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.

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.

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.

A rat model system to study complex disease risks, fitness, aging, and longevity.

Science.gov (United States)

Koch, Lauren Gerard; Britton, Steven L; Wisløff, Ulrik

2012-02-01

The association between low exercise capacity and all-cause morbidity and mortality is statistically strong yet mechanistically unresolved. By connecting clinical observation with a theoretical base, we developed a working hypothesis that variation in capacity for oxygen metabolism is the central mechanistic determinant between disease and health (aerobic hypothesis). As an unbiased test, we show that two-way artificial selective breeding of rats for low and high intrinsic endurance exercise capacity also produces rats that differ for numerous disease risks, including the metabolic syndrome, cardiovascular complications, premature aging, and reduced longevity. This contrasting animal model system may prove to be translationally superior relative to more widely used simplistic models for understanding geriatric biology and medicine. Copyright © 2012 Elsevier Inc. All rights reserved.

Disease processes as hybrid dynamical systems

Directory of Open Access Journals (Sweden)

Pietro Liò

2012-08-01

Full Text Available We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.

Systems biology from micro-organisms to human metabolic diseases: the role of detailed kinetic models.

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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.

Prediction of population with Alzheimer's disease in the European Union using a system dynamics model.

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Tomaskova, Hana; Kuhnova, Jitka; Cimler, Richard; Dolezal, Ondrej; Kuca, Kamil

2016-01-01

Alzheimer's disease (AD) is a slowly progressing neurodegenerative brain disease with irreversible brain effects; it is the most common cause of dementia. With increasing age, the probability of suffering from AD increases. In this research, population growth of the European Union (EU) until the year 2080 and the number of patients with AD are modeled. The aim of this research is to predict the spread of AD in the EU population until year 2080 using a computer simulation. For the simulation of the EU population and the occurrence of AD in this population, a system dynamics modeling approach has been used. System dynamics is a useful and effective method for the investigation of complex social systems. Over the past decades, its applicability has been demonstrated in a wide variety of applications. In this research, this method has been used to investigate the growth of the EU population and predict the number of patients with AD. The model has been calibrated on the population prediction data created by Eurostat. Based on data from Eurostat, the EU population until year 2080 has been modeled. In 2013, the population of the EU was 508 million and the number of patients with AD was 7.5 million. Based on the prediction, in 2040, the population of the EU will be 524 million and the number of patients with AD will be 13.1 million. By the year 2080, the EU population will be 520 million and the number of patients with AD will be 13.7 million. System dynamics modeling approach has been used for the prediction of the number of patients with AD in the EU population till the year 2080. These results can be used to determine the economic burden of the treatment of these patients. With different input data, the simulation can be used also for the different regions as well as for different noncontagious disease predictions.

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

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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.

Large Mammalian Animal Models of Heart Disease

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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.

Neurophysiology of Drosophila models of Parkinson's disease.

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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.

Mathematical models used to inform study design or surveillance systems in infectious diseases: a systematic review.

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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.

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 ...

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.

Evaluation of models of Parkinson’s Disease

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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.

Disease modeling in genetic kidney diseases: zebrafish.

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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.

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

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

Optimal control on hybrid ode systems with application to a tick disease model.

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Ding, Wandi

2007-10-01

We are considering an optimal control problem for a type of hybrid system involving ordinary differential equations and a discrete time feature. One state variable has dynamics in only one season of the year and has a jump condition to obtain the initial condition for that corresponding season in the next year. The other state variable has continuous dynamics. Given a general objective functional, existence, necessary conditions and uniqueness for an optimal control are established. We apply our approach to a tick-transmitted disease model with age structure in which the tick dynamics changes seasonally while hosts have continuous dynamics. The goal is to maximize disease-free ticks and minimize infected ticks through an optimal control strategy of treatment with acaricide. Numerical examples are given to illustrate the results.

Disease Compass- a navigation system for disease knowledge based on ontology and linked data techniques.

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Kozaki, Kouji; Yamagata, Yuki; Mizoguchi, Riichiro; Imai, Takeshi; Ohe, Kazuhiko

2017-06-19

Medical ontologies are expected to contribute to the effective use of medical information resources that store considerable amount of data. In this study, we focused on disease ontology because the complicated mechanisms of diseases are related to concepts across various medical domains. The authors developed a River Flow Model (RFM) of diseases, which captures diseases as the causal chains of abnormal states. It represents causes of diseases, disease progression, and downstream consequences of diseases, which is compliant with the intuition of medical experts. In this paper, we discuss a fact repository for causal chains of disease based on the disease ontology. It could be a valuable knowledge base for advanced medical information systems. We developed the fact repository for causal chains of diseases based on our disease ontology and abnormality ontology. This section summarizes these two ontologies. It is developed as linked data so that information scientists can access it using SPARQL queries through an Resource Description Framework (RDF) model for causal chain of diseases. We designed the RDF model as an implementation of the RFM for the fact repository based on the ontological definitions of the RFM. 1554 diseases and 7080 abnormal states in six major clinical areas, which are extracted from the disease ontology, are published as linked data (RDF) with SPARQL endpoint (accessible API). Furthermore, the authors developed Disease Compass, a navigation system for disease knowledge. Disease Compass can browse the causal chains of a disease and obtain related information, including abnormal states, through two web services that provide general information from linked data, such as DBpedia, and 3D anatomical images. Disease Compass can provide a complete picture of disease-associated processes in such a way that fits with a clinician's understanding of diseases. Therefore, it supports user exploration of disease knowledge with access to pertinent information

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.

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.

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.

Systems pharmacology - Towards the modeling of network interactions.

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Danhof, Meindert

2016-10-30

Mechanism-based pharmacokinetic and pharmacodynamics (PKPD) and disease system (DS) models have been introduced in drug discovery and development research, to predict in a quantitative manner the effect of drug treatment in vivo in health and disease. This requires consideration of several fundamental properties of biological systems behavior including: hysteresis, non-linearity, variability, interdependency, convergence, resilience, and multi-stationarity. Classical physiology-based PKPD models consider linear transduction pathways, connecting processes on the causal path between drug administration and effect, as the basis of drug action. Depending on the drug and its biological target, such models may contain expressions to characterize i) the disposition and the target site distribution kinetics of the drug under investigation, ii) the kinetics of target binding and activation and iii) the kinetics of transduction. When connected to physiology-based DS models, PKPD models can characterize the effect on disease progression in a mechanistic manner. These models have been found useful to characterize hysteresis and non-linearity, yet they fail to explain the effects of the other fundamental properties of biological systems behavior. Recently systems pharmacology has been introduced as novel approach to predict in vivo drug effects, in which biological networks rather than single transduction pathways are considered as the basis of drug action and disease progression. These models contain expressions to characterize the functional interactions within a biological network. Such interactions are relevant when drugs act at multiple targets in the network or when homeostatic feedback mechanisms are operative. As a result systems pharmacology models are particularly useful to describe complex patterns of drug action (i.e. synergy, oscillatory behavior) and disease progression (i.e. episodic disorders). In this contribution it is shown how physiology-based PKPD and

Big Data for Infectious Disease Surveillance and Modeling.

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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.

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.

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

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.

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.

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

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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.

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

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.

Association between periodontal diseases and systemic diseases

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Patrícia Weidlich

2008-08-01

Full Text Available Current evidence suggests that periodontal disease may be associated with systemic diseases. This paper reviewed the published data about the relationship between periodontal disease and cardiovascular diseases, adverse pregnancy outcomes, diabetes and respiratory diseases, focusing on studies conducted in the Brazilian population. Only a few studies were found in the literature focusing on Brazilians (3 concerning cardiovascular disease, 7 about pregnancy outcomes, 9 about diabetes and one regarding pneumonia. Although the majority of them observed an association between periodontitis and systemic conditions, a causal relationship still needs to be demonstrated. Further studies, particularly interventional well-designed investigations, with larger sample sizes, need to be conducted in Brazilian populations.

Experimental models of autoimmune inflammatory ocular diseases

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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.

Animal Models of Cardiovascular Diseases

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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.

Interprofessional Collaborative Practice Models in Chronic Disease Management.

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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.

Systemic autoimmunity induced by the TLR7/8 agonist Resiquimod causes myocarditis and dilated cardiomyopathy in a new mouse model of autoimmune heart disease

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Muneer G. Hasham

2017-03-01

Full Text Available Systemic autoimmune diseases such as systemic lupus erythematosus (SLE and rheumatoid arthritis (RA show significant heart involvement and cardiovascular morbidity, which can be due to systemically increased levels of inflammation or direct autoreactivity targeting cardiac tissue. Despite high clinical relevance, cardiac damage secondary to systemic autoimmunity lacks inducible rodent models. Here, we characterise immune-mediated cardiac tissue damage in a new model of SLE induced by topical application of the Toll-like receptor 7/8 (TLR7/8 agonist Resiquimod. We observe a cardiac phenotype reminiscent of autoimmune-mediated dilated cardiomyopathy, and identify auto-antibodies as major contributors to cardiac tissue damage. Resiquimod-induced heart disease is a highly relevant mouse model for mechanistic and therapeutic studies aiming to protect the heart during autoimmunity.

Model systems to study immunomodulation in domestic food animals.

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Roth, J A; Flaming, K P

1990-01-01

Development of immunomodulators for use in food producing animals is an active area of research. This research has generally incorporated aspects of immunosuppression in model systems. This methodology is appropriate because most of the research has been aimed at developing immunomodulators for certain economically significant diseases in which immunosuppression is believed to be an important component of their pathogenesis. The primary focus has been on stress-associated diseases (especially bovine respiratory disease), infectious diseases in young animals, and mastitis. The model systems used have limitations, but they have demonstrated that immunomodulators are capable of significantly increasing resistance to these important infectious disease syndromes. As our understanding of molecular immunology increases and as more potential immunomodulators become available, the use of relevant model systems should greatly aid advancement in the field of immunomodulation.

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.

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)

Evolution of the archaeal and mammalian information processing systems: towards an archaeal model for human disease.

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Lyu, Zhe; Whitman, William B

2017-01-01

Current evolutionary models suggest that Eukaryotes originated from within Archaea instead of being a sister lineage. To test this model of ancient evolution, we review recent studies and compare the three major information processing subsystems of replication, transcription and translation in the Archaea and Eukaryotes. Our hypothesis is that if the Eukaryotes arose within the archaeal radiation, their information processing systems will appear to be one of kind and not wholly original. Within the Eukaryotes, the mammalian or human systems are emphasized because of their importance in understanding health. Biochemical as well as genetic studies provide strong evidence for the functional similarity of archaeal homologs to the mammalian information processing system and their dissimilarity to the bacterial systems. In many independent instances, a simple archaeal system is functionally equivalent to more elaborate eukaryotic homologs, suggesting that evolution of complexity is likely an central feature of the eukaryotic information processing system. Because fewer components are often involved, biochemical characterizations of the archaeal systems are often easier to interpret. Similarly, the archaeal cell provides a genetically and metabolically simpler background, enabling convenient studies on the complex information processing system. Therefore, Archaea could serve as a parsimonious and tractable host for studying human diseases that arise in the information processing systems.

Effect of diseases on symbiotic systems.

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Tiwari, Pankaj Kumar; Sasmal, Sourav Kumar; Sha, Amar; Venturino, Ezio; Chattopadhyay, Joydev

2017-09-01

There are many species living in symbiotic communities. In this study, we analyzed models in which populations are in the mutualism symbiotic relations subject to a disease spreading among one of the species. The main goal is the characterization of symbiotic relations of coexisting species through their mutual influences on their respective carrying capacities, taking into account that this influence can be quite strong. The functional dependence of the carrying capacities reflects the fact that the correlations between populations cannot be realized merely through direct interactions, as in the usual predator-prey Lotka-Volterra model, but also through the influence of each species on the carrying capacities of the other one. Equilibria are analyzed for feasibility and stability, substantiated via numerical simulations, and global sensitivity analysis identifies the important parameters having a significant impact on the model dynamics. The infective growth rate and the disease-related mortality rate may alter the stability behavior of the system. Our results show that introducing a symbiotic species is a plausible way to control the disease in the population. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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.

Systemic delivery of a glucosylceramide synthase inhibitor reduces CNS substrates and increases lifespan in a mouse model of type 2 Gaucher disease.

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Mario A Cabrera-Salazar

Full Text Available Neuropathic Gaucher disease (nGD, also known as type 2 or type 3 Gaucher disease, is caused by a deficiency of the enzyme glucocerebrosidase (GC. This deficiency impairs the degradation of glucosylceramide (GluCer and glucosylsphingosine (GluSph, leading to their accumulation in the brains of patients and mouse models of the disease. These accumulated substrates have been thought to cause the severe neuropathology and early death observed in patients with nGD and mouse models. Substrate accumulation is evident at birth in both nGD mouse models and humans affected with the most severe type of the disease. Current treatment of non-nGD relies on the intravenous delivery of recombinant human glucocerebrosidase to replace the missing enzyme or the administration of glucosylceramide synthase inhibitors to attenuate GluCer production. However, the currently approved drugs that use these mechanisms do not cross the blood brain barrier, and thus are not expected to provide a benefit for the neurological complications in nGD patients. Here we report the successful reduction of substrate accumulation and CNS pathology together with a significant increase in lifespan after systemic administration of a novel glucosylceramide synthase inhibitor to a mouse model of nGD. To our knowledge this is the first compound shown to cross the blood brain barrier and reduce substrates in this animal model while significantly enhancing its lifespan. These results reinforce the concept that systemically administered glucosylceramide synthase inhibitors could hold enhanced therapeutic promise for patients afflicted with neuropathic lysosomal storage diseases.

Systemic delivery of a glucosylceramide synthase inhibitor reduces CNS substrates and increases lifespan in a mouse model of type 2 Gaucher disease.

Science.gov (United States)

Cabrera-Salazar, Mario A; Deriso, Matthew; Bercury, Scott D; Li, Lingyun; Lydon, John T; Weber, William; Pande, Nilesh; Cromwell, Mandy A; Copeland, Diane; Leonard, John; Cheng, Seng H; Scheule, Ronald K

2012-01-01

Neuropathic Gaucher disease (nGD), also known as type 2 or type 3 Gaucher disease, is caused by a deficiency of the enzyme glucocerebrosidase (GC). This deficiency impairs the degradation of glucosylceramide (GluCer) and glucosylsphingosine (GluSph), leading to their accumulation in the brains of patients and mouse models of the disease. These accumulated substrates have been thought to cause the severe neuropathology and early death observed in patients with nGD and mouse models. Substrate accumulation is evident at birth in both nGD mouse models and humans affected with the most severe type of the disease. Current treatment of non-nGD relies on the intravenous delivery of recombinant human glucocerebrosidase to replace the missing enzyme or the administration of glucosylceramide synthase inhibitors to attenuate GluCer production. However, the currently approved drugs that use these mechanisms do not cross the blood brain barrier, and thus are not expected to provide a benefit for the neurological complications in nGD patients. Here we report the successful reduction of substrate accumulation and CNS pathology together with a significant increase in lifespan after systemic administration of a novel glucosylceramide synthase inhibitor to a mouse model of nGD. To our knowledge this is the first compound shown to cross the blood brain barrier and reduce substrates in this animal model while significantly enhancing its lifespan. These results reinforce the concept that systemically administered glucosylceramide synthase inhibitors could hold enhanced therapeutic promise for patients afflicted with neuropathic lysosomal storage diseases.

Research of Uncertainty Reasoning in Pineapple Disease Identification System

Science.gov (United States)

Liu, Liqun; Fan, Haifeng

In order to deal with the uncertainty of evidences mostly existing in pineapple disease identification system, a reasoning model based on evidence credibility factor was established. The uncertainty reasoning method is discussed,including: uncertain representation of knowledge, uncertain representation of rules, uncertain representation of multi-evidences and update of reasoning rules. The reasoning can fully reflect the uncertainty in disease identification and reduce the influence of subjective factors on the accuracy of the system.

Computational disease modeling – fact or fiction?

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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.

Diversity of aging of the immune system classified in the cotton rat (Sigmodon hispidus) model of human infectious diseases.

NARCIS (Netherlands)

Guichelaar, Teun; van Erp, Elisabeth A; Hoeboer, Jeroen; Smits, Noortje A M; van Els, Cécile A C M; Pieren, Daan K J; Luytjes, Willem

2018-01-01

Susceptibility and declined resistance to human pathogens like respiratory syncytial virus (RSV) at old age is well represented in the cotton rat (Sigmodon hispidus). Despite providing a preferred model of human infectious diseases, little is known about aging of its adaptive immune system. We aimed

Periodontal Disease and Systemic Diseases: An Update for the Clinician.

Science.gov (United States)

John, Vanchit; Alqallaf, Hawra; De Bedout, Tatiana

2016-01-01

A link between periodontal disease and various systemic diseases has been investigated for several years. Interest in unearthing such a link has grown as the health care profession is looking for a better understanding of disease processes and their relationships to periodontal and other oral diseases. The article aims to provide recent information on the relationship between periodontal disease and systemic diseases such as; cardiovascular, respiratory, endocrine, musculoskeletal, and reproductive system related abnormalities.

Cardiovascular Disease Modeling Using Patient-Specific Induced Pluripotent Stem Cells

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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.

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

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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

The zebrafish as a gerontology model in nervous system aging, disease, and repair.

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Van Houcke, Jessie; De Groef, Lies; Dekeyster, Eline; Moons, Lieve

2015-11-01

Considering the increasing number of elderly in the world's population today, developing effective treatments for age-related pathologies is one of the biggest challenges in modern medical research. Age-related neurodegeneration, in particular, significantly impacts important sensory, motor, and cognitive functions, seriously constraining life quality of many patients. Although our understanding of the causal mechanisms of aging has greatly improved in recent years, animal model systems still have much to tell us about this complex process. Zebrafish (Danio rerio) have gained enormous popularity for this research topic over the past decade, since their life span is relatively short but, like humans, they are still subject to gradual aging. In addition, the extensive characterization of its well-conserved molecular and cellular physiology makes the zebrafish an excellent model to unravel the underlying mechanisms of aging, disease, and repair. This review provides a comprehensive overview of the progress made in zebrafish gerontology, with special emphasis on nervous system aging. We review the evidence that classic hallmarks of aging can also be recognized within this small vertebrate, both at the molecular and cellular level. Moreover, we illustrate the high level of similarity with age-associated human pathologies through a survey of the functional deficits that arise as zebrafish age. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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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.

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.

ICT use for information management in healthcare system for chronic disease patient

Science.gov (United States)

Wawrzyniak, Zbigniew M.; Lisiecka-Biełanowicz, Mira

2013-10-01

Modern healthcare systems are designed to fulfill needs of the patient, his system environment and other determinants of the treatment with proper support of technical aids. A whole system of care is compatible to the technical solutions and organizational framework based on legal rules. The purpose of this study is to present how can we use Information and Communication Technology (ICT) systemic tools in a new model of patient-oriented care, improving the effectiveness of healthcare for patients with chronic diseases. The study material is the long-term process of healthcare for patients with chronic illness. Basing on the knowledge of the whole circumstances of patient's ecosystem and his needs allow us to build a new ICT model of long term care. The method used is construction, modeling and constant improvement the efficient ICT layer for the patient-centered healthcare model. We present a new constructive approach to systemic process how to use ICT for information management in healthcare system for chronic disease patient. The use of ICT tools in the model for chronic disease can improve all aspects of data management and communication, and the effectiveness of long-term complex healthcare. In conclusion: ICT based model of healthcare can be constructed basing on the interactions of ecosystem's functional parts through information feedback and the provision of services and models as well as the knowledge of the patient itself. Systematic approach to the model of long term healthcare assisted functionally by ICT tools and data management methods will increase the effectiveness of patient care and organizational efficiency.

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...

A model to evaluate quality and effectiveness of disease management.

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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.

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

Science.gov (United States)

Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

Systemic disease manifestations associated with epilepsy in tuberous sclerosis complex.

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Jeong, Anna; Wong, Michael

2016-09-01

Epilepsy is one of the most disabling symptoms of tuberous sclerosis complex (TSC) and is a leading cause of morbidity and mortality in affected individuals. The relationship between systemic disease manifestations and the presence of epilepsy has not been thoroughly investigated. This study utilizes a multicenter TSC Natural History Database including 1,816 individuals to test the hypothesis that systemic disease manifestations of TSC are associated with epilepsy. Univariate analysis was used to identify patient characteristics (e.g., age, gender, race, and TSC mutation status) associated with the presence of epilepsy. Individual logistic regression models were built to examine the association between epilepsy and each candidate systemic or neurologic disease variable, controlling for the patient characteristics found to be significant on univariate analysis. Finally, a multivariable logistic regression model was constructed, using the variables found to be significant on the individual analyses as well as the patient characteristics that were significant on univariate analysis. Nearly 88% of our cohort had a history of epilepsy. After adjusting for age, gender, and TSC mutation status, multiple systemic disease manifestations including cardiac rhabdomyomas (odds ratio [OR] 2.3, 95% confidence interval [CI] 1.3-3.9, p = 0.002), retinal hamartomas (OR 2.1, CI 1.0-4.3, p = 0.04), renal cysts (OR 2.1, CI 1.3-3.4, p = 0.002), renal angiomyolipomas (OR 3.0, CI 1.8-5.1, p epilepsy. In the multivariable logistic regression model, cardiac rhabdomyomas (OR 1.9, CI 1.0-3.5, p = 0.04) remained significantly associated with the presence of epilepsy. The identification of systemic disease manifestations such as cardiac rhabdomyomas that confer a higher risk of epilepsy development in TSC could contribute to disease prognostication and assist in the identification of individuals who may receive maximal benefit from potentially novel, targeted, preventative therapies. Wiley

Multi-disease data management system platform for vector-borne diseases.

Directory of Open Access Journals (Sweden)

Lars Eisen

2011-03-01

Full Text Available Emerging information technologies present new opportunities to reduce the burden of malaria, dengue and other infectious diseases. For example, use of a data management system software package can help disease control programs to better manage and analyze their data, and thus enhances their ability to carry out continuous surveillance, monitor interventions and evaluate control program performance.We describe a novel multi-disease data management system platform (hereinafter referred to as the system with current capacity for dengue and malaria that supports data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The system is comprised exclusively of software components that can be distributed without the user incurring licensing costs. It was designed to maximize the ability of the user to adapt the system to local conditions without involvement of software developers. Key points of system adaptability include 1 customizable functionality content by disease, 2 configurable roles and permissions, 3 customizable user interfaces and display labels and 4 configurable information trees including a geographical entity tree and a term tree. The system includes significant portions of functionality that is entirely or in large part re-used across diseases, which provides an economy of scope as new diseases downstream are added to the system at decreased cost.We have developed a system with great potential for aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector management programs. Next steps include evaluations of operational implementations of the current system with capacity for dengue and malaria, and the inclusion in the system platform of other important vector-borne diseases.

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

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

Using Human Induced Pluripotent Stem Cells to Model Skeletal Diseases.

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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.

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

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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

Modeling human diseases: an education in interactions and interdisciplinary approaches

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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.

Early motor deficits in mouse disease models are reliably uncovered using an automated home-cage wheel-running system: a cross-laboratory validation.

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Mandillo, Silvia; Heise, Ines; Garbugino, Luciana; Tocchini-Valentini, Glauco P; Giuliani, Alessandro; Wells, Sara; Nolan, Patrick M

2014-03-01

Deficits in motor function are debilitating features in disorders affecting neurological, neuromuscular and musculoskeletal systems. Although these disorders can vary greatly with respect to age of onset, symptomatic presentation, rate of progression and severity, the study of these disease models in mice is confined to the use of a small number of tests, most commonly the rotarod test. To expand the repertoire of meaningful motor function tests in mice, we tested, optimised and validated an automated home-cage-based running-wheel system, incorporating a conventional wheel with evenly spaced rungs and a complex wheel with particular rungs absent. The system enables automated assessment of motor function without handler interference, which is desirable in longitudinal studies involving continuous monitoring of motor performance. In baseline studies at two test centres, consistently significant differences in performance on both wheels were detectable among four commonly used inbred strains. As further validation, we studied performance in mutant models of progressive neurodegenerative diseases--Huntington's disease [TgN(HD82Gln)81Dbo; referred to as HD mice] and amyotrophic lateral sclerosis [Tg(SOD1G93A)(dl)1/GurJ; referred to as SOD1 mice]--and in a mutant strain with subtle gait abnormalities, C-Snap25(Bdr)/H (Blind-drunk, Bdr). In both models of progressive disease, as with the third mutant, we could reliably and consistently detect specific motor function deficits at ages far earlier than any previously recorded symptoms in vivo: 7-8 weeks for the HD mice and 12 weeks for the SOD1 mice. We also conducted longitudinal analysis of rotarod and grip strength performance, for which deficits were still not detectable at 12 weeks and 23 weeks, respectively. Several new parameters of motor behaviour were uncovered using principal component analysis, indicating that the wheel-running assay could record features of motor function that are independent of rotarod

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...

A mobile, high-throughput semi-automated system for testing cognition in large non-primate animal models of Huntington disease.

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McBride, Sebastian D; Perentos, Nicholas; Morton, A Jennifer

2016-05-30

For reasons of cost and ethical concerns, models of neurodegenerative disorders such as Huntington disease (HD) are currently being developed in farm animals, as an alternative to non-human primates. Developing reliable methods of testing cognitive function is essential to determining the usefulness of such models. Nevertheless, cognitive testing of farm animal species presents a unique set of challenges. The primary aims of this study were to develop and validate a mobile operant system suitable for high throughput cognitive testing of sheep. We designed a semi-automated testing system with the capability of presenting stimuli (visual, auditory) and reward at six spatial locations. Fourteen normal sheep were used to validate the system using a two-choice visual discrimination task. Four stages of training devised to acclimatise animals to the system are also presented. All sheep progressed rapidly through the training stages, over eight sessions. All sheep learned the 2CVDT and performed at least one reversal stage. The mean number of trials the sheep took to reach criterion in the first acquisition learning was 13.9±1.5 and for the reversal learning was 19.1±1.8. This is the first mobile semi-automated operant system developed for testing cognitive function in sheep. We have designed and validated an automated operant behavioural testing system suitable for high throughput cognitive testing in sheep and other medium-sized quadrupeds, such as pigs and dogs. Sheep performance in the two-choice visual discrimination task was very similar to that reported for non-human primates and strongly supports the use of farm animals as pre-clinical models for the study of neurodegenerative diseases. Copyright © 2015 Elsevier B.V. All rights reserved.

Drosophila as an In Vivo Model for Human Neurodegenerative Disease

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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

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

Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies.

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Du, Qingyun; Zhang, Mingxiao; Li, Yayan; Luan, Hui; Liang, Shi; Ren, Fu

2016-04-20

Incorporating the information of hypertension, this paper applies Bayesian multi-disease analysis to model the spatial patterns of Ischemic Heart Disease (IHD) risks. Patterns of harmful alcohol intake (HAI) and overweight/obesity are also modelled as they are common risk factors contributing to both IHD and hypertension. The hospitalization data of IHD and hypertension in 2012 were analyzed with three Bayesian multi-disease models at the sub-district level of Shenzhen. Results revealed that the IHD high-risk cluster shifted slightly north-eastward compared with the IHD Standardized Hospitalization Ratio (SHR). Spatial variations of overweight/obesity and HAI were found to contribute most to the IHD patterns. Identified patterns of IHD risk would benefit IHD integrated prevention. Spatial patterns of overweight/obesity and HAI could supplement the current disease surveillance system by providing information about small-area level risk factors, and thus benefit integrated prevention of related chronic diseases. Middle southern Shenzhen, where high risk of IHD, overweight/obesity, and HAI are present, should be prioritized for interventions, including alcohol control, innovative healthy diet toolkit distribution, insurance system revision, and community-based chronic disease intervention. Related health resource planning is also suggested to focus on these areas first.

Caenorhabditis elegans as a model system for studying non-cell-autonomous mechanisms in protein-misfolding diseases

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Carmen I. Nussbaum-Krammer

2014-01-01

Full Text Available Caenorhabditis elegans has a number of distinct advantages that are useful for understanding the basis for cellular and organismal dysfunction underlying age-associated diseases of protein misfolding. Although protein aggregation, a key feature of human neurodegenerative diseases, has been typically explored in vivo at the single-cell level using cells in culture, there is now increasing evidence that proteotoxicity has a non-cell-autonomous component and is communicated between cells and tissues in a multicellular organism. These discoveries have opened up new avenues for the use of C. elegans as an ideal animal model system to study non-cell-autonomous proteotoxicity, prion-like propagation of aggregation-prone proteins, and the organismal regulation of stress responses and proteostasis. This Review focuses on recent evidence that C. elegans has mechanisms to transmit certain classes of toxic proteins between tissues and a complex stress response that integrates and coordinates signals from single cells and tissues across the organism. These findings emphasize the potential of C. elegans to provide insights into non-cell-autonomous proteotoxic mechanisms underlying age-related protein-misfolding diseases.

Exploration of the financing and management model of a children's critical disease security system in China based on the implementation of Shanghai Children Hospital Care Aid.

Science.gov (United States)

Zhang, Zhi-ruo; Wen, Zhao-jun; Chen, Sai-juan; Chen, Zhu

2011-03-01

This study is designed to serve as a reference for the establishment of health security systems for children’s critical diseases. Through analysis of the operation of Shanghai Children Hospital Care Aid (SCHCA), this study explored the financing model and management of a children’s critical disease healthcare system and analyzed the possibility of expanding this system to other areas. It is found that a premium as low as RMB 7 per capita per year under SCHCA can provide high-level security for children’s critical diseases. With the good experience in Shanghai and based on the current basic medical insurance system for urban residents and the new rural cooperative medical scheme (NRCMS), it is necessary and feasible to build a health security system for children’s critical diseases at the national level.

A Framework for Modeling Emerging Diseases to Inform Management.

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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.

Risk Zone Modelling and Early Warning System for Visceral Leishmaniasis Kala-Azar Disease in Bihar, India Using Remote Sensing and GIS

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Jeyaram, A.; Kesari, S.; Bajpai, A.; Bhunia, G. S.; Krishna Murthy, Y. V. N.

2012-07-01

Visceral Leishmaniasis (VL) commonly known as Kala-azar is one of the most neglected tropical disease affecting approximately 200 million poorest populations 'at risk in 109 districts of three endemic countries namely Bangladesh, India and Nepal at different levels. This tropical disease is caused by the protozoan parasite Leishmania donovani and transmitted by female Phlebotomus argentipes sand flies. The analysis of disease dynamics indicate the periodicity at seasonal and inter-annual temporal scale which forms the basis for development of advanced early warning system. Study area of highly endemic Vaishali district, Bihar, India has been taken for model development. A Systematic study of geo-environmental parameters derived from satellite data in conjunction with ground intelligence enabled modelling of infectious disease and risk villages. High resolution Indian satellites data of IRS LISS IV (multi-spectral) and Cartosat-1 (Pan) have been used for studying environmentally risk parameters viz. peri-domestic vegetation, dwelling condition, wetland ecosystem, cropping pattern, Normalised Difference Vegetation Index (NDVI), detailed land use etc towards risk assessment. Univariate analysis of the relationship between vector density and various land cover categories and climatic variables suggested that all the variables are significantly correlated. Using the significantly correlated variables with vector density, a seasonal multivariate regression model has been carried out incorporating geo-environmental parameters, climate variables and seasonal time series disease parameters. Linear and non-linear models have been applied for periodicity and interannual temporal scale to predict Man-hour-density (MHD) and 'out-of-fit' data set used for validating the model with reasonable accuracy. To improve the MHD predictive approach, fuzzy model has also been incorporated in GIS environment combining spatial geo-environmental and climatic variables using fuzzy membership

Prevalence of periodontal disease, its association with systemic diseases and prevention.

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Nazir, Muhammad Ashraf

2017-01-01

Periodontal diseases are prevalent both in developed and developing countries and affect about 20-50% of global population. High prevalence of periodontal disease in adolescents, adults, and older individuals makes it a public health concern. Several risk factors such as smoking, poor oral hygiene, diabetes, medication, age, hereditary, and stress are related to periodontal diseases. Robust evidence shows the association of periodontal diseases with systemic diseases such as cardiovascular disease, diabetes, and adverse pregnancy outcomes. Periodontal disease is likely to cause 19% increase in the risk of cardiovascular disease, and this increase in relative risk reaches to 44% among individuals aged 65 years and over. Type 2 diabetic individuals with severe form of periodontal disease have 3.2 times greater mortality risk compared with individuals with no or mild periodontitis. Periodontal therapy has been shown to improve glycemic control in type 2 diabetic subjects. Periodontitis is related to maternal infection, preterm birth, low birth weight, and preeclampsia. Oral disease prevention strategies should be incorporated in chronic systemic disease preventive initiatives to curtail the burden of disease in populations. The reduction in the incidence and prevalence of periodontal disease can reduce its associated systemic diseases and can also minimize their financial impact on the health-care systems. It is hoped that medical, dental practitioners, and other health-care professionals will get familiar with perio-systemic link and risk factors, and need to refer to the specialized dental or periodontal care.

Ideal Experimental Rat Models for Liver Diseases.

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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.

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.

Periodontal disease and systemic complications

Directory of Open Access Journals (Sweden)

Rui Vicente Oppermann

2012-01-01

Full Text Available Periodontal diseases comprise a number of infectious and inflammatory conditions brought about by the interaction between supragingival and subgingival biofilms and the host inflammatory response. Periodontal diseases should be considered systemic conditions. This means that they are both modulated by the body's systems and play a role as a risk factor for systemic derangements. The current evidence supports some of these interactions, such as smoking as a risk factor for periodontal disease and diabetes mellitus, as both influenced by and influencing inflammatory changes in the periodontal tissue. Other potential associations are still being researched, such as obesity, hormonal changes, cardiovascular disease, and adverse outcomes in pregnancy. These, and others, still require further investigation before the repercussions of periodontal disease can be fully elucidated. Nevertheless, at the present time, the treatment of periodontal diseases-and, most importantly, their prevention-enables adequate intervention as a means of ensuring periodontal health.

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.

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.

Decision Support System for Hepatitis Disease Diagnosis using Bayesian Network

Directory of Open Access Journals (Sweden)

Shamshad Lakho

2017-12-01

Full Text Available Medical judgments are tough and challenging as the decisions are often based on the deficient and ambiguous information. Moreover, the result of decision process has direct effects on human lives. The act of human decision declines in emergency situations due to the complication, time limit, and high risks. Therefore, provision of medical diagnosis plays a dynamic role, specifically in the preliminary stage when a physician has limited diagnosis experience and identifies the directions to be taken for the treatment process. Computerized Decision Support Systems have brought a revolution in the medical diagnosis. These automatic systems support the diagnosticians in the course of diagnosis. The major role of Decision Support Systems is to support the medical personnel in decision-making procedures regarding disease diagnosis and treatment recommendation. The proposed system provides easy support in Hepatitis disease recognition. The system is developed using the Bayesian network model. The physician provides the input to the system in the form of symptoms stated by the patient. These signs and symptoms match with the casual relationships present in the knowledge model. The Bayesian network infers conclusion from the knowledge model and calculates the probability of occurrence of Hepatitis B, C and D disorders.

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

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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

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

Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies

Directory of Open Access Journals (Sweden)

Qingyun Du

2016-04-01

Full Text Available Incorporating the information of hypertension, this paper applies Bayesian multi-disease analysis to model the spatial patterns of Ischemic Heart Disease (IHD risks. Patterns of harmful alcohol intake (HAI and overweight/obesity are also modelled as they are common risk factors contributing to both IHD and hypertension. The hospitalization data of IHD and hypertension in 2012 were analyzed with three Bayesian multi-disease models at the sub-district level of Shenzhen. Results revealed that the IHD high-risk cluster shifted slightly north-eastward compared with the IHD Standardized Hospitalization Ratio (SHR. Spatial variations of overweight/obesity and HAI were found to contribute most to the IHD patterns. Identified patterns of IHD risk would benefit IHD integrated prevention. Spatial patterns of overweight/obesity and HAI could supplement the current disease surveillance system by providing information about small-area level risk factors, and thus benefit integrated prevention of related chronic diseases. Middle southern Shenzhen, where high risk of IHD, overweight/obesity, and HAI are present, should be prioritized for interventions, including alcohol control, innovative healthy diet toolkit distribution, insurance system revision, and community-based chronic disease intervention. Related health resource planning is also suggested to focus on these areas first.

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....

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

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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.

Preclinical murine models of Chronic Obstructive Pulmonary Disease.

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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.

Early motor deficits in mouse disease models are reliably uncovered using an automated home-cage wheel-running system: a cross-laboratory validation

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Mandillo, Silvia; Heise, Ines; Garbugino, Luciana; Tocchini-Valentini, Glauco P.; Giuliani, Alessandro; Wells, Sara; Nolan, Patrick M.

2014-01-01

Deficits in motor function are debilitating features in disorders affecting neurological, neuromuscular and musculoskeletal systems. Although these disorders can vary greatly with respect to age of onset, symptomatic presentation, rate of progression and severity, the study of these disease models in mice is confined to the use of a small number of tests, most commonly the rotarod test. To expand the repertoire of meaningful motor function tests in mice, we tested, optimised and validated an automated home-cage-based running-wheel system, incorporating a conventional wheel with evenly spaced rungs and a complex wheel with particular rungs absent. The system enables automated assessment of motor function without handler interference, which is desirable in longitudinal studies involving continuous monitoring of motor performance. In baseline studies at two test centres, consistently significant differences in performance on both wheels were detectable among four commonly used inbred strains. As further validation, we studied performance in mutant models of progressive neurodegenerative diseases – Huntington’s disease [TgN(HD82Gln)81Dbo; referred to as HD mice] and amyotrophic lateral sclerosis [Tg(SOD1G93A)dl1/GurJ; referred to as SOD1 mice] – and in a mutant strain with subtle gait abnormalities, C-Snap25Bdr/H (Blind-drunk, Bdr). In both models of progressive disease, as with the third mutant, we could reliably and consistently detect specific motor function deficits at ages far earlier than any previously recorded symptoms in vivo: 7–8 weeks for the HD mice and 12 weeks for the SOD1 mice. We also conducted longitudinal analysis of rotarod and grip strength performance, for which deficits were still not detectable at 12 weeks and 23 weeks, respectively. Several new parameters of motor behaviour were uncovered using principal component analysis, indicating that the wheel-running assay could record features of motor function that are independent of rotarod

Ophthalmologic complications of systemic disease.

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Klig, Jean E

2008-02-01

The human eye, as an organ, can offer critical clues to the presence of systemic disease. This article discusses the various ophthalmologic manifestations of systemic disease that can be evident on examination by an emergency department provider, as well as some findings that can be discerned with specialty consultation. The following topics are reviewed with respect to potential ocular signs and complications: syphilis, herpes zoster, Lyme disease, acquired immunodeficiency syndrome, Reiter's syndrome, Kawasaki's disease, temporal arteritis, endocarditis, hypertension, and diabetes mellitus. Indications for emergent ophthalmologic consultation are also emphasized.

Animal models of chronic obstructive pulmonary disease.

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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.

Systems thinking in combating infectious diseases.

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Xia, Shang; Zhou, Xiao-Nong; Liu, Jiming

2017-09-11

The transmission of infectious diseases is a dynamic process determined by multiple factors originating from disease pathogens and/or parasites, vector species, and human populations. These factors interact with each other and demonstrate the intrinsic mechanisms of the disease transmission temporally, spatially, and socially. In this article, we provide a comprehensive perspective, named as systems thinking, for investigating disease dynamics and associated impact factors, by means of emphasizing the entirety of a system's components and the complexity of their interrelated behaviors. We further develop the general steps for performing systems approach to tackling infectious diseases in the real-world settings, so as to expand our abilities to understand, predict, and mitigate infectious diseases.

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

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Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

A Knowledge-Base for a Personalized Infectious Disease Risk Prediction System.

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Vinarti, Retno; Hederman, Lucy

2018-01-01

We present a knowledge-base to represent collated infectious disease risk (IDR) knowledge. The knowledge is about personal and contextual risk of contracting an infectious disease obtained from declarative sources (e.g. Atlas of Human Infectious Diseases). Automated prediction requires encoding this knowledge in a form that can produce risk probabilities (e.g. Bayesian Network - BN). The knowledge-base presented in this paper feeds an algorithm that can auto-generate the BN. The knowledge from 234 infectious diseases was compiled. From this compilation, we designed an ontology and five rule types for modelling IDR knowledge in general. The evaluation aims to assess whether the knowledge-base structure, and its application to three disease-country contexts, meets the needs of personalized IDR prediction system. From the evaluation results, the knowledge-base conforms to the system's purpose: personalization of infectious disease risk.

The big bang of genome editing technology: development and application of the CRISPR/Cas9 system in disease animal models

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SHAO, Ming; XU, Tian-Rui; CHEN, Ce-Shi

2016-01-01

Targeted genome editing technology has been widely used in biomedical studies. The CRISPR-associated RNA-guided endonuclease Cas9 has become a versatile genome editing tool. The CRISPR/Cas9 system is useful for studying gene function through efficient knock-out, knock-in or chromatin modification of the targeted gene loci in various cell types and organisms. It can be applied in a number of fields, such as genetic breeding, disease treatment and gene functional investigation. In this review, we introduce the most recent developments and applications, the challenges, and future directions of Cas9 in generating disease animal model. Derived from the CRISPR adaptive immune system of bacteria, the development trend of Cas9 will inevitably fuel the vital applications from basic research to biotechnology and biomedicine. PMID:27469250

The big bang of genome editing technology: development and application of the CRISPR/Cas9 system in disease animal models.

Science.gov (United States)

Shao, Ming; Xu, Tian-Rui; Chen, Ce-Shi

2016-07-18

Targeted genome editing technology has been widely used in biomedical studies. The CRISPR-associated RNA-guided endonuclease Cas9 has become a versatile genome editing tool. The CRISPR/Cas9 system is useful for studying gene function through efficient knock-out, knock-in or chromatin modification of the targeted gene loci in various cell types and organisms. It can be applied in a number of fields, such as genetic breeding, disease treatment and gene functional investigation. In this review, we introduce the most recent developments and applications, the challenges, and future directions of Cas9 in generating disease animal model. Derived from the CRISPR adaptive immune system of bacteria, the development trend of Cas9 will inevitably fuel the vital applications from basic research to biotechnology and bio-medicine.

Physiological Dynamics in Demyelinating Diseases: Unraveling Complex Relationships through Computer Modeling

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Jay S. Coggan

2015-09-01

Full Text Available Despite intense research, few treatments are available for most neurological disorders. Demyelinating diseases are no exception. This is perhaps not surprising considering the multifactorial nature of these diseases, which involve complex interactions between immune system cells, glia and neurons. In the case of multiple sclerosis, for example, there is no unanimity among researchers about the cause or even which system or cell type could be ground zero. This situation precludes the development and strategic application of mechanism-based therapies. We will discuss how computational modeling applied to questions at different biological levels can help link together disparate observations and decipher complex mechanisms whose solutions are not amenable to simple reductionism. By making testable predictions and revealing critical gaps in existing knowledge, such models can help direct research and will provide a rigorous framework in which to integrate new data as they are collected. Nowadays, there is no shortage of data; the challenge is to make sense of it all. In that respect, computational modeling is an invaluable tool that could, ultimately, transform how we understand, diagnose, and treat demyelinating diseases.

Design of an advanced positron emission tomography detector system and algorithms for imaging small animal models of human disease

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Foudray, Angela Marie Klohs

Detecting, quantifying and visualizing biochemical mechanism in a living system without perturbing function is the goal of the instrument and algorithms designed in this thesis. Biochemical mechanisms of cells have long been known to be dependent on the signals they receive from their environment. Studying biological processes of cells in-vitro can vastly distort their function, since you are removing them from their natural chemical signaling environment. Mice have become the biological system of choice for various areas of biomedical research due to their genetic and physiological similarities with humans, the relatively low cost of their care, and their quick breeding cycle. Drug development and efficacy assessment along with disease detection, management, and mechanism research all have benefited from the use of small animal models of human disease. A high resolution, high sensitivity, three-dimensional (3D) positioning positron emission tomography (PET) detector system was designed through device characterization and Monte Carlo simulation. Position-sensitive avalanche photodiodes (PSAPDs) were characterized in various packaging configurations; coupled to various configurations of lutetium oxyorthosilicate (LSO) scintillation crystals. Forty novelly packaged final design devices were constructed and characterized, each providing characteristics superior to commercially available scintillation detectors used in small animal imaging systems: ˜1mm crystal identification, 14-15% of 511 keV energy resolution, and averaging 1.9 to 5.6 ns coincidence time resolution. A closed-cornered box-shaped detector configuration was found to provide optimal photon sensitivity (˜10.5% in the central plane) using dual LSO-PSAPD scintillation detector modules and Monte Carlo simulation. Standard figures of merit were used to determine optimal system acquisition parameters. A realistic model for constituent devices was developed for understanding the signals reported by the

Humanized Mouse Models of Epstein-Barr Virus Infection and Associated Diseases

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Fujiwara, Shigeyoshi; Matsuda, Go; Imadome, Ken-Ichi

2013-01-01

Epstein-Barr virus (EBV) is a ubiquitous herpesvirus infecting more than 90% of the adult population of the world. EBV is associated with a variety of diseases including infectious mononucleosis, lymphoproliferative diseases, malignancies such as Burkitt lymphoma and nasopharyngeal carcinoma, and autoimmune diseases including rheumatoid arthritis (RA). EBV in nature infects only humans, but in an experimental setting, a limited species of new-world monkeys can be infected with the virus. Small animal models, suitable for evaluation of novel therapeutics and vaccines, have not been available. Humanized mice, defined here as mice harboring functioning human immune system components, are easily infected with EBV that targets cells of the hematoimmune system. Furthermore, humanized mice can mount both cellular and humoral immune responses to EBV. Thus, many aspects of human EBV infection, including associated diseases (e.g., lymphoproliferative disease, hemophagocytic lymphohistiocytosis and erosive arthritis resembling RA), latent infection, and T-cell-mediated and humoral immune responses have been successfully reproduced in humanized mice. Here we summarize recent achievements in the field of humanized mouse models of EBV infection and show how they have been utilized to analyze EBV pathogenesis and normal and aberrant human immune responses to the virus. PMID:25436886

Modeling-Enabled Systems Nutritional Immunology

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Verma, Meghna; Hontecillas, Raquel; Abedi, Vida; Leber, Andrew; Tubau-Juni, Nuria; Philipson, Casandra; Carbo, Adria; Bassaganya-Riera, Josep

2016-01-01

This review highlights the fundamental role of nutrition in the maintenance of health, the immune response, and disease prevention. Emerging global mechanistic insights in the field of nutritional immunology cannot be gained through reductionist methods alone or by analyzing a single nutrient at a time. We propose to investigate nutritional immunology as a massively interacting system of interconnected multistage and multiscale networks that encompass hidden mechanisms by which nutrition, microbiome, metabolism, genetic predisposition, and the immune system interact to delineate health and disease. The review sets an unconventional path to apply complex science methodologies to nutritional immunology research, discovery, and development through “use cases” centered around the impact of nutrition on the gut microbiome and immune responses. Our systems nutritional immunology analyses, which include modeling and informatics methodologies in combination with pre-clinical and clinical studies, have the potential to discover emerging systems-wide properties at the interface of the immune system, nutrition, microbiome, and metabolism. PMID:26909350

Modeling-Enabled Systems Nutritional Immunology

Directory of Open Access Journals (Sweden)

Meghna eVerma

2016-02-01

Full Text Available This review highlights the fundamental role of nutrition in the maintenance of health, the immune response and disease prevention. Emerging global mechanistic insights in the field of nutritional immunology cannot be gained through reductionist methods alone or by analyzing a single nutrient at a time. We propose to investigate nutritional immunology as a massively interacting system of interconnected multistage and multiscale networks that encompass hidden mechanisms by which nutrition, microbiome, metabolism, genetic predisposition and the immune system interact to delineate health and disease. The review sets an unconventional path to applying complex science methodologies to nutritional immunology research, discovery and development through ‘use cases’ centered around the impact of nutrition on the gut microbiome and immune responses. Our systems nutritional immunology analyses, that include modeling and informatics methodologies in combination with pre-clinical and clinical studies, have the potential to discover emerging systems-wide properties at the interface of the immune system, nutrition, microbiome, and metabolism.

NASA Models of Space Radiation Induced Cancer, Circulatory Disease, and Central Nervous System Effects

Science.gov (United States)

Cucinotta, Francis A.; Chappell, Lori J.; Kim, Myung-Hee Y.

2013-01-01

The risks of late effects from galactic cosmic rays (GCR) and solar particle events (SPE) are potentially a limitation to long-term space travel. The late effects of highest concern have significant lethality including cancer, effects to the central nervous system (CNS), and circulatory diseases (CD). For cancer and CD the use of age and gender specific models with uncertainty assessments based on human epidemiology data for low LET radiation combined with relative biological effectiveness factors (RBEs) and dose- and dose-rate reduction effectiveness factors (DDREF) to extrapolate these results to space radiation exposures is considered the current "state-of-the-art". The revised NASA Space Risk Model (NSRM-2014) is based on recent radio-epidemiology data for cancer and CD, however a key feature of the NSRM-2014 is the formulation of particle fluence and track structure based radiation quality factors for solid cancer and leukemia risk estimates, which are distinct from the ICRP quality factors, and shown to lead to smaller uncertainties in risk estimates. Many persons exposed to radiation on earth as well as astronauts are life-time never-smokers, which is estimated to significantly modify radiation cancer and CD risk estimates. A key feature of the NASA radiation protection model is the classification of radiation workers by smoking history in setting dose limits. Possible qualitative differences between GCR and low LET radiation increase uncertainties and are not included in previous risk estimates. Two important qualitative differences are emerging from research studies. The first is the increased lethality of tumors observed in animal models compared to low LET radiation or background tumors. The second are Non- Targeted Effects (NTE), which include bystander effects and genomic instability, which has been observed in cell and animal models of cancer risks. NTE's could lead to significant changes in RBE and DDREF estimates for GCR particles, and the potential

Novel approaches to models of Alzheimer's disease pathology for drug screening and development.

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Shaughnessy, Laura; Chamblin, Beth; McMahon, Lori; Nair, Ayyappan; Thomas, Mary Beth; Wakefield, John; Koentgen, Frank; Ramabhadran, Ram

2004-01-01

Development of therapeutics for Alzheimer's disease (AD) requires appropriate cell culture models that reflect the errant biochemical pathways and animal models that reflect the pathological hallmarks of the disease as well as the clinical manifestations. In the past two decades AD research has benefited significantly from the use of genetically engineered cell lines expressing components of the amyloid-generating pathway, as well as from the study of transgenic mice that develop the pathological hallmarks of the disease, mainly neuritic plaques. The choice of certain cell types and the choice of mouse as the model organism have been mandated by the feasibility of introduction and expression of foreign genes into these model systems. We describe a universal and efficient gene-delivery system, using lentiviral vectors, that permits the development of relevant cell biological systems using neuronal cells, including primary neurons and animal models in mammalian species best suited for the study of AD. In addition, lentiviral gene delivery provides avenues for creation of novel models by direct and prolonged expression of genes in the brain in any vertebrate animal. TranzVector is a lentiviral vector optimized for efficiency and safety that delivers genes to cells in culture, in tissue explants, and in live animals regardless of the dividing or differentiated status of the cells. Genes can also be delivered efficiently to fertilized single-cell-stage embryos of a wide range of mammalian species, broadening the range of the model organism (from rats to nonhuman primates) for the study of disease mechanism as well as for development of therapeutics. Copyright 2004 Humana Press Inc.

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

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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

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...

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

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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

Models of marine molluscan diseases: Trends and challenges.

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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

Estimating cardiovascular disease incidence from prevalence: a spreadsheet based model

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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.

A HUMANIZED CLINICALLY CALIBRATED QUANTITATIVE SYSTEMS PHARMACOLOGY MODEL FOR HYPOKINETIC MOTOR SYMPTOMS IN PARKINSON’S DISEASE

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Hugo eGeerts

2016-02-01

Full Text Available The current treatment of Parkinson’s disease with dopamine-centric approaches such as L-DOPA and dopamine agonists, although very succesfull, is in need of alternative treatment strategies, both in terms of disease modification and symptom management. Various non-dopaminergic treatment approaches did not result in a clear clinical benefit, despite showing a clear effect in preclinical animal models. In addition, polypharmacy is common, sometimes leading to unintended effects on non-motor symptoms such as in cognitive and psychiatric domains. To explore novel targets for symptomatic treatment and possible synergistic pharmacodynamic effects between different drugs, we developed a Quantitative Systems Pharmacology (QSP platform of the closed cortico-striatal-thalamic-cortical basal ganglia loop of the dorsal motor circuit. This mechanism-based simulation platform is based on the known neuro-anatomy and neurophysiology of the basal ganglia and explicitly incorporates domain expertise in a formalized way. The calculated beta/gamma power ratio of the local field potential in the subthalamic nucleus correlates well (R2=0.71 with clinically observed extra-pyramidal symptoms triggered by antipsychotics during schizophrenia treatment (43 drug-dose combinations. When incorporating Parkinsonian (PD pathology and reported compensatory changes, the computer model suggests a major increase in b/g ratio (corresponding to bradykinesia and rigidity from a dopamine depletion of 70% onwards. The correlation between the outcome of the QSP model and the reported changes in UPDRS III Motor Part for 22 placebo-normalized drug-dose combinations is R2=0.84. The model also correctly recapitulates the lack of clinical benefit for perampanel, MK-0567 and flupirtine and offers a hypothesis for the translational disconnect. Finally, using human PET imaging studies with placebo response, the computer model predicts well the placebo response for chronic treatment, but not

Poisson Mixture Regression Models for Heart Disease Prediction.

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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.

Poisson Mixture Regression Models for Heart Disease Prediction

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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

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

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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.

[Oral microbiota: a promising predictor of human oral and systemic diseases].

Science.gov (United States)

Xin, Xu; Junzhi, He; Xuedong, Zhou

2015-12-01

A human oral microbiota is the ecological community of commensal, symbiotic, and pathogenic microorganisms found in human oral cavity. Oral microbiota exists mostly in the form of a biofilm and maintains a dynamic ecological equilibrium with the host body. However, the disturbance of this ecological balance inevitably causes oral infectious diseases, such as dental caries, apical periodontitis, periodontal diseases, pericoronitis, and craniofacial bone osteomyelitis. Oral microbiota is also correlated with many systemic diseases, including cancer, diabetes mellitus, rheumatoid arthritis, cardiovascular diseases, and preterm birth. Hence, oral microbiota has been considered as a potential biomarker of human diseases. The "Human Microbiome Project" and other metagenomic projects worldwide have advanced our knowledge of the human oral microbiota. The integration of these metadata has been the frontier of oral microbiology to improve clinical translation. By reviewing recent progress on studies involving oral microbiota-related oral and systemic diseases, we aimed to propose the essential role of oral microbiota in the prediction of the onset, progression, and prognosis of oral and systemic diseases. An oral microbiota-based prediction model helps develop a new paradigm of personalized medicine and benefits the human health in the post-metagenomics era.

Integrated Knowledge Based Expert System for Disease Diagnosis System

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Arbaiy, Nureize; Sulaiman, Shafiza Eliza; Hassan, Norlida; Afizah Afip, Zehan

2017-08-01

The role and importance of healthcare systems to improve quality of life and social welfare in a society have been well recognized. Attention should be given to raise awareness and implementing appropriate measures to improve health care. Therefore, a computer based system is developed to serve as an alternative for people to self-diagnose their health status based on given symptoms. This strategy should be emphasized so that people can utilize the information correctly as a reference to enjoy healthier life. Hence, a Web-based Community Center for Healthcare Diagnosis system is developed based on expert system technique. Expert system reasoning technique is employed in the system to enable information about treatment and prevention of the diseases based on given symptoms. At present, three diseases are included which are arthritis, thalassemia and pneumococcal. Sets of rule and fact are managed in the knowledge based system. Web based technology is used as a platform to disseminate the information to users in order for them to optimize the information appropriately. This system will benefit people who wish to increase health awareness and seek expert knowledge on the diseases by performing self-diagnosis for early disease detection.

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

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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.

Radiological approach to systemic connective tissue diseases

Energy Technology Data Exchange (ETDEWEB)

Wiesmann, W; Schneider, M

1988-07-01

Systemic lupus erythematosus (SLE) and progressive systemic sclerosis (PSS) represent the most frequent manifestations of systemic connective tissue diseases (collagen diseases). Radiological examinations are employed to estimate the extension and degree of the pathological process. In addition, progression of the disease can be verified. In both of the above collagen diseases, specific radiological findings can be observed that permit them to be differentiated from other entities. An algorithm for the adequate radiological work-up of collagen diseases is presented.

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

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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.

The Thalamostriatal System in Normal and Diseased States

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Yoland eSmith

2014-01-01

Full Text Available Because of our limited knowledge of the functional role of the thalamostriatal system, this massive network is often ignored in models of the pathophysiology of brain disorders of basal ganglia origin, such as Parkinson’s disease. However, over the past decade, significant advances have led to a deeper understanding of the anatomical, electrophysiological, behavioral and pathological aspects of the thalamostriatal system. The cloning of the vesicular glutamate transporters 1 and 2 (vGluT1 and vGluT2 has provided powerful tools to differentiate thalamostriatal from corticostriatal glutamatergic terminals, allowing us to carry out comparative studies of the synaptology and plasticity of these two systems in normal and pathological conditions. Findings from these studies have led to the recognition of two thalamostriatal systems, based on their differential origin from the caudal intralaminar nuclear group, the centre median/parafascicular (CM/Pf complex, or other thalamic nuclei. The recent use of optogenetic methods supports this model of the organization of the thalamostriatal systems, showing differences in functionality and glutamate receptor localization at thalamostriatal synapses from Pf and other thalamic nuclei. At the functional level, evidence largely gathered from thalamic recordings in awake monkeys strongly suggests that the thalamostriatal system from the CM/Pf is involved in regulating alertness and switching behaviors. Importantly, there is evidence that the caudal intralaminar nuclei and their axonal projections to the striatum partly degenerate in Parkinson’s disease and that CM/Pf deep brain stimulation may be therapeutically useful in several movement disorders.

Animal Models for Periodontal Disease

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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.

Animal Models for Periodontal Disease

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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

Data-driven models of dominantly-inherited Alzheimer's disease progression.

Science.gov (United States)

Oxtoby, Neil P; Young, Alexandra L; Cash, David M; Benzinger, Tammie L S; Fagan, Anne M; Morris, John C; Bateman, Randall J; Fox, Nick C; Schott, Jonathan M; Alexander, Daniel C

2018-03-22

.35 years versus 5.54 years. The models reveal hidden detail on dominantly-inherited Alzheimer's disease progression, as well as providing data-driven systems for fine-grained patient staging and prediction of symptom onset with great potential utility in clinical trials.

Systems Pharmacology Dissecting Holistic Medicine for Treatment of Complex Diseases: An Example Using Cardiocerebrovascular Diseases Treated by TCM.

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Wang, Yonghua; Zheng, Chunli; Huang, Chao; Li, Yan; Chen, Xuetong; Wu, Ziyin; Wang, Zhenzhong; Xiao, Wei; Zhang, Boli

2015-01-01

Holistic medicine is an interdisciplinary field of study that integrates all types of biological information (protein, small molecules, tissues, organs, external environmental signals, etc.) to lead to predictive and actionable models for health care and disease treatment. Despite the global and integrative character of this discipline, a comprehensive picture of holistic medicine for the treatment of complex diseases is still lacking. In this study, we develop a novel systems pharmacology approach to dissect holistic medicine in treating cardiocerebrovascular diseases (CCDs) by TCM (traditional Chinese medicine). Firstly, by applying the TCM active ingredients screened out by a systems-ADME process, we explored and experimentalized the signed drug-target interactions for revealing the pharmacological actions of drugs at a molecule level. Then, at a/an tissue/organ level, the drug therapeutic mechanisms were further investigated by a target-organ location method. Finally, a translational integrating pathway approach was applied to extract the diseases-therapeutic modules for understanding the complex disease and its therapy at systems level. For the first time, the feature of the drug-target-pathway-organ-cooperations for treatment of multiple organ diseases in holistic medicine was revealed, facilitating the development of novel treatment paradigm for complex diseases in the future.

Solid lipid nanoparticles as anti-inflammatory drug delivery system in a human inflammatory bowel disease whole-blood model.

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Serpe, Loredana; Canaparo, Roberto; Daperno, Marco; Sostegni, Raffaello; Martinasso, Germana; Muntoni, Elisabetta; Ippolito, Laura; Vivenza, Nicoletta; Pera, Angelo; Eandi, Mario; Gasco, Maria Rosa; Zara, Gian Paolo

2010-03-18

Standard treatment for inflammatory bowel diseases (IBD) necessitates frequent intake of anti-inflammatory and/or immunosuppressive drugs, leading to significant adverse events. To evaluate the role solid lipid nanoparticles (SLN) play as drug delivery system in enhancing anti-inflammatory activity for drugs such as dexamethasone and butyrate in a human inflammatory bowel diseases whole-blood model. ELISA assay and the peripheral blood mononuclear cell (PBMC) cytokine mRNA expression levels were evaluated by quantitative SYBR Green real-time RT-PCR to determine the IL-1beta, TNF-alpha, IFN-gamma and IL-10 secretion in inflammatory bowel diseases patients' PBMC culture supernatants. There was a significant decrease in IL-1beta (p<0.01) and TNF-alpha (p<0.001) secretion, whilst IL-10 (p<0.05) secretion significantly increased after cholesteryl butyrate administration, compared to that of butyrate alone at the highest concentration tested (100 microM), at 24h exposure. There was a significant decrease in IL-1beta (p<0.01), TNF-alpha (p<0.001) and IL-10 (p<0.001) secretion after dexamethasone loaded SLN administration, compared to dexamethasone alone at the highest concentration tested (250 nM) at 24h exposure. No IFN-gamma was detected under any conditions and no cytotoxic effects observed even at the highest concentration tested. The incorporation of butyrate and dexamethasone into SLN has a significant positive anti-inflammatory effect in the human inflammatory bowel disease whole-blood model. Copyright 2010 Elsevier B.V. All rights reserved.

A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation.

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Warren D Anderson

2017-07-01

Full Text Available Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension. We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.

Radiological approach to systemic connective tissue diseases

International Nuclear Information System (INIS)

Wiesmann, W.; Schneider, M.

1988-01-01

Systemic lupus erythematosus (SLE) and progressive systemic sclerosis (PSS) represent the most frequent manifestations of systemic connective tissue diseases (collagen diseases). Radiological examinations are employed to estimate the extension and degree of the pathological process. In addition, progression of the disease can be verified. In both of the above collagen diseases, specific radiological findings can be observed that permit them to be differentiated from other entities. An algorithm for the adequate radiological work-up of collagen diseases is presented. (orig.) [de

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...

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

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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.

Reproduction numbers of infectious disease models

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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

Healthcare model with use of information and communication technology for patients with chronic disease.

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Lisiecka-Biełanowicz, Mira; Wawrzyniak, Zbigniew

2016-07-15

The healthcare system is positioned in the patient's environment and works with other determinants of the treatment. Patient care requires a whole system compatible to the needs of organizational and technical solutions. The purpose of this study is to present a new model of patient-oriented care, in which the use of information and communication technology (ICT) can improve the effectiveness of healthcare for patients with chronic diseases. The study material is the process of healthcare for chronically ill patients. Knowledge of the circumstances surrounding ecosystem and of the patients' needs, taking into account the fundamental healthcare goals allows us to build a new models of care, starting with the economic assumptions. The method used is modeling the construction of efficient healthcare system with the patient-centered model using ICT tools. We present a new systemic concept of building patient's environment in which he is the central figure of the healthcare organization - so called patient centered system. The use of ICT in the model of chronic patient's healthcare can improve the effectiveness of this kind of care. The concept is a vision to making wide platform of information management in chronic disease in a real environment ecosystem of patient using ICT tools. On the basis of a systematic approach to the model of chronic disease, and the knowledge of the patient itself, a model of the ecosystem impacts and interactions through information feedback and the provision of services can be constructed. ICT assisted techniques will increase the effectiveness of patient care, in which nowadays information exchange plays a key role.

Towards a Hybrid Agent-based Model for Mosquito Borne Disease.

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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.

The Research of Clinical Decision Support System Based on Three-Layer Knowledge Base Model

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Yicheng Jiang

2017-01-01

Full Text Available In many clinical decision support systems, a two-layer knowledge base model (disease-symptom of rule reasoning is used. This model often does not express knowledge very well since it simply infers disease from the presence of certain symptoms. In this study, we propose a three-layer knowledge base model (disease-symptom-property to utilize more useful information in inference. The system iteratively calculates the probability of patients who may suffer from diseases based on a multisymptom naive Bayes algorithm, in which the specificity of these disease symptoms is weighted by the estimation of the degree of contribution to diagnose the disease. It significantly reduces the dependencies between attributes to apply the naive Bayes algorithm more properly. Then, the online learning process for parameter optimization of the inference engine was completed. At last, our decision support system utilizing the three-layer model was formally evaluated by two experienced doctors. By comparisons between prediction results and clinical results, our system can provide effective clinical recommendations to doctors. Moreover, we found that the three-layer model can improve the accuracy of predictions compared with the two-layer model. In light of some of the limitations of this study, we also identify and discuss several areas that need continued improvement.

NETs: The missing link between cell death and systemic autoimmune diseases?

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Felipe eAndrade

2013-01-01

Full Text Available For almost 20 years, apoptosis and secondary necrosis have been considered the major source of autoantigens and endogenous adjuvants in the pathogenic model of systemic autoimmune diseases. This focus is justified in part because initial evidence in systemic lupus erythematosus (SLE guided investigators toward the study of apoptosis, but also because other forms of cell death were unknown. To date, it is known that many other forms of cell death occur, and that they vary in their capacity to stimulate as well as inhibit the immune system. Among these, NETosis (an antimicrobial form of death in neutrophils in which nuclear material is extruded from the cell forming extracellular traps, is gaining major interest as a process that may trigger some of the immune features found in SLE, granulomatosis with polyangiitis (formerly Wegener’s granulomatosis and Felty’s syndrome. Although there have been volumes of very compelling studies published on the role of cell death in autoimmunity, no unifying theory has been adopted nor have any successful therapeutics been developed based on this important pathway. The recent inclusion of NETosis into the pathogenic model of autoimmune diseases certainly adds novel insights into this paradigm, but also reveals a previously unappreciated level of complexity and raises many new questions. This review discusses the role of cell death in systemic autoimmune diseases with a focus on apoptosis and NETosis, highlights the current short comings in our understanding of the vast complexity of cell death, and considers the potential shift in the cell death paradigm in autoimmunity. Understanding this complexity is critical in order to develop tools to clearly define the death pathways that are active in systemic autoimmune diseases, identify drivers of disease propagation, and develop novel therapeutics.

A small nonhuman primate model for filovirus-induced disease.

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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.

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.

Modeling rapidly disseminating infectious disease during mass gatherings

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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.

An image-based model of brain volume biomarker changes in Huntington's disease.

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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.

[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.

Design of Knowledge Management System for Diabetic Complication Diseases

Science.gov (United States)

Fiarni, Cut

2017-01-01

This paper examines how to develop a Model for Knowledge Management System (KMS) for diabetes complication diseases. People with diabetes have a higher risk of developing a series of serious health problems. Each patient has different condition that could lead to different disease and health problem. But, with the right information, patient could have early detection so the health risk could be minimized and avoided. Hence, the objective of this research is to propose a conceptual framework that integrates social network model, Knowledge Management activities, and content based reasoning (CBR) for designing such a diabetes health and complication disease KMS. The framework indicates that the critical knowledge management activities are in the process to find similar case and the index table for algorithm to fit the framework for the social media. With this framework, KMS developers can work with healthcare provider to easily identify the suitable IT associated with the CBR process when developing a diabetes KMS.

A study on periodontal disease and systemic disease relationship a hospital based study in Bangalore

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Sukhvinder Singh Oberoi

2013-01-01

Full Text Available Background: Periodontal deterioration has been reported to be associated with various systemic conditions like Cardiovascular disease, Diabetes, Respiratory disease, Liver cirrhosis, Bacterial Pneumonia, Nutritional deficiencies and adverse pregnancy outcomes. Aim: To assess the periodontal disease among patients with systemic disease/conditions. Materials and Method: A total of 500 patients with systemic disease/conditions (Diabetes, Cardiovascular disease, Respiratory disease and Renal disease and 500-age and gender matched controls without systemic disease/conditions were selected from the Government Hospitals in Bangalore City. The medical conditions were recorded and the periodontal status of the study population was assessed using the CPITN index. Results: The prevalence of CPITN Code 4 was found to be more among the patients with systemic disease/conditions (46.2%. The mean number of sextants with CPITN code 3 and 4 were more among the patients with systemic disease/conditions. The prevalence of CPITN code was found to be more among the patients with Respiratory disease whereas the mean number of sextants was found to be more among the patients with Diabetes, Cardiovascular and Renal disease. Conclusion: It may be concluded that the systemic diseases/conditions are associated with higher severity of periodontal disease.

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.

The dopaminergic system in autoimmune diseases

Directory of Open Access Journals (Sweden)

Rodrigo ePacheco

2014-03-01

Full Text Available Bidirectional interactions between the immune and the nervous systems are of considerable interest both for deciphering their functioning and for designing novel therapeutic strategies. The past decade has brought a burst of insights into the molecular mechanisms involved in neuro-immune communications mediated by dopamine. Studies of dendritic cells (DCs revealed that they express the whole machinery to synthesize and store dopamine, which may act in an autocrine manner to stimulate dopamine receptors (DARs. Depending on specific DARs stimulated on DCs and T cells, dopamine may differentially favor CD4+ T cell differentiation into Th1 or Th17 inflammatory cells. Regulatory T cells can also release high amounts of dopamine that acts in an autocrine DAR-mediated manner to inhibit their suppressive activity. These dopaminergic regulations could represent a driving force during autoimmunity. Indeed, dopamine levels are altered in the brain of mouse models of multiple sclerosis (MS and lupus, and in inflamed tissues of patients with inflammatory bowel diseases or rheumatoid arthritis. The distorted expression of DARs in peripheral lymphocytes of lupus and MS patients also supports the importance of dopaminergic regulations in autoimmunity. Moreover, dopamine analogs had beneficial therapeutic effects in animal models, and in patients with lupus or rheumatoid arthritis. We propose models that may underlie key roles of dopamine and its receptors in autoimmune diseases.

Human immune system mouse models of Ebola virus infection.

Science.gov (United States)

Spengler, Jessica R; Prescott, Joseph; Feldmann, Heinz; Spiropoulou, Christina F

2017-08-01

Human immune system (HIS) mice, immunodeficient mice engrafted with human cells (with or without donor-matched tissue), offer a unique opportunity to study pathogens that cause disease predominantly or exclusively in humans. Several HIS mouse models have recently been used to study Ebola virus (EBOV) infection and disease. The results of these studies are encouraging and support further development and use of these models in Ebola research. HIS mice provide a small animal model to study EBOV isolates, investigate early viral interactions with human immune cells, screen vaccines and therapeutics that modulate the immune system, and investigate sequelae in survivors. Here we review existing models, discuss their use in pathogenesis studies and therapeutic screening, and highlight considerations for study design and analysis. Finally, we point out caveats to current models, and recommend future efforts for modeling EBOV infection in HIS mice. Published by Elsevier B.V.

Food system consequences of a fungal disease epidemic in a major crop.

Science.gov (United States)

Godfray, H Charles J; Mason-D'Croz, Daniel; Robinson, Sherman

2016-12-05

Fungal diseases are major threats to the most important crops upon which humanity depends. Were there to be a major epidemic that severely reduced yields, its effects would spread throughout the globalized food system. To explore these ramifications, we use a partial equilibrium economic model of the global food system (IMPACT) to study a hypothetical severe but short-lived epidemic that reduces rice yields in the countries affected by 80%. We modelled a succession of epidemic scenarios of increasing severity, starting with the disease in a single country in southeast Asia and ending with the pathogen present in most of eastern Asia. The epidemic and subsequent crop losses led to substantially increased global rice prices. However, as long as global commodity trade was unrestricted and able to respond fast enough, the effects on individual calorie consumption were, to a large part, mitigated. Some of the worse effects were projected to be experienced by poor net-rice importing countries in sub-Saharan Africa, which were not affected directly by the disease but suffered because of higher rice prices. We critique the assumptions of our models and explore political economic pressures to restrict trade at times of crisis. We finish by arguing for the importance of 'stress-testing' the resilience of the global food system to crop disease and other shocks.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Author(s).

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.

Electronic Integrated Disease Surveillance System and Pathogen Asset Control System

Directory of Open Access Journals (Sweden)

Tom G. Wahl

2012-06-01

Full Text Available Electronic Integrated Disease Surveillance System (EIDSS has been used to strengthen and support monitoring and prevention of dangerous diseases within One Health concept by integrating veterinary and human surveillance, passive and active approaches, case-based records including disease-specific clinical data based on standardised case definitions and aggregated data, laboratory data including sample tracking linked to each case and event with test results and epidemiological investigations. Information was collected and shared in secure way by different means: through the distributed nodes which are continuously synchronised amongst each other, through the web service, through the handheld devices. Electronic Integrated Disease Surveillance System provided near real time information flow that has been then disseminated to the appropriate organisations in a timely manner. It has been used for comprehensive analysis and visualisation capabilities including real time mapping of case events as these unfold enhancing decision making. Electronic Integrated Disease Surveillance System facilitated countries to comply with the IHR 2005 requirements through a data transfer module reporting diseases electronically to the World Health Organisation (WHO data center as well as establish authorised data exchange with other electronic system using Open Architecture approach. Pathogen Asset Control System (PACS has been used for accounting, management and control of biological agent stocks. Information on samples and strains of any kind throughout their entire lifecycle has been tracked in a comprehensive and flexible solution PACS. Both systems have been used in a combination and individually. Electronic Integrated Disease Surveillance System and PACS are currently deployed in the Republics of Kazakhstan, Georgia and Azerbaijan as a part of the Cooperative Biological Engagement Program (CBEP sponsored by the US Defense Threat Reduction Agency (DTRA.

Electronic integrated disease surveillance system and pathogen asset control system.

Science.gov (United States)

Wahl, Tom G; Burdakov, Aleksey V; Oukharov, Andrey O; Zhilokov, Azamat K

2012-06-20

Electronic Integrated Disease Surveillance System (EIDSS) has been used to strengthen and support monitoring and prevention of dangerous diseases within One Health concept by integrating veterinary and human surveillance, passive and active approaches, case-based records including disease-specific clinical data based on standardised case definitions and aggregated data, laboratory data including sample tracking linked to each case and event with test results and epidemiological investigations. Information was collected and shared in secure way by different means: through the distributed nodes which are continuously synchronised amongst each other, through the web service, through the handheld devices. Electronic Integrated Disease Surveillance System provided near real time information flow that has been then disseminated to the appropriate organisations in a timely manner. It has been used for comprehensive analysis and visualisation capabilities including real time mapping of case events as these unfold enhancing decision making. Electronic Integrated Disease Surveillance System facilitated countries to comply with the IHR 2005 requirements through a data transfer module reporting diseases electronically to the World Health Organisation (WHO) data center as well as establish authorised data exchange with other electronic system using Open Architecture approach. Pathogen Asset Control System (PACS) has been used for accounting, management and control of biological agent stocks. Information on samples and strains of any kind throughout their entire lifecycle has been tracked in a comprehensive and flexible solution PACS.Both systems have been used in a combination and individually. Electronic Integrated Disease Surveillance System and PACS are currently deployed in the Republics of Kazakhstan, Georgia and Azerbaijan as a part of the Cooperative Biological Engagement Program (CBEP) sponsored by the US Defense Threat Reduction Agency (DTRA).

The Collaborative Cross Resource for Systems Genetics Research of Infectious Diseases.

Science.gov (United States)

Maurizio, Paul L; Ferris, Martin T

2017-01-01

An increasing body of evidence highlights the role of host genetic variation in driving susceptibility to severe disease following pathogen infection. In order to fully appreciate the importance of host genetics on infection susceptibility and resulting disease, genetically variable experimental model systems should be employed. These systems allow for the identification, characterization, and mechanistic dissection of genetic variants that cause differential disease responses. Herein we discuss application of the Collaborative Cross (CC) panel of recombinant inbred strains to study viral pathogenesis, focusing on practical considerations for experimental design, assessment and analysis of disease responses within the CC, as well as some of the resources developed for the CC. Although the focus of this chapter is on viral pathogenesis, many of the methods presented within are applicable to studies of other pathogens, as well as to case-control designs in genetically diverse populations.

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.

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.

Premature atherosclerosis in systemic autoimmune diseases

NARCIS (Netherlands)

Leeuw, Karina de

2008-01-01

Systemic autoimmune diseases such as systemic lupus erythematosus (SLE) and Wegener’s granulomatosis (WG) are associated with a significantly increased prevalence of cardiovascular disease (CVD) compared to age- and sex-matched controls. Many risk factors are involved in the pathogenesis of

R0-modeling as a tool for early warning and surveillance of exotic vector borne diseases in Denmark

DEFF Research Database (Denmark)

Bødker, Rene

2011-01-01

for predicting permanent establishment of presently exotic diseases, mean temperatures may not predict the true potential for local spread and limited outbreaks resulting from accidental introductions in years with temporary periods of warm weather. DTU-Veterinary Institute is developing a system for continuous...... a truly risk based surveillance system for insect borne diseases. R0 models for many vector borne diseases are simple and the available estimates of model parameters like vector densities and survival rates may be uncertain. The quantitative value of R0 estimated from such models is therefore likely......Modeling the potential transmission intensity of insect borne diseases with climate driven R0 process models is frequently used to assess the potential for veterinary and human infections to become established in non endemic areas. Models are often based on mean temperatures of an arbitrary time...

Systems medicine advances in interstitial lung disease.

Science.gov (United States)

Greiffo, Flavia R; Eickelberg, Oliver; Fernandez, Isis E

2017-09-30

Fibrotic lung diseases involve subject-environment interactions, together with dysregulated homeostatic processes, impaired DNA repair and distorted immune functions. Systems medicine-based approaches are used to analyse diseases in a holistic manner, by integrating systems biology platforms along with clinical parameters, for the purpose of understanding disease origin, progression, exacerbation and remission.Interstitial lung diseases (ILDs) refer to a heterogeneous group of complex fibrotic diseases. The increase of systems medicine-based approaches in the understanding of ILDs provides exceptional advantages by improving diagnostics, unravelling phenotypical differences, and stratifying patient populations by predictable outcomes and personalised treatments. This review discusses the state-of-the-art contributions of systems medicine-based approaches in ILDs over the past 5 years. Copyright ©ERS 2017.

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 ...

A positioning system for forest diseases and pests based on GIS and PTZ camera

International Nuclear Information System (INIS)

Wang, Z B; Zhao, F F; Wang, C B; Wang, L L

2014-01-01

Forest diseases and pests cause enormous economic losses and ecological damage every year in China. To prevent and control forest diseases and pests, the key is to get accurate information timely. In order to improve monitoring coverage rate and economize on manpower, a cooperative investigation model for forest diseases and pests is put forward. It is composed of video positioning system and manual labor reconnaissance with mobile GIS embedded in PDA. Video system is used to scan the disaster area, and is particularly effective on where trees are withered. Forest diseases prevention and control workers can check disaster area with PDA system. To support this investigation model, we developed a positioning algorithm and a positioning system. The positioning algorithm is based on DEM and PTZ camera. Moreover, the algorithm accuracy is validated. The software consists of 3D GIS subsystem, 2D GIS subsystem, video control subsystem and disaster positioning subsystem. 3D GIS subsystem makes positioning visual, and practically easy to operate. 2D GIS subsystem can output disaster thematic map. Video control subsystem can change Pan/Tilt/Zoom of a digital camera remotely, to focus on the suspected area. Disaster positioning subsystem implements the positioning algorithm. It is proved that the positioning system can observe forest diseases and pests in practical application for forest departments

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

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

Energy Technology Data Exchange (ETDEWEB)

Shumilov, V. N., E-mail: vnshumilov@rambler.ru; Syryamkin, V. I., E-mail: maximus70sir@gmail.com; Syryamkin, M. V., E-mail: maximus70sir@gmail.com [National Research Tomsk State University, 634050, Tomsk, Lenin Avenue, 36 (Russian Federation)

2015-11-17

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervous systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of

Modelling of pathologies of the nervous system by the example of computational and electronic models of elementary nervous systems

International Nuclear Information System (INIS)

Shumilov, V. N.; Syryamkin, V. I.; Syryamkin, M. V.

2015-01-01

The paper puts forward principles of action of devices operating similarly to the nervous system and the brain of biological systems. We propose an alternative method of studying diseases of the nervous system, which may significantly influence prevention, medical treatment, or at least retardation of development of these diseases. This alternative is to use computational and electronic models of the nervous system. Within this approach, we represent the brain in the form of a huge electrical circuit composed of active units, namely, neuron-like units and connections between them. As a result, we created computational and electronic models of elementary nervous systems, which are based on the principles of functioning of biological nervous systems that we have put forward. Our models demonstrate reactions to external stimuli and their change similarly to the behavior of simplest biological organisms. The models possess the ability of self-training and retraining in real time without human intervention and switching operation/training modes. In our models, training and memorization take place constantly under the influence of stimuli on the organism. Training is without any interruption and switching operation modes. Training and formation of new reflexes occur by means of formation of new connections between excited neurons, between which formation of connections is physically possible. Connections are formed without external influence. They are formed under the influence of local causes. Connections are formed between outputs and inputs of two neurons, when the difference between output and input potentials of excited neurons exceeds a value sufficient to form a new connection. On these grounds, we suggest that the proposed principles truly reflect mechanisms of functioning of biological nervous systems and the brain. In order to confirm the correspondence of the proposed principles to biological nature, we carry out experiments for the study of processes of

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

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.

Disease management projects and the Chronic Care Model in action: baseline qualitative research

Science.gov (United States)

2012-01-01

Background Disease management programs, especially those based on the Chronic Care Model (CCM), are increasingly common in the Netherlands. While disease management programs have been well-researched quantitatively and economically, less qualitative research has been done. The overall aim of the study is to explore how disease management programs are implemented within primary care settings in the Netherlands; this paper focuses on the early development and implementation stages of five disease management programs in the primary care setting, based on interviews with project leadership teams. Methods Eleven semi-structured interviews were conducted at the five selected sites with sixteen professionals interviewed; all project directors and managers were interviewed. The interviews focused on each project’s chosen chronic illness (diabetes, eating disorders, COPD, multi-morbidity, CVRM) and project plan, barriers to development and implementation, the project leaders’ action and reactions, as well as their roles and responsibilities, and disease management strategies. Analysis was inductive and interpretive, based on the content of the interviews. After analysis, the results of this research on disease management programs and the Chronic Care Model are viewed from a traveling technology framework. Results This analysis uncovered four themes that can be mapped to disease management and the Chronic Care Model: (1) changing the health care system, (2) patient-centered care, (3) technological systems and barriers, and (4) integrating projects into the larger system. Project leaders discussed the paths, both direct and indirect, for transforming the health care system to one that addresses chronic illness. Patient-centered care was highlighted as needed and a paradigm shift for many. Challenges with technological systems were pervasive. Project leaders managed the expenses of a traveling technology, including the social, financial, and administration involved

Disease management projects and the Chronic Care Model in action: baseline qualitative research.

Science.gov (United States)

Walters, Bethany Hipple; Adams, Samantha A; Nieboer, Anna P; Bal, Roland

2012-05-11

Disease management programs, especially those based on the Chronic Care Model (CCM), are increasingly common in The Netherlands. While disease management programs have been well-researched quantitatively and economically, less qualitative research has been done. The overall aim of the study is to explore how disease management programs are implemented within primary care settings in The Netherlands; this paper focuses on the early development and implementation stages of five disease management programs in the primary care setting, based on interviews with project leadership teams. Eleven semi-structured interviews were conducted at the five selected sites with sixteen professionals interviewed; all project directors and managers were interviewed. The interviews focused on each project's chosen chronic illness (diabetes, eating disorders, COPD, multi-morbidity, CVRM) and project plan, barriers to development and implementation, the project leaders' action and reactions, as well as their roles and responsibilities, and disease management strategies. Analysis was inductive and interpretive, based on the content of the interviews. After analysis, the results of this research on disease management programs and the Chronic Care Model are viewed from a traveling technology framework. This analysis uncovered four themes that can be mapped to disease management and the Chronic Care Model: (1) changing the health care system, (2) patient-centered care, (3) technological systems and barriers, and (4) integrating projects into the larger system. Project leaders discussed the paths, both direct and indirect, for transforming the health care system to one that addresses chronic illness. Patient-centered care was highlighted as needed and a paradigm shift for many. Challenges with technological systems were pervasive. Project leaders managed the expenses of a traveling technology, including the social, financial, and administration involved. At the sites, project leaders served

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

Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission

Directory of Open Access Journals (Sweden)

Guégan Jean-François

2008-10-01

Full Text Available Abstract Background Computational biology is often associated with genetic or genomic studies only. However, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. Such modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. So far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with SIR models could be seen as an implicit standard in epidemiology. Unfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. For instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and SIR models might not be the most suitable tool to truly capture the overall disease circulation within that environment. This limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems. Results Computational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. In this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. We developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment. Conclusion Here we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. To conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.

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

Chronic disease management: time for consultant physicians to take more leadership in system redesign.

Science.gov (United States)

Brand, C; Scott, I; Greenberg, P; Sargious, P

2007-09-01

There is a need for system redesign to meet the needs of individuals with chronic disease. New models of chronic disease care include team-based paradigms that focus on continuous and patient-centred care. In such models the roles of providers and patients must change. In this article we focus on new roles for consultant physicians, as well as barriers and incentives to these roles.

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.

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.

Stress and Systemic Inflammation: Yin-Yang Dynamics in Health and Diseases.

Science.gov (United States)

Yan, Qing

2018-01-01

Studies in psychoneuroimmunology (PNI) would provide better insights into the "whole mind-body system." Systems biology models of the complex adaptive systems (CASs), such as a conceptual framework of "Yin-Yang dynamics," may be helpful for identifying systems-based biomarkers and targets for more effective prevention and treatment. The disturbances in the Yin-Yang dynamical balance may result in stress, inflammation, and various disorders including insomnia, Alzheimer's disease, obesity, diabetes, cardiovascular diseases, skin disorders, and cancer. At the molecular and cellular levels, the imbalances in the cytokine pathways, mitochondria networks, redox systems, and various signaling pathways may contribute to systemic inflammation. In the nervous system, Yin and Yang may represent the dynamical associations between the progressive and regressive processes in aging and neurodegenerative diseases. In response to the damages to the heart, the Yin-Yang dynamical balance between proinflammatory and anti-inflammatory cytokine networks is crucial. The studies of cancer have revealed the importance of the Yin-Yang dynamics in the tumoricidal and tumorigenic activities of the immune system. Stress-induced neuroimmune imbalances are also essential in chronic skin disorders including atopic dermatitis and psoriasis. With the integrative framework, the restoration of the Yin-Yang dynamics can become the objective of dynamical systems medicine.

A Systems Biology Approach to Understanding Alcoholic Liver Disease Molecular Mechanism: The Development of Static and Dynamic Models.

Science.gov (United States)

Shafaghati, Leila; Razaghi-Moghadam, Zahra; Mohammadnejad, Javad

2017-11-01

Alcoholic liver disease (ALD) is a complex disease characterized by damages to the liver and is the consequence of excessive alcohol consumption over years. Since this disease is associated with several pathway failures, pathway reconstruction and network analysis are likely to explicit the molecular basis of the disease. To this aim, in this paper, a network medicine approach was employed to integrate interactome (protein-protein interaction and signaling pathways) and transcriptome data to reconstruct both a static network of ALD and a dynamic model for it. Several data sources were exploited to assemble a set of ALD-associated genes which further was used for network reconstruction. Moreover, a comprehensive literature mining reveals that there are four signaling pathways with crosstalk (TLR4, NF- [Formula: see text]B, MAPK and Apoptosis) which play a major role in ALD. These four pathways were exploited to reconstruct a dynamic model of ALD. The results assure that these two models are consistent with a number of experimental observations. The static network of ALD and its dynamic model are the first models provided for ALD which offer potentially valuable information for researchers in this field.

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).

Computational 3-D Model of the Human Respiratory System

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We are developing a comprehensive, morphologically-realistic computational model of the human respiratory system that can be used to study the inhalation, deposition, and clearance of contaminants, while being adaptable for age, race, gender, and health/disease status. The model ...

Review of the systems biology of the immune system using agent-based models.

Science.gov (United States)

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self-organisation, self-adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation-based modelling (EBM) and agent-based modelling. Owing to certain shortcomings of the EBM, agent-based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent-based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent-based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.

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...

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.

Infectious Disease Surveillance in the Big Data Era: Towards Faster and Locally Relevant Systems.

Science.gov (United States)

Simonsen, Lone; Gog, Julia R; Olson, Don; Viboud, Cécile

2016-12-01

While big data have proven immensely useful in fields such as marketing and earth sciences, public health is still relying on more traditional surveillance systems and awaiting the fruits of a big data revolution. A new generation of big data surveillance systems is needed to achieve rapid, flexible, and local tracking of infectious diseases, especially for emerging pathogens. In this opinion piece, we reflect on the long and distinguished history of disease surveillance and discuss recent developments related to use of big data. We start with a brief review of traditional systems relying on clinical and laboratory reports. We then examine how large-volume medical claims data can, with great spatiotemporal resolution, help elucidate local disease patterns. Finally, we review efforts to develop surveillance systems based on digital and social data streams, including the recent rise and fall of Google Flu Trends. We conclude by advocating for increased use of hybrid systems combining information from traditional surveillance and big data sources, which seems the most promising option moving forward. Throughout the article, we use influenza as an exemplar of an emerging and reemerging infection which has traditionally been considered a model system for surveillance and modeling. 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.

Infectious Disease Surveillance in the Big Data Era: Towards Faster and Locally Relevant Systems

Science.gov (United States)

Simonsen, Lone; Gog, Julia R.; Olson, Don; Viboud, Cécile

2016-01-01

While big data have proven immensely useful in fields such as marketing and earth sciences, public health is still relying on more traditional surveillance systems and awaiting the fruits of a big data revolution. A new generation of big data surveillance systems is needed to achieve rapid, flexible, and local tracking of infectious diseases, especially for emerging pathogens. In this opinion piece, we reflect on the long and distinguished history of disease surveillance and discuss recent developments related to use of big data. We start with a brief review of traditional systems relying on clinical and laboratory reports. We then examine how large-volume medical claims data can, with great spatiotemporal resolution, help elucidate local disease patterns. Finally, we review efforts to develop surveillance systems based on digital and social data streams, including the recent rise and fall of Google Flu Trends. We conclude by advocating for increased use of hybrid systems combining information from traditional surveillance and big data sources, which seems the most promising option moving forward. Throughout the article, we use influenza as an exemplar of an emerging and reemerging infection which has traditionally been considered a model system for surveillance and modeling. PMID:28830112

Modeling congenital disease and inborn errors of development in Drosophila melanogaster

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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

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.

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.

Estrogen in cardiovascular disease during systemic lupus erythematosus.

Science.gov (United States)

Gilbert, Emily L; Ryan, Michael J

2014-12-01

Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease that disproportionately affects women during their childbearing years. Cardiovascular disease is the leading cause of mortality in this patient population at an age when women often have low cardiovascular risk. Hypertension is a major cardiovascular disease risk factor, and its prevalence is markedly increased in women with SLE. Estrogen has traditionally been implicated in SLE disease progression because of the prevalence of the disease in women; however, its role in cardiovascular risk factors such as hypertension is unclear. The objective of this review is to discuss evidence for the role of estrogen in both human and murine SLE with emphasis on the effect of estrogen on cardiovascular risk factors, including hypertension. PubMed was used to search for articles with terms related to estradiol and SLE. The references of retrieved publications were also reviewed. The potential permissive role of estrogen in SLE development is supported by studies from experimental animal models of lupus in which early removal of estrogen or its effects leads to attenuation of SLE disease parameters, including autoantibody production and renal injury. However, data about the role of estrogens in human SLE are much less clear, with most studies not reaching firm conclusions about positive or negative outcomes after hormonal manipulations involving estrogen during SLE (ie, oral contraceptives, hormone therapy). Significant gaps in knowledge remain about the effect of estrogen on cardiovascular risk factors during SLE. Studies in women with SLE were not designed to determine the effect of estrogen or hormone therapy on blood pressure even though hypertension is highly prevalent, and risk of premature ovarian failure could necessitate use of hormone therapy in women with SLE. Recent evidence from an experimental animal model of lupus found that estrogen may protect against cardiovascular risk factors in

Estrogen in Cardiovascular Disease during Systemic Lupus Erythematosus

Science.gov (United States)

Gilbert, Emily L.; Ryan, Michael J.

2015-01-01

Purpose Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease that disproportionately affects women during their childbearing years. Cardiovascular disease is the leading cause of mortality in this patient population at an age when women often have low cardiovascular risk. Hypertension is a major cardiovascular disease risk factor, and its prevalence is markedly increased in women with SLE. Estrogen has traditionally been implicated in SLE disease progression because of the prevalence of the disease in women; however, its role in cardiovascular risk factors such as hypertension is unclear. The objective of this review is to discuss evidence for the role of estrogen in both human and murine SLE with emphasis on the effect of estrogen on cardiovascular risk factors, including hypertension. Methods PubMed was used to search for articles with terms related to estradiol and SLE. The references of retrieved publications were also reviewed. Findings The potential permissive role of estrogen in SLE development is supported by studies from experimental animal models of lupus in which early removal of estrogen or its effects leads to attenuation of SLE disease parameters, including autoantibody production and renal injury. However, data about the role of estrogens in human SLE are much less clear, with most studies not reaching firm conclusions about positive or negative outcomes after hormonal manipulations involving estrogen during SLE (ie, oral contraceptives, hormone therapy). Significant gaps in knowledge remain about the effect of estrogen on cardiovascular risk factors during SLE. Studies in women with SLE were not designed to determine the effect of estrogen or hormone therapy on blood pressure even though hypertension is highly prevalent, and risk of premature ovarian failure could necessitate use of hormone therapy in women with SLE. Recent evidence from an experimental animal model of lupus found that estrogen may protect against

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

Review: the role of vitamin D in nervous system health and disease.

Science.gov (United States)

DeLuca, G C; Kimball, S M; Kolasinski, J; Ramagopalan, S V; Ebers, G C

2013-08-01

Vitamin D and its metabolites have pleomorphic roles in both nervous system health and disease. Animal models have been paramount in contributing to our knowledge and understanding of the consequences of vitamin D deficiency on brain development and its implications for adult psychiatric and neurological diseases. The conflation of in vitro, ex vivo, and animal model data provide compelling evidence that vitamin D has a crucial role in proliferation, differentiation, neurotrophism, neuroprotection, neurotransmission, and neuroplasticity. Vitamin D exerts its biological function not only by influencing cellular processes directly, but also by influencing gene expression through vitamin D response elements. This review highlights the epidemiological, neuropathological, experimental and molecular genetic evidence implicating vitamin D as a candidate in influencing susceptibility to a number of psychiatric and neurological diseases. The strength of evidence varies for schizophrenia, autism, Parkinson's disease, amyotrophic lateral sclerosis, Alzheimer's disease, and is especially strong for multiple sclerosis. © 2013 British Neuropathological Society.

Prevalence of periodontal disease, its association with systemic diseases and prevention

OpenAIRE

Nazir, Muhammad Ashraf

2017-01-01

Periodontal diseases are prevalent both in developed and developing countries and affect about 20-50% of global population. High prevalence of periodontal disease in adolescents, adults, and older individuals makes it a public health concern. Several risk factors such as smoking, poor oral hygiene, diabetes, medication, age, hereditary, and stress are related to periodontal diseases. Robust evidence shows the association of periodontal diseases with systemic diseases such as cardiovascular di...

Poverty, Disease, and the Ecology of Complex Systems

Science.gov (United States)

Pluciński, Mateusz M.; Murray, Megan B.; Farmer, Paul E.; Barrett, Christopher B.; Keenan, Donald C.

2014-01-01

Understanding why some human populations remain persistently poor remains a significant challenge for both the social and natural sciences. The extremely poor are generally reliant on their immediate natural resource base for subsistence and suffer high rates of mortality due to parasitic and infectious diseases. Economists have developed a range of models to explain persistent poverty, often characterized as poverty traps, but these rarely account for complex biophysical processes. In this Essay, we argue that by coupling insights from ecology and economics, we can begin to model and understand the complex dynamics that underlie the generation and maintenance of poverty traps, which can then be used to inform analyses and possible intervention policies. To illustrate the utility of this approach, we present a simple coupled model of infectious diseases and economic growth, where poverty traps emerge from nonlinear relationships determined by the number of pathogens in the system. These nonlinearities are comparable to those often incorporated into poverty trap models in the economics literature, but, importantly, here the mechanism is anchored in core ecological principles. Coupled models of this sort could be usefully developed in many economically important biophysical systems—such as agriculture, fisheries, nutrition, and land use change—to serve as foundations for deeper explorations of how fundamental ecological processes influence structural poverty and economic development. PMID:24690902

Development and reliability of a multi-modality scoring system for evaluation of disease progression in pre-clinical models of osteoarthritis: celecoxib may possess disease-modifying properties.

Science.gov (United States)

Panahifar, A; Jaremko, J L; Tessier, A G; Lambert, R G; Maksymowych, W P; Fallone, B G; Doschak, M R

2014-10-01

We sought to develop a comprehensive scoring system for evaluation of pre-clinical models of osteoarthritis (OA) progression, and use this to evaluate two different classes of drugs for management of OA. Post-traumatic OA (PTOA) was surgically induced in skeletally mature rats. Rats were randomly divided in three groups receiving either glucosamine (high dose of 192 mg/kg) or celecoxib (clinical dose) or no treatment. Disease progression was monitored utilizing micro-magnetic resonance imaging (MRI), micro-computed tomography (CT) and histology. Pertinent features such as osteophytes, subchondral sclerosis, joint effusion, bone marrow lesion (BML), cysts, loose bodies and cartilage abnormalities were included in designing a sensitive multi-modality based scoring system, termed the rat arthritis knee scoring system (RAKSS). Overall, an inter-observer correlation coefficient (ICC) of greater than 0.750 was achieved for each scored feature. None of the treatments prevented cartilage loss, synovitis, joint effusion, or sclerosis. However, celecoxib significantly reduced osteophyte development compared to placebo. Although signs of inflammation such as synovitis and joint effusion were readily identified at 4 weeks post-operation, we did not detect any BML. We report the development of a sensitive and reliable multi-modality scoring system, the RAKSS, for evaluation of OA severity in pre-clinical animal models. Using this scoring system, we found that celecoxib prevented enlargement of osteophytes in this animal model of PTOA, and thus it may be useful in preventing OA progression. However, it did not show any chondroprotective effect using the recommended dose. In contrast, high dose glucosamine had no measurable effects. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

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.

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.

[Corneal manifestations in systemic diseases].

Science.gov (United States)

Zarranz Ventura, J; De Nova, E; Moreno-Montañés, J

2008-01-01

Systemic diseases affecting the cornea have a wide range of manifestations. The detailed study of all pathologies that cause corneal alteration is unapproachable, so we have centered our interest in the most prevalent or characteristic of them. In this paper we have divided these pathologies in sections to facilitate their study. Pulmonar and conective tissue (like colagen, rheumatologic and idiopathic inflamatory diseases), dermatologic, cardiovascular, hematologic, digestive and hepatopancreatic diseases with corneal alteration are described. Endocrine and metabolic diseases, malnutrition and carential states are also studied, as well as some otorhinolaryngologic and genetic diseases that affect the cornea. Finally, a brief report of ocular toxicity induced by drugs is referred.

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.

Fully Implantable Deep Brain Stimulation System with Wireless Power Transmission for Long-term Use in Rodent Models of Parkinson's Disease.

Science.gov (United States)

Heo, Man Seung; Moon, Hyun Seok; Kim, Hee Chan; Park, Hyung Woo; Lim, Young Hoon; Paek, Sun Ha

2015-03-01

The purpose of this study to develop new deep-brain stimulation system for long-term use in animals, in order to develop a variety of neural prostheses. Our system has two distinguished features, which are the fully implanted system having wearable wireless power transfer and ability to change the parameter of stimulus parameter. It is useful for obtaining a variety of data from a long-term experiment. To validate our system, we performed pre-clinical test in Parkinson's disease-rat models for 4 weeks. Through the in vivo test, we observed the possibility of not only long-term implantation and stability, but also free movement of animals. We confirmed that the electrical stimulation neither caused any side effect nor damaged the electrodes. We proved possibility of our system to conduct the long-term pre-clinical test in variety of parameter, which is available for development of neural prostheses.

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

KAUST Repository

Hoehndorf, Robert

2015-02-19

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, druggable therapeutic targets, and determination of pathogenicity. Results: We have developed PhenomeNET 2, a system that enables similarity-based searches over a large repository of phenotypes in real-time. It can be used to identify strains of model organisms that are phenotypically similar to human patients, diseases that are phenotypically similar to model organism phenotypes, or drug effect profiles that are similar to the phenotypes observed in a patient or model organism. PhenomeNET 2 is available at http://aber-owl.net/phenomenet. Conclusions: Phenotype-similarity searches can provide a powerful tool for the discovery and investigation of molecular mechanisms underlying an observed phenotypic manifestation. PhenomeNET 2 facilitates user-defined similarity searches and allows researchers to analyze their data within a large repository of human, mouse and rat phenotypes.

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.

Aberrant and alternative splicing in skeletal system disease.

Science.gov (United States)

Fan, Xin; Tang, Liling

2013-10-01

The main function of skeletal system is to support the body and help movement. A variety of factors can lead to skeletal system disease, including age, exercise, and of course genetic makeup and expression. Pre-mRNA splicing plays a crucial role in gene expression, by creating multiple protein variants with different biological functions. The recent studies show that several skeletal system diseases are related to pre-mRNA splicing. This review focuses on the relationship between pre-mRNA splicing and skeletal system disease. On the one hand, splice site mutation that leads to aberrant splicing often causes genetic skeletal system disease, like COL1A1, SEDL and LRP5. On the other hand, alternative splicing without genomic mutation may generate some marker protein isoforms, for example, FN, VEGF and CD44. Therefore, understanding the relationship between pre-mRNA splicing and skeletal system disease will aid in uncovering the mechanism of disease and contribute to the future development of gene therapy. © 2013 Elsevier B.V. All rights reserved.

Breast manifestations of systemic diseases

Directory of Open Access Journals (Sweden)

Dilaveri CA

2012-02-01

Full Text Available Christina A Dilaveri, Maire Brid Mac Bride, Nicole P Sandhu, Lonzetta Neal, Karthik Ghosh, Dietlind L Wahner-RoedlerDivision of General Internal Medicine, Mayo Clinic, Rochester, MN, USAAbstract: Although much emphasis has been placed on the primary presentations of breast cancer, little focus has been placed on how systemic illnesses may affect the breast. In this article, we discuss systemic illnesses that can manifest in the breast. We summarize the clinical features, imaging, histopathology, and treatment recommendations for endocrine, vascular, systemic inflammatory, infectious, and hematologic diseases, as well as for the extramammary malignancies that can present in the breast. Despite the rarity of these manifestations of systemic disease, knowledge of these conditions is critical to the appropriate evaluation and treatment of patients presenting with breast symptoms.Keywords: breast, endocrine, hematologic, infectious, vascular

Health Systems Sustainability and Rare Diseases.

Science.gov (United States)

Ferrelli, Rita Maria; De Santis, Marta; Egle Gentile, Amalia; Taruscio, Domenica

2017-01-01

The paper is addressing aspects of health system sustainability for rare diseases in relation to the current economic crisis and equity concerns. It takes into account the results of the narrative review carried out in the framework of the Joint Action for Rare Diseases (Joint RD-Action) "Promoting Implementation of Recommendations on Policy, Information and Data for Rare Diseases", that identified networks as key factors for health systems sustainability for rare diseases. The legal framework of European Reference Networks and their added value is also presented. Networks play a relevant role for health systems sustainability, since they are based upon, pay special attention to and can intervene on health systems knowledge development, partnership, organizational structure, resources, leadership and governance. Moreover, sustainability of health systems can not be separated from the analysis of the context and the action on it, including fiscal equity. As a result of the financial crisis of 2008, cuts of public health-care budgets jeopardized health equity, since the least wealthy suffered from the greatest health effects. Moreover, austerity policies affected economic growth much more adversely than previously believed. Therefore, reducing public health expenditure not only is going to jeopardise citizens' health, but also to hamper fair and sustainable development.

Care delivery for Filipino Americans using the Neuman systems model.

Science.gov (United States)

Angosta, Alona D; Ceria-Ulep, Clementina D; Tse, Alice M

2014-04-01

Filipino Americans are at risk of coronary heart disease due to the presence of multiple cardiometabolic factors. Selecting a framework that addresses the factors leading to coronary heart disease is vital when providing care for this population. The Neuman systems model is a comprehensive and wholistic framework that offers an innovative method of viewing clients, their families, and the healthcare system across multiple dimensions. Using the Neuman systems model, advanced practice nurses can develop and implement interventions that will help reduce the potential cardiovascular problems of clients with multiple risk factors. The authors in this article provides insight into the cardiovascular health of Filipino Americans and has implications for nurses and other healthcare providers working with various Southeast Asian groups in the United States.

A Highly Infectious Disease Care Network in the US Healthcare System.

Science.gov (United States)

Le, Aurora B; Biddinger, Paul D; Smith, Philip W; Herstein, Jocelyn J; Levy, Deborah A; Gibbs, Shawn G; Lowe, John J

During the 2014-15 Ebola outbreak in West Africa, the United States responded by stratifying hospitals into 1 of 3 Centers for Disease Control and Prevention (CDC)-designated categories-based on the hospital's ability to identify, isolate, assess, and provide care to patients with suspected or confirmed Ebola virus disease (EVD)-in an attempt to position the US healthcare system to safely isolate and care for potential patients. Now, with the Ebola epidemic quelled, it is crucial that we act on the lessons learned from the EVD response to broaden our national perspective on infectious disease mitigation and management, build on our newly enhanced healthcare capabilities to respond to infectious disease threats, develop a more cost-effective and sustainable model of infectious disease prevention, and continue to foster training so that the nation is not in a vulnerable position once more. We propose the formal creation of a US Highly Infectious Disease Care Network (HIDCN) modeled after 2 previous highly infectious disease consensus efforts in the United States and the European Union. A US Highly Infectious Disease Care Network can provide a common platform for the exchange of training, protocols, research, knowledge, and capability sharing among high-level isolation units. Furthermore, we envision the network will cultivate relationships among facilities and serve as a means of establishing national standards for infectious disease response, which will strengthen domestic preparedness and the nation's ability to respond to the next highly infectious disease threat.

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.

Stepwise approach to myopathy in systemic disease.

Science.gov (United States)

Chawla, Jasvinder

2011-01-01

Muscle diseases can constitute a large variety of both acquired and hereditary disorders. Myopathies in systemic disease results from several different disease processes including endocrine, inflammatory, paraneoplastic, infectious, drug- and toxin-induced, critical illness myopathy, metabolic, and myopathies with other systemic disorders. Patients with systemic myopathies often present acutely or sub acutely. On the other hand, familial myopathies or dystrophies generally present in a chronic fashion with exceptions of metabolic myopathies where symptoms on occasion can be precipitated acutely. Most of the inflammatory myopathies can have a chance association with malignant lesions; the incidence appears to be specifically increased only in patients with dermatomyositis. In dealing with myopathies associated with systemic illnesses, the focus will be on the acquired causes. Management is beyond the scope of this chapter. Prognosis is based upon the underlying cause and, most of the time, carries a good prognosis. In order to approach a patient with suspected myopathy from systemic disease, a stepwise approach is utilized.

Associations of Systemic Diseases with Intermediate Uveitis.

Science.gov (United States)

Shoughy, Samir S; Kozak, Igor; Tabbara, Khalid F

2016-01-01

To determine the associations of systemic diseases with intermediate uveitis. The medical records of 50 consecutive cases with intermediate uveitis referred to The Eye Center in Riyadh, Saudi Arabia, were reviewed. Age- and sex-matched patients without uveitis served as controls. Patients had complete ophthalmic and medical examinations. There were 27 male and 23 female patients. Mean age was 29 years with a range of 5-62 years. Overall, 21 cases (42%) had systemic disorders associated with intermediate uveitis and 29 cases (58%) had no associated systemic disease. A total of 11 patients (22%) had asthma, 4 (8%) had multiple sclerosis, 3 (6%) had presumed ocular tuberculosis, 1 (2%) had inflammatory bowel disease, 1 (2%) had non-Hodgkin lymphoma and 1 (2%) had sarcoidosis. Evidence of systemic disease was found in 50 (5%) of the 1,000 control subjects. Bronchial asthma was found in 37 patients (3.7 %), multiple sclerosis in 9 patients (0.9%), inflammatory bowel disease in 3 patients (0.3%), and tuberculosis in 1 patient (0.1%). None of the control patients had sarcoidosis or lymphoma. There were statistically significant associations between intermediate uveitis and bronchial asthma (p = 0.0001), multiple sclerosis (p = 0.003) and tuberculosis (p = 0.0005). Bronchial asthma and multiple sclerosis were the most frequently encountered systemic diseases associated with intermediate uveitis in our patient population. Patients with intermediate uveitis should undergo careful history-taking and investigations to rule out associated systemic illness.

Role of the Immune System in Diabetic Kidney Disease.

Science.gov (United States)

Hickey, Fionnuala B; Martin, Finian

2018-03-12

The purpose of this review is to examine the proposed role of immune modulation in the development and progression of diabetic kidney disease (DKD). Diabetic kidney disease has not historically been considered an immune-mediated disease; however, increasing evidence is emerging in support of an immune role in its pathophysiology. Both systemic and local renal inflammation have been associated with DKD. Infiltration of immune cells, predominantly macrophages, into the kidney has been reported in a number of both experimental and clinical studies. In addition, increased levels of circulating pro-inflammatory cytokines have been linked to disease progression. Consequently, a variety of therapeutic strategies involving modulation of the immune response are currently being investigated in diabetic kidney disease. Although no current therapies for DKD are directly based on immune modulation many of the therapies in clinical use have anti-inflammatory effects along with their primary actions. Macrophages emerge as the most likely beneficial immune cell target and compounds which reduce macrophage infiltration to the kidney have shown potential in both animal models and clinical trials.

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.

Induced Pluripotency and Gene Editing in Disease Modelling: Perspectives and Challenges

Science.gov (United States)

Seah, Yu Fen Samantha; EL Farran, Chadi A.; Warrier, Tushar; Xu, Jian; Loh, Yuin-Han

2015-01-01

Embryonic stem cells (ESCs) are chiefly characterized by their ability to self-renew and to differentiate into any cell type derived from the three main germ layers. It was demonstrated that somatic cells could be reprogrammed to form induced pluripotent stem cells (iPSCs) via various strategies. Gene editing is a technique that can be used to make targeted changes in the genome, and the efficiency of this process has been significantly enhanced by recent advancements. The use of engineered endonucleases, such as homing endonucleases, zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and Cas9 of the CRISPR system, has significantly enhanced the efficiency of gene editing. The combination of somatic cell reprogramming with gene editing enables us to model human diseases in vitro, in a manner considered superior to animal disease models. In this review, we discuss the various strategies of reprogramming and gene targeting with an emphasis on the current advancements and challenges of using these techniques to model human diseases. PMID:26633382

Induced Pluripotency and Gene Editing in Disease Modelling: Perspectives and Challenges

Directory of Open Access Journals (Sweden)

Yu Fen Samantha Seah

2015-12-01

Full Text Available Embryonic stem cells (ESCs are chiefly characterized by their ability to self-renew and to differentiate into any cell type derived from the three main germ layers. It was demonstrated that somatic cells could be reprogrammed to form induced pluripotent stem cells (iPSCs via various strategies. Gene editing is a technique that can be used to make targeted changes in the genome, and the efficiency of this process has been significantly enhanced by recent advancements. The use of engineered endonucleases, such as homing endonucleases, zinc finger nucleases (ZFNs, transcription activator-like effector nucleases (TALENs and Cas9 of the CRISPR system, has significantly enhanced the efficiency of gene editing. The combination of somatic cell reprogramming with gene editing enables us to model human diseases in vitro, in a manner considered superior to animal disease models. In this review, we discuss the various strategies of reprogramming and gene targeting with an emphasis on the current advancements and challenges of using these techniques to model human diseases.

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.

Animal models for Gaucher disease research

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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.

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.

Eight challenges in modelling infectious livestock diseases

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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.

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.

Modeling Viral Infectious Diseases and Development of Antiviral Therapies Using Human Induced Pluripotent Stem Cell-Derived Systems.

Science.gov (United States)

Trevisan, Marta; Sinigaglia, Alessandro; Desole, Giovanna; Berto, Alessandro; Pacenti, Monia; Palù, Giorgio; Barzon, Luisa

2015-07-13

The recent biotechnology breakthrough of cell reprogramming and generation of induced pluripotent stem cells (iPSCs), which has revolutionized the approaches to study the mechanisms of human diseases and to test new drugs, can be exploited to generate patient-specific models for the investigation of host-pathogen interactions and to develop new antimicrobial and antiviral therapies. Applications of iPSC technology to the study of viral infections in humans have included in vitro modeling of viral infections of neural, liver, and cardiac cells; modeling of human genetic susceptibility to severe viral infectious diseases, such as encephalitis and severe influenza; genetic engineering and genome editing of patient-specific iPSC-derived cells to confer antiviral resistance.

Modeling Viral Infectious Diseases and Development of Antiviral Therapies Using Human Induced Pluripotent Stem Cell-Derived Systems

Directory of Open Access Journals (Sweden)

Marta Trevisan

2015-07-01

Full Text Available The recent biotechnology breakthrough of cell reprogramming and generation of induced pluripotent stem cells (iPSCs, which has revolutionized the approaches to study the mechanisms of human diseases and to test new drugs, can be exploited to generate patient-specific models for the investigation of host–pathogen interactions and to develop new antimicrobial and antiviral therapies. Applications of iPSC technology to the study of viral infections in humans have included in vitro modeling of viral infections of neural, liver, and cardiac cells; modeling of human genetic susceptibility to severe viral infectious diseases, such as encephalitis and severe influenza; genetic engineering and genome editing of patient-specific iPSC-derived cells to confer antiviral resistance.

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.

Stability Analysis of a Reaction-Diffusion System Modeling Atherogenesis

KAUST Repository

Ibragimov, Akif; Ritter, Laura; Walton, Jay R.

2010-01-01

This paper presents a linear, asymptotic stability analysis for a reaction-diffusionconvection system modeling atherogenesis, the initiation of atherosclerosis, as an inflammatory instability. Motivated by the disease paradigm articulated by Ross

Peripheral Nervous System Manifestations in Systemic Autoimmune Diseases

OpenAIRE

COJOCARU, Inimioara Mihaela; COJOCARU, Manole; SILOSI, Isabela; VRABIE, Camelia Doina

2014-01-01

The peripheral nervous system refers to parts of the nervous system outside the brain and spinal cord. Systemic autoimmune diseases can affect both the central and peripheral nervous systems in a myriad of ways and through a heterogeneous number of mechanisms leading to many different clinical manifestations. As a result, neurological complications of these disorders can result in significant morbidity and mortality. The most common complication of peripheral nervous system (PNS) involvement ...

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

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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

Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders

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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

Systemic diseases and the elderly.

LENUS (Irish Health Repository)

McCreary, Christine

2010-11-01

Although systemic diseases can occur at any age, they are more common in older patients. Accurate and detailed medical and drug histories are important in dental practice as many conditions and medications can influence oral health and dental care in patients. Not only can these conditions influence patient care in the surgery and oral hygiene at home, but access to dental services may also be adversely affected. Clinical Relevance: The systemic diseases can impact upon oral care or can have oral manifestations. Many of the pharmacological interventions prescribed for chronic conditions can have multiple and diverse adverse effects on the oral environment.

Lipid Involvement in Neurodegenerative Diseases of the Motor System: Insights from Lysosomal Storage Diseases.

Science.gov (United States)

Dodge, James C

2017-01-01

Lysosomal storage diseases (LSDs) are a heterogeneous group of rare inherited metabolic diseases that are frequently triggered by the accumulation of lipids inside organelles of the endosomal-autophagic-lysosomal system (EALS). There is now a growing realization that disrupted lysosomal homeostasis (i.e., lysosomal cacostasis) also contributes to more common neurodegenerative disorders such as Parkinson disease (PD). Lipid deposition within the EALS may also participate in the pathogenesis of some additional neurodegenerative diseases of the motor system. Here, I will highlight the lipid abnormalities and clinical manifestations that are common to LSDs and several diseases of the motor system, including amyotrophic lateral sclerosis (ALS), atypical forms of spinal muscular atrophy, Charcot-Marie-Tooth disease (CMT), hereditary spastic paraplegia (HSP), multiple system atrophy (MSA), PD and spinocerebellar ataxia (SCA). Elucidating the underlying basis of intracellular lipid mislocalization as well as its consequences in each of these disorders will likely provide innovative targets for therapeutic research.

A model of patient participation with chronic disease in nursing care

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Forough Rafii

2011-04-01

Full Text Available Introduction: Chronic diseases are one of the greatest challenges that health systems facing with them today. Recently, patient participation is considered as a key element in chronic care models. However, there are few studies about participation of patients with chronic disease in caring activities. The aim of this study was to identify the factors, which are relevant to patient participation and the nature of participation in caring activities. Material and Methods: A qualitative approach with a basic theory method was used in this study. 22 persons including 9 patients, 8 nurses, and 5 family members were recruited using purposeful and theoretical sampling in three hospitals affiliated with Iran University of Medical Sciences. Data were collected with semi-structured interview and participant observation. Constant comparison was used for data analysis. Results: Findings of this study indicated that participation of patients with chronic disease in nursing care is a dynamic and interactive concept that occurs between nurse, patient and family member in a care-servicing system. The core theme of this study was "convergence of caring agents" that included four categories: adhering, involving, sharing and true participation. Conclusion: This study suggests a pyramid model for explaining patient participation. Participation occurs in different levels, which depends on the factors related to caring agents.

Classic and New Animal Models of Parkinson's Disease

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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.

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....

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...

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.

Evaluation of an automated connective tissue disease screening assay in Korean patients with systemic rheumatic diseases.

Science.gov (United States)

Jeong, Seri; Yang, Heeyoung; Hwang, Hyunyong

2017-01-01

This study aimed to evaluate the diagnostic utilities of the automated connective tissues disease screening assay, CTD screen, in patients with systemic rheumatic diseases. A total of 1093 serum samples were assayed using CTD screen and indirect immunofluorescent (IIF) methods. Among them, 162 were diagnosed with systemic rheumatic disease, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and mixed connective tissue disease (MCT). The remaining 931 with non-systemic rheumatic disease were assigned to the control group. The median ratios of CTD screen tests were significantly higher in the systemic rheumatic disease group than in the control group. The positive likelihood ratios of the CTD screen were higher than those of IIF in patients with total rheumatic diseases (4.1 vs. 1.6), including SLE (24.3 vs. 10.7). The areas under the receiver operating characteristic curves (ROC-AUCs) of the CTD screen for discriminating total rheumatic diseases, RA, SLE, and MCT from controls were 0.68, 0.56, 0.92 and 0.80, respectively. The ROC-AUCs of the combinations with IIF were significantly higher in patients with total rheumatic diseases (0.72) and MCT (0.85) than in those of the CTD screen alone. Multivariate analysis indicated that both the CTD screen and IIF were independent variables for predicting systemic rheumatic disease. CTD screen alone and in combination with IIF were a valuable diagnostic tool for predicting systemic rheumatic diseases, particularly for SLE.

Evaluation of an automated connective tissue disease screening assay in Korean patients with systemic rheumatic diseases.

Directory of Open Access Journals (Sweden)

Seri Jeong

Full Text Available This study aimed to evaluate the diagnostic utilities of the automated connective tissues disease screening assay, CTD screen, in patients with systemic rheumatic diseases. A total of 1093 serum samples were assayed using CTD screen and indirect immunofluorescent (IIF methods. Among them, 162 were diagnosed with systemic rheumatic disease, including rheumatoid arthritis (RA, systemic lupus erythematosus (SLE, and mixed connective tissue disease (MCT. The remaining 931 with non-systemic rheumatic disease were assigned to the control group. The median ratios of CTD screen tests were significantly higher in the systemic rheumatic disease group than in the control group. The positive likelihood ratios of the CTD screen were higher than those of IIF in patients with total rheumatic diseases (4.1 vs. 1.6, including SLE (24.3 vs. 10.7. The areas under the receiver operating characteristic curves (ROC-AUCs of the CTD screen for discriminating total rheumatic diseases, RA, SLE, and MCT from controls were 0.68, 0.56, 0.92 and 0.80, respectively. The ROC-AUCs of the combinations with IIF were significantly higher in patients with total rheumatic diseases (0.72 and MCT (0.85 than in those of the CTD screen alone. Multivariate analysis indicated that both the CTD screen and IIF were independent variables for predicting systemic rheumatic disease. CTD screen alone and in combination with IIF were a valuable diagnostic tool for predicting systemic rheumatic diseases, particularly for SLE.

Chronic stress impacts the cardiovascular system: animal models and clinical outcomes.

Science.gov (United States)

Golbidi, Saeid; Frisbee, Jefferson C; Laher, Ismail

2015-06-15

Psychological stresses are associated with cardiovascular diseases to the extent that cardiovascular diseases are among the most important group of psychosomatic diseases. The longstanding association between stress and cardiovascular disease exists despite a large ambiguity about the underlying mechanisms. An array of possibilities have been proposed including overactivity of the autonomic nervous system and humoral changes, which then converge on endothelial dysfunction that initiates unwanted cardiovascular consequences. We review some of the features of the two most important stress-activated systems, i.e., the humoral and nervous systems, and focus on alterations in endothelial function that could ensue as a result of these changes. Cardiac and hematologic consequences of stress are also addressed briefly. It is likely that activation of the inflammatory cascade in association with oxidative imbalance represents key pathophysiological components of stress-induced cardiovascular changes. We also review some of the commonly used animal models of stress and discuss the cardiovascular outcomes reported in these models of stress. The unique ability of animals for adaptation under stressful conditions lessens the extrapolation of laboratory findings to conditions of human stress. An animal model of unpredictable chronic stress, which applies various stress modules in a random fashion, might be a useful solution to this predicament. The use of stress markers as indicators of stress intensity is also discussed in various models of animal stress and in clinical studies. Copyright © 2015 the American Physiological Society.

The role of the sociotype in managing chronic disease: integrating bio-psycho-sociology with systems biology.

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Berry, Elliot M

2011-10-01

Attempts have been made to replace the bio-medical approach with that of systems biology, which considers dynamic human behavior (internal factors) for chronic (rather than acute) disease management. They have not yet incorporated the Bio-psycho-social (BPS) model of Engel which adds patients' background and cultural beliefs (external factors) contributing to their susceptibility to, and coping strategies for, non-communicable diseases (NCDs) the increasing domain of global Public Health. The problem is how to include the social determinants of disease in a comprehensive model of care, especially in the management of chronic disease. The concept of "sociotype" is proposed as a framework for understanding the interactions between the social, cultural and environmental inputs that influence the growth, development and life-long behavior of a person, including relationships, lifestyle and coping strategies. Pre-/peri-natal influences on development and subsequent susceptibility to chronic disease are examples of interactions between the sociotype, genotype and phenotype. Disorders of the sociotype, encompassing social determinants (e.g. poverty, education, networking), of disease are major contributors to the increase in NCDs, as well as for mental illness and absenteeism. Thus, people are the product of a threefold cord--genotype, phenotype and sociotype. WHAT NEXT?: Holistic management of patients through the BPS model have to be aligned with the relevant elements of systems biology--context, space, time and robustness--that pertain to the sociotype. Medical curricula should balance basic sciences with disciplines such as psychology, sociology, anthropology and public health that attempt to explain human behavior and the social determinants of disease. This requires methodologies combining qualitative and quantitative research to study simultaneous interactions (and their possible mechanisms) between systems biology and the BPS model. The neologism "sociotype

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

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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

Review of family relational stress and pediatric asthma: the value of biopsychosocial systemic models.

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Wood, Beatrice L; Miller, Bruce D; Lehman, Heather K

2015-06-01

Asthma is the most common chronic disease in children. Despite dramatic advances in pharmacological treatments, asthma remains a leading public health problem, especially in socially disadvantaged minority populations. Some experts believe that this health gap is due to the failure to address the impact of stress on the disease. Asthma is a complex disease that is influenced by multilevel factors, but the nature of these factors and their interrelations are not well understood. This paper aims to integrate social, psychological, and biological literatures on relations between family/parental stress and pediatric asthma, and to illustrate the utility of multilevel systemic models for guiding treatment and stimulating future research. We used electronic database searches and conducted an integrated analysis of selected epidemiological, longitudinal, and empirical studies. Evidence is substantial for the effects of family/parental stress on asthma mediated by both disease management and psychobiological stress pathways. However, integrative models containing specific pathways are scarce. We present two multilevel models, with supporting data, as potential prototypes for other such models. We conclude that these multilevel systems models may be of substantial heuristic value in organizing investigations of, and clinical approaches to, the complex social-biological aspects of family stress in pediatric asthma. However, additional systemic models are needed, and the models presented herein could serve as prototypes for model development. © 2015 Family Process Institute.

Modeling Kidney Disease with iPS Cells

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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

Disease Extinction Versus Persistence in Discrete-Time Epidemic Models.

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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].

Spectacular manifestations of systemic diseases of the snake

DEFF Research Database (Denmark)

Da Silva, Mari-Ann Otkjær; Bertelsen, Mads Frost; Heegaard, Steffen

2015-01-01

This paper reports histopathological findings in the spectacles of four snakes diagnosed with systemic gout, inclusion body disease, disseminated lymphoma and myeloproliferative disease, respectively. Gout was characterised by urate ghost tophi in the stroma and outer epithelium of the spectacle...... to four different systemic diseases with world-wide distribution........ Inclusion body disease affected all layers of the spectacle with intracytoplasmic eosinophilic inclusions. Two cases of neoplasia, lymphoma and myeloproliferative disease, affected the ocular adnexa and the spectacular transition zone. These cases provide novel insight into how the spectacle may respond...

Modeling Neuropsychiatric and Neurodegenerative Diseases With Induced Pluripotent Stem Cells

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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.

Animal Models of Calcific Aortic Valve Disease

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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.

Xenopus: An Emerging Model for Studying Congenital Heart Disease

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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

Can the silkworm (Bombyx mori) be used as a human disease model?

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Tabunoki, Hiroko; Bono, Hidemasa; Ito, Katsuhiko; Yokoyama, Takeshi

2016-02-01

Bombyx mori (silkworm) is the most famous lepidopteran in Japan. B. mori has long been used in the silk industry and also as a model insect for agricultural research. In recent years, B. mori has attracted interest in its potential for use in pathological analysis of model animals. For example, the human macular carotenoid transporter was discovered using information of B. mori carotenoid transporter derived from yellow-cocoon strain. The B. mori carotenoid transport system is useful in human studies. To develop a human disease model, we characterized the human homologs of B. mori, and by constructing KAIKO functional annotation pipeline, and to analyze gene expression profile of a unique B. mori mutant strain using microarray analysis. As a result, we identified a novel molecular network involved in Parkinson's disease. Here we describe the potential use of a spontaneous mutant silkworm strain as a human disease model. We also summarize recent progress in the application of genomic information for annotation of human homologs in B. mori. The B. mori mutant will provide a clue to pathological mechanisms, and the findings will be helpful for the development of therapies and for medical drug discovery.

[Development of expert diagnostic system for common respiratory diseases].

Science.gov (United States)

Xu, Wei-hua; Chen, You-ling; Yan, Zheng

2014-03-01

To develop an internet-based expert diagnostic system for common respiratory diseases. SaaS system was used to build architecture; pattern of forward reasoning was applied for inference engine design; ASP.NET with C# from the tool pack of Microsoft Visual Studio 2005 was used for website-interview medical expert system.The database of the system was constructed with Microsoft SQL Server 2005. The developed expert system contained large data memory and high efficient function of data interview and data analysis for diagnosis of various diseases.The users were able to perform this system to obtain diagnosis for common respiratory diseases via internet. The developed expert system may be used for internet-based diagnosis of various respiratory diseases,particularly in telemedicine setting.

Stem Cells as In Vitro Model of Parkinson's Disease

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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.

Management system of occupational diseases in Korea: statistics, report and monitoring system.

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Rhee, Kyung Yong; Choe, Seong Weon

2010-12-01

The management system of occupational diseases in Korea can be assessed from the perspective of a surveillance system. Workers' compensation insurance reports are used to produce official statistics on occupational diseases in Korea. National working conditions surveys are used to monitor the magnitude of work-related symptoms and signs in the labor force. A health examination program was introduced to detect occupational diseases through both selective and mass screening programs. The Working Environment Measurement Institution assesses workers' exposure to hazards in the workplace. Government regulates that the employer should do health examinations and working conditions measurement through contracted private agencies and following the Occupational Safety and Health Act. It is hoped that these institutions may be able to effectively detect and monitor occupational diseases and hazards in the workplace. In view of this, the occupational management system in Korea is well designed, except for the national survey system. In the future, national surveys for detection of hazards and ill-health outcomes in workers should be developed. The existing surveillance system for occupational disease can be improved by providing more refined information through statistical analysis of surveillance data.

Use of rodents as models of human diseases

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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.

METABO: a new paradigm towards diabetes disease management. An innovative business model.

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Guillén, Alejandra; Colás, Javier; Fico, Giuseppe; Guillén, Sergio

2011-01-01

Dealing with a chronic disease and, more specifically, with Diabetes Mellitus and other metabolic disorders, represents a great challenge for care givers, patients and the healthcare systems as their treatment requires continuous medical care and patient self management. The engagement of patients in the adoption of healthy lifestyles with a positive impact in the progression of their diseases is fundamental to avoid the appearance of chronic complications or co-morbidities. This paper presents the externalization of the health management of diabetic patients as an alternative to the current models of care for these patients that can help improve the quality of follow up and care delivery and contribute to the sustainability of the healthcare systems.

Periodontal and systemic diseases among Swedish dental school patients - a retrospective register study.

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Marjanovic, Marija; Buhlin, Kåre

2013-01-01

To investigate if patients with periodontitis attending the Dental School in Huddinge, Sweden presented with more signs of systemic diseases, such as cardiovascular disease, diabetes mellitus and respiratory diseases, compared to healthy and gingivitis patients. In this retrospective study, dental charts were examined where the periodontal diagnoses of patients were known. A total of 325 patients with severe periodontitis and 149 patients without periodontitis, born 1928 to 1968, were identified. Diagnosis regarding the systemic diseases was self-reported. Odds ratios for cardiovascular diseases, diabetes mellitus and respiratory diseases were calculated with a logistic regression model that was adjusted for age, gender and smoking. It was observed that more cases of periodontitis were found in older individuals than the controls (61.7 vs 56.2 years; P < 0.001). A total of 44.3% of patients with severe periodontitis also suffered from cardiovascular diseases, 19.1% respiratory diseases and 21.2% from diabetes mellitus. Among the controls, 30.9% had cardiovascular disease, 23.5% suffered from respiratory diseases and 6.7% had diabetes mellitus. Across both groups, hypertension was the most frequent diagnosis. There was a significant association between periodontitis and cardiovascular disease (odds ratio [OR] = 1.79, confidence interval [CI] 1.12-2.86), but not between respiratory diseases and periodontitis (OR= 0.88, CI 0.53-1.47). The risk of diabetes mellitus was greater among those patients with periodontitis (OR= 2.95, CI 1.45- 6.01). This study found that patients with periodontitis presented with more systemic diseases, such as cardiovascular disease and diabetes mellitus than control patients. However, no association was found between periodontitis and respiratory diseases. At the present time, the reasons for the associations or lack of association are unknown.

Cardiac disease and arrhythmogenesis: Mechanistic insights from mouse models

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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.

Disease Recording Systems and Herd Health Schemes for Production Diseases

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Østerås O

2001-03-01

Full Text Available Disease recording of cattle is compulsory in Sweden and Norway. Sweden and Denmark also have mandatory disease recording for swine, whereas Finland and Norway only have compulsory recording of infectious diseases. Both compulsory and voluntary systems are databased, the first ones developed in the 1970's. Disease recording at pig slaughtering is somewhat older. The veterinary practitioner, and often also the farmer, can report treated cases as well as fertility disturbances to the systems. Disease recording at slaughter is carried out by veterinarians and inspection officers. The databases are handled by the veterinary authorities or the agricultural organisations in each country. Costs are defrayed by the authorities and/or the agricultural industry. The farmers receive periodic reports. Data are stored for three to ten years, often longer. Affiliation to animal health schemes for cattle or swine is voluntary. In Sweden and Denmark (cattle they are run within the scope of government regulations. Affiliation to animal health programmes may also be demanded by organisations within the agricultural industry. These organisations are also responsible for the administration of the programmes. Costs to take part in herd health schemes are covered by the farmers themselves. In certain cases, grants are received from agricultural organisations, authorities, or the European Union. Recording of diseases and the format of animal health schemes in the Nordic countries are described here in order to illustrate the possibilities to compare data between countries.

Immunogenetic mechanisms for the coexistence of organ-specific and systemic autoimmune diseases.

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Fridkis-Hareli, Masha

2008-02-15

Organ-specific autoimmune diseases affect particular targets in the body, whereas systemic diseases engage multiple organs. Both types of autoimmune diseases may coexist in the same patient, either sequentially or concurrently, sustained by the presence of autoantibodies directed against the corresponding autoantigens. Multiple factors, including those of immunological, genetic, endocrine and environmental origin, contribute to the above condition. Due to association of certain autoimmune disorders with HLA alleles, it has been intriguing to examine the immunogenetic basis for autoantigen presentation leading to the production of two or more autoantibodies, each distinctive of an organ-specific or systemic disease. This communication offers the explanation for shared autoimmunity as illustrated by organ-specific blistering diseases and the connective tissue disorders of systemic nature. Several hypothetical mechanisms implicating HLA determinants, autoantigenic peptides, T cells, and B cells have been proposed to elucidate the process by which two autoimmune diseases are induced in the same individual. One of these scenarios, based on the assumption that the patient carries two disease-susceptible HLA genes, arises when a single T cell epitope of each autoantigen recognizes its HLA protein, leading to the generation of two types of autoreactive B cells, which produce autoantibodies. Another mechanism functioning whilst an epitope derived from either autoantigen binds each of the HLA determinants, resulting in the induction of both diseases by cross-presentation. Finally, two discrete epitopes originating from the same autoantigen may interact with each of the HLA specificities, eliciting the production of both types of autoantibodies. Despite the lack of immediate or unequivocal experimental evidence supporting the present hypothesis, several approaches may secure a better understanding of shared autoimmunity. Among these are animal models expressing the transgenes

Surveillance System for Infectious Diseases of Pets, Santiago, Chile

Science.gov (United States)

López, Javier; Abarca, Katia; Valenzuela, Berta; Lorca, Lilia; Olea, Andrea; Aguilera, Ximena

2009-01-01

Pet diseases may pose risks to human health but are rarely included in surveillance systems. A pilot surveillance system of pet infectious diseases in Santiago, Chile, found that 4 canine and 3 feline diseases accounted for 90.1% and 98.4% of notifications, respectively. Data also suggested association between poverty and pet diseases. PMID:19861073

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.

Periodontal disease and systemic diseases in an older population.

Science.gov (United States)

Özçaka, Özgün; Becerik, Sema; Bıçakcı, Nurgün; Kiyak, Asuman H

2014-01-01

To evaluate the relationship between older adults' medical and oral conditions and their self-reports of periodontal conditions with clinically obtained data. Concerns about oral health of elders and its association with systemic diseases have been gaining more attention. A total of 201 older subjects were interviewed about their previous medical and dental histories and were asked to complete a health questionnaire. Each subject received full mouth exam, including counting number of natural teeth remaining, gingival (GI) and plaque index (PI), CPITN and denture status. Elders who completed health questionnaires had mean age of 62.5. Mean CPITN score was 1.62(± 1.12), PI was 1.57(± 1.48), and GI was 1.55(± 1.31). Women had higher prevalence of CVD and osteoporosis than men (p=0.008, p=0.0001, respectively). Subjects who reported bleeding upon brushing had higher PI and GI scores (p=0.03, p=0.05, respectively). Smokers were more likely to describe their periodontal tissues as unhealthy (72.3% vs. 27.7%, p=0.01), whereas self-reports of healthy vs. unhealthy gums did not differ between non-smokers. These findings suggest that a number of systemic conditions are associated with indicators of periodontal disease, and self-reports of oral conditions are independent of systemic diseases. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Oxidative Stress in Oral Diseases: Understanding Its Relation with Other Systemic Diseases

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Jaya Kumar

2017-09-01

Full Text Available Oxidative stress occurs in diabetes, various cancers, liver diseases, stroke, rheumatoid arthritis, chronic inflammation, and other degenerative diseases related to the nervous system. The free radicals have deleterious effect on various organs of the body. This is due to lipid peroxidation and irreversible protein modification that leads to cellular apoptosis or programmed cell death. During recent years, there is a rise in the oral diseases related to oxidative stress. Oxidative stress in oral disease is related to other systemic diseases in the body such as periodontitis, cardiovascular, pancreatic, gastric, and liver diseases. In the present review, we discuss the various pathways that mediate oxidative cellular damage. Numerous pathways mediate oxidative cellular damage and these include caspase pathway, PERK/NRF2 pathway, NADPH oxidase 4 pathways and JNK/mitogen-activated protein (MAP kinase pathway. We also discuss the role of inflammatory markers, lipid peroxidation, and role of oxygen species linked to oxidative stress. Knowledge of different pathways, role of inflammatory markers, and importance of low-density lipoprotein, fibrinogen, creatinine, nitric oxide, nitrates, and highly sensitive C-reactive proteins may be helpful in understanding the pathogenesis and plan better treatment for oral diseases which involve oxidative stress.

Development of a disease risk prediction model for downy mildew (Peronospora sparsa) in boysenberry.

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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).

Cost of post-weaning multi-systemic wasting syndrome and porcine circovirus type-2 subclinical infection in England - an economic disease model.

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Alarcon, Pablo; Rushton, Jonathan; Wieland, Barbara

2013-06-01

Post-weaning multi-systemic wasting syndrome (PMWS) is a multi-factorial disease with major economic implications for the pig industry worldwide. The present study aimed to assess the economic impact of PMWS and porcine circovirus type 2 (PCV2) subclinical infections (PCV2SI) for farrow-to-finish farms and to estimate the resulting cost to the English pig industry. A disease model was built to simulate the varying proportions of pigs in a batch that get infected with PCV2 and develop either PMWS, subclinical disease (reduce growth without evident clinical signs) or remain healthy (normal growth and no clinical signs), depending on the farm level PMWS severity. This PMWS severity measure accounted for the level of post-weaning mortality, PMWS morbidity and proportion of PCV2 infected pigs observed on farms. The model generated six outcomes: infected pigs with PMWS that die (PMWS-D); infected pigs with PMWS that recover (PMWS-R); subclinical pigs that die (Sub-D); subclinical pigs that reach slaughter age (Sub-S); healthy pigs sold (H-S); and pigs, infected or non-infected by PCV2, that die due to non-PCV2 related causes (nonPCV2-D). Enterprise and partial budget analyses were used to assess the deficit/profits and the extra costs/extra benefits of a change in disease status, respectively. Results from the economic analysis at pig level were combined with the disease model's estimates of the proportion of different pigs produced at different severity scores to assess the cost of PMWS and subclinical disease at farm level, and these were then extrapolated to estimate costs at national level. The net profit for a H-S pig was £19.2. The mean loss for a PMWS-D pig was £84.1 (90% CI: 79.6-89.1), £24.5 (90% CI: 15.1-35.4) for a PMWS-R pig, £82.3 (90% CI: 78.1-87.5) for a Sub-D pig, and £8.1 (90% CI: 2.18-15.1) for a Sub-S pig. At farm level, the greatest proportion of negative economic impact was attributed to PCV2 subclinical pigs. The economic impact for the English

Periodontitis in coronary heart disease patients: strong association between bleeding on probing and systemic biomarkers.

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Bokhari, Syed Akhtar H; Khan, Ayyaz A; Butt, Arshad K; Hanif, Mohammad; Izhar, Mateen; Tatakis, Dimitris N; Ashfaq, Mohammad

2014-11-01

Few studies have examined the relationship of individual periodontal parameters with individual systemic biomarkers. This study assessed the possible association between specific clinical parameters of periodontitis and systemic biomarkers of coronary heart disease risk in coronary heart disease patients with periodontitis. Angiographically proven coronary heart disease patients with periodontitis (n = 317), aged >30 years and without other systemic illness were examined. Periodontal clinical parameters of bleeding on probing (BOP), probing depth (PD), and clinical attachment level (CAL) and systemic levels of high-sensitivity C-reactive protein (CRP), fibrinogen (FIB) and white blood cells (WBC) were noted and analyzed to identify associations through linear and stepwise multiple regression analyses. Unadjusted linear regression showed significant associations between periodontal and systemic parameters; the strongest association (r = 0.629; p periodontal and systemic inflammation marker, respectively. Stepwise regression analysis models revealed that BOP was a predictor of systemic CRP levels (p periodontal parameter significantly associated with each systemic parameter (CRP, FIB, and WBC). In coronary heart disease patients with periodontitis, BOP is strongly associated with systemic CRP levels; this association possibly reflects the potential significance of the local periodontal inflammatory burden for systemic inflammation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Accelerated atherosclerosis in patients with systemic autoimmune diseases

NARCIS (Netherlands)

De Leeuw, K.; Kallenberg, Cees; Bijl, Marc; Shoenfeld, Y.; Gershwin, M.E.; Shoenfeld, Y; Gershwin, ME

2005-01-01

Systemic autoimmune diseases such as systemic lupus erythematosus and Wegener's granulomatosis are associated with a significantly increased prevalence of cardiovascular disease (CVD) compared with age- and sex-matched controls. Many risk factors are involved in the pathogenesis of atherosclerosis,

Mitochondrial and Ubiquitin Proteasome System Dysfunction in Ageing and Disease: Two Sides of the Same Coin?

Directory of Open Access Journals (Sweden)

Jaime M. Ross

2015-08-01

Full Text Available Mitochondrial dysfunction and impairment of the ubiquitin proteasome system have been described as two hallmarks of the ageing process. Additionally, both systems have been implicated in the etiopathogenesis of many age-related diseases, particularly neurodegenerative disorders, such as Alzheimer’s and Parkinson’s disease. Interestingly, these two systems are closely interconnected, with the ubiquitin proteasome system maintaining mitochondrial homeostasis by regulating organelle dynamics, the proteome, and mitophagy, and mitochondrial dysfunction impairing cellular protein homeostasis by oxidative damage. Here, we review the current literature and argue that the interplay of the two systems should be considered in order to better understand the cellular dysfunction observed in ageing and age-related diseases. Such an approach may provide valuable insights into molecular mechanisms underlying the ageing process, and further discovery of treatments to counteract ageing and its associated diseases. Furthermore, we provide a hypothetical model for the heterogeneity described among individuals during ageing.

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

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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.

Qualitative properties and hopf bifurcation in haematopoietic disease model with chemotherapy

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Yafia R.

2014-01-01

Full Text Available In this paper, we consider a model describing the dynamics of Hematopoietic Stem Cells (HSC disease with chemotherapy. The model is given by a system of three ordinary differential equations with discrete delay. Its dynamics are studied in term of local stability of the possible steady states for the case without drug intervention term. We prove the existence of periodic oscillations for each case when the delay passes trough a critical values. In the end, we illustrate our results by some numerical simulations.

Interstitial lung disease in systemic autoimmune rheumatic diseases: a comprehensive review.

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Atzeni, Fabiola; Gerardi, Maria Chiara; Barilaro, Giuseppe; Masala, Ignazio Francesco; Benucci, Maurizio; Sarzi-Puttini, Piercarlo

2018-01-01

Interstitial lung diseases (ILDs) are among the most serious complications associated with systemic rheumatic diseases, and lead to significant morbidity and mortality; they may also be the first manifestation of connective tissue diseases (CTDs). The aim of this narrative review is to summarise the data concerning the pathogenesis of CTD/ILD and its distinguishing features in different rheumatic diseseas. Areas covered: The pathogenesis, clinical aspects and treatment of ILD associated with rheumatic systemic diseases and CTDs were reviewed by searching the PubMed, Medline, and Cochrane Library databases for papers published between 1995 and February 2017 using combinations of words or terms. Articles not written in English were excluded. Expert commentary: The management of CTD-ILD is challenging because of the lack of robust data regarding the treatments used, the heterogeneity of the diseases themselves, and the scarcity of well-defined outcome measures. Treatment decisions are often made clinically on the basis of functional, radiographic progression, and exacerbating factors such as age and the burden of comorbidities. Given the complexities of diagnosis and the paucity of treatment trials, the management of CTD patients with ILD requires multidisciplinary collaboration between rheumatologists and pulmonologists in CTD-ILD clinics.

Pharmacokinetic modeling of therapies for systemic lupus erythematosus

OpenAIRE

Yang, Xiaoyan; Sherwin, Catherine MT; Yu, Tian; Yellepeddi, Venkata K; Brunner, Hermine I; Vinks, Alexander A

2015-01-01

With the increasing use of different types of therapies in treating autoimmune diseases such as systemic lupus erythematosus (SLE), there is a need to utilize pharmacokinetic (PK) strategies to optimize the clinical outcome of these treatments. Various PK analysis approaches, including population PK modeling and physiologically based PK modeling, have been used to evaluate drug PK characteristics and population variability or to predict drug PK profiles in a mechanistic manner. This review ou...

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine

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Mizeranschi, A.; Groen, D.; Borgdorff, J.; Hoekstra, A.G.; Chopard, B.; Dubitzky, W.; Schmitz, U; Wolkenhauer, O.

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases.

Endodontic medicine: connections between apical periodontitis and systemic diseases.

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Segura-Egea, J J; Martín-González, J; Castellanos-Cosano, L

2015-10-01

The prevalence of apical periodontitis (AP) in Europe has been reported to affect 61% of individuals and 14% of teeth, and increase with age. Likewise, the prevalence of root canal treatment (RCT) in Europe is estimated to be around 30-50% of individuals and 2-9% of teeth with radiographic evidence of chronic persistent AP in 30-65% of root filled teeth (RFT). AP is not only a local phenomenon and for some time the medical and dental scientific community have analysed the possible connection between apical periodontits and systemic health. Endodontic medicine has developed, with increasing numbers of reports describing the association between periapical inflammation and systemic diseases. The results of studies carried out both in animal models and humans are not conclusive, but suggest an association between endodontic variables, that is AP and RCT, and diabetes mellitus (DM), tobacco smoking, coronary heart disease and other systemic diseases. Several studies have reported a higher prevalence of periapical lesions, delayed periapical repair, greater size of osteolityc lesions, greater likelihood of asymptomatic infections and poorer prognosis for RFT in diabetic patients. On the other hand, recent studies have found that a poorer periapical status correlates with higher HbA1c levels and poor glycaemic control in type 2 diabetic patients. However, there is no scientific evidence supporting a causal effect of periapical inflammation on diabetes metabolic control. The possible association between smoking habits and endodontic infection has also been investigated, with controversial results. The aim of this paper was to review the literature on the association between endodontic variables and systemic health (especially DM and smoking habits). © 2015 International Endodontic Journal. Published by John Wiley & Sons Ltd.

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

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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.

Modelling Alzheimer’s disease: from past to future

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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.

Nephrolithiasis as a common urinary system manifestation of inflammatory bowel diseases; a clinical review and meta-analysis.

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Ganji-Arjenaki, Mahboube; Nasri, Hamid; Rafieian-Kopaei, Mahmoud

2017-07-01

The extra-intestinal manifestations of inflammatory bowel disease (IBD) are common and involve other organs or systems for example; urinary system. For this review, we used a variety of sources by searching through Web of Science, PubMed, EMBASE, Scopus and directory of open access journals (DOAJ). Urinary complications may occur in up to 22% of patients and nephrolithiasis or renal/kidney stones have been suggested to be a common manifestation of disease in forms of uric acid, calcium phosphate or calcium oxalate. We performed a meta-analysis on five clinical trials and reported that correlation between IBD and formation of stone in renal system is positive and significant (Fix-effect model; CI: 95%, P <0.001, and randomeffect model; CI: 95%, P = 0.03). Based on the reports of the clinical trials, calcium oxalate is more prevalent in Crohn's disease (CD) than in ulcerative colitis (UC).

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.

It's all in the timing: modeling isovolumic contraction through development and disease with a dynamic dual electromechanical bioreactor system.

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Morgan, Kathy Ye; Black, Lauren Deems

2014-01-01

This commentary discusses the rationale behind our recently reported work entitled "Mimicking isovolumic contraction with combined electromechanical stimulation improves the development of engineered cardiac constructs," introduces new data supporting our hypothesis, and discusses future applications of our bioreactor system. The ability to stimulate engineered cardiac tissue in a bioreactor system that combines both electrical and mechanical stimulation offers a unique opportunity to simulate the appropriate dynamics between stretch and contraction and model isovolumic contraction in vitro. Our previous study demonstrated that combined electromechanical stimulation that simulated the timing of isovolumic contraction in healthy tissue improved force generation via increased contractile and calcium handling protein expression and improved hypertrophic pathway activation. In new data presented here, we further demonstrate that modification of the timing between electrical and mechanical stimulation to mimic a non-physiological process negatively impacts the functionality of the engineered constructs. We close by exploring the various disease states that have altered timing between the electrical and mechanical stimulation signals as potential future directions for the use of this system.

Optimizing agent-based transmission models for infectious diseases.

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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.

Internet-based surveillance systems for monitoring emerging infectious diseases.

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Milinovich, Gabriel J; Williams, Gail M; Clements, Archie C A; Hu, Wenbiao

2014-02-01

Emerging infectious diseases present a complex challenge to public health officials and governments; these challenges have been compounded by rapidly shifting patterns of human behaviour and globalisation. The increase in emerging infectious diseases has led to calls for new technologies and approaches for detection, tracking, reporting, and response. Internet-based surveillance systems offer a novel and developing means of monitoring conditions of public health concern, including emerging infectious diseases. We review studies that have exploited internet use and search trends to monitor two such diseases: influenza and dengue. Internet-based surveillance systems have good congruence with traditional surveillance approaches. Additionally, internet-based approaches are logistically and economically appealing. However, they do not have the capacity to replace traditional surveillance systems; they should not be viewed as an alternative, but rather an extension. Future research should focus on using data generated through internet-based surveillance and response systems to bolster the capacity of traditional surveillance systems for emerging infectious diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

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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.

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

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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

A Mathematical Model of Skeletal Muscle Disease and Immune Response in the mdx Mouse

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Abdul Salam Jarrah

2014-01-01

Full Text Available Duchenne muscular dystrophy (DMD is a genetic disease that results in the death of affected boys by early adulthood. The genetic defect responsible for DMD has been known for over 25 years, yet at present there is neither cure nor effective treatment for DMD. During early disease onset, the mdx mouse has been validated as an animal model for DMD and use of this model has led to valuable but incomplete insights into the disease process. For example, immune cells are thought to be responsible for a significant portion of muscle cell death in the mdx mouse; however, the role and time course of the immune response in the dystrophic process have not been well described. In this paper we constructed a simple mathematical model to investigate the role of the immune response in muscle degeneration and subsequent regeneration in the mdx mouse model of Duchenne muscular dystrophy. Our model suggests that the immune response contributes substantially to the muscle degeneration and regeneration processes. Furthermore, the analysis of the model predicts that the immune system response oscillates throughout the life of the mice, and the damaged fibers are never completely cleared.

Insulin-Like Growth Factor (IGF System in Liver Diseases

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Agnieszka Adamek

2018-04-01

Full Text Available Hepatocyte differentiation, proliferation, and apoptosis are affected by growth factors produced in liver. Insulin-like growth factor 1 and 2 (IGF1 and IGF2 act in response to growth hormone (GH. Other IGF family components include at least six binding proteins (IGFBP1 to 6, manifested by both IGFs develop due to interaction through the type 1 receptor (IGF1R. The data based on animal models and/or in vitro studies suggest the role of IGF system components in cellular aspects of hepatocarcinogenesis (cell cycle progression, uncontrolled proliferation, cell survival, migration, inhibition of apoptosis, protein synthesis and cell growth, and show that systemic IGF1 administration can reduce fibrosis and ameliorate general liver function. In epidemiologic and clinicopathological studies on chronic liver disease (CLD, lowered serum levels, decreased tissue expression of IGF1, elevated production of IGF1R and variable IGF2 expression has been noted, from the start of preneoplastic alterations up to the developed hepatocellular carcinoma (HCC stage. These changes result in well-known clinical symptoms of IGF1 deficiency. This review summarized the current data of the complex role of IGF system components in the most common CLD (nonalcoholic fatty liver disease, cirrhosis, and hepatocellular carcinoma. Better recognition and understanding of this system can contribute to discovery of new and improved versions of current preventive and therapeutic actions in CLD.

Home Automated Telemanagement (HAT System to Facilitate Self-Care of Patients with Chronic Diseases

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Joseph Finkelstein

2003-06-01

Full Text Available Successful patient self-management requires a multidisciplinary approach that includes regular patient assessment, disease-specific education, control of medication adherence, implementation of health behavior change models and social support. Existing systems for computer-assisted disease management do not provide this multidisciplinary patient support and do not address treatment compliance issues. We developed the Home Automated Telemanagement (HAT system for patients with different chronic health conditions to facilitate their self-care. The HAT system consists of a home unit, HAT server, and clinician units. Patients at home use a palmtop or a laptop connected with a disease monitor on a regular basis. Each HAT session consists of self-testing, feedback, and educational components. The self-reported symptom data and objective results obtained from disease-specific sensors are automatically sent from patient homes to the HAT server in the hospital. Any web-enabled device can serve as a clinician unit to review patient results. The HAT system monitors self-testing results and patient compliance. The HAT system has been implemented and tested in patients receiving anticoagulation therapy, patients with asthma, COPD and other health conditions. Evaluation results indicated high level of acceptance of the HAT system by the patients and that the system has a positive impact on main clinical outcomes and patient satisfaction with medical care.

Information system for diagnosis of respiratory system diseases

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Abramov, G. V.; Korobova, L. A.; Ivashin, A. L.; Matytsina, I. A.

2018-05-01

An information system is for the diagnosis of patients with lung diseases. The main problem solved by this system is the definition of the parameters of cough fragments in the monitoring recordings using a voice recorder. The authors give the recognition criteria of recorded cough moments, audio records analysis. The results of the research are systematized. The cough recognition system can be used by the medical specialists to diagnose the condition of the patients and to monitor the process of their treatment.

The role of geographic information systems inwildlife epidemiology: models of chronic wasting disease in Colorado mule deer

OpenAIRE

Farnsworth, Matthew L.; Hoeting, Jennifer A.; Hobbs, N. Thompson; Conner, Mary M.; Burnham, Kenneth P.; Wolfe, Lisa L.; Williams, Elizabeth S.; Theobald, David M.; Miller, Michael W.

2007-01-01

The authors present findings from two landscape epidemiology studies of chronic wasting disease (CWD) in northern Colorado mule deer (Odocoileus hemionus). First, the effects of human land use on disease prevalence were explored by formulating a set of models estimating CWD prevalence in relation to differences in human land use, sex and geographic location. Prevalence was higher in developed areas and among male deer suggesting that anthropogenic influences (changes in land use), differences...

Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

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Urbain, Jay

2015-12-01

We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic patients over time. The system was originally developed for the 2014 i2b2 Challenges in Natural Language in Clinical Data. The system's strengths included a high level of accuracy for identifying named entities associated with heart disease risk factor events. The system's primary weakness was due to inaccuracies when characterizing the attributes of some events. For example, determining the relative time of an event with respect to the record date, whether an event is attributable to the patient's history or the patient's family history, and differentiating between current and prior smoking status. We believe these inaccuracies were due in large part to the lack of an effective approach for integrating context into our event detection model. To address these inaccuracies, we explore the addition of a distributional semantic model for characterizing contextual evidence of heart disease risk factor events. Using this semantic model, we raise our initial 2014 i2b2 Challenges in Natural Language of Clinical data F1 score of 0.838 to 0.890 and increased precision by 10.3% without use of any lexicons that might bias our results. Copyright © 2015 Elsevier Inc. All rights reserved.

Mathematical Models and Methods for Living Systems

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Chaplain, Mark; Pugliese, Andrea

2016-01-01

The aim of these lecture notes is to give an introduction to several mathematical models and methods that can be used to describe the behaviour of living systems. This emerging field of application intrinsically requires the handling of phenomena occurring at different spatial scales and hence the use of multiscale methods. Modelling and simulating the mechanisms that cells use to move, self-organise and develop in tissues is not only fundamental to an understanding of embryonic development, but is also relevant in tissue engineering and in other environmental and industrial processes involving the growth and homeostasis of biological systems. Growth and organization processes are also important in many tissue degeneration and regeneration processes, such as tumour growth, tissue vascularization, heart and muscle functionality, and cardio-vascular diseases.

Diabetes mellitus disease management in a safety net hospital system: translating evidence into practice.

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Butler, Michael K; Kaiser, Michael; Johnson, Jolene; Besse, Jay; Horswell, Ronald

2010-12-01

The Louisiana State University Health Care Services Division system assessed the effectiveness of implementing a multisite disease management program targeting diabetes mellitus in an indigent patient population. A population-based disease management program centered on evidence-based clinical care guidelines was applied from the system level. Specific clinic modifications and models were used, as well as ancillary services such as medication assistance and equipment subsidies. Marked improvement in process goals led to improved clinical outcomes. From 2001 to 2008, the percentage of patients with a hemoglobin A1c management programs can be successfully implemented and achieve statistically significant results.

Visual system manifestations of Alzheimer's disease.

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Kusne, Yael; Wolf, Andrew B; Townley, Kate; Conway, Mandi; Peyman, Gholam A

2017-12-01

Alzheimer's disease (AD) is an increasingly common disease with massive personal and economic costs. While it has long been known that AD impacts the visual system, there has recently been an increased focus on understanding both pathophysiological mechanisms that may be shared between the eye and brain and how related biomarkers could be useful for AD diagnosis. Here, were review pertinent cellular and molecular mechanisms of AD pathophysiology, the presence of AD pathology in the visual system, associated functional changes, and potential development of diagnostic tools based on the visual system. Additionally, we discuss links between AD and visual disorders, including possible pathophysiological mechanisms and their relevance for improving our understanding of AD. © 2016 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

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

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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.

[Evaluation on application of China Disease Prevention and Control Information System of Hydatid Disease II System integration and simulation tests].

Science.gov (United States)

Qing, Yu; Shuai, Han; Qiang, Wang; Jing-Bo, Xue

2017-06-08

To report the integrated progress of the hydatid disease information management system, and to provide the reference for further system improvements by analysis of results on simulation test feedback. The work of institutional code matching by collecting fundamental and integrated information of the system in epidemic areas of hydatid disease was carried out, and professional control agencies were selected to carry out the simulation test. The results of agencies code matching at stage indicated the average completion rate was 94.30% on administrative agencies, 69.94% on registered professional agencies and 56.40% on professional institutions matching related to hydatid disease prevention and control implements in seven provinces (autonomous regions) and Xinjiang Production and Construction Corps. Meanwhile, the response rate of open-ended proposals was 93.33% on fifteen feedbacks, and the statistics showed 21.43% believed the system was low fluency, 64.29% considered the system was inconvenience for data inputs and 42.86% considered it would be improved on system statistics functions, of which 27.78% were provincial users, 22.22% were the city users and 50.00% were the county users. The hydatid disease prevention information management system meets the fundamental needs of the majority agencies in hyperendemic areas of echinococcosis, it needs to develop the further test with more agencies joining after the work of the institutional code matching completion and the system service improvement in the next stage.

System dynamics model for environment - human systems interaction in the mining industry

International Nuclear Information System (INIS)

Pal, B.K.

1994-01-01

Use of advanced technology in the mining activities are polluting the natural environment, interfering with the normal life of the miners/residents. In this paper, health hazards due to underground workings and effect of environmental conditions on men are discussed. A composite system inter-relationship of the mining industries with the Government, society and environmental sectors is established. Allowing certain level of pollution, a system dynamics model is developed considering the parameters like more revenues from the mining industries, degradation of quality of life index - environmental index on long-term and short-term basis, new diseases due to pollution, social awareness, health care facilities, tax exemption etc. This model will help us to understand the optimisation of the parameters to establish the better interaction in the environment-human systems in the mining industries. 14 refs., 4 figs., 2 tabs

Fetal Origins of Life Stage Disease: A Zebrafish Model for the ...

Science.gov (United States)

In the U.S., childhood obesity has more than doubled in children and quadrupled in adolescents in the past 30 years, affects 35% of adults, and costs the U.S. healthcare industry >$200 billion annually. The chemical environment in the womb may cause susceptibility to different life-stage and life-long metabolic diseases including obesity. The challenge is to understand if exposures during developmentally sensitive windows impact life-stage disease, such as obesity, by increasing adipose tissue mass. In vitro models lack the integrated systems approach needed to assess adipose development, while mammalian models are impractical in a screen of thousands of chemicals. Therefore, an obesogen screening method was developed to interrogate bioactivity using a full systems approach, in a vertebrate zebrafish model with complete metabolic activity, at a time when the full signaling repertoire is expressed and active, to optimally examine how chemical dose and duration impact life-stage adipose mass. A time-line for adipose depot formation was mapped in zebrafish 6−14 days post fertilization (dpf) using the lipophilic dye, Nile Red, in combination with fluorescent microscopy. Those time points were then used to investigate the impact of embryonic tributyltin chloride (TBT, a known obesogen) exposure (10nM daily renewal, 0−5dpf) on adipose mass. Fluorescent microscopy revealed adipose depots that were larger and appeared 2 days earlier in TBT treated compared to contro

The Regional Healthcare Ecosystem Analyst (RHEA): a simulation modeling tool to assist infectious disease control in a health system.

Science.gov (United States)

Lee, Bruce Y; Wong, Kim F; Bartsch, Sarah M; Yilmaz, S Levent; Avery, Taliser R; Brown, Shawn T; Song, Yeohan; Singh, Ashima; Kim, Diane S; Huang, Susan S

2013-06-01

As healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare 'ecosystem' in infection control. We developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases. To demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity). Our model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities. A decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.

Diversity of aging of the immune system classified in the cotton rat (Sigmodon hispidus) model of human infectious diseases.

Science.gov (United States)

Guichelaar, Teun; van Erp, Elisabeth A; Hoeboer, Jeroen; Smits, Noortje A M; van Els, Cécile A C M; Pieren, Daan K J; Luytjes, Willem

2018-05-01

Susceptibility and declined resistance to human pathogens like respiratory syncytial virus (RSV) at old age is well represented in the cotton rat (Sigmodon hispidus). Despite providing a preferred model of human infectious diseases, little is known about aging of its adaptive immune system. We aimed to define aging-related changes of the immune system of this species. Concomitantly, we asked whether the rate of immunological alterations may be stratified by physiological aberrations encountered during aging. With increasing age, cotton rats showed reduced frequencies of T cells, impaired induction of antibodies to RSV, higher incidence of aberrations of organs and signs of lipemia. Moreover, old animals expressed high biological heterogeneity, but the age-related reduction of T cell frequency was only observed in those specimens that displayed aberrant organs. Thus, cotton rats show age-related alterations of lymphocytes that can be classified by links with health status. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

The role of the immune system in kidney disease.

Science.gov (United States)

Tecklenborg, J; Clayton, D; Siebert, S; Coley, S M

2018-05-01

The immune system and the kidneys are closely linked. In health the kidneys contribute to immune homeostasis, while components of the immune system mediate many acute forms of renal disease and play a central role in progression of chronic kidney disease. A dysregulated immune system can have either direct or indirect renal effects. Direct immune-mediated kidney diseases are usually a consequence of autoantibodies directed against a constituent renal antigen, such as collagen IV in anti-glomerular basement membrane disease. Indirect immune-mediated renal disease often follows systemic autoimmunity with immune complex formation, but can also be due to uncontrolled activation of the complement pathways. Although the range of mechanisms of immune dysregulation leading to renal disease is broad, the pathways leading to injury are similar. Loss of immune homeostasis in renal disease results in perpetual immune cell recruitment and worsening damage to the kidney. Uncoordinated attempts at tissue repair, after immune-mediated disease or non-immune mediated injury, result in fibrosis of structures important for renal function, leading eventually to kidney failure. As renal disease often manifests clinically only when substantial damage has already occurred, new diagnostic methods and indeed treatments must be identified to inhibit further progression and promote appropriate tissue repair. Studying cases in which immune homeostasis is re-established may reveal new treatment possibilities. © 2018 British Society for Immunology.

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.

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

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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.

Using Cultural Modeling to Inform a NEDSS-Compatible System Functionality Evaluation

Science.gov (United States)

Anderson, Olympia; Torres-Urquidy, Miguel

2013-01-01

Objective The culture by which public health professionals work defines their organizational objectives, expectations, policies, and values. These aspects of culture are often intangible and difficult to qualify. The introduction of an information system could further complicate the culture of a jurisdiction if the intangibles of a culture are not clearly understood. This report describes how cultural modeling can be used to capture intangible elements or factors that may affect NEDSS-compatible (NC) system functionalities within the culture of public health jurisdictions. Introduction The National Notifiable Disease Surveillance System (NNDSS) comprises many activities including collaborations, processes, standards, and systems which support gathering data from US states and territories. As part of NNDSS, the National Electronic Disease Surveillance System (NEDSS) provides the standards, tools, and resources to support reporting public health jurisdictions (jurisdictions). The NEDSS Base System (NBS) is a CDC-developed, software application available to jurisdictions to collect, manage, analyze and report national notifiable disease (NND) data. An evaluation of NEDSS with the objective of identifying the functionalities of NC systems and the impact of these features on the user’s culture is underway. Methods We used cultural models to capture additional NC system functionality gaps within the culture of the user. Cultural modeling is a process of graphically depicting people and organizations referred to as influencers and the intangible factors that affect the user’s operations or work as influences. Influencers are denoted as bubbles while influences are depicted as arrows penetrating the bubbles. In the cultural model, influence can be seen by the size and proximity (or lack of) in the model. We restricted the models to secondary data sources and interviews of CDC programs (data users) and public health jurisdictions (data reporters). Results Three cultural

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.

Simulating Nationwide Pandemics: Applying the Multi-scale Epidemiologic Simulation and Analysis System to Human Infectious Diseases

Energy Technology Data Exchange (ETDEWEB)

Dombroski, M; Melius, C; Edmunds, T; Banks, L E; Bates, T; Wheeler, R

2008-09-24

This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to human epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future

Pathway reconstruction of airway remodeling in chronic lung diseases: a systems biology approach.

Directory of Open Access Journals (Sweden)

Ali Najafi

Full Text Available Airway remodeling is a pathophysiologic process at the clinical, cellular, and molecular level relating to chronic obstructive airway diseases such as chronic obstructive pulmonary disease (COPD, asthma and mustard lung. These diseases are associated with the dysregulation of multiple molecular pathways in the airway cells. Little progress has so far been made in discovering the molecular causes of complex disease in a holistic systems manner. Therefore, pathway and network reconstruction is an essential part of a systems biology approach to solve this challenging problem. In this paper, multiple data sources were used to construct the molecular process of airway remodeling pathway in mustard lung as a model of airway disease. We first compiled a master list of genes that change with airway remodeling in the mustard lung disease and then reconstructed the pathway by generating and merging the protein-protein interaction and the gene regulatory networks. Experimental observations and literature mining were used to identify and validate the master list. The outcome of this paper can provide valuable information about closely related chronic obstructive airway diseases which are of great importance for biologists and their future research. Reconstructing the airway remodeling interactome provides a starting point and reference for the future experimental study of mustard lung, and further analysis and development of these maps will be critical to understanding airway diseases in patients.

[Neurophysiology of systemic diseases].

Science.gov (United States)

Attarian, S

2004-01-01

Connective tissue diseases represent a varied and challenging group of disorders. Neuromuscular structures are highly susceptible targets for damage. In this review, the neurophysiological explorations of the neuromuscular complications are examined with particular attention to the peripheral nerve system. The most common presentations are sensorimotor polyneuropathy, mononeuritis multiplex, distal symmetric neuropathy, compression neuropathy and trigeminal sensory neuropathy.

Thyroid disease and the cardiovascular system.

Science.gov (United States)

Danzi, Sara; Klein, Irwin

2014-06-01

Thyroid hormones, specifically triiodothyronine (T3), have significant effects on the heart and cardiovascular system. Hypothyroidism, hyperthyroidism, subclinical thyroid disease, and low T3 syndrome each cause cardiac and cardiovascular abnormalities through both genomic and nongenomic effects on cardiac myocytes and vascular smooth muscle cells. In compromised health, such as occurs in heart disease, alterations in thyroid hormone metabolism may further impair cardiac and cardiovascular function. Diagnosis and treatment of cardiac disease may benefit from including analysis of thyroid hormone status, including serum total T3 levels. Copyright © 2014 Elsevier Inc. All rights reserved.

Innovative measures to combat rare diseases in China: The national rare diseases registry system, larger-scale clinical cohort studies, and studies in combination with precision medicine research.

Science.gov (United States)

Song, Peipei; He, Jiangjiang; Li, Fen; Jin, Chunlin

2017-02-01

China is facing the great challenge of treating the world's largest rare disease population, an estimated 16 million patients with rare diseases. One effort offering promise has been a pilot national project that was launched in 2013 and that focused on 20 representative rare diseases. Another government-supported special research program on rare diseases - the "Rare Diseases Clinical Cohort Study" - was launched in December 2016. According to the plan for this research project, the unified National Rare Diseases Registry System of China will be established as of 2020, and a large-scale cohort study will be conducted from 2016 to 2020. The project plans to develop 109 technical standards, to establish and improve 2 national databases of rare diseases - a multi-center clinical database and a biological sample library, and to conduct studies on more than 50,000 registered cases of 50 different rare diseases. More importantly, this study will be combined with the concept of precision medicine. Chinese population-specific basic information on rare diseases, clinical information, and genomic information will be integrated to create a comprehensive predictive model with a follow-up database system and a model to evaluate prognosis. This will provide the evidence for accurate classification, diagnosis, treatment, and estimation of prognosis for rare diseases in China. Numerous challenges including data standardization, protecting patient privacy, big data processing, and interpretation of genetic information still need to be overcome, but research prospects offer great promise.

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.

PERIODONTAL INFECTIONS AS A RISK FACTOR FOR VARIOUS SYSTEMIC DISEASES

OpenAIRE

Solanki, Gaurav; Solanki, Renu

2012-01-01

A healthy periodontium is needed for the general well being of an individual. However, periodontal diseases are common and periodontal infections are increasingly associated with systemic diseases. The literature is focused on the association between periodontal infections and systemic diseases. The individuals with periodontal disease may be at higher risk for adverse medical outcomes including cardiovascular diseases, respiratory infections, adverse pregnancy outcomes, rheumatoid arthritis ...

[Parasitic diseases of the central nervous system].

Science.gov (United States)

Schmutzhard, E

2010-02-01

Central nervous system infections and infestations by protozoa and helminths constitute a problem of increasing importance throughout all of central European and northern/western countries. This is partially due to the globalisation of our society, tourists and business people being more frequently exposed to parasitic infection/infestation in tropical countries than in moderate climate countries. On top of that, migrants may import chronic infestations and infections with parasitic pathogens, eventually also--sometimes exclusively--involving the nervous system. Knowledge of epidemiology, initial clinical signs and symptoms, diagnostic procedures as well as specific chemotherapeutic therapies and adjunctive therapeutic strategies is of utmost important in all of these infections and infestations of the nervous systems, be it by protozoa or helminths. This review lists, mainly in the form of tables, all possible infections and infestations of the nervous systems by protozoa and by helminths. Besides differentiating parasitic diseases of the nervous system seen in migrants, tourists etc., it is very important to have in mind that disease-related (e.g. HIV) or iatrogenic immunosuppression has led to the increased occurrence of a wide variety of parasitic infections and infestations of the nervous system (e. g. babesiosis, Chagas disease, Strongyloides stercoralis infestation, toxoplasmosis, etc.).

Virtual Systems Pharmacology (ViSP software for mechanistic system-level model simulations

Directory of Open Access Journals (Sweden)

Sergey eErmakov

2014-10-01

Full Text Available Multiple software programs are available for designing and running large scale system-level pharmacology models used in the drug development process. Depending on the problem, scientists may be forced to use several modeling tools that could increase model development time, IT costs and so on. Therefore it is desirable to have a single platform that allows setting up and running large-scale simulations for the models that have been developed with different modeling tools. We developed a workflow and a software platform in which a model file is compiled into a self-contained executable that is no longer dependent on the software that was used to create the model. At the same time the full model specifics is preserved by presenting all model parameters as input parameters for the executable. This platform was implemented as a model agnostic, therapeutic area agnostic and web-based application with a database back-end that can be used to configure, manage and execute large-scale simulations for multiple models by multiple users. The user interface is designed to be easily configurable to reflect the specifics of the model and the user’s particular needs and the back-end database has been implemented to store and manage all aspects of the systems, such as Models, Virtual Patients, User Interface Settings, and Results. The platform can be adapted and deployed on an existing cluster or cloud computing environment. Its use was demonstrated with a metabolic disease systems pharmacology model that simulates the effects of two antidiabetic drugs, metformin and fasiglifam, in type 2 diabetes mellitus patients.

A novel blood-brain barrier co-culture system for drug targeting of Alzheimer's disease: establishment by using acitretin as a model drug.

Science.gov (United States)

Freese, Christian; Reinhardt, Sven; Hefner, Gudrun; Unger, Ronald E; Kirkpatrick, C James; Endres, Kristina

2014-01-01

In the pathogenesis of Alzheimer's disease (AD) the homeostasis of amyloid precursor protein (APP) processing in the brain is impaired. The expression of the competing proteases ADAM10 (a disintegrin and metalloproteinase 10) and BACE-1 (beta site APP cleaving enzyme 1) is shifted in favor of the A-beta generating enzyme BACE-1. Acitretin--a synthetic retinoid-e.g., has been shown to increase ADAM10 gene expression, resulting in a decreased level of A-beta peptides within the brain of AD model mice and thus is of possible value for AD therapy. A striking challenge in evaluating novel therapeutically applicable drugs is the analysis of their potential to overcome the blood-brain barrier (BBB) for central nervous system targeting. In this study, we established a novel cell-based bio-assay model to test ADAM10-inducing drugs for their ability to cross the BBB. We therefore used primary porcine brain endothelial cells (PBECs) and human neuroblastoma cells (SH-SY5Y) transfected with an ADAM10-promoter luciferase reporter vector in an indirect co-culture system. Acitretin served as a model substance that crosses the BBB and induces ADAM10 expression. We ensured that ADAM10-dependent constitutive APP metabolism in the neuronal cells was unaffected under co-cultivation conditions. Barrier properties established by PBECs were augmented by co-cultivation with SH-SY5Y cells and they remained stable during the treatment with acitretin as demonstrated by electrical resistance measurement and permeability-coefficient determination. As a consequence of transcellular acitretin transport measured by HPLC, the activity of the ADAM10-promoter reporter gene was significantly increased in co-cultured neuronal cells as compared to vehicle-treated controls. In the present study, we provide a new bio-assay system relevant for the study of drug targeting of AD. This bio-assay can easily be adapted to analyze other Alzheimer- or CNS disease-relevant targets in neuronal cells, as their

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...

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.

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

Numeric, Agent-based or System dynamics model? Which modeling approach is the best for vast population simulation?

Science.gov (United States)

Cimler, Richard; Tomaskova, Hana; Kuhnova, Jitka; Dolezal, Ondrej; Pscheidl, Pavel; Kuca, Kamil

2018-02-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25 % of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Mouse Model of Chronic West Nile Virus Disease.

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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.

Microscopic and macroscopic models for the onset and progression of Alzheimer's disease

Science.gov (United States)

Bertsch, Michiel; Franchi, Bruno; Carla Tesi, Maria; Tosin, Andrea

2017-10-01

In the first part of this paper we review a mathematical model for the onset and progression of Alzheimer’s disease (AD) that was developed in subsequent steps over several years. The model is meant to describe the evolution of AD in vivo. In Achdou et al (2013 J. Math. Biol. 67 1369-92) we treated the problem at a microscopic scale, where the typical length scale is a multiple of the size of the soma of a single neuron. Subsequently, in Bertsch et al (2017 Math. Med. Biol. 34 193-214) we concentrated on the macroscopic scale, where brain neurons are regarded as a continuous medium, structured by their degree of malfunctioning. In the second part of the paper we consider the relation between the microscopic and the macroscopic models. In particular we show under which assumptions the kinetic transport equation, which in the macroscopic model governs the evolution of the probability measure for the degree of malfunctioning of neurons, can be derived from a particle-based setting. The models are based on aggregation and diffusion equations for β-Amyloid (Aβ from now on), a protein fragment that healthy brains regularly produce and eliminate. In case of dementia Aβ monomers are no longer properly washed out and begin to coalesce forming eventually plaques. Two different mechanisms are assumed to be relevant for the temporal evolution of the disease: (i) diffusion and agglomeration of soluble polymers of amyloid, produced by damaged neurons; (ii) neuron-to-neuron prion-like transmission. In the microscopic model we consider mechanism (i), modelling it by a system of Smoluchowski equations for the amyloid concentration (describing the agglomeration phenomenon), with the addition of a diffusion term as well as of a source term on the neuronal membrane. At the macroscopic level instead we model processes (i) and (ii) by a system of Smoluchowski equations for the amyloid concentration, coupled to a kinetic-type transport equation for the distribution function of the

Stabilization and complex dynamics in a predator-prey model with predator suffering from an infectious disease

NARCIS (Netherlands)

Kooi, B.W.; Voorn, van G.A.K.; Das, pada Krishna

2011-01-01

We study the effects of a non-specified infectious disease of the predator on the dynamics a predator–prey system, by evaluating the dynamics of a three-dimensional model. The predator population in this (PSI) model is split into a susceptible and an unrecoverable infected population, while all

Stabilization and complex dynamics in a predator-prey model with predator suffering from an infectious disease.

NARCIS (Netherlands)

Kooi, B.W.; van Voorn, G.A.K.; Pada Das, K.

2011-01-01

We study the effects of a non-specified infectious disease of the predator on the dynamics a predator-prey system, by evaluating the dynamics of a three-dimensional model. The predator population in this (PSI) model is split into a susceptible and an unrecoverable infected population, while all

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.

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

A Rat Model of Alzheimer’s Disease Based on Abeta42 and Pro-oxidative Substances Exhibits Cognitive Deficit and Alterations in Glutamatergic and Cholinergic Neurotransmitter Systems

Czech Academy of Sciences Publication Activity Database

Petrásek, Tomáš; Škurlová, Martina; Malenínská, Kristýna; Vojtěchová, Iveta; Krištofíková, Z.; Matušková, H.; Šírová, J.; Valeš, Karel; Řípová, D.; Stuchlík, Aleš

2016-01-01

Roč. 8, APR 20 (2016), s. 83 ISSN 1663-4365 R&D Projects: GA ČR(CZ) GBP304/12/G069; GA MŠk(CZ) LH14053 Institutional support: RVO:67985823 Keywords : animal model * Alzheimer’s disease * sporadic AD * learning and memory * cognition * neurochemistry of the acetylcholine system * hippocampus Subject RIV: FH - Neurology Impact factor: 4.504, year: 2016

[Pregnancy in systemic autoimmune diseases: Myths, certainties and doubts].

Science.gov (United States)

Danza, Álvaro; Ruiz-Irastorza, Guillermo; Khamashta, Munther

2016-10-07

Systemic autoimmune diseases especially affect young women during childbearing age. The aim of this review is to update systemic lupus erythematosus, antiphospholipid syndrome and systemic sclerosis management during pregnancy. These diseases present variable maternal and fetal risks. Studies show that an appropriate disease control and a reasonable remission period prior to pregnancy are associated with satisfactory obstetric outcomes. Antiphospholipid autoantibodies profile, anti-Ro/anti-La antibodies, pulmonary pressure and activity evaluation are crucial to assess the pregnancy risk. Monitoring requires a multidisciplinary team, serial analytic controls and Doppler ultrasound of maternal and fetal circulation. Evaluation of the activity of the disease is essential. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

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

Stability Analysis of a Reaction-Diffusion System Modeling Atherogenesis

KAUST Repository

Ibragimov, Akif

2010-01-01

This paper presents a linear, asymptotic stability analysis for a reaction-diffusionconvection system modeling atherogenesis, the initiation of atherosclerosis, as an inflammatory instability. Motivated by the disease paradigm articulated by Ross, atherogenesis is viewed as an inflammatory spiral with a positive feedback loop involving key cellular and chemical species interacting and reacting within the intimal layer of muscular arteries. The inflammatory spiral is initiated as an instability from a healthy state which is defined to be an equilibrium state devoid of certain key inflammatory markers. Disease initiation is studied through a linear, asymptotic stability analysis of a healthy equilibrium state. Various theorems are proved, giving conditions on system parameters guaranteeing stability of the health state, and a general framework is developed for constructing perturbations from a healthy state that exhibit blow-up, which are interpreted as corresponding to disease initiation. The analysis reveals key features that arterial geometry, antioxidant levels, and the source of inflammatory components (through coupled third-kind boundary conditions or through body sources) play in disease initiation. © 2010 Society for Industrial and Applied Mathematics.

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

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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.

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.

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.

The oral-systemic disease connection: a retrospective study.

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Joseph, Bobby K; Kullman, Leif; Sharma, Prem N

2016-11-01

The study aimed at determining the association between oral disease and systemic health based on panoramic radiographs and general health of patients treated at Kuwait University Dental Center. The objective was to determine whether individuals exhibiting good oral health have lower propensity to systemic diseases. A total of 1000 adult patients treated at Kuwait University Dental Center were randomly selected from the patient's records. The general health of patients was assessed from the medical history of each patient recorded during their visit to the clinic. The number of reported diseases and serious symptoms were used to develop a medical index. The oral health of these patients was assessed from panoramic radiographs to create an oral index by evaluating such parameters as caries, periodontitis, periapical lesions, pericoronitis, and tooth loss. In a total of 887 patients, 43.8 % had an oral index between 3 and 8, of which significantly higher (62.1 %) patients were with medical conditions compared to those without (33.2 %; p relationship when the diagnosis of oral disease was based primarily on radiographic findings. Future research needs to include prospective clinical and interventional studies. The significance of the oral-systemic disease connection highlights the importance of preventing and treating oral disease which have profound medical implications on general health.

Personalized medicine for cystic fibrosis: establishing human model systems.

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Mou, Hongmei; Brazauskas, Karissa; Rajagopal, Jayaraj

2015-10-01

With over 1,500 identifiable mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene that result in distinct functional and phenotypical abnormalities, it is virtually impossible to perform randomized clinical trials to identify the best therapeutics for all patients. Therefore, a personalized medicine approach is essential. The only way to realistically accomplish this is through the development of improved in vitro human model systems. The lack of a readily available and infinite supply of human CFTR-expressing airway epithelial cells is a key bottleneck. We propose that a concerted two-pronged approach is necessary for patient-specific cystic fibrosis research to continue to prosper and realize its potential: (1) more effective culture and differentiation conditions for growing primary human airway and nasal epithelial cells and (2) the development of collective protocols for efficiently differentiating disease- and patient-specific induced pluripotent stem cells (iPSC) into pure populations of adult epithelial cells. Ultimately, we need a personalized human model system for cystic fibrosis with the capacity for uncomplicated bankability, widespread availability, and universal applicability for patient-specific disease modeling, novel pharmacotherapy investigation and screening, and readily executable genetic modification. © 2015 Wiley Periodicals, Inc.

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

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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.

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 ...

[Mental disorders in digestive system diseases - internist's and psychiatrist's insight].

Science.gov (United States)

Kukla, Urszula; Łabuzek, Krzysztof; Chronowska, Justyna; Krzystanek, Marek; Okopień, BogusŁaw

2015-05-01

Mental disorders accompanying digestive system diseases constitute interdisciplinary yet scarcely acknowledged both diagnostic and therapeutic problem. One of the mostly recognized examples is coeliac disease where patients endure the large spectrum of psychopathological symptoms, starting with attention deficit all the way down to the intellectual disability in extreme cases. It has not been fully explained how the pathomechanism of digestive system diseases affects patient's mental health, however one of the hypothesis suggests that it is due to serotonergic or opioid neurotransmission imbalance caused by gluten and gluten metabolites effect on central nervous system. Behavioral changes can also be invoked by liver or pancreatic diseases, which causes life-threatening abnormalities within a brain. It occurs that these abnormalities reflexively exacerbate the symptoms of primary somatic disease and aggravate its course, which worsens prognosis. The dominant mental disease mentioned in this article is depression which because of its effect on a hypothalamuspituitary- adrenal axis and on an autonomic nervous system, not only aggravates the symptoms of inflammatory bowel diseases but may accelerate their onset in genetically predisposed patients. Depression is known to negatively affects patients' ability to function in a society and a quality of their lives. Moreover, as far as children are concerned, the occurrence of digestive system diseases accompanied by mental disorders, may adversely affect their further physical and psychological development, which merely results in worse school performance. All those aspects of mental disorders indicate the desirability of the psychological care for patients with recognized digestive system disease. The psychological assistance should be provided immediately after diagnosis of a primary disease and be continued throughout the whole course of treatment. © 2015 MEDPRESS.

Systemic Delivery of a Glucosylceramide Synthase Inhibitor Reduces CNS Substrates and Increases Lifespan in a Mouse Model of Type 2 Gaucher Disease

OpenAIRE

Cabrera-Salazar, Mario A.; DeRiso, Matthew; Bercury, Scott D.; Li, Lingyun; Lydon, John T.; Weber, William; Pande, Nilesh; Cromwell, Mandy A.; Copeland, Diane; Leonard, John; Cheng, Seng H.; Scheule, Ronald K.

2012-01-01

Neuropathic Gaucher disease (nGD), also known as type 2 or type 3 Gaucher disease, is caused by a deficiency of the enzyme glucocerebrosidase (GC). This deficiency impairs the degradation of glucosylceramide (GluCer) and glucosylsphingosine (GluSph), leading to their accumulation in the brains of patients and mouse models of the disease. These accumulated substrates have been thought to cause the severe neuropathology and early death observed in patients with nGD and mouse models. Substrate a...

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.

Effects of noise on a computational model for disease states of mood disorders

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