Simple mathematical models of contamination and SIR-model of spreading an infection were used to simulate the time dynamics of the unknown before children disease, which occurred in Chernivtsi (Ukraine. The cause of many cases of alopecia, which began in this city in August 1988 is still not fully clarified. According to the official report of the governmental commission, the last new cases occurred in the middle of November 1988, and the reason of the illness was reported as chemical exogenous intoxication. Later this illness became the name “Chernivtsi chemical disease”. Nevertheless, the significantly increased number of new cases of the local alopecia was registered almost three years and is still not clarified. Objective. The comparison of two different versions of the disease: chemical exogenous intoxication and infection. Identification of the parameters of mathematical models and prediction of the disease development. Methods. Analytical solutions of the contamination models and SIR-model for an epidemic are obtained. The optimal values of parameters with the use of linear regression were found. Results. The optimal values of the models parameters with the use of statistical approach were identified. The calculations showed that the infectious version of the disease is more reliable in comparison with the popular contamination one. The possible date of the epidemic beginning was estimated. Conclusions. The optimal parameters of SIR-model allow calculating the realistic number of victims and other characteristics of possible epidemic. They also show that increased number of cases of local alopecia could be a part of the same epidemic as “Chernivtsi chemical disease”.

  4. Model of two infectious diseases in nettle caterpillar population

    Science.gov (United States)

    Firdausi, F. Z.; Nuraini, N.

    2016-04-01

    Palm oil is a vital commodity to the economy of Indonesia. The area of oil palm plantations in Indonesia has increased from year to year. However, the effectiveness of palm oil production is reduced by pest infestation. One of the pest which often infests oil palm plantations is nettle caterpillar. The pest control used in this study is biological control, viz. biological agents given to oil palm trees. This paper describes a mathematical model of two infectious diseases in nettle caterpillar population. The two infectious diseases arise due to two biological agents, namely Bacillus thuringiensis bacterium and parasite which usually attack nettle caterpillars. The derivation of the model constructed in this paper is obtained from ordinary differential equations without time delay. The equilibrium points are analyzed. Two of three equilibrium points are stable if the Routh-Hurwitz criteria are fulfilled. In addition, this paper also presents the numerical simulation of the model which has been constructed.

  5. Epidemiological models to support animal disease surveillance activities

    DEFF Research Database (Denmark)

    Willeberg, Preben; Paisley, Larry; Lind, Peter

    2011-01-01

    and models for interpreting surveillance data as part of ongoing control or eradication programmes. Two Danish examples are outlined. The first illustrates how models were used in documenting country freedom from disease (trichinellosis) and the second demonstrates how models were of assistance in predicting...... the risk of future cases, detected and undetected, of a waning infection of bovine spongiform encephalopathy. Both studies were successful in advancing European policy changes to reduce the cost of surveillance to appropriate levels given the magnitude of the respective hazards....

  6. Modeling neurodegenerative diseases with patient-derived induced pluripotent cells

    DEFF Research Database (Denmark)

    Poon, Anna; Zhang, Yu; Chandrasekaran, Abinaya

    2017-01-01

    patient-specific induced pluripotent stem cells (iPSCs) and isogenic controls generated using CRISPR-Cas9 mediated genome editing. The iPSCs are self-renewable and capable of being differentiated into the cell types affected by the diseases. These in vitro models based on patient-derived iPSCs provide...... the possibilities of generating three-dimensional (3D) models using the iPSCs-derived cells and compare their advantages and disadvantages to conventional two-dimensional (2D) models....

  7. Modelling the propagation of social response during a disease outbreak.

    Science.gov (United States)

    Fast, Shannon M; González, Marta C; Wilson, James M; Markuzon, Natasha

    2015-03-06

    Epidemic trajectories and associated social responses vary widely between populations, with severe reactions sometimes observed. When confronted with fatal or novel pathogens, people exhibit a variety of behaviours from anxiety to hoarding of medical supplies, overwhelming medical infrastructure and rioting. We developed a coupled network approach to understanding and predicting social response. We couple the disease spread and panic spread processes and model them through local interactions between agents. The social contagion process depends on the prevalence of the disease, its perceived risk and a global media signal. We verify the model by analysing the spread of disease and social response during the 2009 H1N1 outbreak in Mexico City and 2003 severe acute respiratory syndrome and 2009 H1N1 outbreaks in Hong Kong, accurately predicting population-level behaviour. This kind of empirically validated model is critical to exploring strategies for public health intervention, increasing our ability to anticipate the response to infectious disease outbreaks. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  8. Persistent estrus rat models of polycystic ovary disease: an update.

    Science.gov (United States)

    Singh, Krishna B

    2005-10-01

    To critically review published articles on polycystic ovary (PCO) disease in rat models, with a focus on delineating its pathophysiology. Review of the English-language literature published from 1966 to March 2005 was performed through PubMed search. Keywords or phrases used were persistent estrus, chronic anovulation, polycystic ovary, polycystic ovary disease, and polycystic ovary syndrome. Articles were also located via bibliographies of published literature. University Health Sciences Center. Articles on persistent estrus and PCO in rats were selected and reviewed regarding the methods for induction of PCO disease. Changes in the reproductive cycle, ovarian morphology, hormonal parameters, and factors associated with the development of PCO disease in rat models were analyzed. Principal methods for inducing PCO in the rat include exposure to constant light, anterior hypothalamic and amygdaloidal lesions, and the use of androgens, estrogens, antiprogestin, and mifepristone. The validated rat PCO models provide useful information on morphologic and hormonal disturbances in the pathogenesis of chronic anovulation in this condition. These studies have aimed to replicate the morphologic and hormonal characteristics observed in the human PCO syndrome. The implications of these studies to human condition are discussed.

  9. Modeling Neuropsychiatric and Neurodegenerative Diseases With Induced Pluripotent Stem Cells.

    Science.gov (United States)

    LaMarca, Elizabeth A; Powell, Samuel K; Akbarian, Schahram; Brennand, Kristen J

    2018-01-01

    Human-induced pluripotent stem cells (hiPSCs) have revolutionized our ability to model neuropsychiatric and neurodegenerative diseases, and recent progress in the field is paving the way for improved therapeutics. In this review, we discuss major advances in generating hiPSC-derived neural cells and cutting-edge techniques that are transforming hiPSC technology, such as three-dimensional "mini-brains" and clustered, regularly interspersed short palindromic repeats (CRISPR)-Cas systems. We examine specific examples of how hiPSC-derived neural cells are being used to uncover the pathophysiology of schizophrenia and Parkinson's disease, and consider the future of this groundbreaking research.

  10. Big Data for Infectious Disease Surveillance and Modeling

    DEFF Research Database (Denmark)

    Bansal, Shweta; Chowell, Gerardo; Simonsen, Lone

    2016-01-01

    We devote a special issue of the Journal of Infectious Diseases to review the recent advances of big data in strengthening disease surveillance, monitoring medical adverse events, informing transmission models, and tracking patient sentiments and mobility. We consider a broad definition of big data...... issue and highlight several cross-cutting areas that require further research, including representativeness, biases, volatility, and validation, and the need for robust statistical and hypotheses-driven analyses. Overall, we are optimistic that the big-data revolution will vastly improve the granularity...

  11. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  12. Seven challenges for modelling indirect transmission: Vector-borne diseases, macroparasites and neglected tropical diseases

    Directory of Open Access Journals (Sweden)

    T. Déirdre Hollingsworth

    2015-03-01

    Full Text Available Many of the challenges which face modellers of directly transmitted pathogens also arise when modelling the epidemiology of pathogens with indirect transmission – whether through environmental stages, vectors, intermediate hosts or multiple hosts. In particular, understanding the roles of different hosts, how to measure contact and infection patterns, heterogeneities in contact rates, and the dynamics close to elimination are all relevant challenges, regardless of the mode of transmission. However, there remain a number of challenges that are specific and unique to modelling vector-borne diseases and macroparasites. Moreover, many of the neglected tropical diseases which are currently targeted for control and elimination are vector-borne, macroparasitic, or both, and so this article includes challenges which will assist in accelerating the control of these high-burden diseases. Here, we discuss the challenges of indirect measures of infection in humans, whether through vectors or transmission life stages and in estimating the contribution of different host groups to transmission. We also discuss the issues of “evolution-proof” interventions against vector-borne disease.

  13. Humanized Mouse Model of Ebola Virus Disease Mimics the Immune Responses in Human Disease.

    Science.gov (United States)

    Bird, Brian H; Spengler, Jessica R; Chakrabarti, Ayan K; Khristova, Marina L; Sealy, Tara K; Coleman-McCray, JoAnn D; Martin, Brock E; Dodd, Kimberly A; Goldsmith, Cynthia S; Sanders, Jeanine; Zaki, Sherif R; Nichol, Stuart T; Spiropoulou, Christina F

    2016-03-01

    Animal models recapitulating human Ebola virus disease (EVD) are critical for insights into virus pathogenesis. Ebola virus (EBOV) isolates derived directly from human specimens do not, without adaptation, cause disease in immunocompetent adult rodents. Here, we describe EVD in mice engrafted with human immune cells (hu-BLT). hu-BLT mice developed EVD following wild-type EBOV infection. Infection with high-dose EBOV resulted in rapid, lethal EVD with high viral loads, alterations in key human antiviral immune cytokines and chemokines, and severe histopathologic findings similar to those shown in the limited human postmortem data available. A dose- and donor-dependent clinical course was observed in hu-BLT mice infected with lower doses of either Mayinga (1976) or Makona (2014) isolates derived from human EBOV cases. Engraftment of the human cellular immune system appeared to be essential for the observed virulence, as nonengrafted mice did not support productive EBOV replication or develop lethal disease. hu-BLT mice offer a unique model for investigating the human immune response in EVD and an alternative animal model for EVD pathogenesis studies and therapeutic screening. Published by Oxford University Press for the Infectious Diseases Society of America 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  14. Seven challenges for modelling indirect transmission: vector-borne diseases, macroparasites and neglected tropical diseases.

    Science.gov (United States)

    Hollingsworth, T Déirdre; Pulliam, Juliet R C; Funk, Sebastian; Truscott, James E; Isham, Valerie; Lloyd, Alun L

    2015-03-01

    Many of the challenges which face modellers of directly transmitted pathogens also arise when modelling the epidemiology of pathogens with indirect transmission--whether through environmental stages, vectors, intermediate hosts or multiple hosts. In particular, understanding the roles of different hosts, how to measure contact and infection patterns, heterogeneities in contact rates, and the dynamics close to elimination are all relevant challenges, regardless of the mode of transmission. However, there remain a number of challenges that are specific and unique to modelling vector-borne diseases and macroparasites. Moreover, many of the neglected tropical diseases which are currently targeted for control and elimination are vector-borne, macroparasitic, or both, and so this article includes challenges which will assist in accelerating the control of these high-burden diseases. Here, we discuss the challenges of indirect measures of infection in humans, whether through vectors or transmission life stages and in estimating the contribution of different host groups to transmission. We also discuss the issues of "evolution-proof" interventions against vector-borne disease. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

  15. Modeling human diseases: an education in interactions and interdisciplinary approaches

    Directory of Open Access Journals (Sweden)

    Leonard Zon

    2016-06-01

    Full Text Available Traditionally, most investigators in the biomedical arena exploit one model system in the course of their careers. Occasionally, an investigator will switch models. The selection of a suitable model system is a crucial step in research design. Factors to consider include the accuracy of the model as a reflection of the human disease under investigation, the numbers of animals needed and ease of husbandry, its physiology and developmental biology, and the ability to apply genetics and harness the model for drug discovery. In my lab, we have primarily used the zebrafish but combined it with other animal models and provided a framework for others to consider the application of developmental biology for therapeutic discovery. Our interdisciplinary approach has led to many insights into human diseases and to the advancement of candidate drugs to clinical trials. Here, I draw on my experiences to highlight the importance of combining multiple models, establishing infrastructure and genetic tools, forming collaborations, and interfacing with the medical community for successful translation of basic findings to the clinic.

  16. Neurophysiology of Drosophila Models of Parkinson’s Disease

    Directory of Open Access Journals (Sweden)

    Ryan J. H. West

    2015-01-01

    Full Text Available We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson’s disease- (PD- related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson’s disease. Firstly, Drosophila models are instrumental in exploring the mechanisms of neurodegeneration, with several PD-related mutations eliciting related phenotypes including sensitivity to energy supply and vesicular deformities. These are leading to the identification of plausible cellular mechanisms, which may be specific to (dopaminergic neurons and synapses rather than general cellular phenotypes. Secondly, models show noncell autonomous signalling within the nervous system, offering the opportunity to develop our understanding of the way pathogenic signalling propagates, resembling Braak’s scheme of spreading pathology in PD. Thirdly, the models link physiological deficits to changes in synaptic structure. While the structure-function relationship is complex, the genetic tractability of Drosophila offers the chance to separate fundamental changes from downstream consequences. Finally, the strong neuronal phenotypes permit relevant first in vivo drug testing.

  17. [Disease prevention in the elderly: misconceptions in current models].

    Science.gov (United States)

    Veras, Renato Peixoto

    2012-10-01

    The Brazilian population is aging significantly within a context of gradual improvement in the country's social and economic indicators. Increased longevity leads to increased use of health services, pressuring the public and social welfare health services, generating higher costs, and jeopardizing the system's sustainability. The alternative to avoid overburdening the system is to invest in policies for disease prevention, stabilization of chronic diseases, and maintenance of functional capacity. The current article aims to analyze the difficulties in implementing preventive programs and the reasons for the failure of various programs in health promotion, prevention, and management of chronic diseases in the elderly. There can be no solution to the crisis in financing and restructuring the health sector without implementing a preventive logic. Scientific research has already correctly identified the risk factors for the elderly population, but this is not enough. We must use such knowledge to promote the necessary transition from a healthcare-centered model to a preventive one.

  18. Airborne spread of foot-and-mouth disease - Model intercomparison

    DEFF Research Database (Denmark)

    Gloster, John; Jones, Andrew; Redington, Alison

    2010-01-01

    Foot-and-mouth disease virus (FMDV) spreads by direct contact between animals, by animal products (milk, meat and semen), by mechanical transfer on people or fomites and by the airborne route, with the relative importance of each mechanism depending on the particular outbreak characteristics....... Atmospheric dispersion models have been developed to assess airborne spread of FMDV in a number of countries, including the UK, Denmark, Australia, New Zealand, USA and Canada. These models were compared at a Workshop hosted by the Institute for Animal Health/Met Office in 2008. Each modeller was provided...... with data relating to the 1967 outbreak of FMD in Hampshire, UK, and asked to predict the spread of FMDV by the airborne route. A number of key issues emerged from the Workshop and subsequent modelling work: (1) in general all models predicted similar directions for livestock at risk, with much...

  19. New transgenic models of Parkinson's disease using genome editing technology.

    Science.gov (United States)

    Cota-Coronado, J A; Sandoval-Ávila, S; Gaytan-Dávila, Y P; Diaz, N F; Vega-Ruiz, B; Padilla-Camberos, E; Díaz-Martínez, N E

    2017-11-28

    Parkinson's disease (PD) is the second most common neurodegenerative disorder. It is characterised by selective loss of dopaminergic neurons in the substantia nigra pars compacta, which results in dopamine depletion, leading to a number of motor and non-motor symptoms. In recent years, the development of new animal models using nuclease-based genome-editing technology (ZFN, TALEN, and CRISPR/Cas9 nucleases) has enabled the introduction of custom-made modifications into the genome to replicate key features of PD, leading to significant advances in our understanding of the pathophysiology of the disease. We review the most recent studies on this new generation of in vitro and in vivo PD models, which replicate the most relevant symptoms of the disease and enable better understanding of the aetiology and mechanisms of PD. This may be helpful in the future development of effective treatments to halt or slow disease progression. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

  20. Big Data for Infectious Disease Surveillance and Modeling.

    Science.gov (United States)

    Bansal, Shweta; Chowell, Gerardo; Simonsen, Lone; Vespignani, Alessandro; Viboud, Cécile

    2016-12-01

    We devote a special issue of the Journal of Infectious Diseases to review the recent advances of big data in strengthening disease surveillance, monitoring medical adverse events, informing transmission models, and tracking patient sentiments and mobility. We consider a broad definition of big data for public health, one encompassing patient information gathered from high-volume electronic health records and participatory surveillance systems, as well as mining of digital traces such as social media, Internet searches, and cell-phone logs. We introduce nine independent contributions to this special issue and highlight several cross-cutting areas that require further research, including representativeness, biases, volatility, and validation, and the need for robust statistical and hypotheses-driven analyses. Overall, we are optimistic that the big-data revolution will vastly improve the granularity and timeliness of available epidemiological information, with hybrid systems augmenting rather than supplanting traditional surveillance systems, and better prospects for accurate infectious diseases models and forecasts. Published by Oxford University Press for the Infectious Diseases Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  1. Mouse models of ageing and their relevance to disease.

    Science.gov (United States)

    Kõks, Sulev; Dogan, Soner; Tuna, Bilge Guvenc; González-Navarro, Herminia; Potter, Paul; Vandenbroucke, Roosmarijn E

    2016-12-01

    Ageing is a process that gradually increases the organism's vulnerability to death. It affects different biological pathways, and the underlying cellular mechanisms are complex. In view of the growing disease burden of ageing populations, increasing efforts are being invested in understanding the pathways and mechanisms of ageing. We review some mouse models commonly used in studies on ageing, highlight the advantages and disadvantages of the different strategies, and discuss their relevance to disease susceptibility. In addition to addressing the genetics and phenotypic analysis of mice, we discuss examples of models of delayed or accelerated ageing and their modulation by caloric restriction. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  2. Using Stem Cells to Model Diseases of the Outer Retina

    Directory of Open Access Journals (Sweden)

    Camille Yvon

    2015-01-01

    Full Text Available Retinal degeneration arises from the loss of photoreceptors or retinal pigment epithelium (RPE. It is one of the leading causes of irreversible blindness worldwide with limited effective treatment options. Generation of induced pluripotent stem cell (IPSC-derived retinal cells and tissues from individuals with retinal degeneration is a rapidly evolving technology that holds a great potential for its use in disease modelling. IPSCs provide an ideal platform to investigate normal and pathological retinogenesis, but also deliver a valuable source of retinal cell types for drug screening and cell therapy. In this review, we will provide some examples of the ways in which IPSCs have been used to model diseases of the outer retina including retinitis pigmentosa (RP, Usher syndrome (USH, Leber congenital amaurosis (LCA, gyrate atrophy (GA, juvenile neuronal ceroid lipofuscinosis (NCL, Best vitelliform macular dystrophy (BVMD and age related macular degeneration (AMD.

  3. Using Stem Cells to Model Diseases of the Outer Retina.

    Science.gov (United States)

    Yvon, Camille; Ramsden, Conor M; Lane, Amelia; Powner, Michael B; da Cruz, Lyndon; Coffey, Peter J; Carr, Amanda-Jayne F

    2015-01-01

    Retinal degeneration arises from the loss of photoreceptors or retinal pigment epithelium (RPE). It is one of the leading causes of irreversible blindness worldwide with limited effective treatment options. Generation of induced pluripotent stem cell (IPSC)-derived retinal cells and tissues from individuals with retinal degeneration is a rapidly evolving technology that holds a great potential for its use in disease modelling. IPSCs provide an ideal platform to investigate normal and pathological retinogenesis, but also deliver a valuable source of retinal cell types for drug screening and cell therapy. In this review, we will provide some examples of the ways in which IPSCs have been used to model diseases of the outer retina including retinitis pigmentosa (RP), Usher syndrome (USH), Leber congenital amaurosis (LCA), gyrate atrophy (GA), juvenile neuronal ceroid lipofuscinosis (NCL), Best vitelliform macular dystrophy (BVMD) and age related macular degeneration (AMD).

  4. Fatal Prion Disease in a Mouse Model of Genetic E200K Creutzfeldt-Jakob Disease

    Science.gov (United States)

    Friedman-Levi, Yael; Meiner, Zeev; Canello, Tamar; Frid, Kati; Kovacs, Gabor G.; Budka, Herbert; Avrahami, Dana; Gabizon, Ruth

    2011-01-01

    Genetic prion diseases are late onset fatal neurodegenerative disorders linked to pathogenic mutations in the prion protein-encoding gene, PRNP. The most prevalent of these is the substitution of Glutamate for Lysine at codon 200 (E200K), causing genetic Creutzfeldt-Jakob disease (gCJD) in several clusters, including Jews of Libyan origin. Investigating the pathogenesis of genetic CJD, as well as developing prophylactic treatments for young asymptomatic carriers of this and other PrP mutations, may well depend upon the availability of appropriate animal models in which long term treatments can be evaluated for efficacy and toxicity. Here we present the first effective mouse model for E200KCJD, which expresses chimeric mouse/human (TgMHu2M) E199KPrP on both a null and a wt PrP background, as is the case for heterozygous patients and carriers. Mice from both lines suffered from distinct neurological symptoms as early as 5–6 month of age and deteriorated to death several months thereafter. Histopathological examination of the brain and spinal cord revealed early gliosis and age-related intraneuronal deposition of disease-associated PrP similarly to human E200K gCJD. Concomitantly we detected aggregated, proteinase K resistant, truncated and oxidized PrP forms on immunoblots. Inoculation of brain extracts from TgMHu2ME199K mice readily induced, the first time for any mutant prion transgenic model, a distinct fatal prion disease in wt mice. We believe that these mice may serve as an ideal platform for the investigation of the pathogenesis of genetic prion disease and thus for the monitoring of anti-prion treatments. PMID:22072968

  5. Fatal prion disease in a mouse model of genetic E200K Creutzfeldt-Jakob disease.

    Directory of Open Access Journals (Sweden)

    Yael Friedman-Levi

    2011-11-01

    Full Text Available Genetic prion diseases are late onset fatal neurodegenerative disorders linked to pathogenic mutations in the prion protein-encoding gene, PRNP. The most prevalent of these is the substitution of Glutamate for Lysine at codon 200 (E200K, causing genetic Creutzfeldt-Jakob disease (gCJD in several clusters, including Jews of Libyan origin. Investigating the pathogenesis of genetic CJD, as well as developing prophylactic treatments for young asymptomatic carriers of this and other PrP mutations, may well depend upon the availability of appropriate animal models in which long term treatments can be evaluated for efficacy and toxicity. Here we present the first effective mouse model for E200KCJD, which expresses chimeric mouse/human (TgMHu2M E199KPrP on both a null and a wt PrP background, as is the case for heterozygous patients and carriers. Mice from both lines suffered from distinct neurological symptoms as early as 5-6 month of age and deteriorated to death several months thereafter. Histopathological examination of the brain and spinal cord revealed early gliosis and age-related intraneuronal deposition of disease-associated PrP similarly to human E200K gCJD. Concomitantly we detected aggregated, proteinase K resistant, truncated and oxidized PrP forms on immunoblots. Inoculation of brain extracts from TgMHu2ME199K mice readily induced, the first time for any mutant prion transgenic model, a distinct fatal prion disease in wt mice. We believe that these mice may serve as an ideal platform for the investigation of the pathogenesis of genetic prion disease and thus for the monitoring of anti-prion treatments.

  6. Striatal grafts in a rat model of Huntington's disease

    DEFF Research Database (Denmark)

    Guzman, R; Meyer, M; Lövblad, K O

    1999-01-01

    Survival and integration into the host brain of grafted tissue are crucial factors in neurotransplantation approaches. The present study explored the feasibility of using a clinical MR scanner to study striatal graft development in a rat model of Huntington's disease. Rat fetal lateral ganglionic...... time-points graft location could not be further verified. Measures for graft size and ventricle size obtained from MR images highly correlated with measures obtained from histologically processed sections (R = 0.8, P fetal rat lateral ganglionic...

  7. Understanding rare disease pathogenesis: a grand challenge for model organisms.

    Science.gov (United States)

    Hieter, Philip; Boycott, Kym M

    2014-10-01

    In this commentary, Philip Hieter and Kym Boycott discuss the importance of model organisms for understanding pathogenesis of rare human genetic diseases, and highlight the work of Brooks et al., "Dysfunction of 60S ribosomal protein L10 (RPL10) disrupts neurodevelopment and causes X-linked microcephaly in humans," published in this issue of GENETICS. Copyright © 2014 by the Genetics Society of America.

  8. Some models for epidemics of vector-transmitted diseases

    Directory of Open Access Journals (Sweden)

    Fred Brauer

    2016-10-01

    Full Text Available Vector-transmitted diseases such as dengue fever and chikungunya have been spreading rapidly in many parts of the world. The Zika virus has been known since 1947 and invaded South America in 2013. It can be transmitted not only by (mosquito vectors but also directly through sexual contact. Zika has developed into a serious global health problem because, while most cases are asymptomatic or very light, babies born to Zika - infected mothers may develop microcephaly and other very serious birth defects.We formulate and analyze two epidemic models for vector-transmitted diseases, one appropriate for dengue and chikungunya fever outbreaks and one that includes direct transmission appropriate for Zika virus outbreaks. This is especially important because the Zika virus is the first example of a disease that can be spread both indirectly through a vector and directly (through sexual contact. In both cases, we obtain expressions for the basic reproduction number and show how to use the initial exponential growth rate to estimate the basic reproduction number. However, for the model that includes direct transmission some additional data would be needed to identify the fraction of cases transmitted directly. Data for the 2015 Zika virus outbreak in Barranquilla, Colombia has been used to fit parameters to the model developed here and to estimate the basic reproduction number.

  9. An ethical assessment model for digital disease detection technologies.

    Science.gov (United States)

    Denecke, Kerstin

    2017-09-20

    Digital epidemiology, also referred to as digital disease detection (DDD), successfully provided methods and strategies for using information technology to support infectious disease monitoring and surveillance or understand attitudes and concerns about infectious diseases. However, Internet-based research and social media usage in epidemiology and healthcare pose new technical, functional and formal challenges. The focus of this paper is on the ethical issues to be considered when integrating digital epidemiology with existing practices. Taking existing ethical guidelines and the results from the EU project M-Eco and SORMAS as starting point, we develop an ethical assessment model aiming at providing support in identifying relevant ethical concerns in future DDD projects. The assessment model has four dimensions: user, application area, data source and methodology. The model supports in becoming aware, identifying and describing the ethical dimensions of DDD technology or use case and in identifying the ethical issues on the technology use from different perspectives. It can be applied in an interdisciplinary meeting to collect different viewpoints on a DDD system even before the implementation starts and aims at triggering discussions and finding solutions for risks that might not be acceptable even in the development phase. From the answers, ethical issues concerning confidence, privacy, data and patient security or justice may be judged and weighted.

  10. Quantitative Systems Pharmacology: A Case for Disease Models.

    Science.gov (United States)

    Musante, C J; Ramanujan, S; Schmidt, B J; Ghobrial, O G; Lu, J; Heatherington, A C

    2017-01-01

    Quantitative systems pharmacology (QSP) has emerged as an innovative approach in model-informed drug discovery and development, supporting program decisions from exploratory research through late-stage clinical trials. In this commentary, we discuss the unique value of disease-scale "platform" QSP models that are amenable to reuse and repurposing to support diverse clinical decisions in ways distinct from other pharmacometrics strategies. © 2016 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of The American Society for Clinical Pharmacology and Therapeutics.

  11. Predicting population extinction or disease outbreaks with stochastic models

    Directory of Open Access Journals (Sweden)

    Linda J. S. Allen

    2017-01-01

    Full Text Available Models of exponential growth, logistic growth and epidemics are common applications in undergraduate differential equation courses. The corresponding stochastic models are not part of these courses, although when population sizes are small their behaviour is often more realistic and distinctly different from deterministic models. For example, the randomness associated with births and deaths may lead to population extinction even in an exponentially growing population. Some background in continuous-time Markov chains and applications to populations, epidemics and cancer are presented with a goal to introduce this topic into the undergraduate mathematics curriculum that will encourage further investigation into problems on conservation, infectious diseases and cancer therapy. MATLAB programs for graphing sample paths of stochastic models are provided in the Appendix.

  12. EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks.

    Science.gov (United States)

    Jenness, Samuel M; Goodreau, Steven M; Morris, Martina

    2018-04-01

    Package EpiModel provides tools for building, simulating, and analyzing mathematical models for the population dynamics of infectious disease transmission in R. Several classes of models are included, but the unique contribution of this software package is a general stochastic framework for modeling the spread of epidemics on networks. EpiModel integrates recent advances in statistical methods for network analysis (temporal exponential random graph models) that allow the epidemic modeling to be grounded in empirical data on contacts that can spread infection. This article provides an overview of both the modeling tools built into EpiModel , designed to facilitate learning for students new to modeling, and the application programming interface for extending package EpiModel , designed to facilitate the exploration of novel research questions for advanced modelers.

  13. A model for intra-familial distribution of an infectious disease (Chagas' disease

    Directory of Open Access Journals (Sweden)

    M. F. Feitosa

    1993-06-01

    Full Text Available A probabilistic model for intra-familial distribution of infectous disease is proposed and applied to the prevalence of positive serology for Trypanosoma cruzi infection in Northeastern Brazilian sample. This double with one tail excess model fits satisfactorily to the data and its interpretation says that around 51% of these 982 families are free of infection risk; among those that are at risk, 3% have a high risk (0.66, probably due to high domestic infestation of the vector bug; while 97% show a small risk (0.11, probably due to accidental, non-domestic transmission.

  14. Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model

    Science.gov (United States)

    Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.

    2012-12-01

    The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that

  15. Mechanistic modeling of aberrant energy metabolism in human disease

    Directory of Open Access Journals (Sweden)

    Vineet eSangar

    2012-10-01

    Full Text Available Dysfunction in energy metabolism—including in pathways localized to the mitochondria—has been implicated in the pathogenesis of a wide array of disorders, ranging from cancer to neurodegenerative diseases to type II diabetes. The inherent complexities of energy and mitochondrial metabolism present a significant obstacle in the effort to understand the role that these molecular processes play in the development of disease. To help unravel these complexities, systems biology methods have been applied to develop an array of computational metabolic models, ranging from mitochondria-specific processes to genome-scale cellular networks. These constraint-based models can efficiently simulate aspects of normal and aberrant metabolism in various genetic and environmental conditions. Development of these models leverages—and also provides a powerful means to integrate and interpret—information from a wide range of sources including genomics, proteomics, metabolomics, and enzyme kinetics. Here, we review a variety of mechanistic modeling studies that explore metabolic functions, deficiency disorders, and aberrant biochemical pathways in mitochondria and related regions in the cell.

  16. Comparison of two models of inflammatory bowel disease in rats.

    Science.gov (United States)

    Catana, Cristina Sorina; Magdas, Cristian; Tabaran, Flaviu Alexandru; Crăciun, Elena Cristina; Deak, Georgiana; Magdaş, Virginia Ana; Cozma, Vasile; Gherman, Călin Mircea; Berindan-Neagoe, Ioana; Dumitraşcu, Dan Lucian

    2018-03-26

    There is a need for experimental animal models for inflammatory bowel diseases (IBD), but no proposed model has been unanimously accepted. The aim of this study was to develop 2 affordable models of IBD in rats and to compare them. We produced IBD in rats using either dextran sodium sulfate (DSS) or 2, 4, 6-trinitrobenzene sulfonic acid (TNBS). The requirements for experimental models were: a predictable clinical course, histopathology and inflammation similar to human ulcerative colitis (UC) and Crohn's disease (CD). The effect of acute administration of DSS and TNBS on oxidative stress (as measured by the assessment of glutathione peroxidase - GPx) was verified. The activity of whole blood GPx was measured using a commercially available Randox kit (Crumlin, UK). The administration of DSS increased GPx activity compared to the control and TNBS-treated groups, but not to a statistically significant degree. Histological examination of the colonic mucosa following the administration of DSS showed multifocal erosions with minimal to mild inflammatory infiltrate, mainly by polymorphonuclear cells (PMN), lymphocytes and plasma cells. For TNBS-induced colitis, the histological changes manifested as multifocal areas of ulcerative colitis with mild to severe inflammatory infiltrate. Whole blood GPx values displayed a direct dependence on the chemical agent used. Our results show a correlation between histopathology, proinflammatory state and oxidative stress. The experimental DSSor TNBS-induced bowel inflammation used in this study corresponds to human IBD and is reproducible with characteristics indicative of acute inflammation in the case of the protocols mentioned.

  17. Risk predictive modelling for diabetes and cardiovascular disease.

    Science.gov (United States)

    Kengne, Andre Pascal; Masconi, Katya; Mbanya, Vivian Nchanchou; Lekoubou, Alain; Echouffo-Tcheugui, Justin Basile; Matsha, Tandi E

    2014-02-01

    Absolute risk models or clinical prediction models have been incorporated in guidelines, and are increasingly advocated as tools to assist risk stratification and guide prevention and treatments decisions relating to common health conditions such as cardiovascular disease (CVD) and diabetes mellitus. We have reviewed the historical development and principles of prediction research, including their statistical underpinning, as well as implications for routine practice, with a focus on predictive modelling for CVD and diabetes. Predictive modelling for CVD risk, which has developed over the last five decades, has been largely influenced by the Framingham Heart Study investigators, while it is only ∼20 years ago that similar efforts were started in the field of diabetes. Identification of predictive factors is an important preliminary step which provides the knowledge base on potential predictors to be tested for inclusion during the statistical derivation of the final model. The derived models must then be tested both on the development sample (internal validation) and on other populations in different settings (external validation). Updating procedures (e.g. recalibration) should be used to improve the performance of models that fail the tests of external validation. Ultimately, the effect of introducing validated models in routine practice on the process and outcomes of care as well as its cost-effectiveness should be tested in impact studies before wide dissemination of models beyond the research context. Several predictions models have been developed for CVD or diabetes, but very few have been externally validated or tested in impact studies, and their comparative performance has yet to be fully assessed. A shift of focus from developing new CVD or diabetes prediction models to validating the existing ones will improve their adoption in routine practice.

  18. Exploration of Disease Markers under Translational Medicine Model

    Directory of Open Access Journals (Sweden)

    Rajagopal Krishnamoorthy

    2015-06-01

    Full Text Available Disease markers are defined as the biomarkers with specific characteristics during the general physical, pathological or therapeutic process, the detection of which can inform the progression of present biological process of organisms. However, the exploration of disease markers is complicated and difficult, and only a few markers can be used in clinical practice and there is no significant difference in the mortality of cancers before and after biomarker exploration. Translational medicine focuses on breaking the blockage between basic medicine and clinical practice. In addition, it also establishes an effective association between researchers engaged on basic scientific discovery and clinical physicians well informed of patients' requirements, and gives particular attentions on how to translate the basic molecular biological research to the most effective and appropriate methods for the diagnosis, treatment and prevention of diseases, hoping to translate basic research into the new therapeutic methods in clinic. Therefore, this study mainly summarized the exploration of disease markers under translational medicine model so as to provide a basis for the translation of basic research results into clinical application.

  19. Neural stem cells for disease modeling of Wolman disease and evaluation of therapeutics.

    Science.gov (United States)

    Aguisanda, Francis; Yeh, Charles D; Chen, Catherine Z; Li, Rong; Beers, Jeanette; Zou, Jizhong; Thorne, Natasha; Zheng, Wei

    2017-06-28

    Wolman disease (WD) is a rare lysosomal storage disorder that is caused by mutations in the LIPA gene encoding lysosomal acid lipase (LAL). Deficiency in LAL function causes accumulation of cholesteryl esters and triglycerides in lysosomes. Fatality usually occurs within the first year of life. While an enzyme replacement therapy has recently become available, there is currently no small-molecule drug treatment for WD. We have generated induced pluripotent stem cells (iPSCs) from two WD patient dermal fibroblast lines and subsequently differentiated them into neural stem cells (NSCs). The WD NSCs exhibited the hallmark disease phenotypes of neutral lipid accumulation, severely deficient LAL activity, and increased LysoTracker dye staining. Enzyme replacement treatment dramatically reduced the WD phenotype in these cells. In addition, δ-tocopherol (DT) and hydroxypropyl-beta-cyclodextrin (HPBCD) significantly reduced lysosomal size in WD NSCs, and an enhanced effect was observed in DT/HPBCD combination therapy. The results demonstrate that these WD NSCs are valid cell-based disease models with characteristic disease phenotypes that can be used to evaluate drug efficacy and screen compounds. DT and HPBCD both reduce LysoTracker dye staining in WD cells. The cells may be used to further dissect the pathology of WD, evaluate compound efficacy, and serve as a platform for high-throughput drug screening to identify new compounds for therapeutic development.

  20. Bioprinted three dimensional human tissues for toxicology and disease modeling.

    Science.gov (United States)

    Nguyen, Deborah G; Pentoney, Stephen L

    2017-03-01

    The high rate of attrition among clinical-stage therapies, due largely to an inability to predict human toxicity and/or efficacy, underscores the need for in vitro models that better recapitulate in vivo human biology. In much the same way that additive manufacturing has revolutionized the production of solid objects, three-dimensional (3D) bioprinting is enabling the automated production of more architecturally and functionally accurate in vitro tissue culture models. Here, we provide an overview of the most commonly used bioprinting approaches and how they are being used to generate complex in vitro tissues for use in toxicology and disease modeling research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Agent-based modeling of noncommunicable diseases: a systematic review.

    Science.gov (United States)

    Nianogo, Roch A; Arah, Onyebuchi A

    2015-03-01

    We reviewed the use of agent-based modeling (ABM), a systems science method, in understanding noncommunicable diseases (NCDs) and their public health risk factors. We systematically reviewed studies in PubMed, ScienceDirect, and Web of Sciences published from January 2003 to July 2014. We retrieved 22 relevant articles; each had an observational or interventional design. Physical activity and diet were the most-studied outcomes. Often, single agent types were modeled, and the environment was usually irrelevant to the studied outcome. Predictive validation and sensitivity analyses were most used to validate models. Although increasingly used to study NCDs, ABM remains underutilized and, where used, is suboptimally reported in public health studies. Its use in studying NCDs will benefit from clarified best practices and improved rigor to establish its usefulness and facilitate replication, interpretation, and application.

  2. Modeling Neuropsychiatric and Neurodegenerative Diseases With Induced Pluripotent Stem Cells

    Directory of Open Access Journals (Sweden)

    Elizabeth A. LaMarca

    2018-04-01

    Full Text Available Human-induced pluripotent stem cells (hiPSCs have revolutionized our ability to model neuropsychiatric and neurodegenerative diseases, and recent progress in the field is paving the way for improved therapeutics. In this review, we discuss major advances in generating hiPSC-derived neural cells and cutting-edge techniques that are transforming hiPSC technology, such as three-dimensional “mini-brains” and clustered, regularly interspersed short palindromic repeats (CRISPR-Cas systems. We examine specific examples of how hiPSC-derived neural cells are being used to uncover the pathophysiology of schizophrenia and Parkinson’s disease, and consider the future of this groundbreaking research.

  3. Xenopus: An Emerging Model for Studying Congenital Heart Disease

    Science.gov (United States)

    Kaltenbrun, Erin; Tandon, Panna; Amin, Nirav M.; Waldron, Lauren; Showell, Chris; Conlon, Frank L.

    2011-01-01

    Congenital heart defects affect nearly 1% of all newborns and are a significant cause of infant death. Clinical studies have identified a number of congenital heart syndromes associated with mutations in genes that are involved in the complex process of cardiogenesis. The African clawed frog, Xenopus, has been instrumental in studies of vertebrate heart development and provides a valuable tool to investigate the molecular mechanisms underlying human congenital heart diseases. In this review, we discuss the methodologies that make Xenopus an ideal model system to investigate heart development and disease. We also outline congenital heart conditions linked to cardiac genes that have been well-studied in Xenopus and describe some emerging technologies that will further aid in the study of these complex syndromes. PMID:21538812

  4. Early chronic kidney disease: diagnosis, management and models of care

    Science.gov (United States)

    Wouters, Olivier J.; O'Donoghue, Donal J.; Ritchie, James; Kanavos, Panos G.; Narva, Andrew S.

    2015-01-01

    Chronic kidney disease (CKD) is a prevalent condition in many countries, and it is estimated that over $1 trillion is spent globally on end-stage renal disease (ESRD) care. There is a clear clinical and economic rationale for designing timely and appropriate health system responses to limit progression from CKD to ESRD. This article reviews the gaps in our knowledge about which early CKD interventions are appropriate, the optimal time to intervene, and what model of care to adopt. The available diagnostic tests exhibit key limitations. Clinical care may improve if early-stage (1–3) CKD with risk for progression towards ESRD is differentiated from early CKD that is unlikely to advance. It is possible that CKD should be re-conceptualized as a part of primary care. Additional research is needed to better understand the risk factors for CKD progression. Systems modelling can be used to evaluate the impact of different care models on CKD outcomes and costs. The US Indian Health Service experience has demonstrated that an integrated, system-wide approach, even in an underfunded system, can produce significant benefits. PMID:26055354

  5. Cardiac disease and arrhythmogenesis: Mechanistic insights from mouse models

    Directory of Open Access Journals (Sweden)

    Lois Choy

    2016-09-01

    Full Text Available The mouse is the second mammalian species, after the human, in which substantial amount of the genomic information has been analyzed. With advances in transgenic technology, mutagenesis is now much easier to carry out in mice. Consequently, an increasing number of transgenic mouse systems have been generated for the study of cardiac arrhythmias in ion channelopathies and cardiomyopathies. Mouse hearts are also amenable to physical manipulation such as coronary artery ligation and transverse aortic constriction to induce heart failure, radiofrequency ablation of the AV node to model complete AV block and even implantation of a miniature pacemaker to induce cardiac dyssynchrony. Last but not least, pharmacological models, despite being simplistic, have enabled us to understand the physiological mechanisms of arrhythmias and evaluate the anti-arrhythmic properties of experimental agents, such as gap junction modulators, that may be exert therapeutic effects in other cardiac diseases. In this article, we examine these in turn, demonstrating that primary inherited arrhythmic syndromes are now recognized to be more complex than abnormality in a particular ion channel, involving alterations in gene expression and structural remodelling. Conversely, in cardiomyopathies and heart failure, mutations in ion channels and proteins have been identified as underlying causes, and electrophysiological remodelling are recognized pathological features. Transgenic techniques causing mutagenesis in mice are extremely powerful in dissecting the relative contributions of different genes play in producing disease phenotypes. Mouse models can serve as useful systems in which to explore how protein defects contribute to arrhythmias and direct future therapy.

  6. Modeling a Mobile Health Management Business Model for Chronic Kidney Disease.

    Science.gov (United States)

    Lee, Ying-Li; Chang, Polun

    2016-01-01

    In these decades, chronic kidney disease (CKD) has become a global public health problem. Information technology (IT) tools have been used widely to empower the patients with chronic disease (e.g., diabetes and hypertension). It is also a potential application to advance the CKD care. In this project, we analyzed the requirements of a mobile health management system for healthcare workers, patients and their families to design a health management business model for CKD patients.

  7. Global economic consequences of selected surgical diseases: a modelling study.

    Science.gov (United States)

    Alkire, Blake C; Shrime, Mark G; Dare, Anna J; Vincent, Jeffrey R; Meara, John G

    2015-04-27

    The surgical burden of disease is substantial, but little is known about the associated economic consequences. We estimate the global macroeconomic impact of the surgical burden of disease due to injury, neoplasm, digestive diseases, and maternal and neonatal disorders from two distinct economic perspectives. We obtained mortality rate estimates for each disease for the years 2000 and 2010 from the Institute of Health Metrics and Evaluation Global Burden of Disease 2010 study, and estimates of the proportion of the burden of the selected diseases that is surgical from a paper by Shrime and colleagues. We first used the value of lost output (VLO) approach, based on the WHO's Projecting the Economic Cost of Ill-Health (EPIC) model, to project annual market economy losses due to these surgical diseases during 2015-30. EPIC attempts to model how disease affects a country's projected labour force and capital stock, which in turn are related to losses in economic output, or gross domestic product (GDP). We then used the value of lost welfare (VLW) approach, which is conceptually based on the value of a statistical life and is inclusive of non-market losses, to estimate the present value of long-run welfare losses resulting from mortality and short-run welfare losses resulting from morbidity incurred during 2010. Sensitivity analyses were performed for both approaches. During 2015-30, the VLO approach projected that surgical conditions would result in losses of 1·25% of potential GDP, or $20·7 trillion (2010 US$, purchasing power parity) in the 128 countries with data available. When expressed as a proportion of potential GDP, annual GDP losses were greatest in low-income and middle-income countries, with up to a 2·5% loss in output by 2030. When total welfare losses are assessed (VLW), the present value of economic losses is estimated to be equivalent to 17% of 2010 GDP, or $14·5 trillion in the 175 countries assessed with this approach. Neoplasm and injury account

  8. Childhood Heart Disease - A partnership model of integrated care

    OpenAIRE

    Williams, Holly; Brooke, Mark

    2018-01-01

    HeartKids is a national charity supporting infants, children, young people and adults living with or impacted by congenital / childhood heart disease. For over 20 years HeartKids has worked in partnership with Lady Cilento Children's Hospital to deliver services and support to families.HeartKids supports families in hosptial and in the commuity with a suite of support programs lead by both health profesisonals and volunteers.  Critical to our model of care is a partnership with Lady Cilento C...

  9. Modeling the Cumulative Effects of Social Exposures on Health: Moving beyond Disease-Specific Models

    Directory of Open Access Journals (Sweden)

    Heather L. White

    2013-03-01

    Full Text Available The traditional explanatory models used in epidemiology are “disease specific”, identifying risk factors for specific health conditions. Yet social exposures lead to a generalized, cumulative health impact which may not be specific to one illness. Disease-specific models may therefore misestimate social factors’ effects on health. Using data from the Canadian Community Health Survey and Canada 2001 Census we construct and compare “disease-specific” and “generalized health impact” (GHI models to gauge the negative health effects of one social exposure: socioeconomic position (SEP. We use logistic and multinomial multilevel modeling with neighbourhood-level material deprivation, individual-level education and household income to compare and contrast the two approaches. In disease-specific models, the social determinants under study were each associated with the health conditions of interest. However, larger effect sizes were apparent when outcomes were modeled as compound health problems (0, 1, 2, or 3+ conditions using the GHI approach. To more accurately estimate social exposures’ impacts on population health, researchers should consider a GHI framework.

  10. Dietary manipulation and social isolation alter disease progression in a murine model of coronary heart disease.

    Directory of Open Access Journals (Sweden)

    Yumiko Nakagawa-Toyama

    Full Text Available BACKGROUND: Mice with a deficiency in the HDL receptor SR-BI and low expression of a modified apolipoprotein E gene (SR-BI KO/ApoeR61(h/h called 'HypoE' when fed an atherogenic, 'Paigen' diet develop occlusive, atherosclerotic coronary arterial disease (CHD, myocardial infarctions (MI, and heart dysfunction and die prematurely (50% mortality ~40 days after initiation of this diet. Because few murine models share with HypoE mice these cardinal, human-like, features of CHD, HypoE mice represent a novel, small animal, diet-inducible and genetically tractable model for CHD. To better describe the properties of this model, we have explored the effects of varying the composition and timing of administration of atherogenic diets, as well as social isolation vs. group housing, on these animals. METHODOLOGY/PRINCIPAL FINDINGS: HypoE mice were maintained on a standard lab chow diet (control until two months of age. Subsequently they received one of three atherogenic diets (Paigen, Paigen without cholate, Western or control diet for varying times and were housed in groups or singly, and we determined the plasma cholesterol levels, extent of cardiomegaly and/or survival. The rate of disease progression could be reduced by lowering the severity of the atherogenic diet and accelerated by social isolation. Disease could be induced by Paigen diets either containing or free of cholate. We also established conditions under which CHD could be initiated by an atherogenic diet and then subsequently, by replacing this diet with standard lab chow, hypercholesterolemia could be reduced and progression to early death prevented. CONCLUSIONS/SIGNIFICANCE: HypoE mice provide a powerful, surgery-free, diet-'titratable' small animal model that can be used to study the onset of recovery from occlusive, atherosclerotic CHD and heart failure due to MI. HypoE mice can be used for the analysis of the effects of environment (diet, social isolation on a variety of features of

  11. A Systems Model of Parkinson's Disease Using Biochemical Systems Theory.

    Science.gov (United States)

    Sasidharakurup, Hemalatha; Melethadathil, Nidheesh; Nair, Bipin; Diwakar, Shyam

    2017-08-01

    Parkinson's disease (PD), a neurodegenerative disorder, affects millions of people and has gained attention because of its clinical roles affecting behaviors related to motor and nonmotor symptoms. Although studies on PD from various aspects are becoming popular, few rely on predictive systems modeling approaches. Using Biochemical Systems Theory (BST), this article attempts to model and characterize dopaminergic cell death and understand pathophysiology of progression of PD. PD pathways were modeled using stochastic differential equations incorporating law of mass action, and initial concentrations for the modeled proteins were obtained from literature. Simulations suggest that dopamine levels were reduced significantly due to an increase in dopaminergic quinones and 3,4-dihydroxyphenylacetaldehyde (DOPAL) relating to imbalances compared to control during PD progression. Associating to clinically observed PD-related cell death, simulations show abnormal parkin and reactive oxygen species levels with an increase in neurofibrillary tangles. While relating molecular mechanistic roles, the BST modeling helps predicting dopaminergic cell death processes involved in the progression of PD and provides a predictive understanding of neuronal dysfunction for translational neuroscience.

  12. Clinical and pathological manifestations of cardiovascular disease in rat models: the influence of acute ozone exposure

    Science.gov (United States)

    This paper shows that rat models of cardiovascular diseases have differential degrees of underlying pathologies at a young age. Rodent models of cardiovascular diseases (CVD) and metabolic disorders are used for examining susceptibility variations to environmental exposures. How...

  13. Pest control through viral disease: mathematical modeling and analysis.

    Science.gov (United States)

    Bhattacharyya, S; Bhattacharya, D K

    2006-01-07

    This paper deals with the mathematical modeling of pest management under viral infection (i.e. using viral pesticide) and analysis of its essential mathematical features. As the viral infection induces host lysis which releases more virus into the environment, on the average 'kappa' viruses per host, kappain(1,infinity), the 'virus replication parameter' is chosen as the main parameter on which the dynamics of the infection depends. We prove that there exists a threshold value kappa(0) beyond which the endemic equilibrium bifurcates from the free disease one. Still for increasing kappa values, the endemic equilibrium bifurcates towards a periodic solution. We further analyse the orbital stability of the periodic orbits arising from bifurcation by applying Poor's condition. A concluding discussion with numerical simulation of the model is then presented.

  14. A System Dynamics Model for Planning Cardiovascular Disease Interventions

    Science.gov (United States)

    Homer, Jack; Evans, Elizabeth; Zielinski, Ann

    2010-01-01

    Planning programs for the prevention and treatment of cardiovascular disease (CVD) is a challenge to every community that wants to make the best use of its limited resources. Selecting programs that provide the greatest impact is difficult because of the complex set of causal pathways and delays that link risk factors to CVD. We describe a system dynamics simulation model developed for a county health department that incorporates and tracks the effects of those risk factors over time on both first-time and recurrent events. We also describe how the model was used to evaluate the potential impacts of various intervention strategies for reducing the county's CVD burden and present the results of those policy tests. PMID:20167899

  15. Dynamic generalized linear models for monitoring endemic diseases

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq

    2016-01-01

    The objective was to use a Dynamic Generalized Linear Model (DGLM) based on abinomial distribution with a linear trend, for monitoring the PRRS (Porcine Reproductive and Respiratory Syndrome sero-prevalence in Danish swine herds. The DGLM was described and its performance for monitoring control...... and eradication programmes based on changes in PRRS sero-prevalence was explored. Results showed a declining trend in PRRS sero-prevalence between 2007 and 2014 suggesting that Danish herds are slowly eradicating PRRS. The simulation study demonstrated the flexibility of DGLMs in adapting to changes intrends...... in sero-prevalence. Based on this, it was possible to detect variations in the growth model component. This study is a proof-of-concept, demonstrating the use of DGLMs for monitoring endemic diseases. In addition, the principles stated might be useful in general research on monitoring and surveillance...

  16. Modeling Test and Treatment Strategies for Presymptomatic Alzheimer Disease

    Science.gov (United States)

    Burke, James F.; Langa, Kenneth M.; Hayward, Rodney A.; Albin, Roger L.

    2014-01-01

    Objectives In this study, we developed a model of presymptomatic treatment of Alzheimer disease (AD) after a screening diagnostic evaluation and explored the circumstances required for an AD prevention treatment to produce aggregate net population benefit. Methods Monte Carlo simulation methods were used to estimate outcomes in a simulated population derived from data on AD incidence and mortality. A wide variety of treatment parameters were explored. Net population benefit was estimated in aggregated QALYs. Sensitivity analyses were performed by individually varying the primary parameters. Findings In the base-case scenario, treatment effects were uniformly positive, and net benefits increased with increasing age at screening. A highly efficacious treatment (i.e. relative risk 0.6) modeled in the base-case is estimated to save 20 QALYs per 1000 patients screened and 221 QALYs per 1000 patients treated. Conclusions Highly efficacious presymptomatic screen and treat strategies for AD are likely to produce substantial aggregate population benefits that are likely greater than the benefits of aspirin in primary prevention of moderate risk cardiovascular disease (28 QALYS per 1000 patients treated), even in the context of an imperfect treatment delivery environment. PMID:25474698

  17. A conceptual and disease model framework for osteoporotic kyphosis.

    Science.gov (United States)

    Bayliss, M; Miltenburger, C; White, M; Alvares, L

    2013-09-01

    This paper presents a multi-method research project to develop a conceptual framework for measuring outcomes in studies of osteoporotic kyphosis. The research involved literature research and qualitative interviews among clinicians who treat patients with kyphosis and among patients with the condition. Kyphosis due to at least one vertebral compression fracture is prevalent among osteoporotic patients, resulting in well-documented symptoms and impact on functioning and well-being. A three-part study led to development of a conceptual measurement framework for comprehensive assessment of symptoms, impact, and treatment benefit for kyphosis. A literature-based disease model (DM) was developed and tested with physicians (n = 10) and patients (n = 10), and FDA guidelines were used to develop a final disease model and a conceptual framework. The DM included signs, symptoms, causes/triggers, exacerbations, and functional status associated with kyphosis. The DM was largely confirmed, but physicians and patients added several concepts related to impact on functioning, and some concepts were not confirmed and removed from the DM. This study confirms the need for more comprehensive assessment of health outcomes in kyphosis, as most current studies omit key concepts.

  18. Genetic mouse models of brain ageing and Alzheimer's disease.

    Science.gov (United States)

    Bilkei-Gorzo, Andras

    2014-05-01

    Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Histaminergic activity in a rodent model of Parkinson's disease.

    Science.gov (United States)

    Nowak, Przemysław; Noras, Lukasz; Jochem, Jerzy; Szkilnik, Ryszard; Brus, Halina; Körossy, Eva; Drab, Jacek; Kostrzewa, Richard M; Brus, Ryszard

    2009-04-01

    Rats lesioned shortly after birth with 6-OHDA have been proposed to be a near-ideal model of severe Parkinson's disease, because of non-lethality of the procedure, near-total destruction of nigrostriatal dopaminergic fibers, and near-total dopamine (DA) denervation of striatum. There are scarce data that in Parkinson's disease, activity of the central histaminergic system is increased. Therefore, the aim of this study was to determine histamine content in the brain and the effect of histamine receptor antagonists on behavior of adult rats. At 3 days after birth, Wistar rats were pretreated with desipramine (20.0 mg/kg ip) 1 h before bilateral icv administration of the catecholaminergic neurotoxin 6-OHDA (67 microg base, on each side) or saline-ascorbic acid (0.1%) vehicle (control). At 8 weeks levels of DA and its metabolites L: -3,4-dihydroxyphenylalanine (DOPAC) and homovanillic acid (HVA) were estimated in the striatum and frontal cortex by HPCL/ED technique. In the hypothalamus, hippocampus, frontal cortex, and medulla oblongata, the level of histamine was analyzed by immunoenzymatic method. Behavioral observations (locomotion, exploratory-, oral-, and stereotyped-activity) were additionally made on control and 6-OHDA neonatally lesioned rats. Effects of DA receptor agonists (SKF 38393, apomorphine) and histamine receptor antagonists (e.g., S(+)chlorpheniramine, H(1); cimetidine, H(2); thioperamide, H(3) agonist) were determined. We confirmed that 6-OHDA significantly reduced contents of DA and its metabolites in the brain in adulthood. Histamine content was significantly increased in the hypothalamus, hipocampus, and medulla oblongata. Moreover, in 6-OHDA-lesioned rats behavioral response was altered mainly by thioperamide (H(3) antagonist). These findings indicate that histamine and the central histaminergic system are altered in the brain of rats lesioned to model Parkinson's disease, and that histaminergic neurons exert a modulating role in Parkinsonian 6

  20. Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

    Science.gov (United States)

    Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

    2017-12-01

    Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

  1. A CASE STUDY ON POINT PROCESS MODELLING IN DISEASE MAPPING

    Directory of Open Access Journals (Sweden)

    Viktor Beneš

    2011-05-01

    Full Text Available We consider a data set of locations where people in Central Bohemia have been infected by tick-borne encephalitis (TBE, and where population census data and covariates concerning vegetation and altitude are available. The aims are to estimate the risk map of the disease and to study the dependence of the risk on the covariates. Instead of using the common area level approaches we base the analysis on a Bayesian approach for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using Markov chain Monte Carlo methods. A particular problem which is thoroughly discussed is to determine a model for the background population density. The risk map shows a clear dependency with the population intensity models and the basic model which is adopted for the population intensity determines what covariates influence the risk of TBE. Model validation is based on the posterior predictive distribution of various summary statistics.

  2. Modeling recall memory for emotional objects in Alzheimer's disease.

    Science.gov (United States)

    Sundstrøm, Martin

    2011-07-01

    To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

  3. Using special functions to model the propagation of airborne diseases

    Science.gov (United States)

    Bolaños, Daniela

    2014-06-01

    Some special functions of the mathematical physics are using to obtain a mathematical model of the propagation of airborne diseases. In particular we study the propagation of tuberculosis in closed rooms and we model the propagation using the error function and the Bessel function. In the model, infected individual emit pathogens to the environment and this infect others individuals who absorb it. The evolution in time of the concentration of pathogens in the environment is computed in terms of error functions. The evolution in time of the number of susceptible individuals is expressed by a differential equation that contains the error function and it is solved numerically for different parametric simulations. The evolution in time of the number of infected individuals is plotted for each numerical simulation. On the other hand, the spatial distribution of the pathogen around the source of infection is represented by the Bessel function K0. The spatial and temporal distribution of the number of infected individuals is computed and plotted for some numerical simulations. All computations were made using software Computer algebra, specifically Maple. It is expected that the analytical results that we obtained allow the design of treatment rooms and ventilation systems that reduce the risk of spread of tuberculosis.

  4. Altered protein glycosylation predicts Alzheimer's disease and modulates its pathology in disease model Drosophila.

    Science.gov (United States)

    Frenkel-Pinter, Moran; Stempler, Shiri; Tal-Mazaki, Sharon; Losev, Yelena; Singh-Anand, Avnika; Escobar-Álvarez, Daniela; Lezmy, Jonathan; Gazit, Ehud; Ruppin, Eytan; Segal, Daniel

    2017-08-01

    The pathological hallmarks of Alzheimer's disease (AD) are pathogenic oligomers and fibrils of misfolded amyloidogenic proteins (e.g., β-amyloid and hyper-phosphorylated tau in AD), which cause progressive loss of neurons in the brain and nervous system. Although deviations from normal protein glycosylation have been documented in AD, their role in disease pathology has been barely explored. Here our analysis of available expression data sets indicates that many glycosylation-related genes are differentially expressed in brains of AD patients compared with healthy controls. The robust differences found enabled us to predict the occurrence of AD with remarkable accuracy in a test cohort and identify a set of key genes whose expression determines this classification. We then studied in vivo the effect of reducing expression of homologs of 6 of these genes in transgenic Drosophila overexpressing human tau, a well-established invertebrate AD model. These experiments have led to the identification of glycosylation genes that may augment or ameliorate tauopathy phenotypes. Our results indicate that OstDelta, l(2)not and beta4GalT7 are tauopathy suppressors, whereas pgnat5 and CG33303 are enhancers, of tauopathy. These results suggest that specific alterations in protein glycosylation may play a causal role in AD etiology. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

    Science.gov (United States)

    Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

    2017-12-01

    The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

  6. Generalizability of the Disease State Index Prediction Model for Identifying Patients Progressing from Mild Cognitive Impairment to Alzheimer's Disease

    NARCIS (Netherlands)

    Hall, A.; Munoz-Ruiz, M.; Mattila, J.; Koikkalainen, J.; Tsolaki, M.; Mecocci, P.; Kloszewska, I.; Vellas, B.; Lovestone, S.; Visser, P.J.; Lotjonen, J.; Soininen, H.

    2015-01-01

    Background: The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease. Objectives: We evaluated how well the DSI generalizes across

  7. Dermatomycosis in a pet inland bearded dragon (Pogona vitticeps) caused by a Chrysosporium species related to Nannizziopsis vriesii.

    Science.gov (United States)

    Abarca, M L; Martorell, J; Castellá, G; Ramis, A; Cabañes, F J

    2009-08-01

    A Chrysosporium sp. related to Nannizziopsis vriesii was isolated in pure culture from squames and biopsies of facial lesions in a pet inland bearded dragon (Pogona vitticeps) in Spain. The presence in histological sections of morphologically consistent fungal elements strongly incriminates this fungus as the aetiological agent of infection. Lesions regressed following treatment with oral ketoconazole and topical chlorhexidine and terbinafine until the lizard was lost to follow up 1 month later. The ITS-5.8S rRNA gene of the isolate was sequenced and a search on the GenBank database revealed a high match with the sequences of two Chrysosporium sp. strains recently isolated from green iguanas (Iguana iguana) with dermatomycosis, also in Spain. Phylogenetic analysis of the sequences revealed that all these strains are related to N. vriesii. This is the first report of dermatomycoses caused by a Chrysosporium species related to N. vriesii in a bearded dragon outside North America.

  8. Tree shrew (Tupaia belangeri as a novel laboratory disease animal model

    Directory of Open Access Journals (Sweden)

    Ji Xiao

    2017-05-01

    Full Text Available The tree shrew (Tupaia belangeri is a promising laboratory animal that possesses a closer genetic relationship to primates than to rodents. In addition, advantages such as small size, easy breeding, and rapid reproduction make the tree shrew an ideal subject for the study of human disease. Numerous tree shrew disease models have been generated in biological and medical studies in recent years. Here we summarize current tree shrew disease models, including models of infectious diseases, cancers, depressive disorders, drug addiction, myopia, metabolic diseases, and immune-related diseases. With the success of tree shrew transgenic technology, this species will be increasingly used in biological and medical studies in the future.

  9. Cultivating a disease management partnership: a value-chain model.

    Science.gov (United States)

    Murray, Carolyn F; Monroe, Wendy; Stalder, Sharon A

    2003-01-01

    Disease management (DM) is one of the health care industry's more innovative value-chain models, whereby multiple relationships are created to bring complex and time-sensitive services to market. The very nature of comprehensive, seamless DM provided through an outsourced arrangement necessitates a level of cooperation, trust, and synergy that may be lacking from more traditional vendor-customer relationships. This discussion highlights the experience of one health plan and its vendor partner and their approach to the development and delivery of an outsourced heart failure (HF) DM program. The program design and rollout are discussed within principles adapted from the theoretical framework of a value-chain model. Within the value-chain model, added value is created by the convergence and synergistic integration of the partners' discrete strengths. Although each partner brings unique attributes to the relationship, those attributes are significantly enhanced by the value-chain model, thus allowing each party to bring the added value of the relationship to their respective customers. This partnership increases innovation, leverages critical capabilities, and improves market responsiveness. Implementing a comprehensive, outsourced DM program is no small task. DM programs incorporate a broad array of services affecting nearly every department in a health plan's organization. When true seamless integration between multiple organizations with multiple stakeholders is the objective, implementation and ongoing operations can become even more complex. To effectively address the complexities presented by an HF DM program, the parties in this case moved beyond a typical purchaser-vendor relationship to one that is more closely akin to a strategic partnership. This discussion highlights the development of this partnership from the perspective of both organizations, as revealed through contracting and implementation activities. It is intended to provide insight into the program

  10. Pitfalls in the detection of cholesterol in Huntington's disease models.

    Science.gov (United States)

    Marullo, Manuela; Valenza, Marta; Leoni, Valerio; Caccia, Claudio; Scarlatti, Chiara; De Mario, Agnese; Zuccato, Chiara; Di Donato, Stefano; Carafoli, Ernesto; Cattaneo, Elena

    2012-10-11

    Background Abnormalities in brain cholesterol homeostasis have been reported in Huntington's disease (HD), an adult-onset neurodegenerative disorder caused by an expansion in the number of CAG repeats in the huntingtin (HTT) gene. However, the results have been contradictory with respect to whether cholesterol levels increase or decrease in HD models. Biochemical and mass spectrometry methods show reduced levels of cholesterol precursors and cholesterol in HD cells and in the brains of several HD animal models. Abnormal brain cholesterol homeostasis was also inferred from studies in HD patients. In contrast, colorimetric and enzymatic methods indicate cholesterol accumulation in HD cells and tissues. Here we used several methods to investigate cholesterol levels in cultured cells in the presence or absence of mutant HTT protein. Results Colorimetric and enzymatic methods with low sensitivity gave variable results, whereas results from a sensitive analytical method, gas chromatography-mass spectrometry, were more reliable. Sample preparation, high cell density and cell clonality also influenced the detection of intracellular cholesterol. Conclusions Detection of cholesterol in HD samples by colorimetric and enzymatic assays should be supplemented by detection using more sensitive analytical methods. Care must be taken to prepare the sample appropriately. By evaluating lathosterol levels using isotopic dilution mass spectrometry, we confirmed reduced cholesterol biosynthesis in knock-in cells expressing the polyQ mutation in a constitutive or inducible manner. *Correspondence should be addressed to Elena Cattaneo: elena.cattaneo@unimi.it.

  11. Bioeconomic modelling of foot and mouth disease and its control in Ethiopia

    NARCIS (Netherlands)

    Jemberu, W.T.

    2016-01-01

    Keywords: Control, cost-benefit, economic impact, epidemiology, Ethiopia, Foot and mouth disease, intention, modelling, production system.

    Bioeconomic Modelling of Foot and Mouth Disease and Its control in Ethiopia

    Foot and mouth disease (FMD) is a

  12. Modelling within-host spatiotemporal dynamics of invasive bacterial disease.

    Directory of Open Access Journals (Sweden)

    Andrew J Grant

    2008-04-01

    Full Text Available Mechanistic determinants of bacterial growth, death, and spread within mammalian hosts cannot be fully resolved studying a single bacterial population. They are also currently poorly understood. Here, we report on the application of sophisticated experimental approaches to map spatiotemporal population dynamics of bacteria during an infection. We analyzed heterogeneous traits of simultaneous infections with tagged Salmonella enterica populations (wild-type isogenic tagged strains [WITS] in wild-type and gene-targeted mice. WITS are phenotypically identical but can be distinguished and enumerated by quantitative PCR, making it possible, using probabilistic models, to estimate bacterial death rate based on the disappearance of strains through time. This multidisciplinary approach allowed us to establish the timing, relative occurrence, and immune control of key infection parameters in a true host-pathogen combination. Our analyses support a model in which shortly after infection, concomitant death and rapid bacterial replication lead to the establishment of independent bacterial subpopulations in different organs, a process controlled by host antimicrobial mechanisms. Later, decreased microbial mortality leads to an exponential increase in the number of bacteria that spread locally, with subsequent mixing of bacteria between organs via bacteraemia and further stochastic selection. This approach provides us with an unprecedented outlook on the pathogenesis of S. enterica infections, illustrating the complex spatial and stochastic effects that drive an infectious disease. The application of the novel method that we present in appropriate and diverse host-pathogen combinations, together with modelling of the data that result, will facilitate a comprehensive view of the spatial and stochastic nature of within-host dynamics.

  13. Epidemiologic Considerations in Network Modeling of Theoretical Disease Events

    National Research Council Canada - National Science Library

    Lem, Marcus

    2006-01-01

    .... Network analysis has shown utility in the study of a range of communicable disease outbreaks affecting both health and commerce, including SARS, tuberculosis, syphilis and foot-and mouth-disease...

  14. Impairment of adolescent hippocampal plasticity in a mouse model for Alzheimer's disease precedes disease phenotype.

    Directory of Open Access Journals (Sweden)

    Daniela Hartl

    Full Text Available The amyloid precursor protein (APP was assumed to be an important neuron-morphoregulatory protein and plays a central role in Alzheimer's disease (AD pathology. In the study presented here, we analyzed the APP-transgenic mouse model APP23 using 2-dimensional gel electrophoresis technology in combination with DIGE and mass spectrometry. We investigated cortex and hippocampus of transgenic and wildtype mice at 1, 2, 7 and 15 months of age. Furthermore, cortices of 16 days old embryos were analyzed. When comparing the protein patterns of APP23 with wildtype mice, we detected a relatively large number of altered protein spots at all age stages and brain regions examined which largely preceded the occurrence of amyloid plaques. Interestingly, in hippocampus of adolescent, two-month old mice, a considerable peak in the number of protein changes was observed. Moreover, when protein patterns were compared longitudinally between age stages, we found that a large number of proteins were altered in wildtype mice. Those alterations were largely absent in hippocampus of APP23 mice at two months of age although not in other stages compared. Apparently, the large difference in the hippocampal protein patterns between two-month old APP23 and wildtype mice was caused by the absence of distinct developmental changes in the hippocampal proteome of APP23 mice. In summary, the absence of developmental proteome alterations as well as a down-regulation of proteins related to plasticity suggest the disturption of a normally occurring peak of hippocampal plasticity during adolescence in APP23 mice. Our findings are in line with the observation that AD is preceded by a clinically silent period of several years to decades. We also demonstrate that it is of utmost importance to analyze different brain regions and different age stages to obtain information about disease-causing mechanisms.

  15. Transgenic miniature pig as a model for the study of Huntington´s Disease

    Czech Academy of Sciences Publication Activity Database

    Baxa, Monika

    2012-01-01

    Roč. 22, č. 2 (2012), s. 23-25 ISSN 1210-1737 Institutional support: RVO:67985904 Keywords : transgenic pig * Huntington ´s disease * large animal model * neurodegenerative disease Subject RIV: EB - Genetics ; Molecular Biology

  16. Animal models of gastrointestinal and liver diseases. Animal models of infant short bowel syndrome

    DEFF Research Database (Denmark)

    Sangild, Per Torp; Ney, Denise M; Sigalet, David L

    2014-01-01

    enterocolitis, atresia, gastroschisis, volvulus and aganglionosis. Patient outcomes have improved, but there is a need to develop new therapies for SBS and to understand intestinal adaptation after different diseases, resection types, nutritional interventions and growth factor therapies. Animal studies may......, newborn pigs and weanling rats represent a translational advantage for infant SBS due to their immature intestine. A balance among practical, economical, experimental and ethical constraints determines the choice of SBS model for each clinical or basic research question....

  17. Animal in vivo models of EBV-associated lymphoproliferative diseases: special references to rabbit models.

    Science.gov (United States)

    Hayashi, K; Teramoto, N; Akagi, T

    2002-10-01

    Animal models of human EBV-associated diseases are essential to elucidate the pathogenesis of EBV-associated diseases. Here we review those previous models using EBV or EBV-like herpesviruses and describe the details on our two newly-developed rabbit models of lymphoproliferative diseases (LPD) induced by simian EBV-like viruses. The first is Cynomolgus-EBV-induced T-cell lymphomas in rabbits inoculated intravenously (77-90%) and orally (82-89%) during 2-5 months. EBV-DNA was detected in peripheral blood by PCR from 2 days after oral inoculation, while anti-EBV-VCA IgG was raised 3 weeks later. Rabbit lymphomas and their cell lines contained EBV-DNA and expressed EBV-encoded RNA-1 (EBER-1). Rabbit lymphoma cell lines, most of which have specific chromosomal abnormality, showed tumorigenicity in nude mice. The second is the first animal model for EBV-infected T-cell LPD with virus-associated hemophagocytic syndrome (VAHS), using rabbits infected with an EBV-like herpesvirus, Herpesvirus papio (HVP). Rabbits inoculated intravenously with HVP-producing cells showed increased anti-EBV-VCA-IgG titers, and most (85%) subsequently died of fatal LPD and VAHS, with bleeding and hepatosplenomegaly, during 22-105 days. Peroral spray of cell-free HVP induced viral infection with seroconversion in 3 out of 5 rabbits, with 2 of the 3 infected rabbits dying of LPD with VAHS. Atypical T lymphocytes containing HVP-DNA and expressing EBER-1 were observed in many organs. Hemophagocytic histiocytosis was observed in the lymph nodes, spleen, bone marrow, and thymus. These rabbit models are also useful and inexpensive alternative experimental model systems for studying the biology and pathogenesis of EBV, and prophylactic and therapeutic regimens.

  18. Dantrolene is neuroprotective in Huntington's disease transgenic mouse model

    Directory of Open Access Journals (Sweden)

    Chen Xi

    2011-11-01

    Full Text Available Abstract Background Huntington's disease (HD is a progressive neurodegenerative disorder caused by a polyglutamine expansion in the Huntingtin protein which results in the selective degeneration of striatal medium spiny neurons (MSNs. Our group has previously demonstrated that calcium (Ca2+ signaling is abnormal in MSNs from the yeast artificial chromosome transgenic mouse model of HD (YAC128. Moreover, we demonstrated that deranged intracellular Ca2+ signaling sensitizes YAC128 MSNs to glutamate-induced excitotoxicity when compared to wild type (WT MSNs. In previous studies we also observed abnormal neuronal Ca2+ signaling in neurons from spinocerebellar ataxia 2 (SCA2 and spinocerebellar ataxia 3 (SCA3 mouse models and demonstrated that treatment with dantrolene, a ryanodine receptor antagonist and clinically relevant Ca2+ signaling stabilizer, was neuroprotective in experiments with these mouse models. The aim of the current study was to evaluate potential beneficial effects of dantrolene in experiments with YAC128 HD mouse model. Results The application of caffeine and glutamate resulted in increased Ca2+ release from intracellular stores in YAC128 MSN cultures when compared to WT MSN cultures. Pre-treatment with dantrolene protected YAC128 MSNs from glutamate excitotoxicty, with an effective concentration of 100 nM and above. Feeding dantrolene (5 mg/kg twice a week to YAC128 mice between 2 months and 11.5 months of age resulted in significantly improved performance in the beam-walking and gait-walking assays. Neuropathological analysis revealed that long-term dantrolene feeding to YAC128 mice significantly reduced the loss of NeuN-positive striatal neurons and reduced formation of Httexp nuclear aggregates. Conclusions Our results support the hypothesis that deranged Ca2+ signaling plays an important role in HD pathology. Our data also implicate the RyanRs as a potential therapeutic target for the treatment of HD and demonstrate that Ryan

  19. Dantrolene is neuroprotective in Huntington's disease transgenic mouse model.

    Science.gov (United States)

    Chen, Xi; Wu, Jun; Lvovskaya, Svetlana; Herndon, Emily; Supnet, Charlene; Bezprozvanny, Ilya

    2011-11-25

    Huntington's disease (HD) is a progressive neurodegenerative disorder caused by a polyglutamine expansion in the Huntingtin protein which results in the selective degeneration of striatal medium spiny neurons (MSNs). Our group has previously demonstrated that calcium (Ca2+) signaling is abnormal in MSNs from the yeast artificial chromosome transgenic mouse model of HD (YAC128). Moreover, we demonstrated that deranged intracellular Ca2+ signaling sensitizes YAC128 MSNs to glutamate-induced excitotoxicity when compared to wild type (WT) MSNs. In previous studies we also observed abnormal neuronal Ca2+ signaling in neurons from spinocerebellar ataxia 2 (SCA2) and spinocerebellar ataxia 3 (SCA3) mouse models and demonstrated that treatment with dantrolene, a ryanodine receptor antagonist and clinically relevant Ca2+ signaling stabilizer, was neuroprotective in experiments with these mouse models. The aim of the current study was to evaluate potential beneficial effects of dantrolene in experiments with YAC128 HD mouse model. The application of caffeine and glutamate resulted in increased Ca2+ release from intracellular stores in YAC128 MSN cultures when compared to WT MSN cultures. Pre-treatment with dantrolene protected YAC128 MSNs from glutamate excitotoxicty, with an effective concentration of 100 nM and above. Feeding dantrolene (5 mg/kg) twice a week to YAC128 mice between 2 months and 11.5 months of age resulted in significantly improved performance in the beam-walking and gait-walking assays. Neuropathological analysis revealed that long-term dantrolene feeding to YAC128 mice significantly reduced the loss of NeuN-positive striatal neurons and reduced formation of Httexp nuclear aggregates. Our results support the hypothesis that deranged Ca2+ signaling plays an important role in HD pathology. Our data also implicate the RyanRs as a potential therapeutic target for the treatment of HD and demonstrate that RyanR inhibitors and Ca2+ signaling stabilizers such as

  20. [Monkey-pox, a model of emergent then reemergent disease].

    Science.gov (United States)

    Georges, A J; Matton, T; Courbot-Georges, M C

    2004-01-01

    The recent emergence of monkey pox in the United States of America highlights the problem (known for other infectious agents) of dissemination of pathogens outside their endemic area, and of subsequent global threats of variable gravity according to agents. It is a real emergency since monkey pox had been confined to Africa for several decades, where small epidemics occurred from time to time, monkey pox is a "miniature smallpox" which, in Africa, evolves on an endemic (zoonotic) mode with, as reservoirs, several species of wild rodents (mainly squirrels) and some monkey species. It can be accidentally transmitted to man then develops as epidemics, sometimes leading to death. The virus was imported in 2003 in the United States of America, via Gambia rats and wild squirrels (all African species), and infected prairie dogs (which are now in fashion as pets), then crossed the species barrier to man. In the United States of America, screening campaigns, epidemiological investigations, and subsequent treatments led to a rapid control of the epidemic, which is a model of emergent disease for this country. Therapeutic and preventive measures directly applicable to monkey pox are discussed. They can also be applied against other pox virus infections (including smallpox). The risk of criminal introduction of pox viruses is discussed since it is, more than ever, a real worldwide threat.

  1. The Rabbit as a Model for Studying Lung Disease and Stem Cell Therapy

    OpenAIRE

    Kamaruzaman, Nurfatin Asyikhin; Kardia, Egi; Kamaldin, Nurulain ‘Atikah; Latahir, Ahmad Zaeri; Yahaya, Badrul Hisham

    2013-01-01

    No single animal model can reproduce all of the human features of both acute and chronic lung diseases. However, the rabbit is a reliable model and clinically relevant facsimile of human disease. The similarities between rabbits and humans in terms of airway anatomy and responses to inflammatory mediators highlight the value of this species in the investigation of lung disease pathophysiology and in the development of therapeutic agents. The inflammatory responses shown by the rabbit model, e...

  2. Modeling Marek's disease virus transmission: A framework for evaluating the impact of farming practices and evolution

    OpenAIRE

    David A. Kennedy; Patricia A. Dunn; Andrew F. Read

    2018-01-01

    Marek's disease virus (MDV) is a pathogen of chickens whose control has twice been undermined by pathogen evolution. Disease ecology is believed to be the main driver of this evolution, yet mathematical models of MDV disease ecology have never been confronted with data to test their reliability. Here, we develop a suite of MDV models that differ in the ecological mechanisms they include. We fit these models with maximum likelihood using iterated filtering in ‘pomp’ to data on MDV concentratio...

  3. From genome-wide association studies to disease mechanisms : celiac disease as a model for autoimmune diseases

    NARCIS (Netherlands)

    Kumar, Vinod; Wijmenga, Cisca; Withoff, Sebo

    Celiac disease is characterized by a chronic inflammatory reaction in the intestine and is triggered by gluten, a constituent derived from grains which is present in the common daily diet in the Western world. Despite decades of research, the mechanisms behind celiac disease etiology are still not

  4. Learning lessons from operational research in infectious diseases: can the same model be used for noncommunicable diseases in developing countries?

    Directory of Open Access Journals (Sweden)

    Bosu WK

    2014-12-01

    Full Text Available William K Bosu Department of Epidemics and Disease Control, West African Health Organisation, Bobo-Dioulasso, Burkina Faso Abstract: About three-quarters of global deaths from noncommunicable diseases (NCDs occur in developing countries. Nearly a third of these deaths occur before the age of 60 years. These deaths are projected to increase, fueled by such factors as urbanization, nutrition transition, lifestyle changes, and aging. Despite this burden, there is a paucity of research on NCDs, due to the higher priority given to infectious disease research. Less than 10% of research on cardiovascular diseases comes from developing countries. This paper assesses what lessons from operational research on infectious diseases could be applied to NCDs. The lessons are drawn from the priority setting for research, integration of research into programs and routine service delivery, the use of routine data, rapid-assessment survey methods, modeling, chemoprophylaxis, and the translational process of findings into policy and practice. With the lines between infectious diseases and NCDs becoming blurred, it is justifiable to integrate the programs for the two disease groups wherever possible, eg, screening for diabetes in tuberculosis. Applying these lessons will require increased political will, research capacity, ownership, use of local expertise, and research funding. Keywords: infectious diseases, noncommunicable diseases, operational research, developing countries, integration

  5. The treatment of Alzheimer's disease using Chinese medicinal plants: from disease models to potential clinical applications.

    Science.gov (United States)

    Su, Yang; Wang, Qiuhong; Wang, Changfu; Chan, Kelvin; Sun, Yanping; Kuang, Haixue

    2014-03-28

    Alzheimer's disease (AD) is characterized by the sustained higher nervous disorders of the activities and functions of the brain. Due to its heavy burden on society and the patients' families, it is urgent to review the treatments for AD to provide basic data for further research and new drug development. Among these treatments, Chinese Material Medica (CMM) has been traditionally clinical used in China to treat AD for a long time with obvious efficacy. With the further research reports of CMM, new therapeutic materials may be recovered from troves of CMM. However, So far, little or no review work has been reported to conclude anti-AD drugs from CMM in literature. Therefore, a systematic introduction of CMM anti-AD research progress is of great importance and necessity. This paper strives to systematically describe the progress of CMM in the treatment of AD, and lays a basis data for anti-AD drug development from CMM, and provides the essential theoretical support for the further development and utilization of CMM resources through a more comprehensive research of the variety of databases regarding CMM anti-AD effects reports. Literature survey was performed via electronic search (SciFinder®, Pubmed®, Google Scholar and Web of Science) on papers and patents and by systematic research in ethnopharmacological literature at various university libraries. This review mainly introduces the current research on the Chinese Material Medica (CMM) theoretical research on Alzheimer's disease (AD), anti-AD active constituent of CMM, anti-AD effects on AD models, anti-AD mechanism of CMM, and anti-AD effect of CMM formula. Scholars around the world have made studies on the anti-AD molecular mechanism of CMM from different pathways, and have made substantial progress. The progress not only enriched the anti-AD theory of CMM, but also provided clinical practical significance and development prospects in using CMM to treat AD. Western pure drugs cannot replace the advantages of

  6. Human Environmental Disease Network: A computational model to assess toxicology of contaminants.

    Science.gov (United States)

    Taboureau, Olivier; Audouze, Karine

    2017-01-01

    During the past decades, many epidemiological, toxicological and biological studies have been performed to assess the role of environmental chemicals as potential toxicants associated with diverse human disorders. However, the relationships between diseases based on chemical exposure rarely have been studied by computational biology. We developed a human environmental disease network (EDN) to explore and suggest novel disease-disease and chemical-disease relationships. The presented scored EDN model is built upon the integration of systems biology and chemical toxicology using information on chemical contaminants and their disease relationships reported in the TDDB database. The resulting human EDN takes into consideration the level of evidence of the toxicant-disease relationships, allowing inclusion of some degrees of significance in the disease-disease associations. Such a network can be used to identify uncharacterized connections between diseases. Examples are discussed for type 2 diabetes (T2D). Additionally, this computational model allows confirmation of already known links between chemicals and diseases (e.g., between bisphenol A and behavioral disorders) and also reveals unexpected associations between chemicals and diseases (e.g., between chlordane and olfactory alteration), thus predicting which chemicals may be risk factors to human health. The proposed human EDN model allows exploration of common biological mechanisms of diseases associated with chemical exposure, helping us to gain insight into disease etiology and comorbidity. This computational approach is an alternative to animal testing supporting the 3R concept.

  7. Animal models of pediatric chronic kidney disease. Is adenine intake an appropriate model?

    Directory of Open Access Journals (Sweden)

    Débora Claramunt

    2015-11-01

    Full Text Available Pediatric chronic kidney disease (CKD has peculiar features. In particular, growth impairment is a major clinical manifestation of CKD that debuts in pediatric age because it presents in a large proportion of infants and children with CKD and has a profound impact on the self-esteem and social integration of the stunted patients. Several factors associated with CKD may lead to growth retardation by interfering with the normal physiology of growth plate, the organ where longitudinal growth rate takes place. The study of growth plate is hardly possible in humans and justifies the use of animal models. Young rats made uremic by 5/6 nephrectomy have been widely used as a model to investigate growth retardation in CKD. This article examines the characteristics of this model and analyzes the utilization of CKD induced by high adenine diet as an alternative research protocol.

  8. Modeling deployment of Pierce’s disease resistant grapevines

    Science.gov (United States)

    Deployment of Pierce’s disease resistant grapevines is a key solution to mitigating economic losses caused by Xylella fastidiosa. While Pierce’s disease resistant grapevines under development display mild symptoms and have lower bacterial populations than susceptible varieties, all appear to remain ...

  9. Interactive use of disease models using a smartphone

    NARCIS (Netherlands)

    Boshuizen, A.J.; Boshuizen, P.C.; Jong, de P.F.

    2015-01-01

    Fruit tree canker (Neonectria ditissima syn. Nectria galligena Bres.) is an important fungal disease in apple (Malus × domestica Borkh.). Leaf fall is the predominant infection period for this disease. However, in The Netherlands and Belgium, no historical data on leaf fall of apple are available.

  10. Modelling pandemics of quarantine pests and diseases: problems and perspectives

    NARCIS (Netherlands)

    Heesterbeek, J.A.P.; Zadoks, J.C.

    1987-01-01

    To develop a general framework for a mathematical theory of pandemics, known facts about pandemics of plant diseases are reconsidered. A pandemic is thought to consist of three parts called zero-order, first-order and second-order epidemics. The zero-order epidemic is the spread of a disease within

  11. Metabotyping of docosahexaenoic acid - treated Alzheimer's disease cell model.

    Directory of Open Access Journals (Sweden)

    Priti Bahety

    Full Text Available BACKGROUND: Despite the significant amount of work being carried out to investigate the therapeutic potential of docosahexaenoic acid (DHA in Alzheimer's disease (AD, the mechanism by which DHA affects amyloid-β precursor protein (AβPP-induced metabolic changes has not been studied. OBJECTIVE: To elucidate the metabolic phenotypes (metabotypes associated with DHA therapy via metabonomic profiling of an AD cell model using gas chromatography time-of-flight mass spectrometry (GC/TOFMS. METHODS: The lysate and supernatant samples of CHO-wt and CHO-AβPP695 cells treated with DHA and vehicle control were collected and prepared for GC/TOFMS metabonomics profiling. The metabolic profiles were analyzed by multivariate data analysis techniques using SIMCA-P+ software. RESULTS: Both principal component analysis and subsequent partial least squares discriminant analysis revealed distinct metabolites associated with the DHA-treated and control groups. A list of statistically significant marker metabolites that characterized the metabotypes associated with DHA treatment was further identified. Increased levels of succinic acid, citric acid, malic acid and glycine and decreased levels of zymosterol, cholestadiene and arachidonic acid correlated with DHA treatment effect. DHA levels were also found to be increased upon treatment. CONCLUSION: Our study shows that DHA plays a role in mitigating AβPP-induced impairment in energy metabolism and inflammation by acting on tricarboxylic acid cycle, cholesterol biosynthesis pathway and fatty acid metabolism. The perturbations of these metabolic pathways by DHA in CHO-wt and CHO-AβPP695 cells shed further mechanistic insights on its neuroprotective actions.

  12. Induced Pluripotent Stem Cells for Disease Modeling and Evaluation of Therapeutics for Niemann-Pick Disease Type A.

    Science.gov (United States)

    Long, Yan; Xu, Miao; Li, Rong; Dai, Sheng; Beers, Jeanette; Chen, Guokai; Soheilian, Ferri; Baxa, Ulrich; Wang, Mengqiao; Marugan, Juan J; Muro, Silvia; Li, Zhiyuan; Brady, Roscoe; Zheng, Wei

    2016-12-01

    : Niemann-Pick disease type A (NPA) is a lysosomal storage disease caused by mutations in the SMPD1 gene that encodes acid sphingomyelinase (ASM). Deficiency in ASM function results in lysosomal accumulation of sphingomyelin and neurodegeneration. Currently, there is no effective treatment for NPA. To accelerate drug discovery for treatment of NPA, we generated induced pluripotent stem cells from two patient dermal fibroblast lines and differentiated them into neural stem cells. The NPA neural stem cells exhibit a disease phenotype of lysosomal sphingomyelin accumulation and enlarged lysosomes. By using this disease model, we also evaluated three compounds that reportedly reduced lysosomal lipid accumulation in Niemann-Pick disease type C as well as enzyme replacement therapy with ASM. We found that α-tocopherol, δ-tocopherol, hydroxypropyl-β-cyclodextrin, and ASM reduced sphingomyelin accumulation and enlarged lysosomes in NPA neural stem cells. Therefore, the NPA neural stem cells possess the characteristic NPA disease phenotype that can be ameliorated by tocopherols, cyclodextrin, and ASM. Our results demonstrate the efficacies of cyclodextrin and tocopherols in the NPA cell-based model. Our data also indicate that the NPA neural stem cells can be used as a new cell-based disease model for further study of disease pathophysiology and for high-throughput screening to identify new lead compounds for drug development. Currently, there is no effective treatment for Niemann-Pick disease type A (NPA). To accelerate drug discovery for treatment of NPA, NPA-induced pluripotent stem cells were generated from patient dermal fibroblasts and differentiated into neural stem cells. By using the differentiated NPA neuronal cells as a cell-based disease model system, α-tocopherol, δ-tocopherol, and hydroxypropyl-β-cyclodextrin significantly reduced sphingomyelin accumulation in these NPA neuronal cells. Therefore, this cell-based NPA model can be used for further study of

  13. Comparison of Perturbed Pathways in Two Different Cell Models for Parkinson's Disease with Structural Equation Model.

    Science.gov (United States)

    Pepe, Daniele; Do, Jin Hwan

    2015-12-16

    Increasing evidence indicates that different morphological types of cell death coexist in the brain of patients with Parkinson's disease (PD), but the molecular explanation for this is still under investigation. In this study, we identified perturbed pathways in two different cell models for PD through the following procedures: (1) enrichment pathway analysis with differentially expressed genes and the Reactome pathway database, and (2) construction of the shortest path model for the enriched pathway and detection of significant shortest path model with fitting time-course microarray data of each PD cell model to structural equation model. Two PD cell models constructed by the same neurotoxin showed different perturbed pathways. That is, one showed perturbation of three Reactome pathways, including cellular senescence, chromatin modifying enzymes, and chromatin organization, while six modules within metabolism pathway represented perturbation in the other. This suggests that the activation of common upstream cell death pathways in PD may result in various down-stream processes, which might be associated with different morphological types of cell death. In addition, our results might provide molecular clues for coexistence of different morphological types of cell death in PD patients.

  14. Generalized glycogen storage and cardiomegaly in a knockout mouse model of Pompe disease

    NARCIS (Netherlands)

    A.G.A. Bijvoet (Agnes); A.T. van der Ploeg (Ans); E.H. van de Kamp; M.A. Kroos (Marian); J.-H. Ding (Jia-Huan); B.Z. Yang (Bing); P. Visser (Pim); C.E. Bakker (Cathy); M.Ph. Verbeet (Martin); B.A. Oostra (Ben); A.J.J. Reuser (Arnold)

    1998-01-01

    textabstractGlycogen storage disease type II (GSDII; Pompe disease), caused by inherited deficiency of acid alpha-glucosidase, is a lysosomal disorder affecting heart and skeletal muscles. A mouse model of this disease was obtained by targeted disruption of the

  15. Modeling chronic diseases: the diabetes module. Justification of (new) input data

    NARCIS (Netherlands)

    Baan CA; Bos G; Jacobs-van der Bruggen MAM; Baan CA; Bos G; Jacobs-van der Bruggen MAM; PZO

    2005-01-01

    The RIVM chronic disease model (CDM) is an instrument designed to estimate the effects of changes in the prevalence of risk factors for chronic diseases on disease burden and mortality. To enable the computation of the effects of various diabetes prevention scenarios, the CDM has been updated and

  16. Modelling the economic impact of three lameness causing diseases using herd and cow level evidence.

    Science.gov (United States)

    Ettema, Jehan; Østergaard, Søren; Kristensen, Anders Ringgaard

    2010-06-01

    Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic profitability of such actions. An existing approach of modelling lameness as one health disorder in a dynamic, stochastic and mechanistic simulation model has been improved in two ways. First of all, three underlying diseases causing lameness were modelled: digital dermatitis, interdigital hyperplasia and claw horn diseases. Secondly, the existing simulation model was set-up in way that it uses hyper-distributions describing diseases risk of the three lameness causing diseases. By combining information on herd level risk factors with prevalence of lameness or prevalence of underlying diseases among cows, marginal posterior probability distributions for disease prevalence in the specific herd are created in a Bayesian network. Random draws from these distributions are used by the simulation model to describe disease risk. Hereby field data on prevalence is used systematically and uncertainty around herd specific risk is represented. Besides the fact that estimated profitability of halving disease risk depended on the hyper-distributions used, the estimates differed for herds with different levels of diseases risk and reproductive efficiency. (c) 2010 Elsevier B.V. All rights reserved.

  17. Modelling the economic impact of three lameness causing diseases using herd and cow level evidence

    DEFF Research Database (Denmark)

    Ettema, Jehan Frans; Østergaard, Søren; Kristensen, Anders Ringgaard

    2010-01-01

    Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic...... horn diseases. Secondly, the existing simulation model was set-up inwaythat it uses hyper-distributions describing diseases risk of the three lameness causing diseases. By combining information on herd level risk factors with prevalence of lameness or prevalence of underlying diseases among cows...

  18. Similarity-based search of model organism, disease and drug effect phenotypes

    KAUST Repository

    Hoehndorf, Robert; Gruenberger, Michael; Gkoutos, Georgios V; Schofield, Paul N

    2015-01-01

    Background: Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions

  19. Leptospirosis disease mapping with standardized morbidity ratio and Poisson-Gamma model: An analysis of Leptospirosis disease in Kelantan, Malaysia

    Science.gov (United States)

    Che Awang, Aznida; Azah Samat, Nor

    2017-09-01

    Leptospirosis is a disease caused by the infection of pathogenic species from the genus of Leptospira. Human can be infected by the leptospirosis from direct or indirect exposure to the urine of infected animals. The excretion of urine from the animal host that carries pathogenic Leptospira causes the soil or water to be contaminated. Therefore, people can become infected when they are exposed to contaminated soil and water by cut on the skin as well as open wound. It also can enter the human body by mucous membrane such nose, eyes and mouth, for example by splashing contaminated water or urine into the eyes or swallowing contaminated water or food. Currently, there is no vaccine available for the prevention or treatment of leptospirosis disease but this disease can be treated if it is diagnosed early to avoid any complication. The disease risk mapping is important in a way to control and prevention of disease. Using a good choice of statistical model will produce a good disease risk map. Therefore, the aim of this study is to estimate the relative risk for leptospirosis disease based initially on the most common statistic used in disease mapping called Standardized Morbidity Ratio (SMR) and Poisson-gamma model. This paper begins by providing a review of the SMR method and Poisson-gamma model, which we then applied to leptospirosis data of Kelantan, Malaysia. Both results are displayed and compared using graph, tables and maps. The result shows that the second method Poisson-gamma model produces better relative risk estimates compared to the SMR method. This is because the Poisson-gamma model can overcome the drawback of SMR where the relative risk will become zero when there is no observed leptospirosis case in certain regions. However, the Poisson-gamma model also faced problems where the covariate adjustment for this model is difficult and no possibility for allowing spatial correlation between risks in neighbouring areas. The problems of this model have

  20. Disease-threat model explains acceptance of genetically modified products

    Directory of Open Access Journals (Sweden)

    Prokop Pavol

    2013-01-01

    Full Text Available Natural selection favoured survival of individuals who were able to avoid disease. The behavioural immune system is activated especially when our sensory system comes into contact with disease-connoting cues and/or when these cues resemble disease threat. We investigated whether or not perception of modern risky technologies, risky behaviour, expected reproductive goals and food neophobia are associated with the behavioural immune system related to specific attitudes toward genetically modified (GM products. We found that respondents who felt themselves more vulnerable to infectious diseases had significantly more negative attitudes toward GM products. Females had less positive attitudes toward GM products, but engaging in risky behaviours, the expected reproductive goals of females and food neophobia did not predict attitudes toward GM products. Our results suggest that evolved psychological mechanisms primarily designed to protect us against pathogen threat are activated by modern technologies possessing potential health risks.

  1. Analyzing differences in operational disease definitions using ontological modeling

    NARCIS (Netherlands)

    Peelen, Linda; Klein, Michel C.A.; Schlobach, Stefan; De Keizer, Nicolette F.; Peek, Niels

    2007-01-01

    In medicine, there are many diseases which cannot be precisely characterized but are considered as natural kinds. In the communication between health care professionals, this is generally not problematic. In biomedical research, however, crisp definitions are required to unambiguously distinguish

  2. Gaucher disease: a model disorder for biomarker discovery

    DEFF Research Database (Denmark)

    Boot, Rolf G; van Breemen, Mariëlle J; Wegdam, Wouter

    2009-01-01

    Gaucher disease is an inherited lysosomal storage disorder, characterized by massive accumulation of glucosylceramide-laden macrophages in the spleen, liver and bone marrow as a consequence of deficient activity of glucocerebrosidase. Gaucher disease has been the playground to develop new therape...... in clinical management of Gaucher patients are discussed. Moreover, the use of several modern proteomic technologies for the identification of Gaucher biomarkers is reviewed....

  3. Development of a Discrete Spatial-Temporal SEIR Simulator for Modeling Infectious Diseases

    Energy Technology Data Exchange (ETDEWEB)

    McKenna, S.A.

    2000-11-01

    Multiple techniques have been developed to model the temporal evolution of infectious diseases. Some of these techniques have also been adapted to model the spatial evolution of the disease. This report examines the application of one such technique, the SEIR model, to the spatial and temporal evolution of disease. Applications of the SEIR model are reviewed briefly and an adaptation to the traditional SEIR model is presented. This adaptation allows for modeling the spatial evolution of the disease stages at the individual level. The transmission of the disease between individuals is modeled explicitly through the use of exposure likelihood functions rather than the global transmission rate applied to populations in the traditional implementation of the SEIR model. These adaptations allow for the consideration of spatially variable (heterogeneous) susceptibility and immunity within the population. The adaptations also allow for modeling both contagious and non-contagious diseases. The results of a number of numerical experiments to explore the effect of model parameters on the spread of an example disease are presented.

  4. Costs and benefits of controlling quarantine diseases : a bio-economic modeling approach

    NARCIS (Netherlands)

    Breukers, M.L.H.; Mourits, M.C.M.; Werf, van der W.; Oude Lansink, A.G.J.M.

    2008-01-01

    This article describes a bio-economic model to quantify the costs and benefits of controlling plant quarantine diseases. The model integrates the epidemiology and economic consequences of a quarantine disease. It allows for ex ante evaluation of control scenarios for their cost-effectiveness, taking

  5. Long-Term Adult Feline Liver Organoid Cultures for Disease Modeling of Hepatic Steatosis

    NARCIS (Netherlands)

    Kruitwagen, Hedwig S.; Oosterhoff, Loes A.; Vernooij, Ingrid G.W.H.; Schrall, Ingrid M.; van Wolferen, Monique E.; Bannink, Farah; Roesch, Camille; van Uden, Lisa; Molenaar, Martijn R.; Helms, J. Bernd; Grinwis, Guy C.M.; Verstegen, Monique M.A.; van der Laan, Luc J.W.; Huch, Meritxell; Geijsen, Niels; Vries, Robert G.; Clevers, Hans; Rothuizen, Jan; Schotanus, Baukje A.; Penning, Louis C.; Spee, Bart

    2017-01-01

    Hepatic steatosis is a highly prevalent liver disease, yet research is hampered by the lack of tractable cellular and animal models. Steatosis also occurs in cats, where it can cause severe hepatic failure. Previous studies demonstrate the potential of liver organoids for modeling genetic diseases.

  6. An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health.

    Science.gov (United States)

    Mancy, Rebecca; Brock, Patrick M; Kao, Rowland R

    2017-01-01

    Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows) or groups of hosts (e.g., herds or farms), how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

  7. Early brain connectivity alterations and cognitive impairment in a rat model of Alzheimer's disease

    OpenAIRE

    Munoz-Moreno, Emma; Tudela, Raúl; López-Gil, Xavier; Soria, Guadalupe

    2018-01-01

    Background Animal models of Alzheimer’s disease (AD) are essential to understanding the disease progression and to development of early biomarkers. Because AD has been described as a disconnection syndrome, magnetic resonance imaging (MRI)-based connectomics provides a highly translational approach to characterizing the disruption in connectivity associated with the disease. In this study, a transgenic rat model of AD (TgF344-AD) was analyzed to describe both cognitive performance and brain c...

  8. Modelling spread of Bluetongue and other vector borne diseases in Denmark and evaluation of intervention strategies

    DEFF Research Database (Denmark)

    Græsbøll, Kaare

    that describes spread of disease using vectors or hosts as agents of the spread. The model is run with bluetongue as the primary case study, and it is demonstrated how an epidemic outbreak of bluetongue 8 in Denmark is sensitive to the use of pasture, climate, vaccination, vector abundance, and flying parameters......The main outcome of this PhD project is a generic model for non-contagious infectious vector-borne disease spread by one vector species between up to two species of hosts distributed on farms and pasture. The model features a within-herd model of disease, combined with a triple movement kernel....... In constructing a more process oriented agent-based approach to spread modeling new parameters describing vector behavior were introduced. When these vector flying parameters have been quantified by experiments, this model can be implemented on areas naïve to the modeled disease with a high predictive power...

  9. Occurrence of spontaneous periodontal disease in the SAMP1/YitFc murine model of Crohn disease.

    Science.gov (United States)

    Pietropaoli, Davide; Del Pinto, Rita; Corridoni, Daniele; Rodriguez-Palacios, Alexander; Di Stefano, Gabriella; Monaco, Annalisa; Weinberg, Aaron; Cominelli, Fabio

    2014-12-01

    Oral involvement is often associated with inflammatory bowel disease (IBD). Recent evidence suggests a high incidence of periodontal disease in patients with Crohn disease (CD). To the best of the authors' knowledge, no animal model of IBD that displays associated periodontal disease was reported previously. The aim of this study is to investigate the occurrence and progression of periodontal disease in SAMP1/YitFc (SAMP) mice that spontaneously develop a CD-like ileitis. In addition, the temporal correlation between the onset and progression of periodontal disease and the onset of ileitis in SAMP mice was studied. At different time points, SAMP and parental AKR/J (AKR) control mice were sacrificed, and mandibles were prepared for stereomicroscopy and histology. Terminal ilea were collected for histologic assessment of inflammation score. Periodontal status, i.e., alveolar bone loss (ABL) and alveolar bone crest, was examined by stereomicroscopy and histomorphometry, respectively. ABL increased in both strains with age. SAMP mice showed greater ABL compared with AKR mice by 12 weeks of age, with maximal differences observed at 27 weeks of age. AKR control mice did not show the same severity of periodontal disease. Interestingly, a strong positive correlation was found between ileitis severity and ABL in SAMP mice, independent of age. The present results demonstrate the occurrence of periodontal disease in a mouse model of progressive CD-like ileitis. In addition, the severity of periodontitis strongly correlated with the severity of ileitis, independent of age, suggesting that common pathogenic mechanisms, such as abnormal immune response and dysbiosis, may be shared between these two phenotypes.

  10. The impact of global environmental change on vector-borne disease risk: a modelling study

    Directory of Open Access Journals (Sweden)

    Rachel Lowe, PhD

    2018-05-01

    Full Text Available Background: Vector-borne diseases, such as dengue virus, Zika virus, and malaria, are highly sensitive to environmental changes, including variations in climate and land-surface characteristics. The emergence and spread of vector-borne diseases is also exacerbated by anthropogenic activities, such as deforestation, mining, urbanisation, and human mobility, which alter the natural habitats of vectors and increase vector–host interactions. Innovative epidemiological modelling tools can help to understand how environmental conditions interact with socioeconomic risk factors to predict the risk of disease transmission. In recent years, climate-health modelling has benefited from computational advances in fitting complex mathematical models; increasing availability of environmental, socioeconomic, and disease surveillance datasets; and improved ability to understand and model the climate system. Climate forecasts at seasonal time scales tend to improve in quality during El Niño-Southern Oscillation events in certain regions of the tropics. Thus, climate forecasts provide an opportunity to anticipate potential outbreaks of vector-borne diseases from several months to a year in advance. The aim of this study was to develop a framework to incorporate seasonal climate forecasts in predictive disease models to understand the future risk of vector-borne diseases, with a focus on dengue fever in Latin America. Methods: A Bayesian spatiotemporal model framework that quantifies the extent to which environmental and socioeconomic indicators can explain variations in disease risk was designed to disentangle the effects of climate from other risk factors using multi-source data and random effects, which account for unknown and unmeasured sources of spatial, seasonal, and inter-annual variation. The model was used to provide probabilistic predictions of monthly dengue incidence and the probability of exceeding outbreak thresholds, which were established in

  11. The mediterranean diet model in inflammatory rheumatic diseases

    Directory of Open Access Journals (Sweden)

    P. Spinella

    2011-06-01

    Full Text Available The Mediterranean diet is based on a pattern of eating that’s closely tied to the Mediterranean region, which includes Greece and southern Italy. Essentially, the traditional diet emphasizes foods from plant sources, limited meat consumption, small amounts of wine and olive oil as the main fat source. The beneficial effects of the Mediterranean diet has been proven not only to cardiovascular diseases but also for diabetes, obesity, arthritis and cancer. Its anti-inflammatory and protective properties are linked to the large presence of ω-3 polyunsaturated fatty acids, vitamins, but especially to the constituents of extra virgin olive oil: oleic acid, phenolic compounds olecanthal, a new recently discovered molecule, with natural anti-inflammatory properties. It has been shown that the Mediterranean diet can reduce disease activity, pain and stiffness in patients with inflammatory arthritis and may thus constitute a valuable support for patients suffering from these diseases.

  12. The chronic care model: Congruency and predictors among patients with cardiovascular diseases and chronic obstructive pulmonary disease in the Netherlands

    NARCIS (Netherlands)

    J.M. Cramm (Jane); A.P. Nieboer (Anna)

    2012-01-01

    textabstractObjective: The Chronic Care Model (CCM) achieved widespread acceptance and reflects the core elements of patient-centred care in chronic diseases such as CVD and COPD. Our aim is to assess the extent to which current care for CVD and COPD patients aligns with the CCM in Dutch healthcare

  13. Modelling the atmospheric dispersion of foot-and-mouth disease virus for emergency preparedness

    DEFF Research Database (Denmark)

    Sørensen, J.H.; Jensen, C.O.; Mikkelsen, T.

    2001-01-01

    A model system for simulating airborne spread of foot-and-mouth disease (FMD) is described. The system includes a virus production model and the local- and mesoscale atmospheric dispersion model RIMPUFF linked to the LINCOM local-scale Row model. LINCOM is used to calculate the sub-grid scale Row...

  14. Consistent partnership formation: application to a sexually transmitted disease model.

    Science.gov (United States)

    Artzrouni, Marc; Deuchert, Eva

    2012-02-01

    We apply a consistent sexual partnership formation model which hinges on the assumption that one gender's choices drives the process (male or female dominant model). The other gender's behavior is imputed. The model is fitted to UK sexual behavior data and applied to a simple incidence model of HSV-2. With a male dominant model (which assumes accurate male reports on numbers of partners) the modeled incidences of HSV-2 are 77% higher for men and 50% higher for women than with a female dominant model (which assumes accurate female reports). Although highly stylized, our simple incidence model sheds light on the inconsistent results one can obtain with misreported data on sexual activity and age preferences. Copyright © 2011 Elsevier Inc. All rights reserved.

  15. An inducible mouse model of late onset Tay-Sachs disease.

    Science.gov (United States)

    Jeyakumar, Mylvaganam; Smith, David; Eliott-Smith, Elena; Cortina-Borja, Mario; Reinkensmeier, Gabriele; Butters, Terry D; Lemm, Thorsten; Sandhoff, Konrad; Perry, V Hugh; Dwek, Raymond A; Platt, Frances M

    2002-08-01

    Mouse models of the G(M2) gangliosidoses, Tay-Sachs and Sandhoff disease, are null for the hexosaminidase alpha and beta subunits respectively. The Sandhoff (Hexb-/-) mouse has severe neurological disease and mimics the human infantile onset variant. However, the Tay-Sachs (Hexa-/-) mouse model lacks an overt phenotype as mice can partially bypass the blocked catabolic pathway and escape disease. We have investigated whether a subset of Tay-Sachs mice develop late onset disease. We have found that approximately 65% of the mice develop one or more clinical signs of the disease within their natural life span (n = 52, P disease at an earlier age (n = 21, P Tay-Sachs mice confirmed that pregnancy induces late onset Tay-Sachs disease. Onset of symptoms correlated with reduced up-regulation of hexosaminidase B, a component of the bypass pathway.

  16. Modeling the burden of poultry disease on the rural poor in Madagascar

    Directory of Open Access Journals (Sweden)

    Cassidy L. Rist

    2015-12-01

    Full Text Available Livestock represent a fundamental economic and nutritional resource for many households in the developing world; however, a high burden of infectious disease limits their production potential. Here we present an ecological framework for estimating the burden of poultry disease based on coupled models of infectious disease and economics. The framework is novel, as it values humans and livestock as co-contributors to household wellbeing, incorporating feedbacks between poultry production and human capital in disease burden estimates. We parameterize this coupled ecological–economic model with household-level data to provide an estimate of the overall burden of poultry disease for the Ifanadiana District in Madagascar, where over 72% of households rely on poultry for economic and food security. Our models indicate that households may lose 10–25% of their monthly income under current disease conditions. Results suggest that advancements in poultry health may serve to support income generation through improvements in both human and animal health.

  17. A survey of basic reproductive ratios in vector-borne disease transmission modeling

    Science.gov (United States)

    Soewono, E.; Aldila, D.

    2015-03-01

    Vector-borne diseases are commonly known in tropical and subtropical countries. These diseases have contributed to more than 10% of world infectious disease cases. Among the vectors responsible for transmitting the diseases are mosquitoes, ticks, fleas, flies, bugs and worms. Several of the diseases are known to contribute to the increasing threat to human health such as malaria, dengue, filariasis, chikungunya, west nile fever, yellow fever, encephalistis, and anthrax. It is necessary to understand the real process of infection, factors which contribute to the complication of the transmission in order to come up with a good and sound mathematical model. Although it is not easy to simulate the real transmission process of the infection, we could say that almost all models have been developed from the already long known Host-Vector model. It constitutes the main transmission processes i.e. birth, death, infection and recovery. From this simple model, the basic concepts of Disease Free and Endemic Equilibria and Basic Reproductive Ratio can be well explained and understood. Theoretical, modeling, control and treatment aspects of disease transmission problems have then been developed for various related diseases. General construction as well as specific forms of basic reproductive ratios for vector-borne diseases are discusses here.

  18. Modeling neurodegenerative diseases with patient-derived induced pluripotent cells: Possibilities and challenges.

    Science.gov (United States)

    Poon, Anna; Zhang, Yu; Chandrasekaran, Abinaya; Phanthong, Phetcharat; Schmid, Benjamin; Nielsen, Troels T; Freude, Kristine K

    2017-10-25

    The rising prevalence of progressive neurodegenerative diseases coupled with increasing longevity poses an economic burden at individual and societal levels. There is currently no effective cure for the majority of neurodegenerative diseases and disease-affected tissues from patients have been difficult to obtain for research and drug discovery in pre-clinical settings. While the use of animal models has contributed invaluable mechanistic insights and potential therapeutic targets, the translational value of animal models could be further enhanced when combined with in vitro models derived from patient-specific induced pluripotent stem cells (iPSCs) and isogenic controls generated using CRISPR-Cas9 mediated genome editing. The iPSCs are self-renewable and capable of being differentiated into the cell types affected by the diseases. These in vitro models based on patient-derived iPSCs provide the opportunity to model disease development, uncover novel mechanisms and test potential therapeutics. Here we review findings from iPSC-based modeling of selected neurodegenerative diseases, including Alzheimer's disease, frontotemporal dementia and spinocerebellar ataxia. Furthermore, we discuss the possibilities of generating three-dimensional (3D) models using the iPSCs-derived cells and compare their advantages and disadvantages to conventional two-dimensional (2D) models. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Stem cells and neurogenesis in relation to Alzheimer's disease Models

    NARCIS (Netherlands)

    Lucassen, P.J.; Jacobs, E.H.; Hoeijmakers, L.; Lesuis, S.L.; Krugers, H.; Korosi, A.; Kuhn, H.G.; Boekhoorn, K.; Kuhn, H.G.; Eisch, A.J.

    2015-01-01

    Alzheimer’s disease (AD) is a devastating neurodegenerative disorder associated with progressive cognitive decline and extensive neuropathology throughout the brain. Its main features include limited cell loss in selected subregions, generalized brain atrophy, and gradual accumulation of β-amyloid

  20. Modelling studies on neurodegenerative disease-causing triplet ...

    Indian Academy of Sciences (India)

    Unknown

    Abbreviations used: DM, dystrophia myotonica; FraX, fragile X syndrome; HD, Huntington disease; rms, root mean square. ... Further, at high salt condition, Greek key type quadruplex ..... tetrads at 30° twist and 3⋅4 Å rise (as observed in fiber.

  1. Modeling elm growth and Dutch elm disease susceptibility

    Science.gov (United States)

    Alberto Santini; Luisa Ghelardini

    2012-01-01

    Elm susceptibility to Dutch elm disease (DED) displays strong seasonal variation. The period during which elms can become infected and express DED symptoms is generally restricted to several weeks after growth resumption in spring, although it can vary among species, provenances, and environmental conditions. The reason for this phenomenon is not understood, but the...

  2. Seven challenges in modeling vaccine preventable diseasesC

    DEFF Research Database (Denmark)

    Metcalf, C. Jessica E.; Andreasen, Viggo; Bjørnstad, Ottar N.

    2015-01-01

    Vaccination has been one of the most successful public health measures since the introduction of basic sanitation. Substantial mortality and morbidity reductions have been achieved via vaccination against many infections, and the list of diseases that are potentially controllable by vaccines is g...

  3. Modeling motor neuron disease: the matter of time

    NARCIS (Netherlands)

    Arbab, Manda; Baars, S.E.; geijsen, n

    2014-01-01

    Stem cell technologies have created new opportunities to generate unlimited numbers of human neurons in the lab and study neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). Although some disease hallmarks have been reported in patient-derived

  4. Modeling motor neuron disease : the matter of time

    NARCIS (Netherlands)

    Arbab, Mandana; Baars, Susanne; Geijsen, Niels

    2014-01-01

    Stem cell technologies have created new opportunities to generate unlimited numbers of human neurons in the lab and study neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). Although some disease hallmarks have been reported in patient-derived

  5. Depression and cardiovascular disease : the end of simple models

    NARCIS (Netherlands)

    de Jonge, Peter; Roest, Annelieke M.

    In this editorial, we propose that the association between depression and cardiovascular disease may be conceptualised as a continuous, bidirectional process that originates in youth. The paper by Aberg and colleagues in this issue adds to this literature showing that low cardiovascular fitness at

  6. A few bad apples: a model of disease influenced agent behaviour in a heterogeneous contact environment.

    Directory of Open Access Journals (Sweden)

    Jessica Enright

    Full Text Available For diseases that infect humans or livestock, transmission dynamics are at least partially dependent on human activity and therefore human behaviour. However, the impact of human behaviour on disease transmission is relatively understudied, especially in the context of heterogeneous contact structures such as described by a social network. Here, we use a strategic game, coupled with a simple disease model, to investigate how strategic agent choices impact the spread of disease over a contact network. Using beliefs that are based on disease status and that build up over time, agents choose actions that stochastically determine disease spread on the network. An agent's disease status is therefore a function of both his own and his neighbours actions. The effect of disease on agents is modelled by a heterogeneous payoff structure. We find that the combination of network shape and distribution of payoffs has a non-trivial impact on disease prevalence, even if the mean payoff remains the same. An important scenario occurs when a small percentage (called noncooperators have little incentive to avoid disease. For diseases that are easily acquired when taking a risk, then even when good behavior can lead to disease eradication, a small increase in the percentage of noncooperators (less than 5% can yield a large (up to 25% increase in prevalence.

  7. Insights into Parkinson's disease models and neurotoxicity using non-invasive imaging

    International Nuclear Information System (INIS)

    Sanchez-Pernaute, Rosario; Brownell, Anna-Liisa; Jenkins, Bruce G.; Isacson, Ole

    2005-01-01

    Loss of dopamine in the nigrostriatal system causes a severe impairment in motor function in patients with Parkinson's disease and in experimental neurotoxic models of the disease. We have used non-invasive imaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (MRI) to investigate in vivo the changes in the dopamine system in neurotoxic models of Parkinson's disease. In addition to classic neurotransmitter studies, in these models, it is also possible to characterize associated and perhaps pathogenic factors, such as the contribution of microglia activation and inflammatory responses to neuronal damage. Functional imaging techniques are instrumental to our understanding and modeling of disease mechanisms, which should in turn lead to development of new therapies for Parkinson's disease and other neurodegenerative disorders

  8. Early-life stress origins of gastrointestinal disease: animal models, intestinal pathophysiology, and translational implications.

    Science.gov (United States)

    Pohl, Calvin S; Medland, Julia E; Moeser, Adam J

    2015-12-15

    Early-life stress and adversity are major risk factors in the onset and severity of gastrointestinal (GI) disease in humans later in life. The mechanisms by which early-life stress leads to increased GI disease susceptibility in adult life remain poorly understood. Animal models of early-life stress have provided a foundation from which to gain a more fundamental understanding of this important GI disease paradigm. This review focuses on animal models of early-life stress-induced GI disease, with a specific emphasis on translational aspects of each model to specific human GI disease states. Early postnatal development of major GI systems and the consequences of stress on their development are discussed in detail. Relevant translational differences between species and models are highlighted. Copyright © 2015 the American Physiological Society.

  9. Use of genome editing tools in human stem cell-based disease modeling and precision medicine.

    Science.gov (United States)

    Wei, Yu-da; Li, Shuang; Liu, Gai-gai; Zhang, Yong-xian; Ding, Qiu-rong

    2015-10-01

    Precision medicine emerges as a new approach that takes into account individual variability. The successful conduct of precision medicine requires the use of precise disease models. Human pluripotent stem cells (hPSCs), as well as adult stem cells, can be differentiated into a variety of human somatic cell types that can be used for research and drug screening. The development of genome editing technology over the past few years, especially the CRISPR/Cas system, has made it feasible to precisely and efficiently edit the genetic background. Therefore, disease modeling by using a combination of human stem cells and genome editing technology has offered a new platform to generate " personalized " disease models, which allow the study of the contribution of individual genetic variabilities to disease progression and the development of precise treatments. In this review, recent advances in the use of genome editing in human stem cells and the generation of stem cell models for rare diseases and cancers are discussed.

  10. Early-life stress origins of gastrointestinal disease: animal models, intestinal pathophysiology, and translational implications

    Science.gov (United States)

    Pohl, Calvin S.; Medland, Julia E.

    2015-01-01

    Early-life stress and adversity are major risk factors in the onset and severity of gastrointestinal (GI) disease in humans later in life. The mechanisms by which early-life stress leads to increased GI disease susceptibility in adult life remain poorly understood. Animal models of early-life stress have provided a foundation from which to gain a more fundamental understanding of this important GI disease paradigm. This review focuses on animal models of early-life stress-induced GI disease, with a specific emphasis on translational aspects of each model to specific human GI disease states. Early postnatal development of major GI systems and the consequences of stress on their development are discussed in detail. Relevant translational differences between species and models are highlighted. PMID:26451004

  11. Chronic Wasting Disease in Bank Voles: Characterisation of the Shortest Incubation Time Model for Prion Diseases

    NARCIS (Netherlands)

    Bari, Di M.A.; Nonno, R.; Castilla, J.; Augostino, D' C.; Pirisinu, L.; Riccardi, G.; Conte, M.; Richt, J.A.; Kunkle, R.; Langeveld, J.P.M.; Vaccari, G.; Agrimi, U.

    2013-01-01

    In order to assess the susceptibility of bank voles to chronic wasting disease (CWD), we inoculated voles carrying isoleucine or methionine at codon 109 (Bv109I and Bv109M, respectively) with CWD isolates from elk, mule deer and white-tailed deer. Efficient transmission rate (100%) was observed with

  12. Modelling breast cancer tumour growth for a stable disease population.

    Science.gov (United States)

    Isheden, Gabriel; Humphreys, Keith

    2017-01-01

    Statistical models of breast cancer tumour progression have been used to further our knowledge of the natural history of breast cancer, to evaluate mammography screening in terms of mortality, to estimate overdiagnosis, and to estimate the impact of lead-time bias when comparing survival times between screen detected cancers and cancers found outside of screening programs. Multi-state Markov models have been widely used, but several research groups have proposed other modelling frameworks based on specifying an underlying biological continuous tumour growth process. These continuous models offer some advantages over multi-state models and have been used, for example, to quantify screening sensitivity in terms of mammographic density, and to quantify the effect of body size covariates on tumour growth and time to symptomatic detection. As of yet, however, the continuous tumour growth models are not sufficiently developed and require extensive computing to obtain parameter estimates. In this article, we provide a detailed description of the underlying assumptions of the continuous tumour growth model, derive new theoretical results for the model, and show how these results may help the development of this modelling framework. In illustrating the approach, we develop a model for mammography screening sensitivity, using a sample of 1901 post-menopausal women diagnosed with invasive breast cancer.

  13. Impact of delay on disease outbreak in a spatial epidemic model

    Science.gov (United States)

    Zhao, Xia-Xia; Wang, Jian-Zhong

    2015-04-01

    One of the central issues in studying epidemic spreading is the mechanism on disease outbreak. In this paper, we investigate the effects of time delay on disease outbreak in spatial epidemics based on a reaction-diffusion model. By mathematical analysis and numerical simulations, we show that when time delay is more than a critical value, the disease outbreaks. The obtained results show that the time delay is an important factor in the spread of the disease, which may provide new insights on disease control.

  14. Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

    Science.gov (United States)

    Lorenz, Alyson; Dhingra, Radhika; Chang, Howard H; Bisanzio, Donal; Liu, Yang; Remais, Justin V

    2014-01-01

    Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. Three models based on measures of vegetation, habitat patch characteristics, and herbaceous landcover emerged as effective predictors of observed disease and vector distribution. An ensemble model containing these three models improved precision and predictive ability over individual models. A priori assessment of qualitative model characteristics effectively identified models that subsequently emerged as better predictors in quantitative analysis. Both a methodology for quantitative model comparison and a checklist for qualitative assessment of candidate models for extrapolation are provided; both tools aim to improve collaboration between those producing models and those interested in applying them to new areas and research questions.

  15. Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.

    Directory of Open Access Journals (Sweden)

    Alyson Lorenz

    Full Text Available Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. Three models based on measures of vegetation, habitat patch characteristics, and herbaceous landcover emerged as effective predictors of observed disease and vector distribution. An ensemble model containing these three models improved precision and predictive ability over individual models. A priori assessment of qualitative model characteristics effectively identified models that subsequently emerged as better predictors in quantitative analysis. Both a methodology for quantitative model comparison and a checklist for qualitative assessment of candidate models for extrapolation are provided; both tools aim to improve collaboration between those producing models and those interested in applying them to new areas and research questions.

  16. Spread of Ebola disease with susceptible exposed infected isolated recovered (SEIIhR) model

    Science.gov (United States)

    Azizah, Afina; Widyaningsih, Purnami; Retno Sari Saputro, Dewi

    2017-06-01

    Ebola is a deadly infectious disease and has caused an epidemic on several countries in West Africa. Mathematical modeling to study the spread of Ebola disease has been developed, including through models susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR). Furthermore, susceptible exposed infected isolated recovered (SEIIhR) model has been derived. The aims of this research are to derive SEIIhR model for Ebola disease, to determine the patterns of its spread, to determine the equilibrium point and stability of the equilibrium point using phase plane analysis, and also to apply the SEIIhR model on Ebola epidemic in Sierra Leone in 2014. The SEIIhR model is a differential equation system. Pattern of ebola disease spread with SEIIhR model is solution of the differential equation system. The equilibrium point of SEIIhR model is unique and it is a disease-free equilibrium point that stable. Application of the model is based on the data Ebola epidemic in Sierra Leone. The free-disease equilibrium point (Se; Ee; Ie; Ihe; Re )=(5743865, 0, 0, 0, 0) is stable.

  17. Spread of Ebola disease with susceptible exposed infected isolated recovered (SEIIhR) model

    International Nuclear Information System (INIS)

    Azizah, Afina; Widyaningsih, Purnami; Saputro, Dewi Retno Sari

    2017-01-01

    Ebola is a deadly infectious disease and has caused an epidemic on several countries in West Africa. Mathematical modeling to study the spread of Ebola disease has been developed, including through models susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR). Furthermore, susceptible exposed infected isolated recovered (SEII h R) model has been derived. The aims of this research are to derive SEII h R model for Ebola disease, to determine the patterns of its spread, to determine the equilibrium point and stability of the equilibrium point using phase plane analysis, and also to apply the SEII h R model on Ebola epidemic in Sierra Leone in 2014. The SEII h R model is a differential equation system. Pattern of ebola disease spread with SEII h R model is solution of the differential equation system. The equilibrium point of SEII h R model is unique and it is a disease-free equilibrium point that stable. Application of the model is based on the data Ebola epidemic in Sierra Leone. The free-disease equilibrium point ( S e ; E e ; I e ; I he ; R e )=(5743865, 0, 0, 0, 0) is stable. (paper)

  18. Non-Clinical Models for Neurodegenerative Diseases: Therapeutic Approach and Drug Validation in Animal Models

    Directory of Open Access Journals (Sweden)

    Caridad Ivette Fernandez

    2017-12-01

    Full Text Available In 2016, 19.8% of the Cuban population was aged 60 or over. As a result, age-associated degenerative diseases and other diseases have become priority targets from a prophylactic, diagnostic and therapeutic perspective. As a result, the Cuban biomedical scientific community has addressed its basic, preclinical and epidemiological research in order to rise up to the challenge. A firm step in this direction has been the international congress “State of the art in non-clinical models for neurodegenerative diseases” which has brought together preclinical and clinical researchers, technicians and regulatory staff members from different countries to review the state of the art in neurodegenerations, find unifying ideas, objectives and collaborations or partnership. The objective is to expose the perspectives of new biotechnological products from Cuba and other countries from the diagnostic, therapeutic and neuroprotective point of view. It is crucial, therefore, that the irreplaceable role of laboratory animals in achieving these objectives is understood but they must be used in rational, adequate and ethical manner. We expose the current development trends in this field, being of common interest to the work directed to the search for potential drugs, diagnostic tools and the promotion of changes in lifestyle as a preventive projection.

  19. Spatial modelling of disease using data- and knowledge-driven approaches.

    Science.gov (United States)

    Stevens, Kim B; Pfeiffer, Dirk U

    2011-09-01

    The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution. Copyright © 2011. Published by Elsevier Ltd.

  20. The selection pressures induced non-smooth infectious disease model and bifurcation analysis

    International Nuclear Information System (INIS)

    Qin, Wenjie; Tang, Sanyi

    2014-01-01

    Highlights: • A non-smooth infectious disease model to describe selection pressure is developed. • The effect of selection pressure on infectious disease transmission is addressed. • The key factors which are related to the threshold value are determined. • The stabilities and bifurcations of model have been revealed in more detail. • Strategies for the prevention of emerging infectious disease are proposed. - Abstract: Mathematical models can assist in the design strategies to control emerging infectious disease. This paper deduces a non-smooth infectious disease model induced by selection pressures. Analysis of this model reveals rich dynamics including local, global stability of equilibria and local sliding bifurcations. Model solutions ultimately stabilize at either one real equilibrium or the pseudo-equilibrium on the switching surface of the present model, depending on the threshold value determined by some related parameters. Our main results show that reducing the threshold value to a appropriate level could contribute to the efficacy on prevention and treatment of emerging infectious disease, which indicates that the selection pressures can be beneficial to prevent the emerging infectious disease under medical resource limitation

  1. A case study on point process modelling in disease mapping

    DEFF Research Database (Denmark)

    Møller, Jesper; Waagepetersen, Rasmus Plenge; Benes, Viktor

    2005-01-01

    of the risk on the covariates. Instead of using the common areal level approaches we base the analysis on a Bayesian approach for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using Markov chain Monte Carlo...... methods. A particular problem which is thoroughly discussed is to determine a model for the background population density. The risk map shows a clear dependency with the population intensity models and the basic model which is adopted for the population intensity determines what covariates influence...... the risk of TBE. Model validation is based on the posterior predictive distribution of various summary statistics....

  2. Anesthesia and Databases: Pediatric Cardiac Disease as a Role Model.

    Science.gov (United States)

    Vener, David F; Pasquali, Sara K; Mossad, Emad B

    2017-02-01

    Large data sets have now become ubiquitous in clinical medicine; they are particularly useful in high-acuity, low-volume conditions such as congenital heart disease where data must be collected from many centers. These data fall into 2 categories: administrative data arising from hospital admissions and charges and clinical data relating to specific diseases or procedures. In congenital cardiac diseases, there are now over a dozen of these data sets or registries focusing on various elements of patient care. Using probabilistic statistic matching, it is possible to marry administrative and clinical data post hoc using common elements to determine valuable information about care patterns, outcomes, and costs. These data sets can also be used in a collaborative fashion between institutions to drive quality improvement (QI). Because these data may include protected health information (PHI), care must be taken to adhere to federal guidelines on their use. A fundamental principle of large data management is the use of a common language and definition (nomenclature) to be effective. In addition, research derived from these information sources must be appropriately balanced to ensure that risk adjustments for preoperative and surgical factors are taken into consideration during the analysis. Care of patients with cardiac disease both in the United States and abroad consistently shows wide variability in mortality, morbidity, and costs, and there has been a tremendous amount of discussion about the benefits of regionalization of care based on center volume and outcome measurements. In the absence of regionalization, collaborative learning techniques have consistently been shown to minimize this variability and improve care at all centers, but before changes can be made it is necessary to accurately measure accurately current patient outcomes. Outcomes measurement generally falls under hospital-based QI initiatives, but more detailed analysis and research require

  3. The mediterranean diet model in inflammatory rheumatic diseases

    OpenAIRE

    P. Spinella; F. Oliviero; C. Sales

    2011-01-01

    The Mediterranean diet is based on a pattern of eating that’s closely tied to the Mediterranean region, which includes Greece and southern Italy. Essentially, the traditional diet emphasizes foods from plant sources, limited meat consumption, small amounts of wine and olive oil as the main fat source. The beneficial effects of the Mediterranean diet has been proven not only to cardiovascular diseases but also for diabetes, obesity, arthritis and cancer. Its anti-inflammatory and protective pr...

  4. Some Models for Epidemics of Vector-Transmitted Diseases

    OpenAIRE

    Brauer, Fred; Castillo-Chavez, Carlos; Mubayi, Anuj; Towers, Sherry

    2016-01-01

    Vector-transmitted diseases such as dengue fever and chikungunya have been spreading rapidly in many parts of the world. The Zika virus has been known since 1947 and invaded South America in 2013. It can be transmitted not only by (mosquito) vectors but also directly through sexual contact. Zika has developed into a serious global health problem because, while most cases are asymptomatic or very light, babies born to Zika - infected mothers may develop microcephaly and other very serious birt...

  5. [Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

    Science.gov (United States)

    Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

    2016-01-01

    To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

  6. Modelling neurodegenerative diseases in vitro: Recent advances in 3D iPSC technologies

    Directory of Open Access Journals (Sweden)

    Elodie J Siney

    2018-03-01

    Full Text Available The discovery of induced pluripotent stem cells (iPSC 12 years ago has fostered the development of innovative patient-derived in vitro models for better understanding of disease mechanisms. This is particularly relevant to neurodegenerative diseases, where availability of live human brain tissue for research is limited and post-mortem interval changes influence readouts from autopsy-derived human tissue. Hundreds of iPSC lines have now been prepared and banked, thanks to several large scale initiatives and cell banks. Patient- or engineered iPSC-derived neural models are now being used to recapitulate cellular and molecular aspects of a variety of neurodegenerative diseases, including early and pre-clinical disease stages. The broad relevance of these models derives from the availability of a variety of differentiation protocols to generate disease-specific cell types and the manipulation to either introduce or correct disease-relevant genetic modifications. Moreover, the use of chemical and physical three-dimensional (3D matrices improves control over the extracellular environment and cellular organization of the models. These iPSC-derived neural models can be utilised to identify target proteins and, importantly, provide high-throughput screening for drug discovery. Choosing Alzheimer’s disease (AD as an example, this review describes 3D iPSC-derived neural models and their advantages and limitations. There is now a requirement to fully characterise and validate these 3D iPSC-derived neural models as a viable research tool that is capable of complementing animal models of neurodegeneration and live human brain tissue. With further optimization of differentiation, maturation and aging protocols, as well as the 3D cellular organisation and extracellular matrix to recapitulate more closely, the molecular extracellular-environment of the human brain, 3D iPSC-derived models have the potential to deliver new knowledge, enable discovery of novel

  7. Variability in results from negative binomial models for Lyme disease measured at different spatial scales.

    Science.gov (United States)

    Tran, Phoebe; Waller, Lance

    2015-01-01

    Lyme disease has been the subject of many studies due to increasing incidence rates year after year and the severe complications that can arise in later stages of the disease. Negative binomial models have been used to model Lyme disease in the past with some success. However, there has been little focus on the reliability and consistency of these models when they are used to study Lyme disease at multiple spatial scales. This study seeks to explore how sensitive/consistent negative binomial models are when they are used to study Lyme disease at different spatial scales (at the regional and sub-regional levels). The study area includes the thirteen states in the Northeastern United States with the highest Lyme disease incidence during the 2002-2006 period. Lyme disease incidence at county level for the period of 2002-2006 was linked with several previously identified key landscape and climatic variables in a negative binomial regression model for the Northeastern region and two smaller sub-regions (the New England sub-region and the Mid-Atlantic sub-region). This study found that negative binomial models, indeed, were sensitive/inconsistent when used at different spatial scales. We discuss various plausible explanations for such behavior of negative binomial models. Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Global gene expression profile progression in Gaucher disease mouse models

    Directory of Open Access Journals (Sweden)

    Zhang Wujuan

    2011-01-01

    Full Text Available Abstract Background Gaucher disease is caused by defective glucocerebrosidase activity and the consequent accumulation of glucosylceramide. The pathogenic pathways resulting from lipid laden macrophages (Gaucher cells in visceral organs and their abnormal functions are obscure. Results To elucidate this pathogenic pathway, developmental global gene expression analyses were conducted in distinct Gba1 point-mutated mice (V394L/V394L and D409 V/null. About 0.9 to 3% of genes had altered expression patterns (≥ ± 1.8 fold change, representing several categories, but particularly macrophage activation and immune response genes. Time course analyses (12 to 28 wk of INFγ-regulated pro-inflammatory (13 and IL-4-regulated anti-inflammatory (11 cytokine/mediator networks showed tissue differential profiles in the lung and liver of the Gba1 mutant mice, implying that the lipid-storage macrophages were not functionally inert. The time course alterations of the INFγ and IL-4 pathways were similar, but varied in degree in these tissues and with the Gba1 mutation. Conclusions Biochemical and pathological analyses demonstrated direct relationships between the degree of tissue glucosylceramides and the gene expression profile alterations. These analyses implicate IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory networks in differential disease progression with implications for understanding the Gaucher disease course and pathophysiology.

  9. Protein modeling of yellow rust disease in wheat

    International Nuclear Information System (INIS)

    Aziz, S.E.; Bano, R.; Zayed, M.E.; Elshikh, M.S.; Khan, M.H.; Chaudhry, Z.

    2017-01-01

    Wheat production in Pakistan is affected by yellow rust disease caused by a fungus Puccinia striiformis. There is a need to broaden the genetic basis of wheat by identifying new resistance genes. The present study was aimed to identify an alternate resistance gene for yellow rust disease in wheat caused by Puccinia striiformis. Genome sequence was compared with databases and similar gene was identified for disease resistance in rye plant. Structural analysis of RGA1 gene (resistance gene in wheat) was carried out using different bioinformatics tools and an alternative gene having same structure was identified on the basis of structural and sequence homology. Rye plant is the proposed plant for the alternate new resistance gene. The result of pairwise alignment of RGA1 gene in wheat and gene of rye plant is 94.2% with accession DQ494535 .The secondary structures of both the genes was compared and found similar to each other. These comparisons between the wheat resistance gene and gene from rye plant depict structural similarities between the two genes. Results of RGA1 gene's structural analysis in wheat is as follow: Helices: 59, Extended sheets: 30, Turns: 12, Coils: 13 and for alternate resistance genes in Rye is as follow: Helices: 52, Extended sheets: 30, Turns: 14, Coils: 17. As structures are similar, the alternate identified gene could be used for resistance in wheat. (author)

  10. A minimal unified model of disease trajectories captures hallmarks of multiple sclerosis

    KAUST Repository

    Kannan, Venkateshan

    2017-03-29

    Multiple Sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) causing demyelination and neurodegeneration leading to accumulation of neurological disability. Here we present a minimal, computational model involving the immune system and CNS that generates the principal subtypes of the disease observed in patients. The model captures several key features of MS, especially those that distinguish the chronic progressive phase from that of the relapse-remitting. In addition, a rare subtype of the disease, progressive relapsing MS naturally emerges from the model. The model posits the existence of two key thresholds, one in the immune system and the other in the CNS, that separate dynamically distinct behavior of the model. Exploring the two-dimensional space of these thresholds, we obtain multiple phases of disease evolution and these shows greater variation than the clinical classification of MS, thus capturing the heterogeneity that is manifested in patients.

  11. Dangerous connections : on binding site models of infectious disease dynamics

    NARCIS (Netherlands)

    Leung, Ka Yin; Diekmann, Odo

    2017-01-01

    We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the

  12. Models of alcoholic liver disease in rodents: a critical evaluation

    DEFF Research Database (Denmark)

    de la M. Hall, P.; Lieber, C.S.; De Carli, L.M.

    2001-01-01

    ) Lieber-DeCarli liquid diet for alcohol-induced liver injury in rats, by C. S. Lieber and L. M. DeCarli; (3) Tsukamoto-French model of alcoholic liver injury, by S. W. French; (4) Animal models to study endotoxin-ethanol interactions, by K. O. Lindros and H. Järveläinen; and (5) Jejunoileal bypass...

  13. Neural stem cells for disease modeling of Wolman disease and evaluation of therapeutics

    OpenAIRE

    Aguisanda, Francis; Yeh, Charles D.; Chen, Catherine Z.; Li, Rong; Beers, Jeanette; Zou, Jizhong; Thorne, Natasha; Zheng, Wei

    2017-01-01

    Background Wolman disease (WD) is a rare lysosomal storage disorder that is caused by mutations in the LIPA gene encoding lysosomal acid lipase (LAL). Deficiency in LAL function causes accumulation of cholesteryl esters and triglycerides in lysosomes. Fatality usually occurs within the first year of life. While an enzyme replacement therapy has recently become available, there is currently no small-molecule drug treatment for WD. Results We have generated induced pluripotent stem cells (iPSCs...

  14. How to become a top model: impact of animal experimentation on human Salmonella disease research.

    Science.gov (United States)

    Tsolis, Renée M; Xavier, Mariana N; Santos, Renato L; Bäumler, Andreas J

    2011-05-01

    Salmonella serotypes are a major cause of human morbidity and mortality worldwide. Over the past decades, a series of animal models have been developed to advance vaccine development, provide insights into immunity to infection, and study the pathogenesis of human Salmonella disease. The successive introduction of new animal models, each suited to interrogate previously neglected aspects of Salmonella disease, has ushered in important conceptual advances that continue to have a strong and sustained influence on the ideas driving research on Salmonella serotypes. This article reviews important milestones in the use of animal models to study human Salmonella disease and identify research needs to guide future work.

  15. Dynamical analysis and simulation of a 2-dimensional disease model with convex incidence

    Science.gov (United States)

    Yu, Pei; Zhang, Wenjing; Wahl, Lindi M.

    2016-08-01

    In this paper, a previously developed 2-dimensional disease model is studied, which can be used for both epidemiologic modeling and in-host disease modeling. The main attention of this paper is focused on various dynamical behaviors of the system, including Hopf and generalized Hopf bifurcations which yield bistability and tristability, Bogdanov-Takens bifurcation, and homoclinic bifurcation. It is shown that the Bogdanov-Takens bifurcation and homoclinic bifurcation provide a new mechanism for generating disease recurrence, that is, cycles of remission and relapse such as the viral blips observed in HIV infection.

  16. Drugs for Neglected Diseases initiative model of drug development for neglected diseases: current status and future challenges.

    Science.gov (United States)

    Ioset, Jean-Robert; Chang, Shing

    2011-09-01

    The Drugs for Neglected Diseases initiative (DNDi) is a patients' needs-driven organization committed to the development of new treatments for neglected diseases. Created in 2003, DNDi has delivered four improved treatments for malaria, sleeping sickness and visceral leishmaniasis. A main DNDi challenge is to build a solid R&D portfolio for neglected diseases and to deliver preclinical candidates in a timely manner using an original model based on partnership. To address this challenge DNDi has remodeled its discovery activities from a project-based academic-bound network to a fully integrated process-oriented platform in close collaboration with pharmaceutical companies. This discovery platform relies on dedicated screening capacity and lead-optimization consortia supported by a pragmatic, structured and pharmaceutical-focused compound sourcing strategy.

  17. Disease-modeling as a tool for surveillance, foresight and control of exotic vector borne diseases in the Nordic countries

    DEFF Research Database (Denmark)

    Bødker, Rene

    period e.g. a monthly temperature mean. Average monthly temperatures are likely to be suitable for predicting permanent establishment of presently exotic diseases. But mean temperatures may not predict the true potential for local spread or limited outbreaks resulting from accidental introductions...... for continuous risk assessment of the potential for local spread of exotic insect borne diseases of veterinary and human importance. In this system R0-models for various vector borne diseases are continuously updated with spatial temperature data to quantify the present risk of autochthonous cases (R0......>0) and the present risk of epidemics (R0>1) should an infected vector or host be introduced to the area. The continuously updated risk assessment maps function as an early warning system allowing authorities and industry to increase awareness and preventive measures when R0 raises above the level of ‗no possible...

  18. Disease mapping based on stochastic SIR-SI model for Dengue and Chikungunya in Malaysia

    Energy Technology Data Exchange (ETDEWEB)

    Samat, N. A.; Ma' arof, S. H. Mohd Imam [Department of Mathematics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Perak (Malaysia)

    2014-12-04

    This paper describes and demonstrates a method for relative risk estimation which is based on the stochastic SIR-SI vector-borne infectious disease transmission model specifically for Dengue and Chikungunya diseases in Malaysia. Firstly, the common compartmental model for vector-borne infectious disease transmission called the SIR-SI model (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) is presented. This is followed by the explanations on the stochastic SIR-SI model which involve the Bayesian description. This stochastic model then is used in the relative risk formulation in order to obtain the posterior relative risk estimation. Then, this relative estimation model is demonstrated using Dengue and Chikungunya data of Malaysia. The viruses of these diseases are transmitted by the same type of female vector mosquito named Aedes Aegypti and Aedes Albopictus. Finally, the findings of the analysis of relative risk estimation for both Dengue and Chikungunya diseases are presented, compared and displayed in graphs and maps. The distribution from risk maps show the high and low risk area of Dengue and Chikungunya diseases occurrence. This map can be used as a tool for the prevention and control strategies for both diseases.

  19. Disease mapping based on stochastic SIR-SI model for Dengue and Chikungunya in Malaysia

    International Nuclear Information System (INIS)

    Samat, N. A.; Ma'arof, S. H. Mohd Imam

    2014-01-01

    This paper describes and demonstrates a method for relative risk estimation which is based on the stochastic SIR-SI vector-borne infectious disease transmission model specifically for Dengue and Chikungunya diseases in Malaysia. Firstly, the common compartmental model for vector-borne infectious disease transmission called the SIR-SI model (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) is presented. This is followed by the explanations on the stochastic SIR-SI model which involve the Bayesian description. This stochastic model then is used in the relative risk formulation in order to obtain the posterior relative risk estimation. Then, this relative estimation model is demonstrated using Dengue and Chikungunya data of Malaysia. The viruses of these diseases are transmitted by the same type of female vector mosquito named Aedes Aegypti and Aedes Albopictus. Finally, the findings of the analysis of relative risk estimation for both Dengue and Chikungunya diseases are presented, compared and displayed in graphs and maps. The distribution from risk maps show the high and low risk area of Dengue and Chikungunya diseases occurrence. This map can be used as a tool for the prevention and control strategies for both diseases

  20. Dynamical behavior of an epidemic model for a vector-borne disease with direct transmission

    International Nuclear Information System (INIS)

    Cai Liming; Li Xuezhi; Li Zhaoqiang

    2013-01-01

    An epidemic model of a vector-borne disease with direct transmission is investigated. The reproduction number (R 0 ) of the model is obtained. Rigorous qualitative analysis of the model reveals the presence of the phenomenon of backward bifurcation (where the stable disease-free equilibrium (DFE) coexists with a stable endemic equilibrium when the reproduction number of the disease is less than unity) in the standard incidence model. The phenomenon shows that the classical epidemiological requirement of having the reproduction number less than unity is no longer sufficient, although necessary, for effectively controlling the spread of some vector-borne diseases in a community. The backward bifurcation phenomenon can be removed by substituting the standard incidence with a bilinear mass action incidence. By using Lyapunov function theory and LaSalle invariance principle, it is shown that the unique endemic equilibrium for the model with a mass action incidence is globally stable if the reproduction number R mass is greater than one in feasible region. This suggests that the use of standard incidence in modelling some vector-borne diseases with direct transmission results in the presence of backward bifurcation. Numerical simulations analyze the effect of the direct transmission and the disease-induced death rate on dynamics of the disease transmission, and also verify our analyzed results.

  1. Disease mapping based on stochastic SIR-SI model for Dengue and Chikungunya in Malaysia

    Science.gov (United States)

    Samat, N. A.; Ma'arof, S. H. Mohd Imam

    2014-12-01

    This paper describes and demonstrates a method for relative risk estimation which is based on the stochastic SIR-SI vector-borne infectious disease transmission model specifically for Dengue and Chikungunya diseases in Malaysia. Firstly, the common compartmental model for vector-borne infectious disease transmission called the SIR-SI model (susceptible-infective-recovered for human populations; susceptible-infective for vector populations) is presented. This is followed by the explanations on the stochastic SIR-SI model which involve the Bayesian description. This stochastic model then is used in the relative risk formulation in order to obtain the posterior relative risk estimation. Then, this relative estimation model is demonstrated using Dengue and Chikungunya data of Malaysia. The viruses of these diseases are transmitted by the same type of female vector mosquito named Aedes Aegypti and Aedes Albopictus. Finally, the findings of the analysis of relative risk estimation for both Dengue and Chikungunya diseases are presented, compared and displayed in graphs and maps. The distribution from risk maps show the high and low risk area of Dengue and Chikungunya diseases occurrence. This map can be used as a tool for the prevention and control strategies for both diseases.

  2. Disease elimination and re-emergence in differential-equation models.

    Science.gov (United States)

    Greenhalgh, Scott; Galvani, Alison P; Medlock, Jan

    2015-12-21

    Traditional differential equation models of disease transmission are often used to predict disease trajectories and evaluate the effectiveness of alternative intervention strategies. However, such models cannot account explicitly for probabilistic events, such as those that dominate dynamics when disease prevalence is low during the elimination and re-emergence phases of an outbreak. To account for the dynamics at low prevalence, i.e. the elimination and risk of disease re-emergence, without the added analytical and computational complexity of a stochastic model, we develop a novel application of control theory. We apply our approach to analyze historical data of measles elimination and re-emergence in Iceland from 1923 to 1938, predicting the temporal trajectory of local measles elimination and re-emerge as a result of disease migration from Copenhagen, Denmark. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Endometriosis research: animal models for the study of a complex disease.

    Science.gov (United States)

    Tirado-González, Irene; Barrientos, Gabriela; Tariverdian, Nadja; Arck, Petra C; García, Mariana G; Klapp, Burghard F; Blois, Sandra M

    2010-11-01

    Endometriosis is a common gynaecological disease that is characterized and defined as the presence of endometrial tissue outside the uterus, causing painful periods and subfertility in approximately 10% of women. After more than 50 years of research, little is known about the mechanisms underlying the development and establishment of this condition. Animal models allow us to study the temporal sequence of events involved in disease establishment and progression. Also, because this disease occurs spontaneously only in humans and non-human primates and there are practical problems associated with studying the disease, animal models have been developed for the evaluation of endometriosis. This review describes the animal models for endometriosis that have been used to date, highlighting their importance for the investigation of disease mechanisms that would otherwise be more difficult to elucidate, and proposing new alternatives aimed at overcoming some of these limitations. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  4. The pathophysiology of mitochondrial disease as modeled in the mouse.

    Science.gov (United States)

    Wallace, Douglas C; Fan, Weiwei

    2009-08-01

    It is now clear that mitochondrial defects are associated with a plethora of clinical phenotypes in man and mouse. This is the result of the mitochondria's central role in energy production, reactive oxygen species (ROS) biology, and apoptosis, and because the mitochondrial genome consists of roughly 1500 genes distributed across the maternal mitochondrial DNA (mtDNA) and the Mendelian nuclear DNA (nDNA). While numerous pathogenic mutations in both mtDNA and nDNA mitochondrial genes have been identified in the past 21 years, the causal role of mitochondrial dysfunction in the common metabolic and degenerative diseases, cancer, and aging is still debated. However, the development of mice harboring mitochondrial gene mutations is permitting demonstration of the direct cause-and-effect relationship between mitochondrial dysfunction and disease. Mutations in nDNA-encoded mitochondrial genes involved in energy metabolism, antioxidant defenses, apoptosis via the mitochondrial permeability transition pore (mtPTP), mitochondrial fusion, and mtDNA biogenesis have already demonstrated the phenotypic importance of mitochondrial defects. These studies are being expanded by the recent development of procedures for introducing mtDNA mutations into the mouse. These studies are providing direct proof that mtDNA mutations are sufficient by themselves to generate major clinical phenotypes. As more different mtDNA types and mtDNA gene mutations are introduced into various mouse nDNA backgrounds, the potential functional role of mtDNA variation in permitting humans and mammals to adapt to different environments and in determining their predisposition to a wide array of diseases should be definitively demonstrated.

  5. CD4+CD25+ regulatory T cells: II. Origin, disease models and clinical aspects

    DEFF Research Database (Denmark)

    Nielsen, Janne; Holm, Thomas Lindebo; Claesson, Mogens H

    2004-01-01

    Autoimmune diseases afflict approximately 5% of the population and reflect a failure in the immune system to discriminate between self and non-self resulting in the breakdown of self-tolerance. Regulatory CD4+CD25+ T cells (Treg cells) have been shown to play an important role in the maintenance ...... in disease models such as autoimmune gastritis and inflammatory bowel disease. Finally, we will consider some aspects of the therapeutic potential of Treg cells....

  6. Caenorhabditis elegans as a model to study renal development and disease: sexy cilia.

    Science.gov (United States)

    Barr, Maureen M

    2005-02-01

    The nematode Caenorhabditis elegans has no kidney per se, yet "the worm" has proved to be an excellent model to study renal-related issues, including tubulogenesis of the excretory canal, membrane transport and ion channel function, and human genetic diseases including autosomal dominant polycystic kidney disease (ADPKD). The goal of this review is to explain how C. elegans has provided insight into cilia development, cilia function, and human cystic kidney diseases.

  7. Human organoids: a model system for intestinal diseases

    OpenAIRE

    Wiegerinck, C.L.

    2015-01-01

    You are what you eat. A common saying that indicates that your physical or mental state can be influenced by your choice of food. Unfortunately, not all people have the luxury to choose what to eat; this can be related to place of birth, social, economic state, or the physical inability of the diseased intestine to take up certain food. A cell layer, the epithelium, covers the intestine, and harbors the main functions of the intestine: uptake, digestion of food, and a barrier against unwanted...

  8. Bayesian disease mapping: hierarchical modeling in spatial epidemiology

    National Research Council Canada - National Science Library

    Lawson, Andrew

    2013-01-01

    Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas...

  9. 78 FR 8535 - Medicare Program: Comprehensive End-Stage Renal Disease Care Model Announcement

    Science.gov (United States)

    2013-02-06

    ... develop and test innovative health care payment and service delivery models that show promise of reducing... test innovative payment and service delivery models that reduce spending under Medicare, Medicaid or...] Medicare Program: Comprehensive End-Stage Renal Disease Care Model Announcement AGENCY: Centers for...

  10. Detection of Severe Respiratory Disease Epidemic Outbreaks by CUSUM-Based Overcrowd-Severe-Respiratory-Disease-Index Model

    Directory of Open Access Journals (Sweden)

    Carlos Polanco

    2013-01-01

    Full Text Available A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008–2010 taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts.

  11. Detection of Severe Respiratory Disease Epidemic Outbreaks by CUSUM-Based Overcrowd-Severe-Respiratory-Disease-Index Model

    Science.gov (United States)

    Castañón-González, Jorge Alberto; Macías, Alejandro E.; Samaniego, José Lino; Buhse, Thomas; Villanueva-Martínez, Sebastián

    2013-01-01

    A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008–2010) taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts. PMID:24069063

  12. Patient-specific induced pluripotent stem cells in neurological disease modeling: the importance of nonhuman primate models

    Directory of Open Access Journals (Sweden)

    Qiu Z

    2013-07-01

    Full Text Available Zhifang Qiu,1,2 Steven L Farnsworth,2 Anuja Mishra,1,2 Peter J Hornsby1,21Geriatric Research Education and Clinical Center, South Texas Veterans Health Care System, San Antonio, TX, USA; 2Barshop Institute for Longevity and Aging Studies, University of Texas Health Science Center, San Antonio, TX, USAAbstract: The development of the technology for derivation of induced pluripotent stem (iPS cells from human patients and animal models has opened up new pathways to the better understanding of many human diseases, and has created new opportunities for therapeutic approaches. Here, we consider one important neurological disease, Parkinson's, the development of relevant neural cell lines for studying this disease, and the animal models that are available for testing the survival and function of the cells, following transplantation into the central nervous system. Rapid progress has been made recently in the application of protocols for neuroectoderm differentiation and neural patterning of pluripotent stem cells. These developments have resulted in the ability to produce large numbers of dopaminergic neurons with midbrain characteristics for further study. These cells have been shown to be functional in both rodent and nonhuman primate (NHP models of Parkinson's disease. Patient-specific iPS cells and derived dopaminergic neurons have been developed, in particular from patients with genetic causes of Parkinson's disease. For complete modeling of the disease, it is proposed that the introduction of genetic changes into NHP iPS cells, followed by studying the phenotype of the genetic change in cells transplanted into the NHP as host animal, will yield new insights into disease processes not possible with rodent models alone.Keywords: Parkinson's disease, pluripotent cell differentiation, neural cell lines, dopaminergic neurons, cell transplantation, animal models

  13. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction.

    Directory of Open Access Journals (Sweden)

    Yiming Hu

    2017-06-01

    Full Text Available Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.

  14. Modeling the transmission dynamics of Ebola virus disease in Liberia.

    Science.gov (United States)

    Xia, Zhi-Qiang; Wang, Shi-Fu; Li, Shen-Long; Huang, Liu-Yu; Zhang, Wen-Yi; Sun, Gui-Quan; Gai, Zhong-Tao; Jin, Zhen

    2015-09-08

    Ebola virus disease (EVD) has erupted many times in some zones since it was first found in 1976. The 2014 EVD outbreak in West Africa is the largest ever, which has caused a large number of deaths and the most serious country is Liberia during the outbreak period. Based on the data released by World Health Organization and the actual transmission situations, we investigate the impact of different transmission routes on the EVD outbreak in Liberia and estimate the basic reproduction number R0 = 2.012 in the absence of effective control measures. Through sensitivity and uncertainty analysis, we reveal that the transmission coefficients of suspected and probable cases have stronger correlations on the basic reproduction number. Furthermore, we study the influence of control measures (isolation and safe burial measures) on EVD outbreak. It is found that if combined control measures are taken, the basic reproduction number will be less than one and thus EVD in Liberia may be well contained. The obtained results may provide new guidance to prevent and control the spread of disease.

  15. Modeling Parkinson's disease falls associated with brainstem cholinergic systems decline.

    Science.gov (United States)

    Kucinski, Aaron; Sarter, Martin

    2015-04-01

    In addition to the primary disease-defining symptoms, approximately half of patients with Parkinson's disease (PD) suffer from postural instability, impairments in gait control and a propensity for falls. Consistent with evidence from patients, we previously demonstrated that combined striatal dopamine (DA) and basal forebrain (BF) cholinergic cell loss causes falls in rats traversing dynamic surfaces. Because evidence suggests that degeneration of brainstem cholinergic neurons arising from the pedunculopontine nucleus (PPN) also contributes to impaired gait and falls, here we assessed the effects of selective cholinergic PPN lesions in combination with striatal DA loss or BF cholinergic cells loss as well as losses in all 3 regions. Results indicate that all combination losses that included the BF cholinergic system slowed traversal and increased slips and falls. However, the performance of rats with losses in all 3 regions (PPN, BF, and DA) was not more severely impaired than following combined BF cholinergic and striatal DA lesions. These results confirm the hypothesis that BF cholinergic-striatal disruption of attentional-motor interactions is a primary source of falls. Additional losses of PPN cholinergic neurons may worsen posture and gait control in situations not captured by the current testing conditions. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  16. Computational Modeling in Support of Global Eradication of Infectious Diseases

    Science.gov (United States)

    Eckhoff, Philip A.; Gates, William H., III; Myhrvold, Nathan P.; Wood, Lowell

    2014-07-01

    The past century has seen tremendous advances in global health, with broad reductions in the worldwide burden of infectious disease. Science has fundamentally advanced our understanding of disease etiology and medicine has provided remarkable capabilities to diagnose many syndromes and to target the causative pathogen. The advent and proliferation of antibiotics has dramatically lowered the impact of infections that were once near certain death sentences. Vaccination has provided a route to protect each new birth cohort from pathogens which once killed a substantial fraction of each generation, and in some countries, vaccination coverage has been raised to sufficiently high levels to fully interrupt transmission of major pathogens. There were 7 million deaths among children under 5 years of age in 2010, substantially down from decades past, and even more so in terms of deaths per capita per year of populations at risk. However, the annual rate globally is 1,070 per 100,000, while in developed countries the rate is only 137 per 100,000 (IHME GBD, 2010). Therefore, bringing global rates down to rates already achieved in developed countries represents the huge gains currently available via means such as vaccination and access to modern health care...

  17. An agent-based model on disease management in potato cultivation in the Netherlands

    NARCIS (Netherlands)

    Pacilly, F.C.A.; Hofstede, G.J.; Groot, J.C.J.; Lammerts Van Bueren, E.

    2015-01-01

    In this project the host-pathogen system of potato (Solanum tuberosum) - late blight (Phytophthora infestans) was analysed as a model system to study management of crop-disease interactions. Resistant cultivars play an important role in sustainable management of the disease. We used an agent-based

  18. A microsimulation model for the development and progression of chronic obstructive pulmonary disease

    NARCIS (Netherlands)

    Tan, E.; Boessen, R.; Fishwick, D.; Klein Entink, R.H.; Meijster, T.; Pronk, A.; Van Duuren-Stuurman, B.; Warren, N.

    2016-01-01

    Chronic obstructive pulmonary disease (COPD) is a chronic lung disease that is thought to affect over one million people in Great Britain. The main factor contributing to the development of COPD is tobacco smoke. This paper presents a microsimulation model for the development of COPD, incorporating

  19. A microsimulation model for the development and progression of chronic obstructive pulmonary disease

    NARCIS (Netherlands)

    Tan, E.; Boessen, R.; Fishwick, D.; Klein Entink, R.; Meijster, T.; Pronk, A.; Duuren-Stuurman, B. van; Warren, N.

    2015-01-01

    Chronic obstructive pulmonary disease (COPD) is a chronic lung disease that is thought to affect over one million people in Great Britain. The main factor contributing to the development of COPD is tobacco smoke. This paper presents a microsimulation model for the development of COPD, incorporating

  20. Roles of amino acids in preventing and treating intestinal diseases: recent studies with pig models.

    Science.gov (United States)

    Liu, Yulan; Wang, Xiuying; Hou, Yongqing; Yin, Yulong; Qiu, Yinsheng; Wu, Guoyao; Hu, Chien-An Andy

    2017-08-01

    Animal models are needed to study and understand a human complex disease. Because of their similarities in anatomy, structure, physiology, and pathophysiology, the pig has proven its usefulness in studying human gastrointestinal diseases, such as inflammatory bowel disease, ischemia/reperfusion injury, diarrhea, and cancer. To understand the pathogenesis of these diseases, a number of experimental models generated in pigs are available, for example, through surgical manipulation, chemical induction, microbial infection, and genetic engineering. Our interests have been using amino acids as therapeutics in pig and human disease models. Amino acids not only play an important role in protein biosynthesis, but also exert significant physiological effects in regulating immunity, anti-oxidation, redox regulation, energy metabolism, signal transduction, and animal behavior. Recent studies in pigs have shown that specific dietary amino acids can improve intestinal integrity and function under normal and pathological conditions that protect the host from different diseases. In this review, we summarize several pig models in intestinal diseases and how amino acids can be used as therapeutics in treating pig and human diseases.

  1. Disease management projects and the Chronic CareModel in action: Baseline qualitative research

    NARCIS (Netherlands)

    B.J. Hipple Walters (Bethany); S.A. Adams (Samantha); A.P. Nieboer (Anna); R.A. Bal (Roland)

    2012-01-01

    textabstractBackground: Disease management programs, especially those based on the Chronic Care Model (CCM),are increasingly common in the Netherlands. While disease management programs have beenwell-researched quantitatively and economically, less qualitative research has been done. Theoverall aim

  2. A final size relation for epidemic models of vector-transmitted diseases

    OpenAIRE

    Fred Brauer

    2017-01-01

    We formulate and analyze an age of infection model for epidemics of diseases transmitted by a vector, including the possibility of direct transmission as well. We show how to determine a basic reproduction number. While there is no explicit final size relation as for diseases transmitted directly, we are able to obtain estimates for the final size of the epidemic.

  3. A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock

    Directory of Open Access Journals (Sweden)

    Richard A Bradhurst

    2015-03-01

    Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model

  4. Caffeine, Adenosine Receptors and Estrogen in Toxin Models of Parkinson's Disease

    National Research Council Canada - National Science Library

    Schwarzschild, Michael A; Xu, Kui

    2008-01-01

    Continued progress has been made toward each of the Specific Aims (SAs) 1 and 2 (SA 3 completed) of our research project, Caffeine, adenosine receptors and estrogen in toxin models of Parkinson's disease...

  5. Asymptotic behaviour of a nonlinear model for the geographic diffusion of infections diseases

    International Nuclear Information System (INIS)

    Kirane, M.; Kouachi, S.

    1994-01-01

    In this paper a nonlinear diffusion model for the geographical spread of infective diseases is studied. In addition to proving well-posedness of the associated initial-boundary value problem, the large time behaviour is analyzed. (author). 4 refs

  6. Pulmonary Complications Resulting from Genetic Cardiovascular Disease in Two Rat Models

    Science.gov (United States)

    Underlying cardiovascular disease (CVD) has been considered a risk factor for exacerbation of air pollution health effects. Therefore, rodent models of CVD are increasingly used to examine mechanisms of variation in susceptibility. Pulmonary complications and altered iron homeost...

  7. Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes Afford New Opportunities in Inherited Cardiovascular Disease Modeling

    Directory of Open Access Journals (Sweden)

    Daniel R. Bayzigitov

    2016-01-01

    Full Text Available Fundamental studies of molecular and cellular mechanisms of cardiovascular disease pathogenesis are required to create more effective and safer methods of their therapy. The studies can be carried out only when model systems that fully recapitulate pathological phenotype seen in patients are used. Application of laboratory animals for cardiovascular disease modeling is limited because of physiological differences with humans. Since discovery of induced pluripotency generating induced pluripotent stem cells has become a breakthrough technology in human disease modeling. In this review, we discuss a progress that has been made in modeling inherited arrhythmias and cardiomyopathies, studying molecular mechanisms of the diseases, and searching for and testing drug compounds using patient-specific induced pluripotent stem cell-derived cardiomyocytes.

  8. Modeling human diseases with induced pluripotent stem cells: from 2D to 3D and beyond.

    Science.gov (United States)

    Liu, Chun; Oikonomopoulos, Angelos; Sayed, Nazish; Wu, Joseph C

    2018-03-08

    The advent of human induced pluripotent stem cells (iPSCs) presents unprecedented opportunities to model human diseases. Differentiated cells derived from iPSCs in two-dimensional (2D) monolayers have proven to be a relatively simple tool for exploring disease pathogenesis and underlying mechanisms. In this Spotlight article, we discuss the progress and limitations of the current 2D iPSC disease-modeling platform, as well as recent advancements in the development of human iPSC models that mimic in vivo tissues and organs at the three-dimensional (3D) level. Recent bioengineering approaches have begun to combine different 3D organoid types into a single '4D multi-organ system'. We summarize the advantages of this approach and speculate on the future role of 4D multi-organ systems in human disease modeling. © 2018. Published by The Company of Biologists Ltd.

  9. Modelling the epidemiology of infectious diseases for decision analysis: a primer.

    Science.gov (United States)

    Jit, Mark; Brisson, Marc

    2011-05-01

    The number of economic evaluations related to infectious disease topics has increased over the last 2 decades. However, many such evaluations rely on models that do not take into account unique features of infectious diseases that can affect the estimated value of interventions against them. These include their transmissibility from infected to susceptible individuals, the possibility of acquiring natural immunity following recovery from infection and the uncertainties that arise as a result of their complex natural history and epidemiology. Modellers conducting economic evaluations of infectious disease interventions need to know the main features of different types of infectious disease models, the situations in which they should be applied and the effects of model choices on the cost effectiveness of interventions.

  10. Pulmonary oxidative stress, inflammation and dysregulated iron homeostatis in rat models of cardiovascular disease

    Science.gov (United States)

    Underlying cardiovascular disease (CVD) is considered a risk factor for the exacerbation of air pollution health effects. Therefore, rodent models of CVD are increasingly used to examine mechanisms ofvariation in susceptibility. Pulmonary oxidative stress, inflammation and altere...

  11. A minimal unified model of disease trajectories captures hallmarks of multiple sclerosis

    KAUST Repository

    Kannan, Venkateshan; Kiani, Narsis A.; Piehl, Fredrik; Tegner, Jesper

    2017-01-01

    Multiple Sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) causing demyelination and neurodegeneration leading to accumulation of neurological disability. Here we present a minimal, computational model involving

  12. Organization-and-technological model of medical care delivered to patients with coronary heart disease

    Directory of Open Access Journals (Sweden)

    Popova Y.V.

    2014-09-01

    Full Text Available Organization-and-technological model of medical care delivered to patients with coronary heart disease based on IDEF0 methodology and corresponded with clinical guidelines is presented.

  13. Evaluation of spatio-temporal Bayesian models for the spread of infectious diseases in oil palm.

    Science.gov (United States)

    Denis, Marie; Cochard, Benoît; Syahputra, Indra; de Franqueville, Hubert; Tisné, Sébastien

    2018-02-01

    In the field of epidemiology, studies are often focused on mapping diseases in relation to time and space. Hierarchical modeling is a common flexible and effective tool for modeling problems related to disease spread. In the context of oil palm plantations infected by the fungal pathogen Ganoderma boninense, we propose and compare two spatio-temporal hierarchical Bayesian models addressing the lack of information on propagation modes and transmission vectors. We investigate two alternative process models to study the unobserved mechanism driving the infection process. The models help gain insight into the spatio-temporal dynamic of the infection by identifying a genetic component in the disease spread and by highlighting a spatial component acting at the end of the experiment. In this challenging context, we propose models that provide assumptions on the unobserved mechanism driving the infection process while making short-term predictions using ready-to-use software. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. POMICS: A Simulation Disease Model for Timing Fungicide Applications in Management of Powdery Mildew of Cucurbits.

    Science.gov (United States)

    Sapak, Z; Salam, M U; Minchinton, E J; MacManus, G P V; Joyce, D C; Galea, V J

    2017-09-01

    A weather-based simulation model, called Powdery Mildew of Cucurbits Simulation (POMICS), was constructed to predict fungicide application scheduling to manage powdery mildew of cucurbits. The model was developed on the principle that conditions favorable for Podosphaera xanthii, a causal pathogen of this crop disease, generate a number of infection cycles in a single growing season. The model consists of two components that (i) simulate the disease progression of P. xanthii in secondary infection cycles under natural conditions and (ii) predict the disease severity with application of fungicides at any recurrent disease cycles. The underlying environmental factors associated with P. xanthii infection were quantified from laboratory and field studies, and also gathered from literature. The performance of the POMICS model when validated with two datasets of uncontrolled natural infection was good (the mean difference between simulated and observed disease severity on a scale of 0 to 5 was 0.02 and 0.05). In simulations, POMICS was able to predict high- and low-risk disease alerts. Furthermore, the predicted disease severity was responsive to the number of fungicide applications. Such responsiveness indicates that the model has the potential to be used as a tool to guide the scheduling of judicious fungicide applications.

  15. Using landscape epidemiological models to understand the distribution of chronic wasting disease in the Midwestern USA

    Science.gov (United States)

    Robinson, Stacie J.; Samuel, Michael D.; Rolley, Robert E.; Shelton, Paul

    2013-01-01

    Animal movement across the landscape plays a critical role in the ecology of infectious wildlife diseases. Dispersing animals can spread pathogens between infected areas and naïve populations. While tracking free-ranging animals over the geographic scales relevant to landscape-level disease management is challenging, landscape features that influence gene flow among wildlife populations may also influence the contact rates and disease spread between populations. We used spatial diffusion and barriers to white-tailed deer gene flow, identified through landscape genetics, to model the distribution of chronic wasting disease (CWD) in the infected region of southern Wisconsin and northern Illinois, USA. Our generalized linear model showed that risk of CWD infection declined exponentially with distance from current outbreaks, and inclusion of gene flow barriers dramatically improved fit and predictive power of the model. Our results indicate that CWD is spreading across the Midwestern landscape from these two endemic foci, but spread is strongly influenced by highways and rivers that also reduce deer gene flow. We used our model to plot a risk map, providing important information for CWD management by identifying likely routes of disease spread and providing a tool for prioritizing disease monitoring and containment efforts. The current analysis may serve as a framework for modeling future disease risk drawing on genetic information to investigate barriers to spread and extending management and monitoring beyond currently affected regions.

  16. Modeling the oxygen uptake kinetics during exercise testing of patients with chronic obstructive pulmonary diseases using nonlinear mixed models

    DEFF Research Database (Denmark)

    Baty, Florent; Ritz, Christian; van Gestel, Arnoldus

    2016-01-01

    describe functionality of the R package medrc that extends the framework of the commonly used packages drc and nlme and allows fitting nonlinear mixed effects models for automated nonlinear regression modeling. The methodology was applied to a data set including 6MWT [Formula: see text]O2 kinetics from 61...... patients with chronic obstructive pulmonary disease (disease severity stage II to IV). The mixed effects approach was compared to a traditional curve-by-curve approach. RESULTS: A six-parameter nonlinear regression model was jointly fitted to the set of [Formula: see text]O2 kinetics. Significant...

  17. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications

    OpenAIRE

    Iddamalgoda, Lahiru; Das, Partha S.; Aponso, Achala; Sundararajan, Vijayaraghava S.; Suravajhala, Prashanth; Valadi, Jayaraman K.

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited ...

  18. Analysis of a Mathematical Model of Emerging Infectious Disease Leading to Amphibian Decline

    OpenAIRE

    Dur-e-Ahmad, Muhammad; Imran, Mudassar; Khan, Adnan

    2014-01-01

    We formulate a three-dimensional deterministic model of amphibian larvae population to investigate the cause of extinction due to the infectious disease. The larvae population of the model is subdivided into two classes, exposed and unexposed, depending on their vulnerability to disease. Reproduction ratio ${\\scr R}_{0}$ has been calculated and we have shown that if ${\\scr R}_{0}1$ , we discussed different scenarios under which an infected population can survive or be eliminated using stabili...

  19. Lexis diagram and illness-death model: simulating populations in chronic disease epidemiology.

    Directory of Open Access Journals (Sweden)

    Ralph Brinks

    Full Text Available Chronic diseases impose a tremendous global health problem of the 21st century. Epidemiological and public health models help to gain insight into the distribution and burden of chronic diseases. Moreover, the models may help to plan appropriate interventions against risk factors. To provide accurate results, models often need to take into account three different time-scales: calendar time, age, and duration since the onset of the disease. Incidence and mortality often change with age and calendar time. In many diseases such as, for example, diabetes and dementia, the mortality of the diseased persons additionally depends on the duration of the disease. The aim of this work is to describe an algorithm and a flexible software framework for the simulation of populations moving in an illness-death model that describes the epidemiology of a chronic disease in the face of the different times-scales. We set up a discrete event simulation in continuous time involving competing risks using the freely available statistical software R. Relevant events are birth, the onset (or diagnosis of the disease and death with or without the disease. The Lexis diagram keeps track of the different time-scales. Input data are birth rates, incidence and mortality rates, which can be given as numerical values on a grid. The algorithm manages the complex interplay between the rates and the different time-scales. As a result, for each subject in the simulated population, the algorithm provides the calendar time of birth, the age of onset of the disease (if the subject contracts the disease and the age at death. By this means, the impact of interventions may be estimated and compared.

  20. An Integrated Framework for Process-Driven Model Construction in Disease Ecology and Animal Health

    Directory of Open Access Journals (Sweden)

    Rebecca Mancy

    2017-09-01

    Full Text Available Process models that focus on explicitly representing biological mechanisms are increasingly important in disease ecology and animal health research. However, the large number of process modelling approaches makes it difficult to decide which is most appropriate for a given disease system and research question. Here, we discuss different motivations for using process models and present an integrated conceptual analysis that can be used to guide the construction of infectious disease process models and comparisons between them. Our presentation complements existing work by clarifying the major differences between modelling approaches and their relationship with the biological characteristics of the epidemiological system. We first discuss distinct motivations for using process models in epidemiological research, identifying the key steps in model design and use associated with each. We then present a conceptual framework for guiding model construction and comparison, organised according to key aspects of epidemiological systems. Specifically, we discuss the number and type of disease states, whether to focus on individual hosts (e.g., cows or groups of hosts (e.g., herds or farms, how space or host connectivity affect disease transmission, whether demographic and epidemiological processes are periodic or can occur at any time, and the extent to which stochasticity is important. We use foot-and-mouth disease and bovine tuberculosis in cattle to illustrate our discussion and support explanations of cases in which different models are used to address similar problems. The framework should help those constructing models to structure their approach to modelling decisions and facilitate comparisons between models in the literature.

  1. Contemporary models and prospects of control of parasitic diseases

    Directory of Open Access Journals (Sweden)

    Petričević Saša M.

    2007-01-01

    Full Text Available Economic, social and expert-scientific factors determine activities in connection with the development of the control of parasitic infections in the upcoming period of the 21st century. The primary research activities are directed at studies of the physiological functions of parasites and the ecological relations between the parasite and the host, and all that is undertaken with the objective of securing adequate pharmacotherapy/pharmacoprophylaxis and immunoprophilaxis. As there is a huge expansion in the synthesis of chemical compounds, there is a great number of potential substances for use in the form of a medicine. Along these lines, activities concerning the development of new antiparasitics and/or modification of existing ones are primarily based on securing a quality target spot for its action. Another possibility in the area of research is connected to the problem of resistance of parasites and intensive studies of the biochemical-physiological characteristics of parasites, as well as the development of an active epidemiological-episootiological network for monitoring resistance. In parallel with the development of medicines, the results of investigations of physiological functions of parasites and their mutual relations with their host, are intensely used for the development of immunological control, and the development of vaccines (for example, the development of vaccines for the control of coccidiosis, babesiosis, echinococcosis. The second important approach is related to studies of parasitic zoonoses, the effect of global warming on the epidemiological-episootiological characteristics of parasitic diseases and the selection of resistant animal breeds/hybrids. Animal welfare is also of importance, the perfecting of reliable, rapid and less-costly methods for diagnosing parasitic diseases and the development of in vitro methods for the examination of resistance to antiparasitics.

  2. Alberta Healthy Living Program--a model for successful integration of chronic disease management services.

    Science.gov (United States)

    Morrin, Louise; Britten, Judith; Davachi, Shahnaz; Knight, Holly

    2013-08-01

    The most common presentation of chronic disease is multimorbidity. Disease management strategies are similar across most chronic diseases. Given the prevalence of multimorbidity and the commonality in approaches, fragmented single disease management must be replaced with integrated care of the whole person. The Alberta Healthy Living Program, a community-based chronic disease management program, supports adults with, or at risk for, chronic disease to improve their health and well being. Participants gain confidence and skills in how to manage their chronic disease(s) by learning to understand their health condition, make healthy eating choices, exercise safely and cope emotionally. The program includes 3 service pillars: disease-specific and general health patient education, disease-spanning supervised exercise and Better Choices, Better Health(TM) self-management workshops. Services are delivered in the community by an interprofessional team and can be tailored to target specific diverse and vulnerable populations, such as Aboriginal, ethno-cultural and francophone groups and those experiencing homelessness. Programs may be offered as a partnership between Alberta Health Services, primary care and community organizations. Common standards reduce provincial variation in care, yet maintain sufficient flexibility to meet local and diverse needs and achieve equity in care. The model has been implemented successfully in 108 communities across Alberta. This approach is associated with reduced acute care utilization and improved clinical indicators, and achieves efficiencies through an integrated, disease-spanning patient-centred approach. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  3. Genetic screens in Caenorhabditis elegans models for neurodegenerative diseases

    NARCIS (Netherlands)

    Alvarenga Fernandes Sin, Olga; Michels, Helen; Nollen, Ellen A. A.

    2014-01-01

    Caenorhabditis elegans comprises unique features that make it an attractive model organism in diverse fields of biology. Genetic screens are powerful to identify genes and C. elegans can be customized to forward or reverse genetic screens and to establish gene function. These genetic screens can be

  4. Disease modeling using human induced pluripotent stem cells: lessons from the liver.

    Science.gov (United States)

    Gieseck, Richard L; Colquhoun, Jennifer; Hannan, Nicholas R F

    2015-01-01

    Human pluripotent stem cells (hPSCs) have the capacity to differentiate into any of the hundreds of distinct cell types that comprise the human body. This unique characteristic has resulted in considerable interest in the field of regenerative medicine, given the potential for these cells to be used to protect, repair, or replace diseased, injured, and aged cells within the human body. In addition to their potential in therapeutics, hPSCs can be used to study the earliest stages of human development and to provide a platform for both drug screening and disease modeling using human cells. Recently, the description of human induced pluripotent stem cells (hIPSCs) has allowed the field of disease modeling to become far more accessible and physiologically relevant, as pluripotent cells can be generated from patients of any genetic background. Disease models derived from hIPSCs that manifest cellular disease phenotypes have been established to study several monogenic diseases; furthermore, hIPSCs can be used for phenotype-based drug screens to investigate complex diseases for which the underlying genetic mechanism is unknown. As a result, the use of stem cells as research tools has seen an unprecedented growth within the last decade as researchers look for in vitro disease models which closely mimic in vivo responses in humans. Here, we discuss the beginnings of hPSCs, starting with isolation of human embryonic stem cells, moving into the development and optimization of hIPSC technology, and ending with the application of hIPSCs towards disease modeling and drug screening applications, with specific examples highlighting the modeling of inherited metabolic disorders of the liver. This article is part of a Special Issue entitled Linking transcription to physiology in lipodomics. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

  5. Chronic wasting disease in bank voles: characterisation of the shortest incubation time model for prion diseases.

    Directory of Open Access Journals (Sweden)

    Michele Angelo Di Bari

    2013-03-01

    Full Text Available In order to assess the susceptibility of bank voles to chronic wasting disease (CWD, we inoculated voles carrying isoleucine or methionine at codon 109 (Bv109I and Bv109M, respectively with CWD isolates from elk, mule deer and white-tailed deer. Efficient transmission rate (100% was observed with mean survival times ranging from 156 to 281 days post inoculation. Subsequent passages in Bv109I allowed us to isolate from all CWD sources the same vole-adapted CWD strain (Bv(109ICWD, typified by unprecedented short incubation times of 25-28 days and survival times of ∼35 days. Neuropathological and molecular characterisation of Bv(109ICWD showed that the classical features of mammalian prion diseases were all recapitulated in less than one month after intracerebral inoculation. Bv(109ICWD was characterised by a mild and discrete distribution of spongiosis and relatively low levels of protease-resistant PrP(Sc (PrP(res in the same brain regions. Despite the low PrP(res levels and the short time lapse available for its accumulation, end-point titration revealed that brains from terminally-ill voles contained up to 10(8,4 i.c. ID50 infectious units per gram. Bv(109ICWD was efficiently replicated by protein misfolding cyclic amplification (PMCA and the infectivity faithfully generated in vitro, as demonstrated by the preservation of the peculiar Bv(109ICWD strain features on re-isolation in Bv109I. Overall, we provide evidence that the same CWD strain was isolated in Bv109I from the three-cervid species. Bv(109ICWD showed unique characteristics of "virulence", low PrP(res accumulation and high infectivity, thus providing exceptional opportunities to improve basic knowledge of the relationship between PrP(Sc, neurodegeneration and infectivity.

  6. Models to capture the potential for disease transmission in domestic sheep flocks.

    Science.gov (United States)

    Schley, David; Whittle, Sophie; Taylor, Michael; Kiss, Istvan Zoltan

    2012-09-15

    Successful control of livestock diseases requires an understanding of how they spread amongst animals and between premises. Mathematical models can offer important insight into the dynamics of disease, especially when built upon experimental and/or field data. Here the dynamics of a range of epidemiological models are explored in order to determine which models perform best in capturing real-world heterogeneities at sufficient resolution. Individual based network models are considered together with one- and two-class compartmental models, for which the final epidemic size is calculated as a function of the probability of disease transmission occurring during a given physical contact between two individuals. For numerical results the special cases of a viral disease with a fast recovery rate (foot-and-mouth disease) and a bacterial disease with a slow recovery rate (brucellosis) amongst sheep are considered. Quantitative results from observational studies of physical contact amongst domestic sheep are applied and results from the differently structured flocks (ewes with newborn lambs, ewes with nearly weaned lambs and ewes only) compared. These indicate that the breeding cycle leads to significant changes in the expected basic reproduction ratio of diseases. The observed heterogeneity of contacts amongst animals is best captured by full network simulations, although simple compartmental models describe the key features of an outbreak but, as expected, often overestimate the speed of an outbreak. Here the weights of contacts are heterogeneous, with many low weight links. However, due to the well-connected nature of the networks, this has little effect and differences between models remain small. These results indicate that simple compartmental models can be a useful tool for modelling real-world flocks; their applicability will be greater still for more homogeneously mixed livestock, which could be promoted by higher intensity farming practices. Copyright © 2012

  7. Strategies, models and biomarkers in experimental non-alcoholic fatty liver disease research

    Science.gov (United States)

    Willebrords, Joost; Pereira, Isabel Veloso Alves; Maes, Michaël; Yanguas, Sara Crespo; Colle, Isabelle; Van Den Bossche, Bert; Da silva, Tereza Cristina; Oliveira, Cláudia P; Andraus, Wellington; Alves, Venâncio Avancini Ferreira; Cogliati, Bruno; Vinken, Mathieu

    2015-01-01

    Non-alcoholic fatty liver disease encompasses a spectrum of liver diseases, including simple steatosis, steatohepatitis, liver fibrosis and cirrhosis and hepatocellular carcinoma. Non-alcoholic fatty liver disease is currently the most dominant chronic liver disease in Western countries due to the fact that hepatic steatosis is associated with insulin resistance, type 2 diabetes mellitus, obesity, metabolic syndrome and drug-induced injury. A variety of chemicals, mainly drugs, and diets is known to cause hepatic steatosis in humans and rodents. Experimental non-alcoholic fatty liver disease models rely on the application of a diet or the administration of drugs to laboratory animals or the exposure of hepatic cell lines to these drugs. More recently, genetically modified rodents or zebrafish have been introduced as non-alcoholic fatty liver disease models. Considerable interest now lies in the discovery and development of novel non-invasive biomarkers of non-alcoholic fatty liver disease, with specific focus on hepatic steatosis. Experimental diagnostic biomarkers of non-alcoholic fatty liver disease, such as (epi)genetic parameters and ‘-omics’-based read-outs are still in their infancy, but show great promise. . In this paper, the array of tools and models for the study of liver steatosis is discussed. Furthermore, the current state-of-art regarding experimental biomarkers such as epigenetic, genetic, transcriptomic, proteomic and metabonomic biomarkers will be reviewed. PMID:26073454

  8. Modelling the influence of human behaviour on the spread of infectious diseases: a review.

    Science.gov (United States)

    Funk, Sebastian; Salathé, Marcel; Jansen, Vincent A A

    2010-09-06

    Human behaviour plays an important role in the spread of infectious diseases, and understanding the influence of behaviour on the spread of diseases can be key to improving control efforts. While behavioural responses to the spread of a disease have often been reported anecdotally, there has been relatively little systematic investigation into how behavioural changes can affect disease dynamics. Mathematical models for the spread of infectious diseases are an important tool for investigating and quantifying such effects, not least because the spread of a disease among humans is not amenable to direct experimental study. Here, we review recent efforts to incorporate human behaviour into disease models, and propose that such models can be broadly classified according to the type and source of information which individuals are assumed to base their behaviour on, and according to the assumed effects of such behaviour. We highlight recent advances as well as gaps in our understanding of the interplay between infectious disease dynamics and human behaviour, and suggest what kind of data taking efforts would be helpful in filling these gaps.

  9. Animal models of Alzheimer disease: historical pitfalls and a path forward.

    Science.gov (United States)

    Cavanaugh, Sarah E; Pippin, John J; Barnard, Neal D

    2014-01-01

    Alzheimer disease (AD) is a medically and financially overwhelming condition, and incidence rates are expected to triple by 2050.Despite decades of research in animal models of AD, the disease remains incompletely understood, with few treatment options. This review summarizes historical and current AD research efforts, with emphasis on the disparity between preclinical animal studies and the reality of human disease and how this has impacted clinical trials. Ultimately, we provide a mechanism for shifting the focus of AD research away from animal models to focus primarily on human biology as a means to improve the applicability of research findings to human disease. Implementation of these alternatives may hasten development of improved strategies to prevent, detect, ameliorate, and possibly cure this devastating disease.

  10. Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

    Directory of Open Access Journals (Sweden)

    Nicola A. Wardrop

    2014-11-01

    Full Text Available The application of spatial modelling to epidemiology has increased significantly over the past decade, delivering enhanced understanding of the environmental and climatic factors affecting disease distributions and providing spatially continuous representations of disease risk (predictive maps. These outputs provide significant information for disease control programmes, allowing spatial targeting and tailored interventions. However, several factors (e.g. sampling protocols or temporal disease spread can influence predictive mapping outputs. This paper proposes a conceptual framework which defines several scenarios and their potential impact on resulting predictive outputs, using simulated data to provide an exemplar. It is vital that researchers recognise these scenarios and their influence on predictive models and their outputs, as a failure to do so may lead to inaccurate interpretation of predictive maps. As long as these considerations are kept in mind, predictive mapping will continue to contribute significantly to epidemiological research and disease control planning.

  11. Imaging noradrenergic influence on amyloid pathology in mouse models of Alzheimer's disease

    International Nuclear Information System (INIS)

    Winkeler, A.; Waerzeggers, Y.; Klose, A.; Monfared, P.; Thomas, A.V.; Jacobs, A.H.; Schubert, M.; Heneka, M.T.

    2008-01-01

    Molecular imaging aims towards the non-invasive characterization of disease-specific molecular alterations in the living organism in vivo. In that, molecular imaging opens a new dimension in our understanding of disease pathogenesis, as it allows the non-invasive determination of the dynamics of changes on the molecular level. The imaging technology being employed includes magnetic resonance imaging (MRI) and nuclear imaging as well as optical-based imaging technologies. These imaging modalities are employed together or alone for disease phenotyping, development of imaging-guided therapeutic strategies and in basic and translational research. In this study, we review recent investigations employing positron emission tomography and MRI for phenotyping mouse models of Alzheimers' disease by imaging. We demonstrate that imaging has an important role in the characterization of mouse models of neurodegenerative diseases. (orig.)

  12. Genome editing of human pluripotent stem cells to generate human cellular disease models

    Directory of Open Access Journals (Sweden)

    Kiran Musunuru

    2013-07-01

    Full Text Available Disease modeling with human pluripotent stem cells has come into the public spotlight with the awarding of the Nobel Prize in Physiology or Medicine for 2012 to Drs John Gurdon and Shinya Yamanaka for the discovery that mature cells can be reprogrammed to become pluripotent. This discovery has opened the door for the generation of pluripotent stem cells from individuals with disease and the differentiation of these cells into somatic cell types for the study of disease pathophysiology. The emergence of genome-editing technology over the past few years has made it feasible to generate and investigate human cellular disease models with even greater speed and efficiency. Here, recent technological advances in genome editing, and its utility in human biology and disease studies, are reviewed.

  13. Contextual and individual determinants of periodontal disease: Multilevel analysis based on Andersen's model.

    Science.gov (United States)

    Valente, Maria I B; Vettore, Mario V

    2018-04-01

    To investigate the relationship of contextual and individual factors with periodontal disease in dentate adults and older people using the Andersen's behavioural model. Secondary individual data from 6011 adults and 2369 older people from the Brazilian Oral Health Survey (2010) were combined with contextual data for 27 cities. Attachment loss (AL) categories for each sextant were coded and summed to obtain the periodontal disease measure. The association of predisposing, enabling and need characteristics at city and individual level with periodontal disease was assessed using an adapted version of the Andersen's behavioural model. Multilevel Poisson regression was used to estimate rate ratios (RR) and 95% CIs. Periodontal disease was associated with contextual predisposing (RR 0.93; 95% CI = 0.87-0.99) and enabling factors (RR 0.99; 95% CI = 0.98-0.99) in adults. Contextual predisposing was also associated with periodontal disease in older people (RR 0.82; 95% CI = 0.73-0.92). Individual predisposing (age, sex and schooling) and need characteristics (perceived treatment need) were common predictors of periodontal disease in adults and older people. Periodontal disease was also associated with behaviours in the latter age group. Contextual predisposing factors and individual characteristics influenced periodontal disease experience in adults and older people. Contextual enabling factors were also meaningful determinants of periodontal disease in the former age group. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  14. The Rabbit as a Model for Studying Lung Disease and Stem Cell Therapy

    Directory of Open Access Journals (Sweden)

    Nurfatin Asyikhin Kamaruzaman

    2013-01-01

    Full Text Available No single animal model can reproduce all of the human features of both acute and chronic lung diseases. However, the rabbit is a reliable model and clinically relevant facsimile of human disease. The similarities between rabbits and humans in terms of airway anatomy and responses to inflammatory mediators highlight the value of this species in the investigation of lung disease pathophysiology and in the development of therapeutic agents. The inflammatory responses shown by the rabbit model, especially in the case of asthma, are comparable with those that occur in humans. The allergic rabbit model has been used extensively in drug screening tests, and this model and humans appear to be sensitive to similar drugs. In addition, recent studies have shown that the rabbit serves as a good platform for cell delivery for the purpose of stem-cell-based therapy.

  15. A Comparison between Two Simulation Models for Spread of Foot-and-Mouth Disease

    DEFF Research Database (Denmark)

    Hisham Beshara Halasa, Tariq; Boklund, Anette; Stockmarr, Anders

    2014-01-01

    Two widely used simulation models of foot-and-mouth disease (FMD) were used in order to compare the models' predictions in term of disease spread, consequence, and the ranking of the applied control strategies, and to discuss the effect of the way disease spread is modeled on the predicted outcomes...... of each model. The DTU-DADS (version 0.100), and ISP (version 2.001.11) were used to simulate a hypothetical spread of FMD in Denmark. Actual herd type, movements, and location data in the period 1st October 2006 and 30th September 2007 was used. The models simulated the spread of FMD using 3 different...... areas and 1,000 in low density swine areas, and 1,000 sheep herds. Generally, DTU-DADS predicted larger, longer duration and costlier epidemics than ISP, except when epidemics started in cattle herds located in high density cattle areas. ISP supported suppressive vaccination rather than pre...

  16. Systemic Character of Legionnaires’ Disease – A Murine Model

    Directory of Open Access Journals (Sweden)

    Marina Šantić

    2003-01-01

    Full Text Available In contrast to lung infection caused by Legionella pneumophila, little is known about the pathogenesis of this disease in other organs. In this study, we analyzed the number of colony forming units (CFU of legionellae not only in lungs but also in EDTA plasma, liver, spleen and kidneys. The number of CFU was determined 2, 24, 48, 72 and 168 h after intratracheal inoculation. Results showed that the inflammatory response was mostly pronounced in lungs. Legionellae, however, were also found in EDTA plasma and all the other investigated organs. The duration of infection was most protracted in lungs, with persistence for at least 168 h. In the remaining organs, legionellae were found for a maximum of 72 h after inoculation. Besides the culture methods used for detection of CFU we also used LightCycler (LC PCR to confirm the presence of bacteria in the blood of intratracheally infected mice. By this method the bacterial DNA could be detected during the first two days of post infection.

  17. Introducing vaccination against serogroup B meningococcal disease: an economic and mathematical modelling study of potential impact.

    Science.gov (United States)

    Christensen, Hannah; Hickman, Matthew; Edmunds, W John; Trotter, Caroline L

    2013-05-28

    Meningococcal disease remains an important cause of morbidity and mortality worldwide. The first broadly effective vaccine against group B disease (which causes considerable meningococcal disease in Europe, the Americas and Australasia) was licensed in the EU in January 2013; our objective was to estimate the potential impact of introducing such a vaccine in England. We developed two models to estimate the impact of introducing a new 'MenB' vaccine. The cohort model assumes the vaccine protects against disease only; the transmission dynamic model also allows the vaccine to protect against carriage (accounting for herd effects). We used these, and economic models, to estimate the case reduction and cost-effectiveness of a number of different vaccine strategies. We estimate 27% of meningococcal disease cases could be prevented over the lifetime of an English birth cohort by vaccinating infants at 2,3,4 and 12 months of age with a vaccine that prevents disease only; this strategy could be cost-effective at £9 per vaccine dose. Substantial reductions in disease (71%) can be produced after 10 years by routinely vaccinating infants in combination with a large-scale catch-up campaign, using a vaccine which protects against carriage as well as disease; this could be cost-effective at £17 per vaccine dose. New 'MenB' vaccines could substantially reduce disease in England and be cost-effective if competitively priced, particularly if the vaccines can prevent carriage as well as disease. These results are relevant to other countries, with a similar epidemiology to England, considering the introduction of a new 'MenB' vaccine. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Non-alcoholic fatty liver disease (NAFLD) models in drug discovery.

    Science.gov (United States)

    Cole, Banumathi K; Feaver, Ryan E; Wamhoff, Brian R; Dash, Ajit

    2018-02-01

    The progressive disease spectrum of non-alcoholic fatty liver disease (NAFLD), which includes non-alcoholic steatohepatitis (NASH), is a rapidly emerging public health crisis with no approved therapy. The diversity of various therapies under development highlights the lack of consensus around the most effective target, underscoring the need for better translatable preclinical models to study the complex progressive disease and effective therapies. Areas covered: This article reviews published literature of various mouse models of NASH used in preclinical studies, as well as complex organotypic in vitro and ex vivo liver models being developed. It discusses translational challenges associated with both kinds of models, and describes some of the studies that validate their application in NAFLD. Expert opinion: Animal models offer advantages of understanding drug distribution and effects in a whole body context, but are limited by important species differences. Human organotypic in vitro and ex vivo models with physiological relevance and translatability need to be used in a tiered manner with simpler screens. Leveraging newer technologies, like metabolomics, proteomics, and transcriptomics, and the future development of validated disease biomarkers will allow us to fully utilize the value of these models to understand disease and evaluate novel drugs in isolation or combination.

  19. Clozapine and GABA transmission in schizophrenia disease models: establishing principles to guide treatments.

    Science.gov (United States)

    O'Connor, William T; O'Shea, Sean D

    2015-06-01

    Schizophrenia disease models are necessary to elucidate underlying changes and to establish new therapeutic strategies towards a stage where drug efficacy in schizophrenia (against all classes of symptoms) can be predicted. Here we summarise the evidence for a GABA dysfunction in schizophrenia and review the functional neuroanatomy of five pathways implicated in schizophrenia, namely the mesocortical, mesolimbic, ventral striopallidal, dorsal striopallidal and perforant pathways including the role of local GABA transmission and we describe the effect of clozapine on local neurotransmitter release. This review also evaluates psychotropic drug-induced, neurodevelopmental and environmental disease models including their compatibility with brain microdialysis. The validity of disease models including face, construct, etiological and predictive validity and how these models constitute theories about this illness is also addressed. A disease model based on the effect of the abrupt withdrawal of clozapine on GABA release is also described. The review concludes that while no single animal model is entirely successful in reproducing schizophreniform symptomatology, a disease model based on an ability to prevent and/or reverse the abrupt clozapine discontinuation-induced changes in GABA release in brain regions implicated in schizophrenia may be useful for hypothesis testing and for in vivo screening of novel ligands not limited to a single pharmacological class. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. A Precision Medicine Initiative for Alzheimer's disease: the road ahead to biomarker-guided integrative disease modeling.

    Science.gov (United States)

    Hampel, H; O'Bryant, S E; Durrleman, S; Younesi, E; Rojkova, K; Escott-Price, V; Corvol, J-C; Broich, K; Dubois, B; Lista, S

    2017-04-01

    After intense scientific exploration and more than a decade of failed trials, Alzheimer's disease (AD) remains a fatal global epidemic. A traditional research and drug development paradigm continues to target heterogeneous late-stage clinically phenotyped patients with single 'magic bullet' drugs. Here, we propose that it is time for a paradigm shift towards the implementation of precision medicine (PM) for enhanced risk screening, detection, treatment, and prevention of AD. The overarching structure of how PM for AD can be achieved will be provided through the convergence of breakthrough technological advances, including big data science, systems biology, genomic sequencing, blood-based biomarkers, integrated disease modeling and P4 medicine. It is hypothesized that deconstructing AD into multiple genetic and biological subsets existing within this heterogeneous target population will provide an effective PM strategy for treating individual patients with the specific agent(s) that are likely to work best based on the specific individual biological make-up. The Alzheimer's Precision Medicine Initiative (APMI) is an international collaboration of leading interdisciplinary clinicians and scientists devoted towards the implementation of PM in Neurology, Psychiatry and Neuroscience. It is hypothesized that successful realization of PM in AD and other neurodegenerative diseases will result in breakthrough therapies, such as in oncology, with optimized safety profiles, better responder rates and treatment responses, particularly through biomarker-guided early preclinical disease-stage clinical trials.

  1. DISEASES

    DEFF Research Database (Denmark)

    Pletscher-Frankild, Sune; Pallejà, Albert; Tsafou, Kalliopi

    2015-01-01

    Text mining is a flexible technology that can be applied to numerous different tasks in biology and medicine. We present a system for extracting disease-gene associations from biomedical abstracts. The system consists of a highly efficient dictionary-based tagger for named entity recognition...... of human genes and diseases, which we combine with a scoring scheme that takes into account co-occurrences both within and between sentences. We show that this approach is able to extract half of all manually curated associations with a false positive rate of only 0.16%. Nonetheless, text mining should...... not stand alone, but be combined with other types of evidence. For this reason, we have developed the DISEASES resource, which integrates the results from text mining with manually curated disease-gene associations, cancer mutation data, and genome-wide association studies from existing databases...

  2. A model to predict multivessel coronary artery disease from the exercise thallium-201 stress test

    International Nuclear Information System (INIS)

    Pollock, S.G.; Abbott, R.D.; Boucher, C.A.; Watson, D.D.; Kaul, S.

    1991-01-01

    The aim of this study was to (1) determine whether nonimaging variables add to the diagnostic information available from exercise thallium-201 images for the detection of multivessel coronary artery disease; and (2) to develop a model based on the exercise thallium-201 stress test to predict the presence of multivessel disease. The study populations included 383 patients referred to the University of Virginia and 325 patients referred to the Massachusetts General Hospital for evaluation of chest pain. All patients underwent both cardiac catheterization and exercise thallium-201 stress testing between 1978 and 1981. In the University of Virginia cohort, at each level of thallium-201 abnormality (no defects, one defect, more than one defect), ST depression and patient age added significantly in the detection of multivessel disease. Logistic regression analysis using data from these patients identified three independent predictors of multivessel disease: initial thallium-201 defects, ST depression, and age. A model was developed to predict multivessel disease based on these variables. As might be expected, the risk of multivessel disease predicted by the model was similar to that actually observed in the University of Virginia population. More importantly, however, the model was accurate in predicting the occurrence of multivessel disease in the unrelated population studied at the Massachusetts General Hospital. It is, therefore, concluded that (1) nonimaging variables (age and exercise-induced ST depression) add independent information to thallium-201 imaging data in the detection of multivessel disease; and (2) a model has been developed based on the exercise thallium-201 stress test that can accurately predict the probability of multivessel disease in other populations

  3. Towards a Unified Theory of Health-Disease: I. Health as a complex model-object

    Directory of Open Access Journals (Sweden)

    Naomar Almeida-Filho

    2013-06-01

    Full Text Available Theory building is one of the most crucial challenges faced by basic, clinical and population research, which form the scientific foundations of health practices in contemporary societies. The objective of the study is to propose a Unified Theory of Health-Disease as a conceptual tool for modeling health-disease-care in the light of complexity approaches. With this aim, the epistemological basis of theoretical work in the health field and concepts related to complexity theory as concerned to health problems are discussed. Secondly, the concepts of model-object, multi-planes of occurrence, modes of health and disease-illness-sickness complex are introduced and integrated into a unified theoretical framework. Finally, in the light of recent epistemological developments, the concept of Health-Disease-Care Integrals is updated as a complex reference object fit for modeling health-related processes and phenomena.

  4. Cardiovascular Disease Modeling Using Patient-Specific Induced Pluripotent Stem Cells

    Directory of Open Access Journals (Sweden)

    Atsushi Tanaka

    2015-08-01

    Full Text Available The generation of induced pluripotent stem cells (iPSCs has opened up a new scientific frontier in medicine. This technology has made it possible to obtain pluripotent stem cells from individuals with genetic disorders. Because iPSCs carry the identical genetic anomalies related to those disorders, iPSCs are an ideal platform for medical research. The pathophysiological cellular phenotypes of genetically heritable heart diseases such as arrhythmias and cardiomyopathies, have been modeled on cell culture dishes using disease-specific iPSC-derived cardiomyocytes. These model systems can potentially provide new insights into disease mechanisms and drug discoveries. This review focuses on recent progress in cardiovascular disease modeling using iPSCs, and discusses problems and future perspectives concerning their use.

  5. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    Directory of Open Access Journals (Sweden)

    Cécile Aenishaenslin

    Full Text Available Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or

  6. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    Science.gov (United States)

    Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

    2015-01-01

    Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector

  7. Mathematical Modeling of Protein Misfolding Mechanisms in Neurological Diseases: A Historical Overview.

    Science.gov (United States)

    Carbonell, Felix; Iturria-Medina, Yasser; Evans, Alan C

    2018-01-01

    Protein misfolding refers to a process where proteins become structurally abnormal and lose their specific 3-dimensional spatial configuration. The histopathological presence of misfolded protein (MP) aggregates has been associated as the primary evidence of multiple neurological diseases, including Prion diseases, Alzheimer's disease, Parkinson's disease, and Creutzfeldt-Jacob disease. However, the exact mechanisms of MP aggregation and propagation, as well as their impact in the long-term patient's clinical condition are still not well understood. With this aim, a variety of mathematical models has been proposed for a better insight into the kinetic rate laws that govern the microscopic processes of protein aggregation. Complementary, another class of large-scale models rely on modern molecular imaging techniques for describing the phenomenological effects of MP propagation over the whole brain. Unfortunately, those neuroimaging-based studies do not take full advantage of the tremendous capabilities offered by the chemical kinetics modeling approach. Actually, it has been barely acknowledged that the vast majority of large-scale models have foundations on previous mathematical approaches that describe the chemical kinetics of protein replication and propagation. The purpose of the current manuscript is to present a historical review about the development of mathematical models for describing both microscopic processes that occur during the MP aggregation and large-scale events that characterize the progression of neurodegenerative MP-mediated diseases.

  8. Route prediction model of infectious diseases for 2018 Winter Olympics in Korea

    International Nuclear Information System (INIS)

    Kim, Eungyeong; Lee, Seok; Byun, Young Tae; Kim, Jae Hun; Lee, Taikjin; Lee, Hyuk-jae

    2014-01-01

    There are many types of respiratory infectious diseases caused by germs, virus, mycetes and parasites. Researchers recently have tried to develop mathematical models to predict the epidemic of infectious diseases. However, with the development of ground transportation system in modern society, the spread of infectious diseases became faster and more complicated in terms of the speed and the pathways. The route of infectious diseases during Vancouver Olympics was predicted based on the Susceptible-Infectious-Recovered (SIR) model. In this model only the air traffic as an essential factor for the intercity migration of infectious diseases was involved. Here, we propose a multi-city transmission model to predict the infection route during 2018 Winter Olympics in Korea based on the pre-existing SIR model. Various types of transportation system such as a train, a car, a bus, and an airplane for the interpersonal contact in both inter- and intra-city are considered. Simulation is performed with assumptions and scenarios based on realistic factors including demographic, transportation and diseases data in Korea. Finally, we analyze an economic profit and loss caused by the variation of the number of tourists during the Olympics

  9. Route prediction model of infectious diseases for 2018 Winter Olympics in Korea

    Science.gov (United States)

    Kim, Eungyeong; Lee, Seok; Byun, Young Tae; Kim, Jae Hun; Lee, Hyuk-jae; Lee, Taikjin

    2014-03-01

    There are many types of respiratory infectious diseases caused by germs, virus, mycetes and parasites. Researchers recently have tried to develop mathematical models to predict the epidemic of infectious diseases. However, with the development of ground transportation system in modern society, the spread of infectious diseases became faster and more complicated in terms of the speed and the pathways. The route of infectious diseases during Vancouver Olympics was predicted based on the Susceptible-Infectious-Recovered (SIR) model. In this model only the air traffic as an essential factor for the intercity migration of infectious diseases was involved. Here, we propose a multi-city transmission model to predict the infection route during 2018 Winter Olympics in Korea based on the pre-existing SIR model. Various types of transportation system such as a train, a car, a bus, and an airplane for the interpersonal contact in both inter- and intra-city are considered. Simulation is performed with assumptions and scenarios based on realistic factors including demographic, transportation and diseases data in Korea. Finally, we analyze an economic profit and loss caused by the variation of the number of tourists during the Olympics.

  10. Infectious disease in cervids of North America: data, models, and management challenges.

    Science.gov (United States)

    Conner, Mary Margaret; Ebinger, Michael Ryan; Blanchong, Julie Anne; Cross, Paul Chafee

    2008-01-01

    Over the past two decades there has been a steady increase in the study and management of wildlife diseases. This trend has been driven by the perception of an increase in emerging zoonotic diseases and the recognition that wildlife can be a critical factor for controlling infectious diseases in domestic animals. Cervids are of recent concern because, as a group, they present a number of unique challenges. Their close ecological and phylogenetic relationship to livestock species places them at risk for receiving infections from, and reinfecting livestock. In addition, cervids are an important resource; revenue from hunting and viewing contribute substantially to agency budgets and local economies. A comprehensive coverage of infectious diseases in cervids is well beyond the scope of this chapter. In North America alone there are a number of infectious diseases that can potentially impact cervid populations, but for most of these, management is not feasible or the diseases are only a potential or future concern. We focus this chapter on three diseases that are of major management concern and the center of most disease research for cervids in North America: bovine tuberculosis, chronic wasting disease, and brucellosis. We discuss the available data and recent advances in modeling and management of these diseases.

  11. Pharmacological Evaluation of the SCID T Cell Transfer Model of Colitis: As a Model of Crohn's Disease

    Directory of Open Access Journals (Sweden)

    Thomas Lindebo Holm

    2012-01-01

    Full Text Available Animal models are important tools in the development of new drug candidates against the inflammatory bowel diseases (IBDs Crohn's disease and ulcerative colitis. In order to increase the translational value of these models, it is important to increase knowledge relating to standard drugs. Using the SCID adoptive transfer colitis model, we have evaluated the effect of currently used IBD drugs and IBD drug candidates, that is, anti-TNF-α, TNFR-Fc, anti-IL-12p40, anti-IL-6, CTLA4-Ig, anti-α4β7 integrin, enrofloxacin/metronidazole, and cyclosporine. We found that anti-TNF-α, antibiotics, anti-IL-12p40, anti-α4β7 integrin, CTLA4-Ig, and anti-IL-6 effectively prevented onset of colitis, whereas TNFR-Fc and cyclosporine did not. In intervention studies, antibiotics, anti-IL-12p40, and CTLA4-Ig induced remission, whereas the other compounds did not. The data suggest that the adoptive transfer model and the inflammatory bowel diseases have some main inflammatory pathways in common. The finding that some well-established IBD therapeutics do not have any effect in the model highlights important differences between the experimental model and the human disease.

  12. Induced Pluripotent Stem Cell Therapies for Degenerative Disease of the Outer Retina: Disease Modeling and Cell Replacement.

    Science.gov (United States)

    Di Foggia, Valentina; Makwana, Priyanka; Ali, Robin R; Sowden, Jane C

    2016-06-01

    Stem cell therapies are being explored as potential treatments for retinal disease. How to replace neurons in a degenerated retina presents a continued challenge for the regenerative medicine field that, if achieved, could restore sight. The major issues are: (i) the source and availability of donor cells for transplantation; (ii) the differentiation of stem cells into the required retinal cells; and (iii) the delivery, integration, functionality, and survival of new cells in the host neural network. This review considers the use of induced pluripotent stem cells (iPSC), currently under intense investigation, as a platform for cell transplantation therapy. Moreover, patient-specific iPSC are being developed for autologous cell transplantation and as a tool for modeling specific retinal diseases, testing gene therapies, and drug screening.

  13. The interaction of host genetics and disease processes in chronic livestock disease: a simulation model of ovine footrot.

    Science.gov (United States)

    Russell, V N L; Green, L E; Bishop, S C; Medley, G F

    2013-03-01

    A stochastic, individual-based, simulation model of footrot in a flock of 200 ewes was developed that included flock demography, disease processes, host genetic variation for traits influencing infection and disease processes, and bacterial contamination of the environment. Sensitivity analyses were performed using ANOVA to examine the contribution of unknown parameters to outcome variation. The infection rate and bacterial death rate were the most significant factors determining the observed prevalence of footrot, as well as the heritability of resistance. The dominance of infection parameters in determining outcomes implies that observational data cannot be used to accurately estimate the strength of genetic control of underlying traits describing the infection process, i.e. resistance. Further work will allow us to address the potential for genetic selection to control ovine footrot. Copyright © 2012 Elsevier B.V. All rights reserved.

  14. Analysis of the cartilage proteome from three different mouse models of genetic skeletal diseases reveals common and discrete disease signatures

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    Peter A. Bell

    2013-06-01

    Pseudoachondroplasia and multiple epiphyseal dysplasia are genetic skeletal diseases resulting from mutations in cartilage structural proteins. Electron microscopy and immunohistochemistry previously showed that the appearance of the cartilage extracellular matrix (ECM in targeted mouse models of these diseases is disrupted; however, the precise changes in ECM organization and the pathological consequences remain unknown. Our aim was to determine the effects of matrilin-3 and COMP mutations on the composition and extractability of ECM components to inform how these detrimental changes might influence cartilage organization and degeneration. Cartilage was sequentially extracted using increasing denaturants and the extraction profiles of specific proteins determined using SDS-PAGE/Western blotting. Furthermore, the relative composition of protein pools was determined using mass spectrometry for a non-biased semi-quantitative analysis. Western blotting revealed changes in the extraction of matrilins, COMP and collagen IX in mutant cartilage. Mass spectrometry confirmed quantitative changes in the extraction of structural and non-structural ECM proteins, including proteins with roles in cellular processes such as protein folding and trafficking. In particular, genotype-specific differences in the extraction of collagens XII and XIV and tenascins C and X were identified; interestingly, increased expression of several of these genes has recently been implicated in susceptibility and/or progression of murine osteoarthritis. We demonstrated that mutation of matrilin-3 and COMP caused changes in the extractability of other cartilage proteins and that proteomic analyses of Matn3 V194D, Comp T585M and Comp DelD469 mouse models revealed both common and discrete disease signatures that provide novel insight into skeletal disease mechanisms and cartilage degradation.

  15. The Dynamics of an HIV/AIDS Model with Screened Disease Carriers

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    S. D. Hove-Musekwa

    2009-01-01

    Full Text Available The presence of carriers usually complicates the dynamics and prevention of a disease. They are not recognized as disease cases themselves unless they are screened and they usually spread the infection without them being aware. We argue that this has been one of the major causes of the spread of human immunodeficiency virus (HIV. We propose, in this paper, a model for the heterogeneous transmission of HIV/acquired immunodeficiency syndrome in the presence of disease carriers. The model allows us to assess the role of screening, as an intervention program that can slow the epidemic. A threshold value ψ*, for the screening rate is obtained. It is shown numerically that if 80% or more of the carrier population is screened, the epidemic can be contained. The qualitative analysis is done in terms of the model reproduction number R. The model has two equilibria, the disease free equilibrium and a unique endemic equilibrium. The disease free equilibrium is globally stable of R  1. A detailed discussion of the model reproduction number is given and numerical simulations are done to show the role of some of the important model parameters.

  16. An image-based model of brain volume biomarker changes in Huntington's disease.

    Science.gov (United States)

    Wijeratne, Peter A; Young, Alexandra L; Oxtoby, Neil P; Marinescu, Razvan V; Firth, Nicholas C; Johnson, Eileanoir B; Mohan, Amrita; Sampaio, Cristina; Scahill, Rachael I; Tabrizi, Sarah J; Alexander, Daniel C

    2018-05-01

    Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages. We employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides. The model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross-validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow-up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers. We used a data-driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event-based model, to provide new insight into Huntington's disease progression and to support fine-grained patient stratification for future precision medicine in Huntington's disease.

  17. How predictive quantitative modelling of tissue organisation can inform liver disease pathogenesis.

    Science.gov (United States)

    Drasdo, Dirk; Hoehme, Stefan; Hengstler, Jan G

    2014-10-01

    From the more than 100 liver diseases described, many of those with high incidence rates manifest themselves by histopathological changes, such as hepatitis, alcoholic liver disease, fatty liver disease, fibrosis, and, in its later stages, cirrhosis, hepatocellular carcinoma, primary biliary cirrhosis and other disorders. Studies of disease pathogeneses are largely based on integrating -omics data pooled from cells at different locations with spatial information from stained liver structures in animal models. Even though this has led to significant insights, the complexity of interactions as well as the involvement of processes at many different time and length scales constrains the possibility to condense disease processes in illustrations, schemes and tables. The combination of modern imaging modalities with image processing and analysis, and mathematical models opens up a promising new approach towards a quantitative understanding of pathologies and of disease processes. This strategy is discussed for two examples, ammonia metabolism after drug-induced acute liver damage, and the recovery of liver mass as well as architecture during the subsequent regeneration process. This interdisciplinary approach permits integration of biological mechanisms and models of processes contributing to disease progression at various scales into mathematical models. These can be used to perform in silico simulations to promote unravelling the relation between architecture and function as below illustrated for liver regeneration, and bridging from the in vitro situation and animal models to humans. In the near future novel mechanisms will usually not be directly elucidated by modelling. However, models will falsify hypotheses and guide towards the most informative experimental design. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

  18. Using the gravity model to estimate the spatial spread of vector-borne diseases

    NARCIS (Netherlands)

    Barrios, J.M.; Verstraeten, W.W.; Maes, P.; Aerts, J.; Farifteh, J.; Coppin, P.

    2012-01-01

    The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the

  19. An integrated chronic disease management model: a diagonal approach to health system strengthening in South Africa.

    Science.gov (United States)

    Mahomed, Ozayr Haroon; Asmall, Shaidah; Freeman, Melvyn

    2014-11-01

    The integrated chronic disease management model provides a systematic framework for creating a fundamental change in the orientation of the health system. This model adopts a diagonal approach to health system strengthening by establishing a service-linked base to training, supervision, and the opportunity to try out, assess, and implement integrated interventions.

  20. Long-Term Adult Feline Liver Organoid Cultures for Disease Modeling of Hepatic Steatosis

    NARCIS (Netherlands)

    Kruitwagen, H.S. (Hedwig S.); Oosterhoff, L.A. (Loes A.); Vernooij, I.G.W.H. (Ingrid G.W.H.); Schrall, I.M. (Ingrid M.); M.E. van Wolferen (Monique); Bannink, F. (Farah); Roesch, C. (Camille); van Uden, L. (Lisa); Molenaar, M.R. (Martijn R.); J.B. Helms (J. Bernd); G.C.M. Grinwis (Guy C.); M.M.A. Verstegen (Monique); L.J.W. van der Laan (Luc); M. Huch (Meritxell); N. Geijsen (Niels); R.G.J. Vries (Robert); H.C. Clevers (Hans); J. Rothuizen (J.); B.A. Schotanus (Baukje A.); C. Penning (Corine); B. Spee (B.)

    2017-01-01

    textabstractHepatic steatosis is a highly prevalent liver disease, yet research is hampered by the lack of tractable cellular and animal models. Steatosis also occurs in cats, where it can cause severe hepatic failure. Previous studies demonstrate the potential of liver organoids for modeling

  1. Repeated holdout Cross-Validation of Model to Estimate Risk of Lyme Disease by Landscape Attributes

    Science.gov (United States)

    We previously modeled Lyme disease (LD) risk at the landscape scale; here we evaluate the model's overall goodness-of-fit using holdout validation. Landscapes were characterized within road-bounded analysis units (AU). Observed LD cases (obsLD) were ascertained per AU. Data were ...

  2. Modeling congenital disease and inborn errors of development in Drosophila melanogaster

    Science.gov (United States)

    Moulton, Matthew J.; Letsou, Anthea

    2016-01-01

    ABSTRACT Fly models that faithfully recapitulate various aspects of human disease and human health-related biology are being used for research into disease diagnosis and prevention. Established and new genetic strategies in Drosophila have yielded numerous substantial successes in modeling congenital disorders or inborn errors of human development, as well as neurodegenerative disease and cancer. Moreover, although our ability to generate sequence datasets continues to outpace our ability to analyze these datasets, the development of high-throughput analysis platforms in Drosophila has provided access through the bottleneck in the identification of disease gene candidates. In this Review, we describe both the traditional and newer methods that are facilitating the incorporation of Drosophila into the human disease discovery process, with a focus on the models that have enhanced our understanding of human developmental disorders and congenital disease. Enviable features of the Drosophila experimental system, which make it particularly useful in facilitating the much anticipated move from genotype to phenotype (understanding and predicting phenotypes directly from the primary DNA sequence), include its genetic tractability, the low cost for high-throughput discovery, and a genome and underlying biology that are highly evolutionarily conserved. In embracing the fly in the human disease-gene discovery process, we can expect to speed up and reduce the cost of this process, allowing experimental scales that are not feasible and/or would be too costly in higher eukaryotes. PMID:26935104

  3. Rasagiline ameliorates olfactory deficits in an alpha-synuclein mouse model of Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Géraldine H Petit

    Full Text Available Impaired olfaction is an early pre-motor symptom of Parkinson's disease. The neuropathology underlying olfactory dysfunction in Parkinson's disease is unknown, however α-synuclein accumulation/aggregation and altered neurogenesis might play a role. We characterized olfactory deficits in a transgenic mouse model of Parkinson's disease expressing human wild-type α-synuclein under the control of the mouse α-synuclein promoter. Preliminary clinical observations suggest that rasagiline, a monoamine oxidase-B inhibitor, improves olfaction in Parkinson's disease. We therefore examined whether rasagiline ameliorates olfactory deficits in this Parkinson's disease model and investigated the role of olfactory bulb neurogenesis. α-Synuclein mice were progressively impaired in their ability to detect odors, to discriminate between odors, and exhibited alterations in short-term olfactory memory. Rasagiline treatment rescued odor detection and odor discrimination abilities. However, rasagiline did not affect short-term olfactory memory. Finally, olfactory changes were not coupled to alterations in olfactory bulb neurogenesis. We conclude that rasagiline reverses select olfactory deficits in a transgenic mouse model of Parkinson's disease. The findings correlate with preliminary clinical observations suggesting that rasagiline ameliorates olfactory deficits in Parkinson's disease.

  4. Relative risk estimation of Chikungunya disease in Malaysia: An analysis based on Poisson-gamma model

    Science.gov (United States)

    Samat, N. A.; Ma'arof, S. H. Mohd Imam

    2015-05-01

    Disease mapping is a method to display the geographical distribution of disease occurrence, which generally involves the usage and interpretation of a map to show the incidence of certain diseases. Relative risk (RR) estimation is one of the most important issues in disease mapping. This paper begins by providing a brief overview of Chikungunya disease. This is followed by a review of the classical model used in disease mapping, based on the standardized morbidity ratio (SMR), which we then apply to our Chikungunya data. We then fit an extension of the classical model, which we refer to as a Poisson-Gamma model, when prior distributions for the relative risks are assumed known. Both results are displayed and compared using maps and we reveal a smoother map with fewer extremes values of estimated relative risk. The extensions of this paper will consider other methods that are relevant to overcome the drawbacks of the existing methods, in order to inform and direct government strategy for monitoring and controlling Chikungunya disease.

  5. A central role for TOR signalling in a yeast model for juvenile CLN3 disease

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    Michael E. Bond

    2015-11-01

    Full Text Available Yeasts provide an excellent genetically tractable eukaryotic system for investigating the function of genes in their biological context, and are especially relevant for those conserved genes that cause disease. We study the role of btn1, the orthologue of a human gene that underlies an early onset neurodegenerative disease (juvenile CLN3 disease, neuronal ceroid lipofuscinosis (NCLs or Batten disease in the fission yeast Schizosaccharomyces pombe. A global screen for genetic interactions with btn1 highlighted a conserved key signalling hub in which multiple components functionally relate to this conserved disease gene. This signalling hub includes two major mitogen-activated protein kinase (MAPK cascades, and centers on the Tor kinase complexes TORC1 and TORC2. We confirmed that yeast cells modelling CLN3 disease exhibit features consistent with dysfunction in the TORC pathways, and showed that modulating TORC function leads to a comprehensive rescue of defects in this yeast disease model. The same pathways may be novel targets in the development of therapies for the NCLs and related diseases.

  6. Lack of miRNA misregulation at early pathological stages in Drosophila neurodegenerative disease models

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    Anita eReinhardt

    2012-10-01

    Full Text Available Late onset neurodegenerative diseases represent a major public health concern as the population in many countries ages. Both frequent diseases such as Alzheimer disease (AD, 14% incidence for 80-84 year old Europeans or Parkinson disease (PD, 1.4% prevalence for > 55 years old share, with other low-incidence neurodegenerative pathologies such as spinocerebellar ataxias (SCAs, 0.01% prevalence and frontotemporal lobar degeneration (FTLD, 0.02% prevalence, a lack of efficient treatment in spite of important research efforts. Besides significant progress, studies with animal models have revealed unexpected complexities in the degenerative process, emphasizing a need to better understand the underlying pathological mechanisms. Recently, microRNAs, a class of small regulatory non-coding RNAs, have been implicated in some neurodegenerative diseases. The current data supporting a role of miRNAs in PD, tauopathies, dominant ataxias and FTLD will first be discussed to emphasize the different levels of the pathological processes which may be affected by miRNAs. To investigate a potential involvement of miRNA dysregulation in the early stages of these neurodegenerative diseases we have used Drosophila models for 7 diseases (PD, 3 FTLD, 3 dominant ataxias that recapitulate many features of the human diseases. We performed deep sequencing of head small RNAs after 3 days of pathological protein expression in the fly head neurons. We found no evidence for a statistically significant difference in miRNA expression in this early stage of the pathological process. In addition, we could not identify small non coding CAG repeat RNAs (sCAG in polyQ disease models. Thus our data suggest that transcriptional deregulation of miRNAs or sCAG is unlikely to play a significant role in the initial stages of neurodegenerative diseases.

  7. A Supervised Learning Process to Validate Online Disease Reports for Use in Predictive Models.

    Science.gov (United States)

    Patching, Helena M M; Hudson, Laurence M; Cooke, Warrick; Garcia, Andres J; Hay, Simon I; Roberts, Mark; Moyes, Catherine L

    2015-12-01

    Pathogen distribution models that predict spatial variation in disease occurrence require data from a large number of geographic locations to generate disease risk maps. Traditionally, this process has used data from public health reporting systems; however, using online reports of new infections could speed up the process dramatically. Data from both public health systems and online sources must be validated before they can be used, but no mechanisms exist to validate data from online media reports. We have developed a supervised learning process to validate geolocated disease outbreak data in a timely manner. The process uses three input features, the data source and two metrics derived from the location of each disease occurrence. The location of disease occurrence provides information on the probability of disease occurrence at that location based on environmental and socioeconomic factors and the distance within or outside the current known disease extent. The process also uses validation scores, generated by disease experts who review a subset of the data, to build a training data set. The aim of the supervised learning process is to generate validation scores that can be used as weights going into the pathogen distribution model. After analyzing the three input features and testing the performance of alternative processes, we selected a cascade of ensembles comprising logistic regressors. Parameter values for the training data subset size, number of predictors, and number of layers in the cascade were tested before the process was deployed. The final configuration was tested using data for two contrasting diseases (dengue and cholera), and 66%-79% of data points were assigned a validation score. The remaining data points are scored by the experts, and the results inform the training data set for the next set of predictors, as well as going to the pathogen distribution model. The new supervised learning process has been implemented within our live site and is

  8. Transgenic Monkey Model of the Polyglutamine Diseases Recapitulating Progressive Neurological Symptoms

    Science.gov (United States)

    Ishibashi, Hidetoshi; Minakawa, Eiko N.; Motohashi, Hideyuki H.; Takayama, Osamu; Popiel, H. Akiko; Puentes, Sandra; Owari, Kensuke; Nakatani, Terumi; Nogami, Naotake; Yamamoto, Kazuhiro; Yonekawa, Takahiro; Tanaka, Yoko; Fujita, Naoko; Suzuki, Hikaru; Aizawa, Shu; Nagano, Seiichi; Yamada, Daisuke; Wada, Keiji; Kohsaka, Shinichi

    2017-01-01

    Abstract Age-associated neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, and the polyglutamine (polyQ) diseases, are becoming prevalent as a consequence of elongation of the human lifespan. Although various rodent models have been developed to study and overcome these diseases, they have limitations in their translational research utility owing to differences from humans in brain structure and function and in drug metabolism. Here, we generated a transgenic marmoset model of the polyQ diseases, showing progressive neurological symptoms including motor impairment. Seven transgenic marmosets were produced by lentiviral introduction of the human ataxin 3 gene with 120 CAG repeats encoding an expanded polyQ stretch. Although all offspring showed no neurological symptoms at birth, three marmosets with higher transgene expression developed neurological symptoms of varying degrees at 3–4 months after birth, followed by gradual decreases in body weight gain, spontaneous activity, and grip strength, indicating time-dependent disease progression. Pathological examinations revealed neurodegeneration and intranuclear polyQ protein inclusions accompanied by gliosis, which recapitulate the neuropathological features of polyQ disease patients. Consistent with neuronal loss in the cerebellum, brain MRI analyses in one living symptomatic marmoset detected enlargement of the fourth ventricle, which suggests cerebellar atrophy. Notably, successful germline transgene transmission was confirmed in the second-generation offspring derived from the symptomatic transgenic marmoset gamete. Because the accumulation of abnormal proteins is a shared pathomechanism among various neurodegenerative diseases, we suggest that this new marmoset model will contribute toward elucidating the pathomechanisms of and developing clinically applicable therapies for neurodegenerative diseases. PMID:28374014

  9. Disease induction by human microbial pathogens in plant-model systems: potential, problems and prospects.

    Science.gov (United States)

    van Baarlen, Peter; van Belkum, Alex; Thomma, Bart P H J

    2007-02-01

    Relatively simple eukaryotic model organisms such as the genetic model weed plant Arabidopsis thaliana possess an innate immune system that shares important similarities with its mammalian counterpart. In fact, some human pathogens infect Arabidopsis and cause overt disease with human symptomology. In such cases, decisive elements of the plant's immune system are likely to be targeted by the same microbial factors that are necessary for causing disease in humans. These similarities can be exploited to identify elementary microbial pathogenicity factors and their corresponding targets in a green host. This circumvents important cost aspects that often frustrate studies in humans or animal models and, in addition, results in facile ethical clearance.

  10. The Application of Contagious Disease Epidemiological Models to Known Population Structure and Movement

    Science.gov (United States)

    2016-03-01

    concept model ( Ebola ) • Time-varying disease transmission rate () Influenza model • Population structure represented via finite scale-free network...I N S T I T U T E F O R D E F E N S E A N A L Y S E S The Application of Contagious Disease Epidemiological Models to Known Population Structure ...Known Population Structure and Movement Julia K. Burr Robert L. Cubeta Lucas A. LaViolet Carl A. Curling This page is intentionally blank. iii

  11. Progresive diseases study using Markov´s multiple stage models

    Directory of Open Access Journals (Sweden)

    René Iral Palomino, Esp estadística

    2005-12-01

    Full Text Available Risk factors and their degree of association with a progressive disease,such as Alzheimerís disease or liver cancer, can be identifi edby using epidemiological models; some examples of these modelsinclude logistic and Poisson regression, log-linear, linear regression,and mixed models. Using models that take into account not onlythe different health status that a person could experience betweenvisits but also his/her characteristics (i.e. age, gender, genetic traits,etc. seems to be reasonable and justifi ed. In this paper we discussa methodology to estimate the effect of covariates that could beassociated with a disease when its progression or regression canbe idealized by means of a multi-state model that incorporates thelongitudinal nature of data. This method is based on the Markovproperty and it is illustrated using simulated data about Alzheimerísdisease. Finally, the merits and limitations of this method are discussed.

  12. Amniotic Fluid Stem Cells: A Novel Source for Modeling of Human Genetic Diseases

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    Ivana Antonucci

    2016-04-01

    Full Text Available In recent years, great interest has been devoted to the use of Induced Pluripotent Stem cells (iPS for modeling of human genetic diseases, due to the possibility of reprogramming somatic cells of affected patients into pluripotent cells, enabling differentiation into several cell types, and allowing investigations into the molecular mechanisms of the disease. However, the protocol of iPS generation still suffers from technical limitations, showing low efficiency, being expensive and time consuming. Amniotic Fluid Stem cells (AFS represent a potential alternative novel source of stem cells for modeling of human genetic diseases. In fact, by means of prenatal diagnosis, a number of fetuses affected by chromosomal or Mendelian diseases can be identified, and the amniotic fluid collected for genetic testing can be used, after diagnosis, for the isolation, culture and differentiation of AFS cells. This can provide a useful stem cell model for the investigation of the molecular basis of the diagnosed disease without the necessity of producing iPS, since AFS cells show some features of pluripotency and are able to differentiate in cells derived from all three germ layers “in vitro”. In this article, we describe the potential benefits provided by using AFS cells in the modeling of human genetic diseases.

  13. Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases

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    Jean-Marie Aerts

    2012-11-01

    Full Text Available The gravity models are commonly used spatial interaction models. They have been widely applied in a large set of domains dealing with interactions amongst spatial entities. The spread of vector-borne diseases is also related to the intensity of interaction between spatial entities, namely, the physical habitat of pathogens’ vectors and/or hosts, and urban areas, thus humans. This study implements the concept behind gravity models in the spatial spread of two vector-borne diseases, nephropathia epidemica and Lyme borreliosis, based on current knowledge on the transmission mechanism of these diseases. Two sources of information on vegetated systems were tested: the CORINE land cover map and MODIS NDVI. The size of vegetated areas near urban centers and a local indicator of occupation-related exposure were found significant predictors of disease risk. Both the land cover map and the space-borne dataset were suited yet not equivalent input sources to locate and measure vegetated areas of importance for disease spread. The overall results point at the compatibility of the gravity model concept and the spatial spread of vector-borne diseases.

  14. LITTLE FISH, BIG DATA: ZEBRAFISH AS A MODEL FOR CARDIOVASCULAR AND METABOLIC DISEASE.

    Science.gov (United States)

    Gut, Philipp; Reischauer, Sven; Stainier, Didier Y R; Arnaout, Rima

    2017-07-01

    The burden of cardiovascular and metabolic diseases worldwide is staggering. The emergence of systems approaches in biology promises new therapies, faster and cheaper diagnostics, and personalized medicine. However, a profound understanding of pathogenic mechanisms at the cellular and molecular levels remains a fundamental requirement for discovery and therapeutics. Animal models of human disease are cornerstones of drug discovery as they allow identification of novel pharmacological targets by linking gene function with pathogenesis. The zebrafish model has been used for decades to study development and pathophysiology. More than ever, the specific strengths of the zebrafish model make it a prime partner in an age of discovery transformed by big-data approaches to genomics and disease. Zebrafish share a largely conserved physiology and anatomy with mammals. They allow a wide range of genetic manipulations, including the latest genome engineering approaches. They can be bred and studied with remarkable speed, enabling a range of large-scale phenotypic screens. Finally, zebrafish demonstrate an impressive regenerative capacity scientists hope to unlock in humans. Here, we provide a comprehensive guide on applications of zebrafish to investigate cardiovascular and metabolic diseases. We delineate advantages and limitations of zebrafish models of human disease and summarize their most significant contributions to understanding disease progression to date. Copyright © 2017 the American Physiological Society.

  15. Construction of an odds model of coronary heart disease using published information: the Cardiovascular Health Improvement Model (CHIME

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    Potts Henry WW

    2008-10-01

    Full Text Available Abstract Background There is a need for a new cardiovascular disease model that includes a wider range of relevant risk factors, in particular lifestyle factors, to aid targeting of interventions and improve population models of the impact of cardiovascular disease and preventive strategies. The model needs to be applicable to a wider population including different ethnic groups, different countries and to those with and without cardiovascular disease. This paper describes the construction of the Cardiovascular Health Improvement Model that aims to meet these requirements. Method An odds model is used. Information was taken from 2003 mortality statistics for England and Wales, the Health Survey for England 2003 and published data on relative risk in those with and without CVD and mean blood pressure values in hypertensives. The odds ratios used were taken from the INTERHEART study. Results A worked example is given calculating the 10-year coronary heart disease risk for a 57 year-old non-diabetic male with no personal or family history of cardiovascular disease, who smokes 30 cigarettes a day and has a systolic blood pressure of 137 mmHg, a total cholesterol (TC of 6.2 mmol/l, a high density lipoprotein (HDL of 1.3 mol/l, and a body mass index of 21. He neither drinks regularly nor exercises. He can give no reliable information about his mental health or fruit and vegetable intake. His 10-year risk of CHD death is 2.47%. Conclusion This paper demonstrates a method for developing a CHD risk model. Further improvements could be made to the model with additional information. The method is applicable to other causes of death.

  16. Modeling screening, prevention, and delaying of Alzheimer's disease: an early-stage decision analytic model

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    Siemers Eric R

    2010-04-01

    Full Text Available Abstract Background Alzheimer's Disease (AD affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development. Methods A time-to-event (TTE simulation provided estimates of screening asymptomatic patients in the general population age ≥55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death. Results The base case results indicated increased AD free years (AD-FYs through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90. Conclusions This study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials.

  17. Modeling screening, prevention, and delaying of Alzheimer's disease: an early-stage decision analytic model.

    Science.gov (United States)

    Furiak, Nicolas M; Klein, Robert W; Kahle-Wrobleski, Kristin; Siemers, Eric R; Sarpong, Eric; Klein, Timothy M

    2010-04-30

    Alzheimer's Disease (AD) affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development. A time-to-event (TTE) simulation provided estimates of screening asymptomatic patients in the general population age > or =55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death. The base case results indicated increased AD free years (AD-FYs) through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years) the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90). This study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials.

  18. Modelling the effects of penetrance and family size on rates of sporadic and familial disease.

    Science.gov (United States)

    Al-Chalabi, Ammar; Lewis, Cathryn M

    2011-01-01

    Many complex diseases show a diversity of inheritance patterns ranging from familial disease, manifesting with autosomal dominant inheritance, through to simplex families in which only one person is affected, manifesting as apparently sporadic disease. The role of ascertainment bias in generating apparent patterns of inheritance is often overlooked. We therefore explored the role of two key parameters that influence ascertainment, penetrance and family size, in rates of observed familiality. We develop a mathematical model of familiality of disease, with parameters for penetrance, mutation frequency and family size, and test this in a complex disease: amyotrophic lateral sclerosis. Monogenic, high-penetrance variants can explain patterns of inheritance in complex diseases and account for a large proportion of those with no apparent family history. With current demographic trends, rates of familiality will drop further. For example, a variant with penetrance 0.5 will cause apparently sporadic disease in 12% of families of size 10, but 80% of families of size 1. A variant with penetrance 0.9 has only an 11% chance of appearing sporadic in families of a size similar to those of Ireland in the past, compared with 57% in one-child families like many in China. These findings have implications for genetic counselling, disease classification and the design of gene-hunting studies. The distinction between familial and apparently sporadic disease should be considered artificial. Copyright © 2011 S. Karger AG, Basel.

  19. Ecological and evolutionary dynamics of a model facultative pathogen: Agrobacterium and crown gall disease of plants.

    Science.gov (United States)

    Barton, Ian S; Fuqua, Clay; Platt, Thomas G

    2018-01-01

    Many important pathogens maintain significant populations in highly disparate disease and non-disease environments. The consequences of this environmental heterogeneity in shaping the ecological and evolutionary dynamics of these facultative pathogens are incompletely understood. Agrobacterium tumefaciens, the causative agent for crown gall disease of plants has proven a productive model for many aspects of interactions between pathogens and their hosts and with other microbes. In this review, we highlight how this past work provides valuable context for the use of this system to examine how heterogeneity and transitions between disease and non-disease environments influence the ecology and evolution of facultative pathogens. We focus on several features common among facultative pathogens, such as the physiological remodelling required to colonize hosts from environmental reservoirs and the consequences of competition with host and non-host associated microbiota. In addition, we discuss how the life history of facultative pathogens likely often results in ecological tradeoffs associated with performance in disease and non-disease environments. These pathogens may therefore have different competitive dynamics in disease and non-disease environments and are subject to shifting selective pressures that can result in pathoadaptation or the within-host spread of avirulent phenotypes. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

  20. From animal models to human disease: a genetic approach for personalized medicine in ALS.

    Science.gov (United States)

    Picher-Martel, Vincent; Valdmanis, Paul N; Gould, Peter V; Julien, Jean-Pierre; Dupré, Nicolas

    2016-07-11

    Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disease in adults. Classical ALS is characterized by the death of upper and lower motor neurons leading to progressive paralysis. Approximately 10 % of ALS patients have familial form of the disease. Numerous different gene mutations have been found in familial cases of ALS, such as mutations in superoxide dismutase 1 (SOD1), TAR DNA-binding protein 43 (TDP-43), fused in sarcoma (FUS), C9ORF72, ubiquilin-2 (UBQLN2), optineurin (OPTN) and others. Multiple animal models were generated to mimic the disease and to test future treatments. However, no animal model fully replicates the spectrum of phenotypes in the human disease and it is difficult to assess how a therapeutic effect in disease models can predict efficacy in humans. Importantly, the genetic and phenotypic heterogeneity of ALS leads to a variety of responses to similar treatment regimens. From this has emerged the concept of personalized medicine (PM), which is a medical scheme that combines study of genetic, environmental and clinical diagnostic testing, including biomarkers, to individualized patient care. In this perspective, we used subgroups of specific ALS-linked gene mutations to go through existing animal models and to provide a comprehensive profile of the differences and similarities between animal models of disease and human disease. Finally, we reviewed application of biomarkers and gene therapies relevant in personalized medicine approach. For instance, this includes viral delivering of antisense oligonucleotide and small interfering RNA in SOD1, TDP-43 and C9orf72 mice models. Promising gene therapies raised possibilities for treating differently the major mutations in familial ALS cases.

  1. Model construction for the intention to use telecare in patients with chronic diseases.

    Science.gov (United States)

    Huang, Jui-Chen; Lee, Yii-Ching

    2013-01-01

    Objective. This study chose patients with chronic diseases as study subjects to investigate their intention to use telecare. Methods. A large medical institute in Taiwan was used as the sample unit. Patients older than 20 years, who had chronic diseases, were sampled by convenience sampling and surveyed with a structural questionnaire, and a total of 500 valid questionnaires were collected. Model construction was based on the Health Belief Model. The reliability and validity of the measurement model were tested using confirmatory factor analysis (CFA), and the causal model was explained by structural equation modeling (SEM). Results. The priority should be on promoting the perceived benefits of telecare, with a secondary focus on the external cues to action, such as promoting the influences of important people on the patients. Conclusion. The findings demonstrated that patients with chronic diseases use telecare differently from the general public. To promote the use and acceptance of telecare in patients with chronic diseases, technology developers should prioritize the promotion of the usefulness of telecare. In addition, policy makers can strengthen the marketing from media and medical personnel, in order to increase the acceptance of telecare by patients with chronic diseases.

  2. Model Construction for the Intention to Use Telecare in Patients with Chronic Diseases

    Directory of Open Access Journals (Sweden)

    Jui-Chen Huang

    2013-01-01

    Full Text Available Objective. This study chose patients with chronic diseases as study subjects to investigate their intention to use telecare. Methods. A large medical institute in Taiwan was used as the sample unit. Patients older than 20 years, who had chronic diseases, were sampled by convenience sampling and surveyed with a structural questionnaire, and a total of 500 valid questionnaires were collected. Model construction was based on the Health Belief Model. The reliability and validity of the measurement model were tested using confirmatory factor analysis (CFA, and the causal model was explained by structural equation modeling (SEM. Results. The priority should be on promoting the perceived benefits of telecare, with a secondary focus on the external cues to action, such as promoting the influences of important people on the patients. Conclusion. The findings demonstrated that patients with chronic diseases use telecare differently from the general public. To promote the use and acceptance of telecare in patients with chronic diseases, technology developers should prioritize the promotion of the usefulness of telecare. In addition, policy makers can strengthen the marketing from media and medical personnel, in order to increase the acceptance of telecare by patients with chronic diseases.

  3. Outcomes and opportunities: a nurse-led model of chronic disease management in Australian general practice.

    Science.gov (United States)

    Eley, Diann S; Patterson, Elizabeth; Young, Jacqui; Fahey, Paul P; Del Mar, Chris B; Hegney, Desley G; Synnott, Robyn L; Mahomed, Rosemary; Baker, Peter G; Scuffham, Paul A

    2013-01-01

    The Australian government's commitment to health service reform has placed general practice at the centre of its agenda to manage chronic disease. Concerns about the capacity of GPs to meet the growing chronic disease burden has stimulated the implementation and testing of new models of care that better utilise practice nurses (PN). This paper reports on a mixed-methods study nested within a larger study that trialled the feasibility and acceptability of a new model of nurse-led chronic disease management in three general practices. Patients over 18 years of age with type 2 diabetes, hypertension or stable ischaemic heart disease were randomised into PN-led or usual GP-led care. Primary outcomes were self-reported quality of life and perceptions of the model's feasibility and acceptability from the perspective of patients and GPs. Over the 12-month study quality of life decreased but the trend between groups was not statistically different. Qualitative data indicate that the PN-led model was acceptable and feasible to GPs and patients. It is possible to extend the scope of PN care to lead the routine clinical management of patients' stable chronic diseases. All GPs identified significant advantages to the model and elected to continue with the PN-led care after our study concluded.

  4. The chick eye in vision research: An excellent model for the study of ocular disease.

    Science.gov (United States)

    Wisely, C Ellis; Sayed, Javed A; Tamez, Heather; Zelinka, Chris; Abdel-Rahman, Mohamed H; Fischer, Andy J; Cebulla, Colleen M

    2017-11-01

    The domestic chicken, Gallus gallus, serves as an excellent model for the study of a wide range of ocular diseases and conditions. The purpose of this manuscript is to outline some anatomic, physiologic, and genetic features of this organism as a robust animal model for vision research, particularly for modeling human retinal disease. Advantages include a sequenced genome, a large eye, relative ease of handling and maintenance, and ready availability. Relevant similarities and differences to humans are highlighted for ocular structures as well as for general physiologic processes. Current research applications for various ocular diseases and conditions, including ocular imaging with spectral domain optical coherence tomography, are discussed. Several genetic and non-genetic ocular disease models are outlined, including for pathologic myopia, keratoconus, glaucoma, retinal detachment, retinal degeneration, ocular albinism, and ocular tumors. Finally, the use of stem cell technology to study the repair of damaged tissues in the chick eye is discussed. Overall, the chick model provides opportunities for high-throughput translational studies to more effectively prevent or treat blinding ocular diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Modeling two strains of disease via aggregate-level infectivity curves.

    Science.gov (United States)

    Romanescu, Razvan; Deardon, Rob

    2016-04-01

    Well formulated models of disease spread, and efficient methods to fit them to observed data, are powerful tools for aiding the surveillance and control of infectious diseases. Our project considers the problem of the simultaneous spread of two related strains of disease in a context where spatial location is the key driver of disease spread. We start our modeling work with the individual level models (ILMs) of disease transmission, and extend these models to accommodate the competing spread of the pathogens in a two-tier hierarchical population (whose levels we refer to as 'farm' and 'animal'). The postulated interference mechanism between the two strains is a period of cross-immunity following infection. We also present a framework for speeding up the computationally intensive process of fitting the ILM to data, typically done using Markov chain Monte Carlo (MCMC) in a Bayesian framework, by turning the inference into a two-stage process. First, we approximate the number of animals infected on a farm over time by infectivity curves. These curves are fit to data sampled from farms, using maximum likelihood estimation, then, conditional on the fitted curves, Bayesian MCMC inference proceeds for the remaining parameters. Finally, we use posterior predictive distributions of salient epidemic summary statistics, in order to assess the model fitted.

  6. Impaired IL-10 transcription and release in animal models of Gaucher disease macrophages.

    Science.gov (United States)

    Kacher, Yaacov; Futerman, Anthony H

    2009-01-01

    A number of studies have shown altered cytokine levels in serum from Gaucher disease patients, including changes in levels of the anti-inflammatory cytokine, interleukin-10 (IL-10). However, the source of IL-10, or the mechanisms leading to changes in IL-10 serum levels are not known. We now show that mouse macrophages treated with an active site-directed inhibitor of glucocerebrosidase, or macrophages from a mouse model of Gaucher disease, the L444P mouse, release significantly less IL-10 than their untreated counterparts, but that TNFalpha release is unaffected. These changes are due to reduced transcription of IL-10 mRNA in macrophages. The reduction in IL-10 secretion observed in animal models of Gaucher disease macrophages may be of relevance to explain the increase in inflammation that is often observed in Gaucher disease.

  7. Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

    Science.gov (United States)

    Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

  8. Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

    Directory of Open Access Journals (Sweden)

    Lahiru Iddamalgoda

    2016-08-01

    Full Text Available Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification and scoring based prioritization methods for determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI methods in conjunction with the K nearest neighbors’ could be used in accurately categorizing the genetic factors in disease causation

  9. Exercise training on cardiovascular diseases: Role of animal models in the elucidation of the mechanisms

    Directory of Open Access Journals (Sweden)

    Bruno Rodrigues

    2017-05-01

    Full Text Available Abstract Cardiovascular diseases, which include hypertension, coronary artery disease/myocardial infarction and heart failure, are one of the major causes of disability and death worldwide. On the other hand, physical exercise acts in the preventionand treatment of these conditions. In fact, several experiments performed in human beings have demonstrated the efficiency of physical exercise to alter clinical signals observed in these diseases, such as high blood pressure and exercise intolerance. However, even if human studies demonstrated the clinical efficiency of physical exercise, most extensive mechanisms responsible for this phenomenon still have to be elucidated. In this sense, studies using animal models seem to be a good option to demonstrate such mechanisms. Therefore, the aims of the present study are describing the main pathophysiological characteristics of the animal models used in the study of cardiovascular diseases, as well as the main mechanismsassociated with the benefits of physical exercise.

  10. Dynamic modeling and analysis of sexually transmitted diseases on heterogeneous networks

    Science.gov (United States)

    Li, Shuping; Jin, Zhen

    2015-06-01

    Considering homosexual contacts and heterosexual contacts in the course of sexual contacts, double degrees which describe the numbers of homosexual contacts and heterosexual contacts are introduced, correlation coefficients about degrees based on the joint probability distribution are given, and an SIS mean-field model about sexually transmitted diseases is presented when degrees are uncorrelated. The basic reproduction number of diseases is studied by the method of next generation matrix. Results show that, when homosexual contacts and heterosexual contacts all exist, once the disease is epidemic in the interior of male (female) population which is caused by male (female) homosexual transmissions, or the disease is epidemic between the two species which is caused by heterosexual transmissions, the disease must be epidemic in the whole population. Numerical simulations confirm the theoretical results.

  11. New lessons learned from disease modeling with induced Pluripotent Stem Cells

    Science.gov (United States)

    Onder, Tamer T.; Daley, George Q.

    2012-01-01

    Cellular reprogramming and generation of induced pluripotent stem cells (iPSCs) from adult cell types has enabled the creation of patient-specific stem cells for use in disease modeling. To date, many iPSC lines have been generated from a variety of disorders, which have then been differentiated into disease-relevant cell types. When a disease-specific phenotype is detectable in such differentiated cells, the reprogramming technology provides a new opportunity to identify aberrant disease-associated pathways and drugs that can block them. Here, we highlight recent progress as well as limitations in the use of iPSCs to recapitulate disease phenotypes and to screen for therapeutics in vitro. PMID:22749051

  12. Stem cell models of polyglutamine diseases and their use in cell-based therapies

    Directory of Open Access Journals (Sweden)

    Evangelia eSiska

    2015-07-01

    Full Text Available Polyglutamine diseases are fatal neurological disorders that affect the central nervous system. They are caused by mutations in disease genes that contain CAG trinucleotide expansions in their coding regions. These mutations are translated into expanded glutamine chains in pathological proteins. Mutant proteins induce cytotoxicity, form intranuclear aggregates and cause neuronal cell death in specific brain regions. At the moment there is no cure for these diseases and only symptomatic treatments are available. Here, we discuss novel therapeutic approaches that aim in neuronal cell replacement using induced pluripotent or adult stem cells. Additionally, we present the beneficial effect of genetically engineered mesenchymal stem cells and their use as disease models or RNAi/gene delivery vehicles. In combination with their paracrine and cell-trophic properties, such cells may prove useful for the development of novel therapies against polyglutamine diseases.

  13. Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders

    Directory of Open Access Journals (Sweden)

    Martin Hofmann-Apitius

    2015-12-01

    Full Text Available Since the decoding of the Human Genome, techniques from bioinformatics, statistics, and machine learning have been instrumental in uncovering patterns in increasing amounts and types of different data produced by technical profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, causally driving diseases, has been limited, in part due to the inherent complexity of biological systems. Whereas we have witnessed progress in the areas of cancer, cardiovascular and metabolic diseases, the area of neurodegenerative diseases has proved to be very challenging. This is in part because the aetiology of neurodegenerative diseases such as Alzheimer´s disease or Parkinson´s disease is unknown, rendering it very difficult to discern early causal events. Here we describe a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge. We identify two complementary strategies—data mining techniques using genetic data as a starting point to be further enriched using other data-types, or alternatively to encode prior knowledge about disease mechanisms in a model based framework supporting reasoning and enrichment analysis. Our review illustrates the challenges entailed in integrating heterogeneous, multiscale and multimodal information in the area of neurology in general and neurodegeneration in particular. We conclude, that progress would be accelerated by increasing efforts on performing systematic collection of multiple data-types over time from each individual suffering from neurodegenerative disease. The work presented here has been driven by project AETIONOMY; a project funded in the course of the Innovative Medicines Initiative (IMI; which is a public-private partnership of the European Federation of Pharmaceutical Industry Associations

  14. Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda

    Science.gov (United States)

    Moore, Sean M.; Monaghan, Andrew; Griffith, Kevin S.; Apangu, Titus; Mead, Paul S.; Eisen, Rebecca J.

    2012-01-01

    Climate and weather influence the occurrence, distribution, and incidence of infectious diseases, particularly those caused by vector-borne or zoonotic pathogens. Thus, models based on meteorological data have helped predict when and where human cases are most likely to occur. Such knowledge aids in targeting limited prevention and control resources and may ultimately reduce the burden of diseases. Paradoxically, localities where such models could yield the greatest benefits, such as tropical regions where morbidity and mortality caused by vector-borne diseases is greatest, often lack high-quality in situ local meteorological data. Satellite- and model-based gridded climate datasets can be used to approximate local meteorological conditions in data-sparse regions, however their accuracy varies. Here we investigate how the selection of a particular dataset can influence the outcomes of disease forecasting models. Our model system focuses on plague (Yersinia pestis infection) in the West Nile region of Uganda. The majority of recent human cases have been reported from East Africa and Madagascar, where meteorological observations are sparse and topography yields complex weather patterns. Using an ensemble of meteorological datasets and model-averaging techniques we find that the number of suspected cases in the West Nile region was negatively associated with dry season rainfall (December-February) and positively with rainfall prior to the plague season. We demonstrate that ensembles of available meteorological datasets can be used to quantify climatic uncertainty and minimize its impacts on infectious disease models. These methods are particularly valuable in regions with sparse observational networks and high morbidity and mortality from vector-borne diseases. PMID:23024750

  15. Development of a disease risk prediction model for downy mildew (Peronospora sparsa) in boysenberry.

    Science.gov (United States)

    Kim, Kwang Soo; Beresford, Robert M; Walter, Monika

    2014-01-01

    Downy mildew caused by Peronospora sparsa has resulted in serious production losses in boysenberry (Rubus hybrid), blackberry (Rubus fruticosus), and rose (Rosa sp.) in New Zealand, Mexico, and the United States and the United Kingdom, respectively. Development of a model to predict downy mildew risk would facilitate development and implementation of a disease warning system for efficient fungicide spray application in the crops affected by this disease. Because detailed disease observation data were not available, a two-step approach was applied to develop an empirical risk prediction model for P. sparsa. To identify the weather patterns associated with a high incidence of downy mildew berry infections (dryberry disease) and derive parameters for the empirical model, classification and regression tree (CART) analysis was performed. Then, fuzzy sets were applied to develop a simple model to predict the disease risk based on the parameters derived from the CART analysis. High-risk seasons with a boysenberry downy mildew incidence >10% coincided with months when the number of hours per day with temperature of 15 to 20°C averaged >9.8 over the month and the number of days with rainfall in the month was >38.7%. The Fuzzy Peronospora Sparsa (FPS) model, developed using fuzzy sets, defined relationships among high-risk events, temperature, and rainfall conditions. In a validation study, the FPS model provided correct identification of both seasons with high downy mildew risk for boysenberry, blackberry, and rose and low risk in seasons when no disease was observed. As a result, the FPS model had a significant degree of agreement between predicted and observed risks of downy mildew for those crops (P = 0.002).

  16. Improvement of disease prediction and modeling through the use of meteorological ensembles: human plague in Uganda.

    Directory of Open Access Journals (Sweden)

    Sean M Moore

    Full Text Available Climate and weather influence the occurrence, distribution, and incidence of infectious diseases, particularly those caused by vector-borne or zoonotic pathogens. Thus, models based on meteorological data have helped predict when and where human cases are most likely to occur. Such knowledge aids in targeting limited prevention and control resources and may ultimately reduce the burden of diseases. Paradoxically, localities where such models could yield the greatest benefits, such as tropical regions where morbidity and mortality caused by vector-borne diseases is greatest, often lack high-quality in situ local meteorological data. Satellite- and model-based gridded climate datasets can be used to approximate local meteorological conditions in data-sparse regions, however their accuracy varies. Here we investigate how the selection of a particular dataset can influence the outcomes of disease forecasting models. Our model system focuses on plague (Yersinia pestis infection in the West Nile region of Uganda. The majority of recent human cases have been reported from East Africa and Madagascar, where meteorological observations are sparse and topography yields complex weather patterns. Using an ensemble of meteorological datasets and model-averaging techniques we find that the number of suspected cases in the West Nile region was negatively associated with dry season rainfall (December-February and positively with rainfall prior to the plague season. We demonstrate that ensembles of available meteorological datasets can be used to quantify climatic uncertainty and minimize its impacts on infectious disease models. These methods are particularly valuable in regions with sparse observational networks and high morbidity and mortality from vector-borne diseases.

  17. Vaccinating in disease-free regions: a vaccine model with application to yellow fever

    OpenAIRE

    Codec¸o, Claudia T; Luz, Paula M; Coelho, Flavio; Galvani, Alison P; Struchiner, Claudio

    2007-01-01

    Concerns regarding natural or induced emergence of infectious diseases have raised a debate on the pros and cons of pre-emptive vaccination of populations under uncertain risk. In the absence of immediate risk, ethical issues arise because even smaller risks associated with the vaccine are greater than the immediate disease risk (which is zero). The model proposed here seeks to formalize the vaccination decision process looking from the perspective of the susceptible individual, and results a...

  18. A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks

    Directory of Open Access Journals (Sweden)

    Cécile Viboud

    2016-06-01

    Conclusions: Our findings reveal significant variation in epidemic growth patterns across different infectious disease outbreaks and highlights that sub-exponential growth is a common phenomenon, especially for pathogens that are not airborne. Sub-exponential growth profiles may result from heterogeneity in contact structures or risk groups, reactive behavior changes, or the early onset of interventions strategies, and consideration of “deceleration parameters” may be useful to refine existing mathematical transmission models and improve disease forecasts.

  19. Grunting in genetically modified minipig animal model for Huntington ´s disease - a pilot experiment

    Czech Academy of Sciences Publication Activity Database

    Tykalová, T.; Hlavnička, J.; Mačáková, Monika; Baxa, Monika; Cmejla, R.; Motlík, Jan; Klempíř, J.; Rusz, J.

    2015-01-01

    Roč. 78, Suppl 2 (2015), s. 12-13 ISSN 1210-7859. [Conference on Animal Models for neurodegenerative Diseases /3./. 08.11.2015-10.11.2015, Liblice] R&D Projects: GA MŠk ED2.1.00/03.0124; GA MŠk(CZ) 7F14308 Institutional support: RVO:67985904 Keywords : Huntington ´s disease * mitochondria * DNA damage Subject RIV: FH - Neurology

  20. Early neurovascular dysfunction in a transgenic rat model of Alzheimer?s disease

    OpenAIRE

    Joo, Illsung L.; Lai, Aaron Y.; Bazzigaluppi, Paolo; Koletar, Margaret M.; Dorr, Adrienne; Brown, Mary E.; Thomason, Lynsie A. M.; Sled, John G.; McLaurin, JoAnne; Stefanovic, Bojana

    2017-01-01

    Alzheimer?s disease (AD), pathologically characterized by amyloid-? peptide (A?) accumulation, neurofibrillary tangle formation, and neurodegeneration, is thought to involve early-onset neurovascular abnormalities. Hitherto studies on AD-associated neurovascular injury have used animal models that exhibit only a subset of AD-like pathologies and demonstrated some A?-dependent vascular dysfunction and destabilization of neuronal network. The present work focuses on the early stage of disease p...

  1. Telemetry Physical Activity Monitoring in Minipig’s Model of Huntington’s Disease

    Czech Academy of Sciences Publication Activity Database

    Pokorný, M.; Juhás, Štefan; Juhásová, Jana; Klíma, Jiří; Motlík, Jan; Klempíř, J.; Havlík, J.

    2015-01-01

    Roč. 78, Suppl 2 (2015), s. 39-42 ISSN 1210-7859. [Conference on Animal Models for neurodegenerative Diseases /3./. Liblice, 08.11.2015-10.11.2015] R&D Projects: GA MŠk ED2.1.00/03.0124; GA MŠk(CZ) 7F14308 Institutional support: RVO:67985904 Keywords : Huntington´s disease * minipig * telemetry Subject RIV: FH - Neurology Impact factor: 0.209, year: 2015

  2. Data mining and Pattern Recognizing Models for Identifying Inherited Diseases: Challenges and Implications

    OpenAIRE

    Lahiru Iddamalgoda; Partha Sarathi Das; Partha Sarathi Das; Achala Aponso; Vijayaraghava Seshadri Sundararajan; Prashanth Suravajhala; Prashanth Suravajhala; Prashanth Suravajhala; Jayaraman K Valadi

    2016-01-01

    Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern r...

  3. Analysis of a general age-dependent vaccination model for a vertically transmitted disease

    International Nuclear Information System (INIS)

    El Doma, M.

    1995-05-01

    A SIR epidemic model of a general age-dependent vaccination for a vertically as well as horizontally transmitted disease is investigated when the total population is time dependent, and fertility, mortality and removal rates depend on age. We establish the existence and the uniqueness of the solution and obtain the asymptotic behaviour for the solution. For the steady state solution a critical vaccination coverage which will eventually eradicate the disease is determined. (author). 18 refs

  4. Latitude, sunshine, and human lactase phenotype distributions may contribute to geographic patterns of modern disease: the inflammatory bowel disease model

    Directory of Open Access Journals (Sweden)

    Szilagyi A

    2014-05-01

    Full Text Available Andrew Szilagyi,1 Henry Leighton,2 Barry Burstein,3 Xiaoqing Xue41Division of Gastroenterology, Department of Medicine, Jewish General Hospital, 2Department of Atmospheric and Oceanic Sciences, 3Department of Medicine, Jewish General Hospital, 4Department of Emergency Medicine, Jewish General Hospital, McGill University, Montreal, QC, CanadaAbstract: Countries with high lactase nonpersistence (LNP or low lactase persistence (LP populations have lower rates of some “western” diseases, mimicking the effects of sunshine and latitude. Inflammatory bowel disease (IBD, ie, Crohn's disease and ulcerative colitis, is putatively also influenced by sunshine. Recent availability of worldwide IBD rates and lactase distributions allows more extensive comparisons. The aim of this study was to evaluate the extent to which modern day lactase distributions interact with latitude, sunshine exposure, and IBD rates. National IBD rates, national distributions of LP/LNP, and population-weighted average national annual ultraviolet B exposure were obtained, estimated, or calculated from the literature. Negative binomial analysis was used to assess the relationship between the three parameters and IBD rates. Analyses for 55 countries were grouped in three geographic domains, ie, global, Europe, and non-Europe. In Europe, both latitude and ultraviolet B exposure correlate well with LP/LNP and IBD. In non-Europe, latitude and ultraviolet B exposure correlate weakly with LP/LNP, but the latter retains a more robust correlation with IBD. In univariate analysis, latitude, ultraviolet B exposure, and LP/LNP all had significant relationships with IBD. Multivariate analysis showed that lactase distributions provided the best model of fit for IBD. The model of IBD reveals the evolutionary effects of the human lactase divide, and suggests that latitude, ultraviolet B exposure, and LP/LNP mimic each other because LP/LNP follows latitudinal directions toward the equator

  5. A Root water uptake model to compensate disease stress in citrus trees

    Science.gov (United States)

    Peddinti, S. R.; Kambhammettu, B. P.; Lad, R. S.; Suradhaniwar, S.

    2017-12-01

    Plant root water uptake (RWU) controls a number of hydrologic fluxes in simulating unsaturated flow and transport processes. Variable saturated models that simulate soil-water-plant interactions within the rizhosphere do not account for the health of the tree. This makes them difficult to analyse RWU patterns for diseased trees. Improper irrigation management activities on diseased (Phytopthora spp. affected) citrus trees of central India has resulted in a significant reduction in crop yield accompanied by disease escalation. This research aims at developing a quantitative RWU model that accounts for the reduction in water stress as a function of plant disease level (hereafter called as disease stress). A total of four research plots with varying disease severity were considered for our field experimentation. A three-dimensional electrical resistivity tomography (ERT) was performed to understand spatio-temporal distribution in soil moisture following irrigation. Evaporation and transpiration were monitored daily using micro lysimeter and sap flow meters respectively. Disease intensity was quantified (on 0 to 9 scale) using pathological analysis on soil samples. Pedo-physocal and pedo-electric relations were established under controlled laboratory conditions. A non-linear disease stress response function for citrus trees was derived considering phonological, hydrological, and pathological parameters. Results of numerical simulations conclude that the propagation of error in RWU estimates by ignoring the health condition of the tree is significant. The developed disease stress function was then validated in the presence of deficit water and nutrient stress conditions. Results of numerical analysis showed a good agreement with experimental data, corroborating the need for alternate management practices for disease citrus trees.

  6. Stargardt disease: clinical features, molecular genetics, animal models and therapeutic options

    Science.gov (United States)

    Tanna, Preena; Strauss, Rupert W; Fujinami, Kaoru; Michaelides, Michel

    2017-01-01

    Stargardt disease (STGD1; MIM 248200) is the most prevalent inherited macular dystrophy and is associated with disease-causing sequence variants in the gene ABCA4. Significant advances have been made over the last 10 years in our understanding of both the clinical and molecular features of STGD1, and also the underlying pathophysiology, which has culminated in ongoing and planned human clinical trials of novel therapies. The aims of this review are to describe the detailed phenotypic and genotypic characteristics of the disease, conventional and novel imaging findings, current knowledge of animal models and pathogenesis, and the multiple avenues of intervention being explored. PMID:27491360

  7. Lentiviral vectors in neurodegenrative disorders - Aspects in gene therapy and disease models

    DEFF Research Database (Denmark)

    Nielsen, Troels Tolstrup

    2009-01-01

    Neurodegenerative disorders remain a complex group of diseases (i.e. Huntington's disease, HD) that are characterized by progressive loss of neurons resulting in movement disorders, cognitive decline, dementia and death. There is no cure for these diseases and treatment relies on symptomatic relief...... expression and escape transgene silencing during differentiation of neural stem cell lines. However, insulator vectors appeared to be impaired in functionality, which has importance for the future use of insulators in viral vectors. Finally, cell based models of HD was constructed to elucidate...

  8. Genotype-phenotype correlations in neurogenetics: Lesch-Nyhan disease as a model disorder.

    Science.gov (United States)

    Fu, Rong; Ceballos-Picot, Irene; Torres, Rosa J; Larovere, Laura E; Yamada, Yasukazu; Nguyen, Khue V; Hegde, Madhuri; Visser, Jasper E; Schretlen, David J; Nyhan, William L; Puig, Juan G; O'Neill, Patrick J; Jinnah, H A

    2014-05-01

    Establishing meaningful relationships between genetic variations and clinical disease is a fundamental goal for all human genetic disorders. However, these genotype-phenotype correlations remain incompletely characterized and sometimes conflicting for many diseases. Lesch-Nyhan disease is an X-linked recessive disorder that is caused by a wide variety of mutations in the HPRT1 gene. The gene encodes hypoxanthine-guanine phosphoribosyl transferase, an enzyme involved in purine metabolism. The fine structure of enzyme has been established by crystallography studies, and its function can be measured with very precise biochemical assays. This rich knowledge of genetic alterations in the gene and their functional effect on its protein product provides a powerful model for exploring factors that influence genotype-phenotype correlations. The present study summarizes 615 known genetic mutations, their influence on the gene product, and their relationship to the clinical phenotype. In general, the results are compatible with the concept that the overall severity of the disease depends on how mutations ultimately influence enzyme activity. However, careful evaluation of exceptions to this concept point to several additional genetic and non-genetic factors that influence genotype-phenotype correlations. These factors are not unique to Lesch-Nyhan disease, and are relevant to most other genetic diseases. The disease therefore serves as a valuable model for understanding the challenges associated with establishing genotype-phenotype correlations for other disorders.

  9. A dynamic model for infectious diseases: The role of vaccination and treatment

    International Nuclear Information System (INIS)

    Raja Sekhara Rao, P.; Naresh Kumar, M.

    2015-01-01

    Understanding dynamics of an infectious disease helps in designing appropriate strategies for containing its spread in a population. Recent mathematical models are aimed at studying dynamics of some specific types of infectious diseases. In this paper we propose a new model for infectious diseases spread having susceptible, infected, and recovered populations and study its dynamics in presence of incubation delays and relapse of the disease. The influence of treatment and vaccination efforts on the spread of infection in presence of time delays are studied. Sufficient conditions for local stability of the equilibria and change of stability are derived in various cases. The problem of global stability is studied for an important special case of the model. Simulations carried out in this study brought out the importance of treatment rate in controlling the disease spread. It is observed that incubation delays have influence on the system even under enhanced vaccination. The present study has clearly brought out the fact that treatment rate even in presence of time delays would contain the disease as compared to popular belief that eradication can only be done through vaccination

  10. Biology and therapy of inherited retinal degenerative disease: insights from mouse models

    Science.gov (United States)

    Veleri, Shobi; Lazar, Csilla H.; Chang, Bo; Sieving, Paul A.; Banin, Eyal; Swaroop, Anand

    2015-01-01

    Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases. PMID:25650393

  11. Biology and therapy of inherited retinal degenerative disease: insights from mouse models

    Directory of Open Access Journals (Sweden)

    Shobi Veleri

    2015-02-01

    Full Text Available Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases.

  12. A knowledge based approach to matching human neurodegenerative disease and animal models

    Directory of Open Access Journals (Sweden)

    Maryann E Martone

    2013-05-01

    Full Text Available Neurodegenerative diseases present a wide and complex range of biological and clinical features. Animal models are key to translational research, yet typically only exhibit a subset of disease features rather than being precise replicas of the disease. Consequently, connecting animal to human conditions using direct data-mining strategies has proven challenging, particularly for diseases of the nervous system, with its complicated anatomy and physiology. To address this challenge we have explored the use of ontologies to create formal descriptions of structural phenotypes across scales that are machine processable and amenable to logical inference. As proof of concept, we built a Neurodegenerative Disease Phenotype Ontology and an associated Phenotype Knowledge Base using an entity-quality model that incorporates descriptions for both human disease phenotypes and those of animal models. Entities are drawn from community ontologies made available through the Neuroscience Information Framework and qualities are drawn from the Phenotype and Trait Ontology. We generated ~1200 structured phenotype statements describing structural alterations at the subcellular, cellular and gross anatomical levels observed in 11 human neurodegenerative conditions and associated animal models. PhenoSim, an open source tool for comparing phenotypes, was used to issue a series of competency questions to compare individual phenotypes among organisms and to determine which animal models recapitulate phenotypic aspects of the human disease in aggregate. Overall, the system was able to use relationships within the ontology to bridge phenotypes across scales, returning non-trivial matches based on common subsumers that were meaningful to a neuroscientist with an advanced knowledge of neuroanatomy. The system can be used both to compare individual phenotypes and also phenotypes in aggregate. This proof of concept suggests that expressing complex phenotypes using formal

  13. Bayesian modelling of Dupuytren disease by using Gaussian copula graphical models

    NARCIS (Netherlands)

    Mohammadi, A.; Abegaz, F.; van den Heuvel, E.R.; Wit, E.C.

    2017-01-01

    Dupuytren disease is a fibroproliferative disorder with unknown aetiology that often progresses and eventually can cause permanent contractures of the fingers affected. We provide a computationally efficient Bayesian framework to discover potential risk factors and investigate which fingers are

  14. Developing an active implementation model for a chronic disease management program.

    Science.gov (United States)

    Smidth, Margrethe; Christensen, Morten Bondo; Olesen, Frede; Vedsted, Peter

    2013-04-01

    Introduction and diffusion of new disease management programs in healthcare is usually slow, but active theory-driven implementation seems to outperform other implementation strategies. However, we have only scarce evidence on the feasibility and real effect of such strategies in complex primary care settings where municipalities, general practitioners and hospitals should work together. The Central Denmark Region recently implemented a disease management program for chronic obstructive pulmonary disease (COPD) which presented an opportunity to test an active implementation model against the usual implementation model. The aim of the present paper is to describe the development of an active implementation model using the Medical Research Council's model for complex interventions and the Chronic Care Model. We used the Medical Research Council's five-stage model for developing complex interventions to design an implementation model for a disease management program for COPD. First, literature on implementing change in general practice was scrutinised and empirical knowledge was assessed for suitability. In phase I, the intervention was developed; and in phases II and III, it was tested in a block- and cluster-randomised study. In phase IV, we evaluated the feasibility for others to use our active implementation model. The Chronic Care Model was identified as a model for designing efficient implementation elements. These elements were combined into a multifaceted intervention, and a timeline for the trial in a randomised study was decided upon in accordance with the five stages in the Medical Research Council's model; this was captured in a PaTPlot, which allowed us to focus on the structure and the timing of the intervention. The implementation strategies identified as efficient were use of the Breakthrough Series, academic detailing, provision of patient material and meetings between providers. The active implementation model was tested in a randomised trial

  15. A Bayesian Spatial Model to Predict Disease Status Using Imaging Data From Various Modalities

    Directory of Open Access Journals (Sweden)

    Wenqiong Xue

    2018-03-01

    Full Text Available Relating disease status to imaging data stands to increase the clinical significance of neuroimaging studies. Many neurological and psychiatric disorders involve complex, systems-level alterations that manifest in functional and structural properties of the brain and possibly other clinical and biologic measures. We propose a Bayesian hierarchical model to predict disease status, which is able to incorporate information from both functional and structural brain imaging scans. We consider a two-stage whole brain parcellation, partitioning the brain into 282 subregions, and our model accounts for correlations between voxels from different brain regions defined by the parcellations. Our approach models the imaging data and uses posterior predictive probabilities to perform prediction. The estimates of our model parameters are based on samples drawn from the joint posterior distribution using Markov Chain Monte Carlo (MCMC methods. We evaluate our method by examining the prediction accuracy rates based on leave-one-out cross validation, and we employ an importance sampling strategy to reduce the computation time. We conduct both whole-brain and voxel-level prediction and identify the brain regions that are highly associated with the disease based on the voxel-level prediction results. We apply our model to multimodal brain imaging data from a study of Parkinson's disease. We achieve extremely high accuracy, in general, and our model identifies key regions contributing to accurate prediction including caudate, putamen, and fusiform gyrus as well as several sensory system regions.

  16. Computational Modelling and Optimal Control of Ebola Virus Disease with non-Linear Incidence Rate

    Science.gov (United States)

    Takaidza, I.; Makinde, O. D.; Okosun, O. K.

    2017-03-01

    The 2014 Ebola outbreak in West Africa has exposed the need to connect modellers and those with relevant data as pivotal to better understanding of how the disease spreads and quantifying the effects of possible interventions. In this paper, we model and analyse the Ebola virus disease with non-linear incidence rate. The epidemic model created is used to describe how the Ebola virus could potentially evolve in a population. We perform an uncertainty analysis of the basic reproductive number R 0 to quantify its sensitivity to other disease-related parameters. We also analyse the sensitivity of the final epidemic size to the time control interventions (education, vaccination, quarantine and safe handling) and provide the cost effective combination of the interventions.

  17. Modeling treatment of ischemic heart disease with partially observable Markov decision processes.

    Science.gov (United States)

    Hauskrecht, M; Fraser, H

    1998-01-01

    Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead they are very often dependent and interleaved over time, mostly due to uncertainty about the underlying disease, uncertainty associated with the response of a patient to the treatment and varying cost of different diagnostic (investigative) and treatment procedures. The framework of Partially observable Markov decision processes (POMDPs) developed and used in operations research, control theory and artificial intelligence communities is particularly suitable for modeling such a complex decision process. In the paper, we show how the POMDP framework could be used to model and solve the problem of the management of patients with ischemic heart disease, and point out modeling advantages of the framework over standard decision formalisms.

  18. A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

    Science.gov (United States)

    Robertson, Colin; Sawford, Kate; Gunawardana, Walimunige S. N.; Nelson, Trisalyn A.; Nathoo, Farouk; Stephen, Craig

    2011-01-01

    Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines. PMID:21949763

  19. Systems biology from micro-organisms to human metabolic diseases: the role of detailed kinetic models.

    Science.gov (United States)

    Bakker, Barbara M; van Eunen, Karen; Jeneson, Jeroen A L; van Riel, Natal A W; Bruggeman, Frank J; Teusink, Bas

    2010-10-01

    Human metabolic diseases are typically network diseases. This holds not only for multifactorial diseases, such as metabolic syndrome or Type 2 diabetes, but even when a single gene defect is the primary cause, where the adaptive response of the entire network determines the severity of disease. The latter may differ between individuals carrying the same mutation. Understanding the adaptive responses of human metabolism naturally requires a systems biology approach. Modelling of metabolic pathways in micro-organisms and some mammalian tissues has yielded many insights, qualitative as well as quantitative, into their control and regulation. Yet, even for a well-known pathway such as glycolysis, precise predictions of metabolite dynamics from experimentally determined enzyme kinetics have been only moderately successful. In the present review, we compare kinetic models of glycolysis in three cell types (African trypanosomes, yeast and skeletal muscle), evaluate their predictive power and identify limitations in our understanding. Although each of these models has its own merits and shortcomings, they also share common features. For example, in each case independently measured enzyme kinetic parameters were used as input. Based on these 'lessons from glycolysis', we will discuss how to make best use of kinetic computer models to advance our understanding of human metabolic diseases.

  20. Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria

    Directory of Open Access Journals (Sweden)

    Kimmel Marek

    2011-05-01

    Full Text Available Abstract Background Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome. Methods Using survival time data from 1190 newly diagnosed lung cancer patients at MD Anderson Cancer Center, we model the time from clinical lung cancer diagnosis to death using an exponential distribution to approximate the length of this interval for a study where lung cancer death serves as the outcome. Incorporating this interval into our previously developed lung cancer risk model, we adjust for the effect of disease status-related eligibility criteria in predicting the number of lung cancer deaths in the control arm of CARET. The effect of the adjustment using the MD Anderson-derived approximation is compared to that based on SEER data. Results Using the adjustment developed in conjunction with our existing lung cancer model, we are able to accurately predict the number of lung cancer deaths observed in the control arm of CARET. Conclusions The resulting adjustment was accurate in predicting the lower rates of disease observed in the early years while still maintaining reasonable prediction ability in the later years of the trial. This method could be used to adjust for, or predict the duration and relative effect of any possible biases related to disease-specific eligibility criteria in modeling studies of volunteer-based cohorts.

  1. Probability-based collaborative filtering model for predicting gene-disease associations.

    Science.gov (United States)

    Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

    2017-12-28

    Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene-disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our model. Firstly, on the basis of a typical latent factorization model, we propose model I with an average heterogeneous regularization. Secondly, we develop modified model II with personal heterogeneous regularization to enhance the accuracy of aforementioned models. In this model, vector space similarity or Pearson correlation coefficient metrics and data on related species are also used. We compared the results of PCFM with the results of four state-of-arts approaches. The results show that PCFM performs better than other advanced approaches. PCFM model can be leveraged for predictions of disease genes, especially for new human genes or diseases with no known relationships.

  2. Polyglutamine Disease Modeling: Epitope Based Screen for Homologous Recombination using CRISPR/Cas9 System.

    Science.gov (United States)

    An, Mahru C; O'Brien, Robert N; Zhang, Ningzhe; Patra, Biranchi N; De La Cruz, Michael; Ray, Animesh; Ellerby, Lisa M

    2014-04-15

    We have previously reported the genetic correction of Huntington's disease (HD) patient-derived induced pluripotent stem cells using traditional homologous recombination (HR) approaches. To extend this work, we have adopted a CRISPR-based genome editing approach to improve the efficiency of recombination in order to generate allelic isogenic HD models in human cells. Incorporation of a rapid antibody-based screening approach to measure recombination provides a powerful method to determine relative efficiency of genome editing for modeling polyglutamine diseases or understanding factors that modulate CRISPR/Cas9 HR.

  3. Musical Electroacupuncture May Be a Better Choice than Electroacupuncture in a Mouse Model of Alzheimer's Disease

    OpenAIRE

    Jiang, Jing; Liu, Gang; Shi, Suhua; Li, Zhigang

    2016-01-01

    Objectives. To compare musical electroacupuncture and electroacupuncture in a mouse model of Alzheimer's disease. Methods. In this study, 7.5-month-old male senescence-accelerated mouse prone 8 (SAMP8) mice were used as an Alzheimer's disease animal model. In the normal control paradigm, 7.5-month-old male SAMR1 mice were used as the blank control group (N group). After 15 days of treatment, using Morris water maze test, micro-PET, and immunohistochemistry, the differences among the musical e...

  4. Analysis of a Mathematical Model of Emerging Infectious Disease Leading to Amphibian Decline

    Directory of Open Access Journals (Sweden)

    Muhammad Dur-e-Ahmad

    2014-01-01

    Full Text Available We formulate a three-dimensional deterministic model of amphibian larvae population to investigate the cause of extinction due to the infectious disease. The larvae population of the model is subdivided into two classes, exposed and unexposed, depending on their vulnerability to disease. Reproduction ratio ℛ0 has been calculated and we have shown that if ℛ01, we discussed different scenarios under which an infected population can survive or be eliminated using stability and persistence analysis. Finally, we also used Hopf bifurcation analysis to study the stability of periodic solutions.

  5. epidemix—An interactive multi-model application for teaching and visualizing infectious disease transmission

    Directory of Open Access Journals (Sweden)

    Ulrich Muellner

    2018-06-01

    Full Text Available Mathematical models of disease transmission are used to improve our understanding of patterns of infection and to identify factors influencing them. During recent public and animal health crises, such as pandemic influenza, Ebola, Zika, foot-and-mouth disease, models have made important contributions in addressing policy questions, especially through the assessment of the trajectory and scale of outbreaks, and the evaluation of control interventions. However, their mathematical formulation means that they may appear as a “black box” to those without the appropriate mathematical background. This may lead to a negative perception of their utility for guiding policy, and generate expectations, which are not in line with what these models can deliver. It is therefore important for policymakers, as well as public health and animal health professionals and researchers who collaborate with modelers and use results generated by these models for policy development or research purpose, to understand the key concepts and assumptions underlying these models.The software application epidemix (http://shinyapps.rvc.ac.uk presented here aims to make mathematical models of disease transmission accessible to a wider audience of users. By developing a visual interface for a suite of eight models, users can develop an understanding of the impact of various modelling assumptions – especially mixing patterns – on the trajectory of an epidemic and the impact of control interventions, without having to directly deal with the complexity of mathematical equations and programming languages. Models are compartmental or individual-based, deterministic or stochastic, and assume homogeneous or heterogeneous-mixing patterns (with the probability of transmission depending on the underlying structure of contact networks, or the spatial distribution of hosts. This application is intended to be used by scientists teaching mathematical modelling short courses to non

  6. Dog as a model in studies on human hereditary diseases and their gene therapy.

    Science.gov (United States)

    Switonski, Marek

    2014-03-01

    During the last 15 years spectacular progress has been achieved in knowledge on the dog genome organization and the molecular background of hereditary diseases in this species. A majority of canine genetic diseases have their counterparts in humans and thus dogs are considered as a very important large animal model in human biomedicine. Among canine monogenic diseases with known causative gene mutations there are two large groups classified as retinal dystrophies and lysosomal storage diseases. Specific types of these diseases are usually diagnosed in a single or several breeds. A well known disorder, restricted to a single breed, is congenital stationary night blindness described in Briards. This disease is a counterpart of Leber amaurosis in children. On the other hand, one of the most common monogenic human diseases (Duchenne muscular dystrophy), has its canine counterparts in several breeds (e.g., the Golden retriever, Beagle and German short-haired pointer). For some of the canine diseases gene therapy strategy was successfully applied, e.g., for congenital stationary night blindness, rod-cone dystrophy and muccopolysaccharydoses type I, IIIB and VII. Since phenotypic variability between the breeds is exceptionally high, the dog is an interesting model to study the molecular background of congenital malformations (e.g., dwarfism and osteoporosis imperfecta). Also disorders of sexual development (DSD), especially testicular or ovotesticular DSD (78,XX; SRY-negative), which is widely distributed across dozens of breeds, are of particular interest. Studies on the genetic background of canine cancers, a major health problem in this species, are also quite advanced. On the other hand, genetic studies on canine counterparts of major human complex diseases (e.g., obesity, the metabolic syndrome and diabetes mellitus) are still in their infancy. Copyright © 2014 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish

  7. Parametric scaling from species relative abundances to absolute abundances in the computation of biological diversity: a first proposal using Shannon's entropy.

    Science.gov (United States)

    Ricotta, Carlo

    2003-01-01

    Traditional diversity measures such as the Shannon entropy are generally computed from the species' relative abundance vector of a given community to the exclusion of species' absolute abundances. In this paper, I first mention some examples where the total information content associated with a given community may be more adequate than Shannon's average information content for a better understanding of ecosystem functioning. Next, I propose a parametric measure of statistical information that contains both Shannon's entropy and total information content as special cases of this more general function.

  8. Identification of age- and disease-related alterations in circulating miRNAs in a mouse model of Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Sylvia eGarza-Manero

    2015-02-01

    Full Text Available Alzheimer's disease (AD is a neurodegenerative disorder characterized clinically by the progressive decline of memory and cognition. Histopathologically, two main hallmarks have been identified in AD: amyloid-β peptide extracellular neuritic plaques and neurofibrillary tangles formed by posttranslational modified tau protein. A definitive diagnosis can only be achieved after the post mortem verification of the histological mentioned alterations. Therefore the development of biomarkers that allow an early diagnosis and/or predict disease progression is imperative. The prospect of a blood-based biomarker is possible with the finding of circulating microRNAs (miRNAs, a class of small non-coding RNAs of 22-25 nucleotides length that regulate mRNA translation rate. miRNAs travel through blood and recent studies performed in potential AD cases suggest the possibility of finding pathology-associated differences in circulating miRNA levels that may serve to assist in early diagnosis of the disease. However, these studies analyzed samples at a single time-point, limiting the use of miRNAs as biomarkers in AD progression. In this study we evaluated miRNA levels in plasma samples at different time-points of the evolution of an AD-like pathology in a transgenic mouse model of the disease (3xTg-AD. We performed multiplex qRT-PCR and compared the plasmatic levels of 84 miRNAs previously associated to central nervous system development and disease. No significant differences were detected between WT and transgenic young mice. However, age-related significant changes in miRNA abundance were observed for both WT and transgenic mice, and some of these were specific for the 3xTg-AD. In agreement, variations in the levels of particular miRNAs were identified between WT and transgenic old mice thus suggesting that the age-dependent evolution of the AD-like pathology, rather than the presence and expression of the transgenes, modifies the circulating miRNA levels in

  9. Using data-driven agent-based models for forecasting emerging infectious diseases

    Directory of Open Access Journals (Sweden)

    Srinivasan Venkatramanan

    2018-03-01

    Full Text Available Producing timely, well-informed and reliable forecasts for an ongoing epidemic of an emerging infectious disease is a huge challenge. Epidemiologists and policy makers have to deal with poor data quality, limited understanding of the disease dynamics, rapidly changing social environment and the uncertainty on effects of various interventions in place. Under this setting, detailed computational models provide a comprehensive framework for integrating diverse data sources into a well-defined model of disease dynamics and social behavior, potentially leading to better understanding and actions. In this paper, we describe one such agent-based model framework developed for forecasting the 2014–2015 Ebola epidemic in Liberia, and subsequently used during the Ebola forecasting challenge. We describe the various components of the model, the calibration process and summarize the forecast performance across scenarios of the challenge. We conclude by highlighting how such a data-driven approach can be refined and adapted for future epidemics, and share the lessons learned over the course of the challenge. Keywords: Emerging infectious diseases, Agent-based models, Simulation optimization, Bayesian calibration, Ebola

  10. Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.

    Science.gov (United States)

    Franke, John E; Yakubu, Abdul-Aziz

    2008-12-01

    The dynamics of simple discrete-time epidemic models without disease-induced mortality are typically characterized by global transcritical bifurcation. We prove that in corresponding models with disease-induced mortality a tiny number of infectious individuals can drive an otherwise persistent population to extinction. Our model with disease-induced mortality supports multiple attractors. In addition, we use a Ricker recruitment function in an SIS model and obtained a three component discrete Hopf (Neimark-Sacker) cycle attractor coexisting with a fixed point attractor. The basin boundaries of the coexisting attractors are fractal in nature, and the example exhibits sensitive dependence of the long-term disease dynamics on initial conditions. Furthermore, we show that in contrast to corresponding models without disease-induced mortality, the disease-free state dynamics do not drive the disease dynamics.

  11. Detailed analysis of the African green monkey model of Nipah virus disease.

    Directory of Open Access Journals (Sweden)

    Sara C Johnston

    Full Text Available Henipaviruses are implicated in severe and frequently fatal pneumonia and encephalitis in humans. There are no approved vaccines or treatments available for human use, and testing of candidates requires the use of well-characterized animal models that mimic human disease. We performed a comprehensive and statistically-powered evaluation of the African green monkey model to define parameters critical to disease progression and the extent to which they correlate with human disease. African green monkeys were inoculated by the intratracheal route with 2.5 × 10(4 plaque forming units of the Malaysia strain of Nipah virus. Physiological data captured using telemetry implants and assessed in conjunction with clinical pathology were consistent with shock, and histopathology confirmed widespread tissue involvement associated with systemic vasculitis in animals that succumbed to acute disease. In addition, relapse encephalitis was identified in 100% of animals that survived beyond the acute disease phase. Our data suggest that disease progression in the African green monkey is comparable to the variable outcome of Nipah virus infection in humans.

  12. Optogenetic approaches to evaluate striatal function in animal models of Parkinson disease.

    Science.gov (United States)

    Parker, Krystal L; Kim, Youngcho; Alberico, Stephanie L; Emmons, Eric B; Narayanan, Nandakumar S

    2016-03-01

    Optogenetics refers to the ability to control cells that have been genetically modified to express light-sensitive ion channels. The introduction of optogenetic approaches has facilitated the dissection of neural circuits. Optogenetics allows for the precise stimulation and inhibition of specific sets of neurons and their projections with fine temporal specificity. These techniques are ideally suited to investigating neural circuitry underlying motor and cognitive dysfunction in animal models of human disease. Here, we focus on how optogenetics has been used over the last decade to probe striatal circuits that are involved in Parkinson disease, a neurodegenerative condition involving motor and cognitive abnormalities resulting from degeneration of midbrain dopaminergic neurons. The precise mechanisms underlying the striatal contribution to both cognitive and motor dysfunction in Parkinson disease are unknown. Although optogenetic approaches are somewhat removed from clinical use, insight from these studies can help identify novel therapeutic targets and may inspire new treatments for Parkinson disease. Elucidating how neuronal and behavioral functions are influenced and potentially rescued by optogenetic manipulation in animal models could prove to be translatable to humans. These insights can be used to guide future brain-stimulation approaches for motor and cognitive abnormalities in Parkinson disease and other neuropsychiatric diseases.

  13. A Nonhuman Primate Model of Human Radiation-Induced Venocclusive Liver Disease and Hepatocyte Injury

    Energy Technology Data Exchange (ETDEWEB)

    Yannam, Govardhana Rao [Department of Surgery, University of Nebraska Medical Center, Omaha, Nebraska (United States); Han, Bing [Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (United States); Department of Hepatobiliary Surgery, First Affiliated Hospital of Xi' an Jiaotong University, Xi' an, Shaanxi (China); Setoyama, Kentaro [Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (United States); Yamamoto, Toshiyuki [Department of Surgery, University of Nebraska Medical Center, Omaha, Nebraska (United States); Ito, Ryotaro; Brooks, Jenna M. [Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (United States); Guzman-Lepe, Jorge [Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (United States); Department of Pathology, Children' s Hospital of Pittsburgh, Pittsburgh, Pennsylvania (United States); Galambos, Csaba [Department of Pathology, Children' s Hospital of Pittsburgh, Pittsburgh, Pennsylvania (United States); Fong, Jason V. [Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania (United States); Deutsch, Melvin; Quader, Mubina A. [Department of Radiation Oncology, Children' s Hospital of Pittsburgh, Pittsburgh, Pennsylvania (United States); Yamanouchi, Kosho [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Marion Bessin Liver Research Center, Albert Einstein College of Medicine, Bronx, New York (United States); Kabarriti, Rafi; Mehta, Keyur [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Soto-Gutierrez, Alejandro [Department of Pathology, Children' s Hospital of Pittsburgh, Pittsburgh, Pennsylvania (United States); McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania (United States); and others

    2014-02-01

    Background: Human liver has an unusual sensitivity to radiation that limits its use in cancer therapy or in preconditioning for hepatocyte transplantation. Because the characteristic veno-occlusive lesions of radiation-induced liver disease do not occur in rodents, there has been no experimental model to investigate the limits of safe radiation therapy or explore the pathogenesis of hepatic veno-occlusive disease. Methods and Materials: We performed a dose-escalation study in a primate, the cynomolgus monkey, using hypofractionated stereotactic body radiotherapy in 13 animals. Results: At doses ≥40 Gy, animals developed a systemic syndrome resembling human radiation-induced liver disease, consisting of decreased albumin, elevated alkaline phosphatase, loss of appetite, ascites, and normal bilirubin. Higher radiation doses were lethal, causing severe disease that required euthanasia approximately 10 weeks after radiation. Even at lower doses in which radiation-induced liver disease was mild or nonexistent, latent and significant injury to hepatocytes was demonstrated by asialoglycoprotein-mediated functional imaging. These monkeys developed hepatic failure with encephalopathy when they received parenteral nutrition containing high concentrations of glucose. Histologically, livers showed central obstruction via an unusual intimal swelling that progressed to central fibrosis. Conclusions: The cynomolgus monkey, as the first animal model of human veno-occlusive radiation-induced liver disease, provides a resource for characterizing the early changes and pathogenesis of venocclusion, for establishing nonlethal therapeutic dosages, and for examining experimental therapies to minimize radiation injury.

  14. A Nonhuman Primate Model of Human Radiation-Induced Venocclusive Liver Disease and Hepatocyte Injury

    International Nuclear Information System (INIS)

    Yannam, Govardhana Rao; Han, Bing; Setoyama, Kentaro; Yamamoto, Toshiyuki; Ito, Ryotaro; Brooks, Jenna M.; Guzman-Lepe, Jorge; Galambos, Csaba; Fong, Jason V.; Deutsch, Melvin; Quader, Mubina A.; Yamanouchi, Kosho; Kabarriti, Rafi; Mehta, Keyur; Soto-Gutierrez, Alejandro

    2014-01-01

    Background: Human liver has an unusual sensitivity to radiation that limits its use in cancer therapy or in preconditioning for hepatocyte transplantation. Because the characteristic veno-occlusive lesions of radiation-induced liver disease do not occur in rodents, there has been no experimental model to investigate the limits of safe radiation therapy or explore the pathogenesis of hepatic veno-occlusive disease. Methods and Materials: We performed a dose-escalation study in a primate, the cynomolgus monkey, using hypofractionated stereotactic body radiotherapy in 13 animals. Results: At doses ≥40 Gy, animals developed a systemic syndrome resembling human radiation-induced liver disease, consisting of decreased albumin, elevated alkaline phosphatase, loss of appetite, ascites, and normal bilirubin. Higher radiation doses were lethal, causing severe disease that required euthanasia approximately 10 weeks after radiation. Even at lower doses in which radiation-induced liver disease was mild or nonexistent, latent and significant injury to hepatocytes was demonstrated by asialoglycoprotein-mediated functional imaging. These monkeys developed hepatic failure with encephalopathy when they received parenteral nutrition containing high concentrations of glucose. Histologically, livers showed central obstruction via an unusual intimal swelling that progressed to central fibrosis. Conclusions: The cynomolgus monkey, as the first animal model of human veno-occlusive radiation-induced liver disease, provides a resource for characterizing the early changes and pathogenesis of venocclusion, for establishing nonlethal therapeutic dosages, and for examining experimental therapies to minimize radiation injury

  15. Barriers to developing a valid rodent model of Alzheimer's disease: from behavioural analysis to etiologicalmechanisms

    Directory of Open Access Journals (Sweden)

    Darryl Christopher Gidyk

    2015-07-01

    Full Text Available Sporadic Alzheimer's disease is the most prevalent form of age-related dementia. As such, great effort has been put forth to investigate the etiology, progression, and underlying mechanisms of the disease. Countless studies have been conducted however the details of this disease remain largely unknown. Rodent models provide opportunities to investigate certain aspects of AD that cannot be ethically studied in humans. These animal models vary from study to study and have provided some insight, but no real advancements in the prevention or treatment of the disease. In this Hypothesis and Theory paper, we discuss what we perceive as barriers to impactful discovery in rodent AD research and we offer solutions for moving forward. Although no single model of AD is capable of providing the solution to the growing epidemic of the disease, we encourage a comprehensive approach that acknowledges the complex etiology of AD with the goal of enhancing the bidirectional translatability from bench to bedside and vice versa.

  16. A process-model based approach to prospective memory impairment in Parkinson's disease.

    Science.gov (United States)

    Kliegel, Matthias; Altgassen, Mareike; Hering, Alexandra; Rose, Nathan S

    2011-07-01

    The present review discusses the current state of research on the clinical neuropsychology of prospective memory in Parkinson's disease. To do so the paper is divided in two sections. In the first section, we briefly outline key features of the (partly implicit) rationale underlying the available literature on the clinical neuropsychology of prospective memory. Here, we present a conceptual model that guides our approach to the clinical neuropsychology of prospective memory in general and to the effects of Parkinson's disease on prospective memory in particular. In the second section, we use this model to guide our review of the available literature and suggest some open issues and future directions motivated by previous findings and the proposed conceptual model. The review suggests that certain phases of the prospective memory process (intention formation und initiation) are particularly impaired by Parkinson's disease. In addition, it is argued that prospective memory may be preserved when tasks involve specific features (e.g., focal cues) that reduce the need for strategic monitoring processes. In terms of suggestions for future directions, it is noted that intervention studies are needed which target the specific phases of the prospective memory process that are impaired in Parkinson's disease, such as planning interventions. Moreover, it is proposed that prospective memory deficits in Parkinson's disease should be explored in the context of a general impairment in the ability to form an intention and plan or coordinate an appropriate series of actions. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. Malaria Disease Mapping in Malaysia based on Besag-York-Mollie (BYM) Model

    Science.gov (United States)

    Azah Samat, Nor; Mey, Liew Wan

    2017-09-01

    Disease mapping is the visual representation of the geographical distribution which give an overview info about the incidence of disease within a population through spatial epidemiology data. Based on the result of map, it helps in monitoring and planning resource needs at all levels of health care and designing appropriate interventions, tailored towards areas that deserve closer scrutiny or communities that lead to further investigations to identify important risk factors. Therefore, the choice of statistical model used for relative risk estimation is important because production of disease risk map relies on the model used. This paper proposes Besag-York-Mollie (BYM) model to estimate the relative risk for Malaria in Malaysia. The analysis involved using the number of Malaria cases that obtained from the Ministry of Health Malaysia. The outcomes of analysis are displayed through graph and map, including Malaria disease risk map that constructed according to the estimation of relative risk. The distribution of high and low risk areas of Malaria disease occurrences for all states in Malaysia can be identified in the risk map.

  18. Developing stochastic epidemiological models to quantify the dynamics of infectious diseases in domestic livestock.

    Science.gov (United States)

    MacKenzie, K; Bishop, S C

    2001-08-01

    A stochastic model describing disease transmission dynamics for a microparasitic infection in a structured domestic animal population is developed and applied to hypothetical epidemics on a pig farm. Rational decision making regarding appropriate control strategies for infectious diseases in domestic livestock requires an understanding of the disease dynamics and risk profiles for different groups of animals. This is best achieved by means of stochastic epidemic models. Methodologies are presented for 1) estimating the probability of an epidemic, given the presence of an infected animal, whether this epidemic is major (requires intervention) or minor (dies out without intervention), and how the location of the infected animal on the farm influences the epidemic probabilities; 2) estimating the basic reproductive ratio, R0 (i.e., the expected number of secondary cases on the introduction of a single infected animal) and the variability of the estimate of this parameter; and 3) estimating the total proportion of animals infected during an epidemic and the total proportion infected at any point in time. The model can be used for assessing impact of altering farm structure on disease dynamics, as well as disease control strategies, including altering farm structure, vaccination, culling, and genetic selection.

  19. Using the mouse to model human disease: increasing validity and reproducibility

    Directory of Open Access Journals (Sweden)

    Monica J. Justice

    2016-02-01

    Full Text Available Experiments that use the mouse as a model for disease have recently come under scrutiny because of the repeated failure of data, particularly derived from preclinical studies, to be replicated or translated to humans. The usefulness of mouse models has been questioned because of irreproducibility and poor recapitulation of human conditions. Newer studies, however, point to bias in reporting results and improper data analysis as key factors that limit reproducibility and validity of preclinical mouse research. Inaccurate and incomplete descriptions of experimental conditions also contribute. Here, we provide guidance on best practice in mouse experimentation, focusing on appropriate selection and validation of the model, sources of variation and their influence on phenotypic outcomes, minimum requirements for control sets, and the importance of rigorous statistics. Our goal is to raise the standards in mouse disease modeling to enhance reproducibility, reliability and clinical translation of findings.

  20. Being human: The role of pluripotent stem cells in regenerative medicine and humanizing Alzheimer's disease models.

    Science.gov (United States)

    Sproul, Andrew A

    2015-01-01

    Human pluripotent stem cells (PSCs) have the capacity to revolutionize medicine by allowing the generation of functional cell types such as neurons for cell replacement therapy. However, the more immediate impact of PSCs on treatment of Alzheimer's disease (AD) will be through improved human AD model systems for mechanistic studies and therapeutic screening. This review will first briefly discuss different types of PSCs and genome-editing techniques that can be used to modify PSCs for disease modeling or for personalized medicine. This will be followed by a more in depth analysis of current AD iPSC models and a discussion of the need for more complex multicellular models, including cell types such as microglia. It will finish with a discussion on current clinical trials using PSC-derived cells and the long-term potential of such strategies for treating AD. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Probability Model of Allele Frequency of Alzheimer’s Disease Genetic Risk Factor

    Directory of Open Access Journals (Sweden)

    Afshin Fayyaz-Movaghar

    2016-06-01

    Full Text Available Background and Purpose: The identification of genetics risk factors of human diseases is very important. This study is conducted to model the allele frequencies (AFs of Alzheimer’s disease. Materials and Methods: In this study, several candidate probability distributions are fitted on a data set of Alzheimer’s disease genetic risk factor. Unknown parameters of the considered distributions are estimated, and some criterions of goodness-of-fit are calculated for the sake of comparison. Results: Based on some statistical criterions, the beta distribution gives the best fit on AFs. However, the estimate values of the parameters of beta distribution lead us to the standard uniform distribution. Conclusion: The AFs of Alzheimer’s disease follow the standard uniform distribution.

  2. Patients' Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test.

    Science.gov (United States)

    Dou, Kaili; Yu, Ping; Deng, Ning; Liu, Fang; Guan, YingPing; Li, Zhenye; Ji, Yumeng; Du, Ningkai; Lu, Xudong; Duan, Huilong

    2017-12-06

    Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients' acceptance of smartphone health technology for chronic disease management. Multiple theories and factors that may influence patients' acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients' acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients' actual use of a smartphone health app. The partial least square method was used to test the theoretical model. The model accounted for .412 of the variance in patients' intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients' smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients' intentions to use the technology. Age and gender had no significant influence on patients' acceptance of smartphone technology. The study also confirmed the positive relationship between intention to use

  3. Patients’ Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test

    Science.gov (United States)

    Dou, Kaili; Yu, Ping; Liu, Fang; Guan, YingPing; Li, Zhenye; Ji, Yumeng; Du, Ningkai; Lu, Xudong; Duan, Huilong

    2017-01-01

    Background Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. Objective The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients’ acceptance of smartphone health technology for chronic disease management. Methods Multiple theories and factors that may influence patients’ acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients’ acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients’ actual use of a smartphone health app. The partial least square method was used to test the theoretical model. Results The model accounted for .412 of the variance in patients’ intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients’ smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients’ intentions to use the technology. Age and gender had no significant influence on patients’ acceptance of smartphone technology. The study also

  4. Preventive Role of Indian Black Pepper in Animal Models of Alzheimer’s Disease

    Science.gov (United States)

    Suresh, RN; MK, Jayanthi; HL, Kalabharathi; AM, Satish; VH, Pushpa

    2015-01-01

    Introduction: Dementia is the clinical symptom of alzheimer’s disease. Brain cholinesterase levels and behavioural changes are the markers for Alzheimer’s disease and aluminium chloride is one causative agent for polymerization of tau protein and amyloid plaque formation in Alzheimer’s disease. Effect of piper nigrum and its role in prevention of alzhimer’s disease and symptoms are well linked in this study. Aim: To study the effect of piper nigrum for the prevention of alzheimer’s associated histopathological, biochemical and behaviour changes in rat model. Materials and Methods: Twenty four rats were taken in this study. Their baseline behavioural parameters were noted and group was separated randomly in four. Rats were pretreated with piper nigrum and Alzheimer’s disease was induced. Biochemical and histopathological changes were noted at the end of experiment. Results: There was marked decrease in cholinesterase level, amyloidal plaque formation in rats brain who were pretreated with piper nigrum. At the same time there was decrease in escape latency time (ELT) and increase in memory in piper treated rats. Conclusion: Piper nigrum prove to be effective for prevention of Alzheimer’s disease. This finding has to be confirmed with studies including larger population. Further research on cholinesterase inhibitors, role of flavonoids on prevention of neurodegeneration in Alzheimer’s disease can be encouraged. PMID:26023568

  5. Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated with Eribulin

    NARCIS (Netherlands)

    Van Hasselt, J. G C; Gupta, A.; Hussein, Z.; Beijnen, J. H.; Schellens, J. H M; Huitema, A. D R

    2015-01-01

    Frameworks that associate cancer dynamic disease progression models with parametric survival models for clinical outcome have recently been proposed to support decision making in early clinical development. Here we developed such a disease progression clinical outcome model for castration-resistant

  6. 77 FR 41985 - Use of Influenza Disease Models To Quantitatively Evaluate the Benefits and Risks of Vaccines: A...

    Science.gov (United States)

    2012-07-17

    ... models to generate quantitative estimates of the benefits and risks of influenza vaccination. The public...] Use of Influenza Disease Models To Quantitatively Evaluate the Benefits and Risks of Vaccines: A... Influenza Disease Models to Quantitatively Evaluate the Benefits and Risks of Vaccines: A Technical Workshop...

  7. Continuous-Time Semi-Markov Models in Health Economic Decision Making : An Illustrative Example in Heart Failure Disease Management

    NARCIS (Netherlands)

    Cao, Qi; Buskens, Erik; Feenstra, Talitha; Jaarsma, Tiny; Hillege, Hans; Postmus, Douwe

    Continuous-time state transition models may end up having large unwieldy structures when trying to represent all relevant stages of clinical disease processes by means of a standard Markov model. In such situations, a more parsimonious, and therefore easier-to-grasp, model of a patient's disease

  8. PARKINSON’S DISEASE MODELS OF ABNORMAL PROTEIN AGGREGATION IN THE GOTTINGEN MINIPIG CNS

    DEFF Research Database (Denmark)

    Glud, Andreas Nørgaard; Landau, Anne M.; Lillethorup, Thea Pinholt

    2015-01-01

    Background: Parkinson's disease (PD) animal models are important translational steps toward clinical applications. The Göttingen minipig(GM) has a large gyrencephalic brain (6x5x4cm) that can be examined using conventional scanning modalities. Preclinical neuromodulatory devices can be evaluated...... and histological signs of PD including aSYN accumulation. Discussion: We predict that these animal models will be beneficial in the understanding of pathological mechanisms of human PD and in the testing of novel therapeutic strategies....

  9. A ketogenic diet reduces amyloid beta 40 and 42 in a mouse model of Alzheimer's disease

    OpenAIRE

    Van Leuven Fred; Wera Stefaan; Van der Auwera Ingrid; Henderson Samuel T

    2005-01-01

    Abstract Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily strikes the elderly. Studies in both humans and animal models have linked the consumption of cholesterol and saturated fats with amyloid-β (Aβ) deposition and development of AD. Yet, these studies did not examine high fat diets in combination with reduced carbohydrate intake. Here we tested the effect of a high saturated fat/low carbohydrate diet on a transgenic mouse model of AD. Results S...

  10. Mathematical models used to inform study design or surveillance systems in infectious diseases: a systematic review.

    Science.gov (United States)

    Herzog, Sereina A; Blaizot, Stéphanie; Hens, Niel

    2017-12-18

    Mathematical models offer the possibility to investigate the infectious disease dynamics over time and may help in informing design of studies. A systematic review was performed in order to determine to what extent mathematical models have been incorporated into the process of planning studies and hence inform study design for infectious diseases transmitted between humans and/or animals. We searched Ovid Medline and two trial registry platforms (Cochrane, WHO) using search terms related to infection, mathematical model, and study design from the earliest dates to October 2016. Eligible publications and registered trials included mathematical models (compartmental, individual-based, or Markov) which were described and used to inform the design of infectious disease studies. We extracted information about the investigated infection, population, model characteristics, and study design. We identified 28 unique publications but no registered trials. Focusing on compartmental and individual-based models we found 12 observational/surveillance studies and 11 clinical trials. Infections studied were equally animal and human infectious diseases for the observational/surveillance studies, while all but one between humans for clinical trials. The mathematical models were used to inform, amongst other things, the required sample size (n = 16), the statistical power (n = 9), the frequency at which samples should be taken (n = 6), and from whom (n = 6). Despite the fact that mathematical models have been advocated to be used at the planning stage of studies or surveillance systems, they are used scarcely. With only one exception, the publications described theoretical studies, hence, not being utilised in real studies.

  11. Genetic human prion disease modelled in PrP transgenic Drosophila.

    Science.gov (United States)

    Thackray, Alana M; Cardova, Alzbeta; Wolf, Hanna; Pradl, Lydia; Vorberg, Ina; Jackson, Walker S; Bujdoso, Raymond

    2017-09-20

    Inherited human prion diseases, such as fatal familial insomnia (FFI) and familial Creutzfeldt-Jakob disease (fCJD), are associated with autosomal dominant mutations in the human prion protein gene PRNP and accumulation of PrP Sc , an abnormal isomer of the normal host protein PrP C , in the brain of affected individuals. PrP Sc is the principal component of the transmissible neurotoxic prion agent. It is important to identify molecular pathways and cellular processes that regulate prion formation and prion-induced neurotoxicity. This will allow identification of possible therapeutic interventions for individuals with, or at risk from, genetic human prion disease. Increasingly, Drosophila has been used to model human neurodegenerative disease. An important unanswered question is whether genetic prion disease with concomitant spontaneous prion formation can be modelled in Drosophila We have used pUAST/PhiC31-mediated site-directed mutagenesis to generate Drosophila transgenic for murine or hamster PrP (prion protein) that carry single-codon mutations associated with genetic human prion disease. Mouse or hamster PrP harbouring an FFI (D178N) or fCJD (E200K) mutation showed mild Proteinase K resistance when expressed in Drosophila Adult Drosophila transgenic for FFI or fCJD variants of mouse or hamster PrP displayed a spontaneous decline in locomotor ability that increased in severity as the flies aged. Significantly, this mutant PrP-mediated neurotoxic fly phenotype was transferable to recipient Drosophila that expressed the wild-type form of the transgene. Collectively, our novel data are indicative of the spontaneous formation of a PrP-dependent neurotoxic phenotype in FFI- or CJD-PrP transgenic Drosophila and show that inherited human prion disease can be modelled in this invertebrate host. © 2017 The Author(s).

  12. Dieback Disease Predictive Model for Sexually and Asexually Propagated Dalbergia Sissoo (Shisham)

    International Nuclear Information System (INIS)

    Ahmad, I.; Siddiqui, M. T.; Nawaz, M. F.; Asif, M.; Atiq, M.; Gul, S.

    2016-01-01

    Dieback disease is a potential threat to Dalbergia sissoo (Shisham) which is a multipurpose tree of the Indian subcontinent. Different factors have been found associated with inciting shisham dieback. Fungal pathogens have been recognized as the major causal organism but changing climate is a main threat to forest dieback. Sexually (seedlings) and asexually (cuttings) propagated shisham were inoculated with the different fungi (Fusarium solani, Botryodiplodia theobromae, Curvularia lunata and Ganoderma lucidum). As environmental factors play critical role in the development of the disease, so the present study was designed to observe the impact of rainfall, temperature, relative humidity and wind velocity on the disease and for the management of disease predictive model was developed. A significant negative correlation was observed between disease and relative humidity both for seedlings (r = - 0.97) and cuttings (r = -0.487), respectively while maximum temperature expressed significant positive correlation with seedlings and cuttings with coefficient of correlation r = 0.734 and r = 0.629, respectively. Path analysis expressed that with one unit increase in rainfall the disease would rise by 7.58 and 15.04 and for maximum temperature it was 2.47 and 5.27 units in seedlings and cuttings, respectively. Multiple regression analysis showed that coefficient of determination (R/sup 2/) value was 0.62 and 0.48 for cuttings and seedlings, respectively. Normed fit index (NFI) and comparative fit index (CFI) values indicate that model is quite a good fit. Similarly comparison of observed and predicted data also validated the model for forecasting the disease. (author)

  13. Developing and evaluating polygenic risk prediction models for stratified disease prevention.

    Science.gov (United States)

    Chatterjee, Nilanjan; Shi, Jianxin; García-Closas, Montserrat

    2016-07-01

    Knowledge of genetics and its implications for human health is rapidly evolving in accordance with recent events, such as discoveries of large numbers of disease susceptibility loci from genome-wide association studies, the US Supreme Court ruling of the non-patentability of human genes, and the development of a regulatory framework for commercial genetic tests. In anticipation of the increasing relevance of genetic testing for the assessment of disease risks, this Review provides a summary of the methodologies used for building, evaluating and applying risk prediction models that include information from genetic testing and environmental risk factors. Potential applications of models for primary and secondary disease prevention are illustrated through several case studies, and future challenges and opportunities are discussed.

  14. The SIR model of Zika virus disease outbreak in Brazil at year 2015

    Science.gov (United States)

    Aik, Lim Eng; Kiang, Lam Chee; Hong, Tan Wei; Abu, Mohd Syafarudy

    2017-05-01

    This research study demonstrates a numerical model intended for comprehension the spread of the year 2015 Zika virus disease utilizing the standard SIR framework. In modeling virulent disease dynamics, it is important to explore whether the illness spread could accomplish a pandemic level or it could be eradicated. Information from the year 2015 Zika virus disease event is utilized and Brazil where the event began is considered in this research study. A three dimensional nonlinear differential equation is formulated and solved numerically utilizing the Euler's method in MS excel. It is appeared from the research study that, with health intercessions of public, the viable regenerative number can be decreased making it feasible for the event to cease to exist. It is additionally indicated numerically that the pandemic can just cease to exist when there are no new infected people in the populace.

  15. Statistical Fractal Models Based on GND-PCA and Its Application on Classification of Liver Diseases

    Directory of Open Access Journals (Sweden)

    Huiyan Jiang

    2013-01-01

    Full Text Available A new method is proposed to establish the statistical fractal model for liver diseases classification. Firstly, the fractal theory is used to construct the high-order tensor, and then Generalized -dimensional Principal Component Analysis (GND-PCA is used to establish the statistical fractal model and select the feature from the region of liver; at the same time different features have different weights, and finally, Support Vector Machine Optimized Ant Colony (ACO-SVM algorithm is used to establish the classifier for the recognition of liver disease. In order to verify the effectiveness of the proposed method, PCA eigenface method and normal SVM method are chosen as the contrast methods. The experimental results show that the proposed method can reconstruct liver volume better and improve the classification accuracy of liver diseases.

  16. Animal models of gastrointestinal and liver diseases. Animal models of acute and chronic pancreatitis

    Science.gov (United States)

    Zhan, Xianbao; Wang, Fan; Bi, Yan

    2016-01-01

    Animal models of pancreatitis are useful for elucidating the pathogenesis of pancreatitis and developing and testing novel interventions. In this review, we aim to summarize the most commonly used animal models, overview their pathophysiology, and discuss their strengths and limitations. We will also briefly describe common animal study procedures and refer readers to more detailed protocols in the literature. Although animal models include pigs, dogs, opossums, and other animals, we will mainly focus on rodent models because of their popularity. Autoimmune pancreatitis and genetically engineered animal models will be reviewed elsewhere. PMID:27418683

  17. Animal models of gastrointestinal and liver diseases. Animal models of acute and chronic pancreatitis.

    Science.gov (United States)

    Zhan, Xianbao; Wang, Fan; Bi, Yan; Ji, Baoan

    2016-09-01

    Animal models of pancreatitis are useful for elucidating the pathogenesis of pancreatitis and developing and testing novel interventions. In this review, we aim to summarize the most commonly used animal models, overview their pathophysiology, and discuss their strengths and limitations. We will also briefly describe common animal study procedures and refer readers to more detailed protocols in the literature. Although animal models include pigs, dogs, opossums, and other animals, we will mainly focus on rodent models because of their popularity. Autoimmune pancreatitis and genetically engineered animal models will be reviewed elsewhere. Copyright © 2016 the American Physiological Society.

  18. A retrospective study and predictive modelling of Newcastle Disease trends among rural poultry of eastern Zambia.

    Science.gov (United States)

    Mubamba, C; Ramsay, G; Abolnik, C; Dautu, G; Gummow, B

    2016-10-01

    Newcastle Disease (ND) is a highly infectious disease of poultry that seriously impacts on food security and livelihoods of livestock farmers and communities in tropical regions of the world. ND is a constant problem in the eastern province of Zambia which has more than 740 000 rural poultry. Very few studies give a situational analysis of the disease that can be used for disease control planning in the region. With this background in mind, a retrospective epidemiological study was conducted using Newcastle Disease data submitted to the eastern province headquarters for the period from 1989 to 2014. The study found that Newcastle Disease cases in eastern Zambia followed a seasonal and cyclic pattern with peaks in the hot dry season (Overall Seasonal Index 1.1) as well as cycles every three years with an estimated provincial incidence range of 0.16 to 1.7% per year. Annual trends were compared with major intervention policies implemented by the Zambian government, which often received donor support from the international community during the study period. Aid delivered through government programmes appeared to have no major impact on ND trends between 1989 and 2014 and reasons for this are discussed. There were apparent spatial shifts in districts with outbreaks over time which could be as a result of veterinary interventions chasing outbreaks rather than implementing uniform control. Data was also fitted to a predictive time series model for ND which could be used to plan for future ND control. Time series modelling showed an increasing trend in ND annual incidence over 25 years if existing interventions continue. A different approach to controlling the disease is needed if this trend is to be halted. Conversely, the positive trend may be a function of improved reporting by farmers as a result of more awareness of the disease. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Sensitivity analysis of infectious disease models: methods, advances and their application

    Science.gov (United States)

    Wu, Jianyong; Dhingra, Radhika; Gambhir, Manoj; Remais, Justin V.

    2013-01-01

    Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design. PMID:23864497

  20. Drug-disease modeling in the pharmaceutical industry - where mechanistic systems pharmacology and statistical pharmacometrics meet.

    Science.gov (United States)

    Helmlinger, Gabriel; Al-Huniti, Nidal; Aksenov, Sergey; Peskov, Kirill; Hallow, Karen M; Chu, Lulu; Boulton, David; Eriksson, Ulf; Hamrén, Bengt; Lambert, Craig; Masson, Eric; Tomkinson, Helen; Stanski, Donald

    2017-11-15

    Modeling & simulation (M&S) methodologies are established quantitative tools, which have proven to be useful in supporting the research, development (R&D), regulatory approval, and marketing of novel therapeutics. Applications of M&S help design efficient studies and interpret their results in context of all available data and knowledge to enable effective decision-making during the R&D process. In this mini-review, we focus on two sets of modeling approaches: population-based models, which are well-established within the pharmaceutical industry today, and fall under the discipline of clinical pharmacometrics (PMX); and systems dynamics models, which encompass a range of models of (patho-)physiology amenable to pharmacological intervention, of signaling pathways in biology, and of substance distribution in the body (today known as physiologically-based pharmacokinetic models) - which today may be collectively referred to as quantitative systems pharmacology models (QSP). We next describe the convergence - or rather selected integration - of PMX and QSP approaches into 'middle-out' drug-disease models, which retain selected mechanistic aspects, while remaining parsimonious, fit-for-purpose, and able to address variability and the testing of covariates. We further propose development opportunities for drug-disease systems models, to increase their utility and applicability throughout the preclinical and clinical spectrum of pharmaceutical R&D. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Drosophila as a Model for Human Diseases-Focus on Innate Immunity in Barrier Epithelia.

    Science.gov (United States)

    Bergman, P; Seyedoleslami Esfahani, S; Engström, Y

    2017-01-01

    Epithelial immunity protects the host from harmful microbial invaders but also controls the beneficial microbiota on epithelial surfaces. When this delicate balance between pathogen and symbiont is disturbed, clinical disease often occurs, such as in inflammatory bowel disease, cystic fibrosis, or atopic dermatitis, which all can be in part linked to impairment of barrier epithelia. Many innate immune receptors, signaling pathways, and effector molecules are evolutionarily conserved between human and Drosophila. This review describes the current knowledge on Drosophila as a model for human diseases, with a special focus on innate immune-related disorders of the gut, lung, and skin. The discovery of antimicrobial peptides, the crucial role of Toll and Toll-like receptors, and the evolutionary conservation of signaling to the immune systems of both human and Drosophila are described in a historical perspective. Similarities and differences between human and Drosophila are discussed; current knowledge on receptors, signaling pathways, and effectors are reviewed, including antimicrobial peptides, reactive oxygen species, as well as autophagy. We also give examples of human diseases for which Drosophila appears to be a useful model. In addition, the limitations of the Drosophila model are mentioned. Finally, we propose areas for future research, which include using the Drosophila model for drug screening, as a validation tool for novel genetic mutations in humans and for exploratory research of microbiota-host interactions, with relevance for infection, wound healing, and cancer. © 2017 Elsevier Inc. All rights reserved.

  2. Strain Differences in Antioxidants in Rat Models of Cardiovascular Disease Exposed to Ozone

    Science.gov (United States)

    We examined the hypothesis that antioxidant substances and enzymes in lung, heart and in bronchoalveolar lavage fluid (BALF) are altered in response to 03 in cardiovascular disease and/or metabolic syndrome (CVD)-prone rat models. CVD strains [spontaneously hypertensive (SH), SH ...

  3. Vascular risk factors and Alzheimer’s disease. Therapeutic approaches in mouse models

    NARCIS (Netherlands)

    Wiesmann, M.

    2017-01-01

    The first aim of this thesis was to elucidate the impact of major vascular risk factors like hypertension, apoE4 and stroke during the very early phase of Alzheimer’s disease (AD) using several mice models. Hypertension has proven to be associated with cerebrovascular impairment already at young age

  4. Review of Mouse Models of Graves' Disease and Orbitopathy-Novel Treatment by Induction of Tolerance.

    Science.gov (United States)

    Ungerer, Martin; Faßbender, Julia; Li, Zhongmin; Münch, Götz; Holthoff, Hans-Peter

    2017-04-01

    Various approaches have been used to model human Graves' disease in mice, including transfected fibroblasts, and plasmid or adenoviral immunisations with the extracellular A subunit of the human thyrotropin receptor (TSHR). Some of these models were only observed for a short time period or were self-limiting. A long-term model for human Graves' disease was established in mice using continuing immunisations (4-weekly injections) with recombinant adenovirus expressing TSHR. Generation of TSHR binding cAMP-stimulatory antibodies, thyroid enlargement and alterations, elevated serum thyroxin levels, tachycardia and cardiac hypertrophy were maintained for at least 9 months in all Ad-TSHR-immunised mice. Here, we show that these mice suffer from orbitopathy, which was detected by serial orbital sectioning and histomorphometry. Attempts to treat established Graves' disease in preclinical mouse model studies have included small molecule allosteric antagonists and specific antagonist antibodies which were isolated from hypothyroid patients. In addition, novel peptides have been conceived which mimic the cylindrical loops of the TSHR leucine-rich repeat domain, in order to re-establish tolerance toward the antigen. Here, we show preliminary results that one set of these peptides improves or even cures all signs and symptoms of Graves' disease in mice after six consecutive monthly injections. First beneficial effects were observed 3-4 months after starting these therapies. In immunologically naïve mice, administration of the peptides did not induce any immune response.

  5. Models to Predict the Burden of Cardiovascular Disease Risk in a Rural Mountainous Region of Vietnam

    NARCIS (Netherlands)

    Nguyen, Thi Phuong Lan; Schuiling-Veninga, Nynke; Nguyen, Thi Bach Yen; Hang, Vu Thi Thu; Wright, E. Pamela; Postma, M.J.

    2014-01-01

    Objective: To compare and identify the most appropriate model to predict cardiovascular disease (CVD) in a rural area in Northern Vietnam, using data on hypertension from the communities. Methods: A cross-sectional survey was conducted including all residents in selected communities, aged 34 to 65

  6. PARKINSON’S DISEASE MODELS OF ABNORMAL PROTEIN AGGREGATION IN THE GOTTINGEN MINIPIG CNS

    DEFF Research Database (Denmark)

    Glud, Andreas Nørgaard

    2015-01-01

    Background: Parkinson's disease (PD) animal models are important translational steps toward clinical applications. The Göttingen minipig(GM) has a large gyrencephalic brain (6x5x4cm) that can be examined using conventional scanning modalities. Preclinical neuromodulatory devices can be evaluated ...

  7. Stability analysis of a general age-dependent vaccination model of a vertically transmitted disease

    International Nuclear Information System (INIS)

    El Doma, M.

    1995-07-01

    An SIR epidemic model of a general age-dependent vaccination of a vertically as well as horizontally transmitted disease is investigated when the population is in steady state and the fertility, mortality and removal rates depends on age. We determine the steady states and examine their stabilities. (author). 24 refs

  8. Bacteria, Yeast, Worms, and Flies: Exploiting Simple Model Organisms to Investigate Human Mitochondrial Diseases

    Science.gov (United States)

    Rea, Shane L.; Graham, Brett H.; Nakamaru-Ogiso, Eiko; Kar, Adwitiya; Falk, Marni J.

    2010-01-01

    The extensive conservation of mitochondrial structure, composition, and function across evolution offers a unique opportunity to expand our understanding of human mitochondrial biology and disease. By investigating the biology of much simpler model organisms, it is often possible to answer questions that are unreachable at the clinical level.…

  9. Development of the Dutch Johne's disease control program supported by a simulation model

    NARCIS (Netherlands)

    Groenendaal, H.; Nielen, M.; Hesselink, J.W.

    2003-01-01

    The development of a simulation model, "JohneSSim", was part of a research program aimed at designing a national Johne's disease control program for The Netherlands. Initially, the focus was mainly directed towards different compulsory "test-and-cull" strategies. However, the results from the

  10. Human iPSC-derived cardiomyocytes and tissue engineering strategies for disease modeling and drug screening.

    Science.gov (United States)

    Smith, Alec S T; Macadangdang, Jesse; Leung, Winnie; Laflamme, Michael A; Kim, Deok-Ho

    Improved methodologies for modeling cardiac disease phenotypes and accurately screening the efficacy and toxicity of potential therapeutic compounds are actively being sought to advance drug development and improve disease modeling capabilities. To that end, much recent effort has been devoted to the development of novel engineered biomimetic cardiac tissue platforms that accurately recapitulate the structure and function of the human myocardium. Within the field of cardiac engineering, induced pluripotent stem cells (iPSCs) are an exciting tool that offer the potential to advance the current state of the art, as they are derived from somatic cells, enabling the development of personalized medical strategies and patient specific disease models. Here we review different aspects of iPSC-based cardiac engineering technologies. We highlight methods for producing iPSC-derived cardiomyocytes (iPSC-CMs) and discuss their application to compound efficacy/toxicity screening and in vitro modeling of prevalent cardiac diseases. Special attention is paid to the application of micro- and nano-engineering techniques for the development of novel iPSC-CM based platforms and their potential to advance current preclinical screening modalities. Published by Elsevier Inc.

  11. Towards a Hybrid Agent-based Model for Mosquito Borne Disease.

    Science.gov (United States)

    Mniszewski, S M; Manore, C A; Bryan, C; Del Valle, S Y; Roberts, D

    2014-07-01

    Agent-based models (ABM) are used to simulate the spread of infectious disease through a population. Detailed human movement, demography, realistic business location networks, and in-host disease progression are available in existing ABMs, such as the Epidemic Simulation System (EpiSimS). These capabilities make possible the exploration of pharmaceutical and non-pharmaceutical mitigation strategies used to inform the public health community. There is a similar need for the spread of mosquito borne pathogens due to the re-emergence of diseases such as chikungunya and dengue fever. A network-patch model for mosquito dynamics has been coupled with EpiSimS. Mosquitoes are represented as a "patch" or "cloud" associated with a location. Each patch has an ordinary differential equation (ODE) mosquito dynamics model and mosquito related parameters relevant to the location characteristics. Activities at each location can have different levels of potential exposure to mosquitoes based on whether they are inside, outside, or somewhere in-between. As a proof of concept, the hybrid network-patch model is used to simulate the spread of chikungunya through Washington, DC. Results are shown for a base case, followed by varying the probability of transmission, mosquito count, and activity exposure. We use visualization to understand the pattern of disease spread.

  12. An analytic method for agent-based modeling of spatially inhomogeneous disease dynamics

    NARCIS (Netherlands)

    Bock, W.; Fattler, T.; Rodiah, I.; Tse, O.T.C.; Villagonzalo, C.D.; Esguerra, J.P.H.; Soriano, M.N.; Bornales, J.B.; Carpio-Bernido, M.V.; Bernido, C.C.

    2017-01-01

    In this article we set up a microscopic model for the spread of an infectious disease based on configuration space analysis. Using the so-called Vlasov scaling we obtained the corresponding mesoscopic (kinetic) equations, describing the density of susceptible and infected individuals (particles) in

  13. Global dynamics of multi-group SEI animal disease models with indirect transmission

    International Nuclear Information System (INIS)

    Wang, Yi; Cao, Jinde

    2014-01-01

    A challenge to multi-group epidemic models in mathematical epidemiology is the exploration of global dynamics. Here we formulate multi-group SEI animal disease models with indirect transmission via contaminated water. Under biologically motivated assumptions, the basic reproduction number R 0 is derived and established as a sharp threshold that completely determines the global dynamics of the system. In particular, we prove that if R 0 <1, the disease-free equilibrium is globally asymptotically stable, and the disease dies out; whereas if R 0 >1, then the endemic equilibrium is globally asymptotically stable and thus unique, and the disease persists in all groups. Since the weight matrix for weighted digraphs may be reducible, the afore-mentioned approach is not directly applicable to our model. For the proofs we utilize the classical method of Lyapunov, graph-theoretic results developed recently and a new combinatorial identity. Since the multiple transmission pathways may correspond to the real world, the obtained results are of biological significance and possible generalizations of the model are also discussed

  14. Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.

    Science.gov (United States)

    Carvalho, B M; Rangel, E F; Vale, M M

    2017-08-01

    Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

  15. Dual purpose use of preterm piglets as a model of pediatric GI disease

    DEFF Research Database (Denmark)

    Oosterloo, Berthe C; Premkumar, Muralidhar; Stoll, Barbara

    2014-01-01

    Necrotizing enterocolitis (NEC) is the most common gastrointestinal complication in human neonates, yet the pathogenesis of this disease remains poorly understood. A fundamental approach to understanding the etiology and underlying biology of NEC is the use of in vivo experimental animal models, ...

  16. Impact of the gut microbiota on rodent models of human disease.

    Science.gov (United States)

    Hansen, Axel Kornerup; Hansen, Camilla Hartmann Friis; Krych, Lukasz; Nielsen, Dennis Sandris

    2014-12-21

    Traditionally bacteria have been considered as either pathogens, commensals or symbionts. The mammal gut harbors 10(14) organisms dispersed on approximately 1000 different species. Today, diagnostics, in contrast to previous cultivation techniques, allow the identification of close to 100% of bacterial species. This has revealed that a range of animal models within different research areas, such as diabetes, obesity, cancer, allergy, behavior and colitis, are affected by their gut microbiota. Correlation studies may for some diseases show correlation between gut microbiota composition and disease parameters higher than 70%. Some disease phenotypes may be transferred when recolonizing germ free mice. The mechanistic aspects are not clear, but some examples on how gut bacteria stimulate receptors, metabolism, and immune responses are discussed. A more deeper understanding of the impact of microbiota has its origin in the overall composition of the microbiota and in some newly recognized species, such as Akkermansia muciniphila, Segmented filamentous bacteria and Faecalibacterium prausnitzii, which seem to have an impact on more or less severe disease in specific models. Thus, the impact of the microbiota on animal models is of a magnitude that cannot be ignored in future research. Therefore, either models with specific microbiota must be developed, or the microbiota must be characterized in individual studies and incorporated into data evaluation.

  17. Modeling the Disease Course of Zaire ebolavirus Infection in the Outbred Guinea Pig.

    Science.gov (United States)

    Cross, Robert W; Fenton, Karla A; Geisbert, Joan B; Mire, Chad E; Geisbert, Thomas W

    2015-10-01

    Rodent models that accurately reflect human filovirus infection are needed as early screens for medical countermeasures. Prior work in rodents with the Zaire species of Ebola virus (ZEBOV) primarily used inbred mice and guinea pigs to model disease. However, these inbred species do not show some of the important features of primate ZEBOV infection, most notably, coagulation abnormalities. Thirty-six outbred guinea pigs were infected with guinea pig-adapted ZEBOV and examined sequentially over an 8-day period to investigate the pathologic events that lead to death. Features of disease in ZEBOV-infected outbred guinea pigs were largely consistent with disease in humans and nonhuman primates and included early infection of macrophages and dendritiform cells, apoptosis of bystander lymphocytes, and increases in levels of proinflammatory cytokines. Most importantly, dysregulation of circulating levels of fibrinogen, protein C activity, and antifibrinolytic proteins and deposition of fibrin in tissues demonstrated both biochemical and microscopic evidence of disseminated intravascular coagulation. These findings suggest that the outbred guinea pig model recapitulates ZEBOV infection of primates better than inbred rodent models, is useful for dissecting key events in the pathogenesis of ZEBOV, and is useful for evaluating candidate interventions prior to assessment in primates. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  18. Aspergillus in chronic lung disease: Modeling what goes on in the airways.

    Science.gov (United States)

    Takazono, Takahiro; Sheppard, Donald C

    2017-01-01

    Aspergillus species cause a range of respiratory diseases in humans. While immunocompromised patients are at risk for the development of invasive infection with these opportunistic molds, patients with underlying pulmonary disease can develop chronic airway infection with Aspergillus species. These conditions span a range of inflammatory and allergic diseases including Aspergillus bronchitis, allergic bronchopulmonary aspergillosis, and severe asthma with fungal sensitization. Animal models are invaluable tools for the study of the molecular mechanism underlying the colonization of airways by Aspergillus and the host response to these non-invasive infections. In this review we summarize the state-of-the-art with respect to the available animal models of noninvasive and allergic Aspergillus airway disease; the key findings of host-pathogen interaction studies using these models; and the limitations and future directions that should guide the development and use of models for the study of these important pulmonary conditions. © The Author 2016. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Sensitivity of Disease Parameters to Flexible Budesonide/Formoterol Treatment in an Allergic Rat Model

    OpenAIRE

    Brange , Charlotte; Smailagic , Amir; Jansson , Anne-Helene; Middleton , Brian; Miller-Larsson , Anna; Taylor , John D.; Silberstein , David S.; Lal , Harbans

    2009-01-01

    Sensitivity of Disease Parameters to Flexible Budesonide/Formoterol Treatment in an Allergic Rat Model correspondance: Corresponding author. Tel.: +46 46 33 6256; fax: +46 46 33 6624. (Brange, Charlotte) (Brange, Charlotte) AstraZeneca R&D Lund--> , Lund--> - SWEDEN (Brange, Charlotte) AstraZeneca R&D Lund--> , Lund--> - SWEDEN (Brange, Charlotte) AstraZeneca R&D Lun...

  20. Chronic kidney disease Markov model comparing paricalcitol to calcitriol for secondary hyperparathyroidism: A US perspective

    NARCIS (Netherlands)

    M.J.C. Nuijten (Mark); D.L. Andress (Dennis); S.E. Marx (Steven); R. Sterz (Raimund)

    2009-01-01

    textabstractObjective: The objective of this study was to determine the cost effectiveness of paricalcitol versus calcitriol for the treatment of secondary hyperparathyroidism in patients with chronic kidney disease in the United States setting. Methods: A Markov process model was developed