Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.

PubMed

Jafarzadeh, S Reza; Johnson, Wesley O; Gardner, Ian A

2016-03-15

The area under the receiver operating characteristic (ROC) curve (AUC) is used as a performance metric for quantitative tests. Although multiple biomarkers may be available for diagnostic or screening purposes, diagnostic accuracy is often assessed individually rather than in combination. In this paper, we consider the interesting problem of combining multiple biomarkers for use in a single diagnostic criterion with the goal of improving the diagnostic accuracy above that of an individual biomarker. The diagnostic criterion created from multiple biomarkers is based on the predictive probability of disease, conditional on given multiple biomarker outcomes. If the computed predictive probability exceeds a specified cutoff, the corresponding subject is allocated as 'diseased'. This defines a standard diagnostic criterion that has its own ROC curve, namely, the combined ROC (cROC). The AUC metric for cROC, namely, the combined AUC (cAUC), is used to compare the predictive criterion based on multiple biomarkers to one based on fewer biomarkers. A multivariate random-effects model is proposed for modeling multiple normally distributed dependent scores. Bayesian methods for estimating ROC curves and corresponding (marginal) AUCs are developed when a perfect reference standard is not available. In addition, cAUCs are computed to compare the accuracy of different combinations of biomarkers for diagnosis. The methods are evaluated using simulations and are applied to data for Johne's disease (paratuberculosis) in cattle. Copyright © 2015 John Wiley & Sons, Ltd.

A vector space model approach to identify genetically related diseases.

PubMed

Sarkar, Indra Neil

2012-01-01

The relationship between diseases and their causative genes can be complex, especially in the case of polygenic diseases. Further exacerbating the challenges in their study is that many genes may be causally related to multiple diseases. This study explored the relationship between diseases through the adaptation of an approach pioneered in the context of information retrieval: vector space models. A vector space model approach was developed that bridges gene disease knowledge inferred across three knowledge bases: Online Mendelian Inheritance in Man, GenBank, and Medline. The approach was then used to identify potentially related diseases for two target diseases: Alzheimer disease and Prader-Willi Syndrome. In the case of both Alzheimer Disease and Prader-Willi Syndrome, a set of plausible diseases were identified that may warrant further exploration. This study furthers seminal work by Swanson, et al. that demonstrated the potential for mining literature for putative correlations. Using a vector space modeling approach, information from both biomedical literature and genomic resources (like GenBank) can be combined towards identification of putative correlations of interest. To this end, the relevance of the predicted diseases of interest in this study using the vector space modeling approach were validated based on supporting literature. The results of this study suggest that a vector space model approach may be a useful means to identify potential relationships between complex diseases, and thereby enable the coordination of gene-based findings across multiple complex diseases.

Heterogeneity in multiple transmission pathways: modelling the spread of cholera and other waterborne disease in networks with a common water source.

PubMed

Robertson, Suzanne L; Eisenberg, Marisa C; Tien, Joseph H

2013-01-01

Many factors influencing disease transmission vary throughout and across populations. For diseases spread through multiple transmission pathways, sources of variation may affect each transmission pathway differently. In this paper we consider a disease that can be spread via direct and indirect transmission, such as the waterborne disease cholera. Specifically, we consider a system of multiple patches with direct transmission occurring entirely within patch and indirect transmission via a single shared water source. We investigate the effect of heterogeneity in dual transmission pathways on the spread of the disease. We first present a 2-patch model for which we examine the effect of variation in each pathway separately and propose a measure of heterogeneity that incorporates both transmission mechanisms and is predictive of R(0). We also explore how heterogeneity affects the final outbreak size and the efficacy of intervention measures. We conclude by extending several results to a more general n-patch setting.

A model for diagnosing and explaining multiple disorders.

PubMed

Jamieson, P W

1991-08-01

The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.

Sensitivity Analysis of Median Lifetime on Radiation Risks Estimates for Cancer and Circulatory Disease amongst Never-Smokers

NASA Technical Reports Server (NTRS)

Chappell, Lori J.; Cucinotta, Francis A.

2011-01-01

Radiation risks are estimated in a competing risk formalism where age or time after exposure estimates of increased risks for cancer and circulatory diseases are folded with a probability to survive to a given age. The survival function, also called the life-table, changes with calendar year, gender, smoking status and other demographic variables. An outstanding problem in risk estimation is the method of risk transfer between exposed populations and a second population where risks are to be estimated. Approaches used to transfer risks are based on: 1) Multiplicative risk transfer models -proportional to background disease rates. 2) Additive risk transfer model -risks independent of background rates. In addition, a Mixture model is often considered where the multiplicative and additive transfer assumptions are given weighted contributions. We studied the influence of the survival probability on the risk of exposure induced cancer and circulatory disease morbidity and mortality in the Multiplicative transfer model and the Mixture model. Risks for never-smokers (NS) compared to the average U.S. population are estimated to be reduced between 30% and 60% dependent on model assumptions. Lung cancer is the major contributor to the reduction for NS, with additional contributions from circulatory diseases and cancers of the stomach, liver, bladder, oral cavity, esophagus, colon, a portion of the solid cancer remainder, and leukemia. Greater improvements in risk estimates for NS s are possible, and would be dependent on improved understanding of risk transfer models, and elucidating the role of space radiation on the various stages of disease formation (e.g. initiation, promotion, and progression).

Lost productivity and burden of illness in cancer survivors with and without other chronic conditions.

PubMed

Dowling, Emily C; Chawla, Neetu; Forsythe, Laura P; de Moor, Janet; McNeel, Timothy; Rozjabek, Heather M; Ekwueme, Donatus U; Yabroff, K Robin

2013-09-15

Cancer survivors may experience long-term and late effects from treatment that adversely affect health and limit functioning. Few studies examine lost productivity and disease burden in cancer survivors compared with individuals who have other chronic conditions or by cancer type. We identified 4960 cancer survivors and 64,431 other individuals from the 2008-2010 Medical Expenditure Panel Survey and compared multiple measures of disease burden, including health status and lost productivity, between conditions and by cancer site for cancer survivors. All analyses controlled for the effects of age, sex, race/ethnicity, and number of comorbid conditions. Overall, in adjusted analyses in multiple models, cancer survivors with another chronic disease (heart disease or diabetes) experienced higher levels of burden compared with individuals with a history of cancer only, chronic disease only, and neither cancer, heart disease, nor diabetes across multiple measures (P < .05). Among cancer survivors, individuals with short survival cancers and multiple cancers consistently had the highest levels of burden across multiple measures (P < .0001). Cancer survivors who have another chronic disease experience more limitations and higher levels of burden across multiple measures. Limitations are particularly severe in cancer survivors with short survival cancer and multiple cancers. © 2013 American Cancer Society.

Lost Productivity and Burden of Illness in Cancer Survivors With and Without Other Chronic Conditions

PubMed Central

Dowling, Emily C.; Chawla, Neetu; Forsythe, Laura P.; de Moor, Janet; McNeel, Timothy; Rozjabek, Heather M.; Ekwueme, Donatus U.; Yabroff, K. Robin

2018-01-01

BACKGROUND Cancer survivors may experience long-term and late effects from treatment that adversely affect health and limit functioning. Few studies examine lost productivity and disease burden in cancer survivors compared with individuals who have other chronic conditions or by cancer type. METHODS We identified 4960 cancer survivors and 64,431 other individuals from the 2008–2010 Medical Expenditure Panel Survey and compared multiple measures of disease burden, including health status and lost productivity, between conditions and by cancer site for cancer survivors. All analyses controlled for the effects of age, sex, race/ethnicity, and number of comorbid conditions. RESULTS Overall, in adjusted analyses in multiple models, cancer survivors with another chronic disease (heart disease or diabetes) experienced higher levels of burden compared with individuals with a history of cancer only, chronic disease only, and neither cancer, heart disease, nor diabetes across multiple measures (P <.05). Among cancer survivors, individuals with short survival cancers and multiple cancers consistently had the highest levels of burden across multiple measures (P <.0001). CONCLUSIONS Cancer survivors who have another chronic disease experience more limitations and higher levels of burden across multiple measures. Limitations are particularly severe in cancer survivors with short survival cancer and multiple cancers. PMID:23794146

Systems Epidemiology: What’s in a Name?

PubMed Central

Dammann, O.; Gray, P.; Gressens, P.; Wolkenhauer, O.; Leviton, A.

2014-01-01

Systems biology is an interdisciplinary effort to integrate molecular, cellular, tissue, organ, and organism levels of function into computational models that facilitate the identification of general principles. Systems medicine adds a disease focus. Systems epidemiology adds yet another level consisting of antecedents that might contribute to the disease process in populations. In etiologic and prevention research, systems-type thinking about multiple levels of causation will allow epidemiologists to identify contributors to disease at multiple levels as well as their interactions. In public health, systems epidemiology will contribute to the improvement of syndromic surveillance methods. We encourage the creation of computational simulation models that integrate information about disease etiology, pathogenetic data, and the expertise of investigators from different disciplines. PMID:25598870

A minimal model for multiple epidemics and immunity spreading.

PubMed

Sneppen, Kim; Trusina, Ala; Jensen, Mogens H; Bornholdt, Stefan

2010-10-18

Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

Gestational bisphenol-A exposure lowers the threshold for autoimmunity in a model of multiple sclerosis.

PubMed

Rogers, James A; Mishra, Manoj K; Hahn, Jennifer; Greene, Catherine J; Yates, Robin M; Metz, Luanne M; Yong, V Wee

2017-05-09

Environmental and hormonal factors are implicated in dysimmunity in multiple sclerosis. We investigated whether bisphenol-A, a prominent contaminant with endocrine-disrupting capabilities, altered susceptibility in an inflammatory model of multiple sclerosis. We found that gestational, but not adult, exposure to bisphenol-A increased the development of experimental autoimmune encephalomyelitis in adulthood in male, but not female, mice when a suboptimal disease-inducing immunization was used. Gestational bisphenol-A in male mice primed macrophages in adulthood and raised granulocyte-colony stimulating factor and neutrophil counts/activity postsuboptimal immunization. Neutralizing granulocyte-colony stimulating factor blocked susceptibility to disease in bisphenol-A mice. Early life exposure to bisphenol-A may represent an environmental consideration in multiple sclerosis.

Care delivery for Filipino Americans using the Neuman systems model.

PubMed

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.

Noninvasive imaging of multiple myeloma using near infrared fluorescent molecular probe

NASA Astrophysics Data System (ADS)

Hathi, Deep; Zhou, Haiying; Bollerman-Nowlis, Alex; Shokeen, Monica; Akers, Walter J.

2016-03-01

Multiple myeloma is a plasma cell malignancy characterized by monoclonal gammopathy and osteolytic bone lesions. Multiple myeloma is most commonly diagnosed in late disease stages, presenting with pathologic fracture. Early diagnosis and monitoring of disease status may improve quality of life and long-term survival for multiple myeloma patients from what is now a devastating and fatal disease. We have developed a near-infrared targeted fluorescent molecular probe with high affinity to the α4β1 integrin receptor (VLA-4)overexpressed by a majority of multiple myeloma cells as a non-radioactive analog to PET/CT tracer currently being developed for human diagnostics. A near-infrared dye that emits about 700 nm was conjugated to a high affinity peptidomimmetic. Binding affinity and specificity for multiple myeloma cells was investigated in vitro by tissue staining and flow cytometry. After demonstration of sensitivity and specificity, preclinical optical imaging studies were performed to evaluate tumor specificity in murine subcutaneous and metastatic multiple myeloma models. The VLA-4-targeted molecular probe showed high affinity for subcutaneous MM tumor xenografts. Importantly, tumor cells specific accumulation in the bone marrow of metastatic multiple myeloma correlated with GFP signal from transfected cells. Ex vivo flow cytometry of tumor tissue and bone marrow further corroborated in vivo imaging data, demonstrating the specificity of the novel agent and potential for quantitative imaging of multiple myeloma burden in these models.

From puddles to planet: modeling approaches to vector-borne diseases at varying resolution and scale.

PubMed

Eckhoff, Philip A; Bever, Caitlin A; Gerardin, Jaline; Wenger, Edward A; Smith, David L

2015-08-01

Since the original Ross-Macdonald formulations of vector-borne disease transmission, there has been a broad proliferation of mathematical models of vector-borne disease, but many of these models retain most to all of the simplifying assumptions of the original formulations. Recently, there has been a new expansion of mathematical frameworks that contain explicit representations of the vector life cycle including aquatic stages, multiple vector species, host heterogeneity in biting rate, realistic vector feeding behavior, and spatial heterogeneity. In particular, there are now multiple frameworks for spatially explicit dynamics with movements of vector, host, or both. These frameworks are flexible and powerful, but require additional data to take advantage of these features. For a given question posed, utilizing a range of models with varying complexity and assumptions can provide a deeper understanding of the answers derived from models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Care Delivery for Filipino Americans Using the Neuman Systems Model

PubMed Central

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

2016-01-01

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. PMID:24740949

The topographical model of multiple sclerosis

PubMed Central

Cook, Karin; De Nino, Scott; Fletcher, Madhuri

2016-01-01

Relapses and progression contribute to multiple sclerosis (MS) disease course, but neither the relationship between them nor the spectrum of clinical heterogeneity has been fully characterized. A hypothesis-driven, biologically informed model could build on the clinical phenotypes to encompass the dynamic admixture of factors underlying MS disease course. In this medical hypothesis, we put forth a dynamic model of MS disease course that incorporates localization and other drivers of disability to propose a clinical manifestation framework that visualizes MS in a clinically individualized way. The topographical model encapsulates 5 factors (localization of relapses and causative lesions; relapse frequency, severity, and recovery; and progression rate), visualized utilizing dynamic 3-dimensional renderings. The central hypothesis is that, like symptom recrudescence in Uhthoff phenomenon and pseudoexacerbations, progression clinically recapitulates prior relapse symptoms and unmasks previously silent lesions, incrementally revealing underlying lesion topography. The model uses real-time simulation software to depict disease course archetypes and illuminate several well-described but poorly reconciled phenomena including the clinical/MRI paradox and prognostic significance of lesion location and burden on disease outcomes. Utilization of this model could allow for earlier and more clinically precise identification of progressive MS and predictive implications can be empirically tested. PMID:27648465

Linear Combinations of Multiple Outcome Measures to Improve the Power of Efficacy Analysis ---Application to Clinical Trials on Early Stage Alzheimer Disease

PubMed Central

Xiong, Chengjie; Luo, Jingqin; Morris, John C; Bateman, Randall

2018-01-01

Modern clinical trials on Alzheimer disease (AD) focus on the early symptomatic stage or even the preclinical stage. Subtle disease progression at the early stages, however, poses a major challenge in designing such clinical trials. We propose a multivariate mixed model on repeated measures to model the disease progression over time on multiple efficacy outcomes, and derive the optimum weights to combine multiple outcome measures by minimizing the sample sizes to adequately power the clinical trials. A cross-validation simulation study is conducted to assess the accuracy for the estimated weights as well as the improvement in reducing the sample sizes for such trials. The proposed methodology is applied to the multiple cognitive tests from the ongoing observational study of the Dominantly Inherited Alzheimer Network (DIAN) to power future clinical trials in the DIAN with a cognitive endpoint. Our results show that the optimum weights to combine multiple outcome measures can be accurately estimated, and that compared to the individual outcomes, the combined efficacy outcome with these weights significantly reduces the sample size required to adequately power clinical trials. When applied to the clinical trial in the DIAN, the estimated linear combination of six cognitive tests can adequately power the clinical trial. PMID:29546251

Factors associated with clinically significant increased walking time in multiple sclerosis: results of a survival analysis of short-term follow-up data from a clinical database.

PubMed

Miller, Deborah M; Thompson, Nicolas R; Cohen, Jeffrey A; Fox, Robert J; Hartman, Jen; Schwetz, Kathleen; Conway, Devon S; Rudick, Richard A

2015-04-01

Because multiple sclerosis (MS) is variable and unpredictable, if symptom worsening could be predicted, patients may feel better prepared to manage changes in function. The objective of this paper is to study the prediction of walking impairment in MS. We retrieved data for all MS patients at our center (2008-2009), including baseline and follow-up timed 25-foot walk (T25FW) times. We assessed the incidence of ≥20% worsening in T25FW by developing two survival models: (1) disease course and (2) Multiple Sclerosis Performance Scales (MSPS) score. The outcome was days until ≥20% worsening in T25FW. Covariates were disease subtype, years since diagnosis, Patient Health Questionnaire-9 (PHQ-9) score, and demographics. Data were interval censored; missing data were handled with multiple imputation. Of 1544 patients, 309 (20%) experienced ≥20% worsening T25FW. For disease course, time to worsening was significantly shorter for secondary progressive vs. relapsing-remitting disease (p < 0.001). For MSPS, patients with lower baseline MSPS scores progressed more slowly (p = 0.001). In both models, sex, baseline T25W, and time since diagnosis were significantly associated with worsening. In the disease course model, PHQ 9 score may be related to worsening (p = 0.07). These findings suggest factors associated with worsening in T25FW and a potential approach to establishing indicators associated with clinically significant change. © The Author(s), 2014.

Cure Models as a Useful Statistical Tool for Analyzing Survival

PubMed Central

Othus, Megan; Barlogie, Bart; LeBlanc, Michael L.; Crowley, John J.

2013-01-01

Cure models are a popular topic within statistical literature but are not as widely known in the clinical literature. Many patients with cancer can be long-term survivors of their disease, and cure models can be a useful tool to analyze and describe cancer survival data. The goal of this article is to review what a cure model is, explain when cure models can be used, and use cure models to describe multiple myeloma survival trends. Multiple myeloma is generally considered an incurable disease, and this article shows that by using cure models, rather than the standard Cox proportional hazards model, we can evaluate whether there is evidence that therapies at the University of Arkansas for Medical Sciences induce a proportion of patients to be long-term survivors. PMID:22675175

Using whole disease modeling to inform resource allocation decisions: economic evaluation of a clinical guideline for colorectal cancer using a single model.

PubMed

Tappenden, Paul; Chilcott, Jim; Brennan, Alan; Squires, Hazel; Glynne-Jones, Rob; Tappenden, Janine

2013-06-01

To assess the feasibility and value of simulating whole disease and treatment pathways within a single model to provide a common economic basis for informing resource allocation decisions. A patient-level simulation model was developed with the intention of being capable of evaluating multiple topics within National Institute for Health and Clinical Excellence's colorectal cancer clinical guideline. The model simulates disease and treatment pathways from preclinical disease through to detection, diagnosis, adjuvant/neoadjuvant treatments, follow-up, curative/palliative treatments for metastases, supportive care, and eventual death. The model parameters were informed by meta-analyses, randomized trials, observational studies, health utility studies, audit data, costing sources, and expert opinion. Unobservable natural history parameters were calibrated against external data using Bayesian Markov chain Monte Carlo methods. Economic analysis was undertaken using conventional cost-utility decision rules within each guideline topic and constrained maximization rules across multiple topics. Under usual processes for guideline development, piecewise economic modeling would have been used to evaluate between one and three topics. The Whole Disease Model was capable of evaluating 11 of 15 guideline topics, ranging from alternative diagnostic technologies through to treatments for metastatic disease. The constrained maximization analysis identified a configuration of colorectal services that is expected to maximize quality-adjusted life-year gains without exceeding current expenditure levels. This study indicates that Whole Disease Model development is feasible and can allow for the economic analysis of most interventions across a disease service within a consistent conceptual and mathematical infrastructure. This disease-level modeling approach may be of particular value in providing an economic basis to support other clinical guidelines. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Impact of treatment heterogeneity on drug resistance and supply chain costs☆

PubMed Central

Spiliotopoulou, Eirini; Boni, Maciej F.; Yadav, Prashant

2013-01-01

The efficacy of scarce drugs for many infectious diseases is threatened by the emergence and spread of resistance. Multiple studies show that available drugs should be used in a socially optimal way to contain drug resistance. This paper studies the tradeoff between risk of drug resistance and operational costs when using multiple drugs for a specific disease. Using a model for disease transmission and resistance spread, we show that treatment with multiple drugs, on a population level, results in better resistance-related health outcomes, but more interestingly, the marginal benefit decreases as the number of drugs used increases. We compare this benefit with the corresponding change in procurement and safety stock holding costs that result from higher drug variety in the supply chain. Using a large-scale simulation based on malaria transmission dynamics, we show that disease prevalence seems to be a less important factor when deciding the optimal width of drug assortment, compared to the duration of one episode of the disease and the price of the drug(s) used. Our analysis shows that under a wide variety of scenarios for disease prevalence and drug cost, it is optimal to simultaneously deploy multiple drugs in the population. If the drug price is high, large volume purchasing discounts are available, and disease prevalence is high, it may be optimal to use only one drug. Our model lends insights to policy makers into the socially optimal size of drug assortment for a given context. PMID:25843982

Impact of treatment heterogeneity on drug resistance and supply chain costs.

PubMed

Spiliotopoulou, Eirini; Boni, Maciej F; Yadav, Prashant

2013-09-01

The efficacy of scarce drugs for many infectious diseases is threatened by the emergence and spread of resistance. Multiple studies show that available drugs should be used in a socially optimal way to contain drug resistance. This paper studies the tradeoff between risk of drug resistance and operational costs when using multiple drugs for a specific disease. Using a model for disease transmission and resistance spread, we show that treatment with multiple drugs, on a population level, results in better resistance-related health outcomes, but more interestingly, the marginal benefit decreases as the number of drugs used increases. We compare this benefit with the corresponding change in procurement and safety stock holding costs that result from higher drug variety in the supply chain. Using a large-scale simulation based on malaria transmission dynamics, we show that disease prevalence seems to be a less important factor when deciding the optimal width of drug assortment, compared to the duration of one episode of the disease and the price of the drug(s) used. Our analysis shows that under a wide variety of scenarios for disease prevalence and drug cost, it is optimal to simultaneously deploy multiple drugs in the population. If the drug price is high, large volume purchasing discounts are available, and disease prevalence is high, it may be optimal to use only one drug. Our model lends insights to policy makers into the socially optimal size of drug assortment for a given context.

Multiple Diseases in Carrier Probability Estimation: Accounting for Surviving All Cancers Other than Breast and Ovary in BRCAPRO

PubMed Central

Katki, Hormuzd A.; Blackford, Amanda; Chen, Sining; Parmigiani, Giovanni

2008-01-01

SUMMARY Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 familes from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO’s concordance index from 0.758 to 0.762 (p = 0.046), improves its positive predictive value from 35% to 39% (p < 10−6) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability < 10%. PMID:18407567

Multiple diseases in carrier probability estimation: accounting for surviving all cancers other than breast and ovary in BRCAPRO.

PubMed

Katki, Hormuzd A; Blackford, Amanda; Chen, Sining; Parmigiani, Giovanni

2008-09-30

Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 families from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO's concordance index from 0.758 to 0.762 (p=0.046), improves its positive predictive value from 35 to 39 per cent (p<10(-6)) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability<10 per cent. Copyright (c) 2008 John Wiley & Sons, Ltd.

Integrating retrogenesis theory to Alzheimer's disease pathology: insight from DTI-TBSS investigation of the white matter microstructural integrity.

PubMed

Alves, Gilberto Sousa; Oertel Knöchel, Viola; Knöchel, Christian; Carvalho, André Férrer; Pantel, Johannes; Engelhardt, Eliasz; Laks, Jerson

2015-01-01

Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD) and may reflect primary or secondary circuitry degeneration (i.e., due to cortical atrophy). The interpretation of diffusion tensor imaging (DTI) eigenvectors, known as multiple indices, may provide new insights into the main pathological models supporting primary or secondary patterns of WM disruption in AD, the retrogenesis, and Wallerian degeneration models, respectively. The aim of this review is to analyze the current literature on the contribution of DTI multiple indices to the understanding of AD neuropathology, taking the retrogenesis model as a reference for discussion. A systematic review using MEDLINE, EMBASE, and PUBMED was performed. Evidence suggests that AD evolves through distinct patterns of WM disruption, in which retrogenesis or, alternatively, the Wallerian degeneration may prevail. Distinct patterns of WM atrophy may be influenced by complex interactions which comprise disease status and progression, fiber localization, concurrent risk factors (i.e., vascular disease, gender), and cognitive reserve. The use of DTI multiple indices in addition to other standard multimodal methods in dementia research may help to determine the contribution of retrogenesis hypothesis to the understanding of neuropathological hallmarks that lead to AD.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378

Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.

PubMed

Franke, John E; Yakubu, Abdul-Aziz

2008-12-01

The dynamics of simple discrete-time epidemic models without disease-induced mortality are typically characterized by global transcritical bifurcation. We prove that in corresponding models with disease-induced mortality a tiny number of infectious individuals can drive an otherwise persistent population to extinction. Our model with disease-induced mortality supports multiple attractors. In addition, we use a Ricker recruitment function in an SIS model and obtained a three component discrete Hopf (Neimark-Sacker) cycle attractor coexisting with a fixed point attractor. The basin boundaries of the coexisting attractors are fractal in nature, and the example exhibits sensitive dependence of the long-term disease dynamics on initial conditions. Furthermore, we show that in contrast to corresponding models without disease-induced mortality, the disease-free state dynamics do not drive the disease dynamics.

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks.

PubMed

Ghosh, Saurav; Chakraborty, Prithwish; Nsoesie, Elaine O; Cohn, Emily; Mekaru, Sumiko R; Brownstein, John S; Ramakrishnan, Naren

2017-01-19

In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations.

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks

NASA Astrophysics Data System (ADS)

Ghosh, Saurav; Chakraborty, Prithwish; Nsoesie, Elaine O.; Cohn, Emily; Mekaru, Sumiko R.; Brownstein, John S.; Ramakrishnan, Naren

2017-01-01

In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations.

Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks

PubMed Central

Ghosh, Saurav; Chakraborty, Prithwish; Nsoesie, Elaine O.; Cohn, Emily; Mekaru, Sumiko R.; Brownstein, John S.; Ramakrishnan, Naren

2017-01-01

In retrospective assessments, internet news reports have been shown to capture early reports of unknown infectious disease transmission prior to official laboratory confirmation. In general, media interest and reporting peaks and wanes during the course of an outbreak. In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence. We introduce an approach that uses supervised temporal topic models to transform large corpora of news articles into temporal topic trends. The key advantages of this approach include: applicability to a wide range of diseases and ability to capture disease dynamics, including seasonality, abrupt peaks and troughs. We evaluated the method using data from multiple infectious disease outbreaks reported in the United States of America (U.S.), China, and India. We demonstrate that temporal topic trends extracted from disease-related news reports successfully capture the dynamics of multiple outbreaks such as whooping cough in U.S. (2012), dengue outbreaks in India (2013) and China (2014). Our observations also suggest that, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regression techniques can estimate disease case counts with increased precision before official reports by health organizations. PMID:28102319

Experimental Autoimmune Encephalomyelitis (EAE) as Animal Models of Multiple Sclerosis (MS).

PubMed

Glatigny, Simon; Bettelli, Estelle

2018-01-08

Multiple sclerosis (MS) is a multifocal demyelinating disease of the central nervous system (CNS) leading to the progressive destruction of the myelin sheath surrounding axons. It can present with variable clinical and pathological manifestations, which might reflect the involvement of distinct pathogenic processes. Although the mechanisms leading to the development of the disease are not fully understood, numerous evidences indicate that MS is an autoimmune disease, the initiation and progression of which are dependent on an autoimmune response against myelin antigens. In addition, genetic susceptibility and environmental triggers likely contribute to the initiation of the disease. At this time, there is no cure for MS, but several disease-modifying therapies (DMTs) are available to control and slow down disease progression. A good number of these DMTs were identified and tested using animal models of MS referred to as experimental autoimmune encephalomyelitis (EAE). In this review, we will recapitulate the characteristics of EAE models and discuss how they help shed light on MS pathogenesis and help test new treatments for MS patients. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

Murine genetically engineered and human xenograft models of chronic lymphocytic leukemia.

PubMed

Chen, Shih-Shih; Chiorazzi, Nicholas

2014-07-01

Chronic lymphocytic leukemia (CLL) is a genetically complex disease, with multiple factors having an impact on onset, progression, and response to therapy. Genetic differences/abnormalities have been found in hematopoietic stem cells from patients, as well as in B lymphocytes of individuals with monoclonal B-cell lymphocytosis who may develop the disease. Furthermore, after the onset of CLL, additional genetic alterations occur over time, often causing disease worsening and altering patient outcomes. Therefore, being able to genetically engineer mouse models that mimic CLL or at least certain aspects of the disease will help us understand disease mechanisms and improve treatments. This notwithstanding, because neither the genetic aberrations responsible for leukemogenesis and progression nor the promoting factors that support these are likely identical in character or influences for all patients, genetically engineered mouse models will only completely mimic CLL when all of these factors are precisely defined. In addition, multiple genetically engineered models may be required because of the heterogeneity in susceptibility genes among patients that can have an effect on genetic and environmental characteristics influencing disease development and outcome. For these reasons, we review the major murine genetically engineered and human xenograft models in use at the present time, aiming to report the advantages and disadvantages of each. Copyright © 2014 Elsevier Inc. All rights reserved.

Best practice assessment of disease modelling for infectious disease outbreaks.

PubMed

Dembek, Z F; Chekol, T; Wu, A

2018-05-08

During emerging disease outbreaks, public health, emergency management officials and decision-makers increasingly rely on epidemiological models to forecast outbreak progression and determine the best response to health crisis needs. Outbreak response strategies derived from such modelling may include pharmaceutical distribution, immunisation campaigns, social distancing, prophylactic pharmaceuticals, medical care, bed surge, security and other requirements. Infectious disease modelling estimates are unavoidably subject to multiple interpretations, and full understanding of a model's limitations may be lost when provided from the disease modeller to public health practitioner to government policymaker. We review epidemiological models created for diseases which are of greatest concern for public health protection. Such diseases, whether transmitted from person-to-person (Ebola, influenza, smallpox), via direct exposure (anthrax), or food and waterborne exposure (cholera, typhoid) may cause severe illness and death in a large population. We examine disease-specific models to determine best practices characterising infectious disease outbreaks and facilitating emergency response and implementation of public health policy and disease control measures.

Inflammation and therapeutic vaccination in CNS diseases

NASA Astrophysics Data System (ADS)

Weiner, Howard L.; Selkoe, Dennis J.

2002-12-01

The spectrum of inflammatory diseases of the central nervous system has been steadily expanding from classical autoimmune disorders such as multiple sclerosis to far more diverse diseases. Evidence now suggests that syndromes such as Alzheimer's disease and stroke have important inflammatory and immune components and may be amenable to treatment by anti-inflammatory and immunotherapeutic approaches. The notion of 'vaccinating' individuals against a neurodegenerative disorder such as Alzheimer's disease is a marked departure from classical thinking about mechanism and treatment, and yet therapeutic vaccines for both Alzheimer's disease and multiple sclerosis have been validated in animal models and are in the clinic. Such approaches, however, have the potential to induce unwanted inflammatory responses as well as to provide benefit.

Cocirculation of infectious diseases on networks

NASA Astrophysics Data System (ADS)

Miller, Joel C.

2013-06-01

We consider multiple diseases spreading in a static configuration model network. We make standard assumptions that infection transmits from neighbor to neighbor at a disease-specific rate and infected individuals recover at a disease-specific rate. Infection by one disease confers immediate and permanent immunity to infection by any disease. Under these assumptions, we find a simple, low-dimensional ordinary differential equations model which captures the global dynamics of the infection. The dynamics depend strongly on initial conditions. Although we motivate this Rapid Communication with infectious disease, the model may be adapted to the spread of other infectious agents such as competing political beliefs, or adoption of new technologies if these are influenced by contacts. As an example, we demonstrate how to model an infectious disease which can be prevented by a behavior change.

Autoantigen cross-reactive environmental antigen can trigger multiple sclerosis-like disease.

PubMed

Reynolds, Catherine J; Sim, Malcolm J W; Quigley, Kathryn J; Altmann, Daniel M; Boyton, Rosemary J

2015-05-13

Multiple sclerosis is generally considered an autoimmune disease resulting from interaction between predisposing genes and environmental factors, together allowing immunological self-tolerance to be compromised. The precise nature of the environmental inputs has been elusive, infectious agents having received considerable attention. A recent study generated an algorithm predicting naturally occurring T cell receptor (TCR) ligands from the proteome database. Taking the example of a multiple sclerosis patient-derived anti-myelin TCR, the study identified a number of stimulatory, cross-reactive peptide sequences from environmental and human antigens. Having previously generated a spontaneous multiple sclerosis (MS) model through expression of this TCR, we asked whether any of these could indeed function in vivo to trigger CNS disease by cross-reactive activation. A number of myelin epitope cross-reactive epitopes could stimulate T cell immunity in this MS anti-myelin TCR transgenic model. Two of the most stimulatory of these 'environmental' epitopes, from Dictyostyelium slime mold and from Emiliania huxleyi, were tested for the ability to induce MS-like disease in the transgenics. We found that immunization with cross-reactive peptide from Dictyostyelium slime mold (but not from E. huxleyi) induces severe disease. These specific environmental epitopes are unlikely to be common triggers of MS, but this study suggests that our search for the cross-reactivity triggers of autoimmune activation leading to MS should encompass epitopes not just from the 'infectome' but also from the full environmental 'exposome.'

Functional connectivity in autosomal dominant and late-onset Alzheimer disease.

PubMed

Thomas, Jewell B; Brier, Matthew R; Bateman, Randall J; Snyder, Abraham Z; Benzinger, Tammie L; Xiong, Chengjie; Raichle, Marcus; Holtzman, David M; Sperling, Reisa A; Mayeux, Richard; Ghetti, Bernardino; Ringman, John M; Salloway, Stephen; McDade, Eric; Rossor, Martin N; Ourselin, Sebastien; Schofield, Peter R; Masters, Colin L; Martins, Ralph N; Weiner, Michael W; Thompson, Paul M; Fox, Nick C; Koeppe, Robert A; Jack, Clifford R; Mathis, Chester A; Oliver, Angela; Blazey, Tyler M; Moulder, Krista; Buckles, Virginia; Hornbeck, Russ; Chhatwal, Jasmeer; Schultz, Aaron P; Goate, Alison M; Fagan, Anne M; Cairns, Nigel J; Marcus, Daniel S; Morris, John C; Ances, Beau M

2014-09-01

Autosomal dominant Alzheimer disease (ADAD) is caused by rare genetic mutations in 3 specific genes in contrast to late-onset Alzheimer disease (LOAD), which has a more polygenetic risk profile. To assess the similarities and differences in functional connectivity changes owing to ADAD and LOAD. We analyzed functional connectivity in multiple brain resting state networks (RSNs) in a cross-sectional cohort of participants with ADAD (n = 79) and LOAD (n = 444), using resting-state functional connectivity magnetic resonance imaging at multiple international academic sites. For both types of AD, we quantified and compared functional connectivity changes in RSNs as a function of dementia severity measured by the Clinical Dementia Rating Scale. In ADAD, we qualitatively investigated functional connectivity changes with respect to estimated years from onset of symptoms within 5 RSNs. A decrease in functional connectivity with increasing Clinical Dementia Rating scores were similar for both LOAD and ADAD in multiple RSNs. Ordinal logistic regression models constructed in one type of Alzheimer disease accurately predicted clinical dementia rating scores in the other, further demonstrating the similarity of functional connectivity loss in each disease type. Among participants with ADAD, functional connectivity in multiple RSNs appeared qualitatively lower in asymptomatic mutation carriers near their anticipated age of symptom onset compared with asymptomatic mutation noncarriers. Resting-state functional connectivity magnetic resonance imaging changes with progressing AD severity are similar between ADAD and LOAD. Resting-state functional connectivity magnetic resonance imaging may be a useful end point for LOAD and ADAD therapy trials. Moreover, the disease process of ADAD may be an effective model for the LOAD disease process.

Modulation by Melatonin of the Pathogenesis of Inflammatory Autoimmune Diseases

PubMed Central

Lin, Gu-Jiun; Huang, Shing-Hwa; Chen, Shyi-Jou; Wang, Chih-Hung; Chang, Deh-Ming; Sytwu, Huey-Kang

2013-01-01

Melatonin is the major secretory product of the pineal gland during the night and has multiple activities including the regulation of circadian and seasonal rhythms, and antioxidant and anti-inflammatory effects. It also possesses the ability to modulate immune responses by regulation of the T helper 1/2 balance and cytokine production. Autoimmune diseases, which result from the activation of immune cells by autoantigens released from normal tissues, affect around 5% of the population. Activation of autoantigen-specific immune cells leads to subsequent damage of target tissues by these activated cells. Melatonin therapy has been investigated in several animal models of autoimmune disease, where it has a beneficial effect in a number of models excepting rheumatoid arthritis, and has been evaluated in clinical autoimmune diseases including rheumatoid arthritis and ulcerative colitis. This review summarizes and highlights the role and the modulatory effects of melatonin in several inflammatory autoimmune diseases including multiple sclerosis, systemic lupus erythematosus, rheumatoid arthritis, type 1 diabetes mellitus, and inflammatory bowel disease. PMID:23727938

New Insights into Multiple Sclerosis Clinical Course from the Topographical Model and Functional Reserve.

PubMed

Krieger, Stephen C; Sumowski, James

2018-02-01

Clinical course in multiple sclerosis (MS) is difficult to predict on group and individual levels. We discuss the topographical model of MS as a new approach to characterizing the clinical course, with the potential to personalize disability progression based on each individual patient's pattern of disease burden (eg, lesion location) and reserve. The dynamic clinical threshold depicted in this visual model may help clinicians to educate patients about clinical phenotype and disease burden, and foster an understanding of the difference between relapses and pseudoexacerbations. There is an emphasis on building reserve against cognitive and physical decline, encouraging agency among patients. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging.

PubMed

Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2014-03-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.

Modelling the effects of phylogeny and body size on within-host pathogen replication and immune response.

PubMed

Banerjee, Soumya; Perelson, Alan S; Moses, Melanie

2017-11-01

Understanding how quickly pathogens replicate and how quickly the immune system responds is important for predicting the epidemic spread of emerging pathogens. Host body size, through its correlation with metabolic rates, is theoretically predicted to impact pathogen replication rates and immune system response rates. Here, we use mathematical models of viral time courses from multiple species of birds infected by a generalist pathogen (West Nile Virus; WNV) to test more thoroughly how disease progression and immune response depend on mass and host phylogeny. We use hierarchical Bayesian models coupled with nonlinear dynamical models of disease dynamics to incorporate the hierarchical nature of host phylogeny. Our analysis suggests an important role for both host phylogeny and species mass in determining factors important for viral spread such as the basic reproductive number, WNV production rate, peak viraemia in blood and competency of a host to infect mosquitoes. Our model is based on a principled analysis and gives a quantitative prediction for key epidemiological determinants and how they vary with species mass and phylogeny. This leads to new hypotheses about the mechanisms that cause certain taxonomic groups to have higher viraemia. For example, our models suggest that higher viral burst sizes cause corvids to have higher levels of viraemia and that the cellular rate of virus production is lower in larger species. We derive a metric of competency of a host to infect disease vectors and thereby sustain the disease between hosts. This suggests that smaller passerine species are highly competent at spreading the disease compared with larger non-passerine species. Our models lend mechanistic insight into why some species (smaller passerine species) are pathogen reservoirs and some (larger non-passerine species) are potentially dead-end hosts for WNV. Our techniques give insights into the role of body mass and host phylogeny in the spread of WNV and potentially other zoonotic diseases. The major contribution of this work is a computational framework for infectious disease modelling at the within-host level that leverages data from multiple species. This is likely to be of interest to modellers of infectious diseases that jump species barriers and infect multiple species. Our method can be used to computationally determine the competency of a host to infect mosquitoes that will sustain WNV and other zoonotic diseases. We find that smaller passerine species are more competent in spreading the disease than larger non-passerine species. This suggests the role of host phylogeny as an important determinant of within-host pathogen replication. Ultimately, we view our work as an important step in linking within-host viral dynamics models to between-host models that determine spread of infectious disease between different hosts. © 2017 The Author(s).

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

PubMed

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

2017-09-01

Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n = 1196) of the resulting predictive models was high (>80%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2-4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation. External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease-modifying therapies at the time of their commencement. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Distinct brain imaging characteristics of autoantibody-mediated CNS conditions and multiple sclerosis.

PubMed

Jurynczyk, Maciej; Geraldes, Ruth; Probert, Fay; Woodhall, Mark R; Waters, Patrick; Tackley, George; DeLuca, Gabriele; Chandratre, Saleel; Leite, Maria I; Vincent, Angela; Palace, Jacqueline

2017-03-01

Brain imaging characteristics of MOG antibody disease are largely unknown and it is unclear whether they differ from those of multiple sclerosis and AQP4 antibody disease. The aim of this study was to identify brain imaging discriminators between those three inflammatory central nervous system diseases in adults and children to support diagnostic decisions, drive antibody testing and generate disease mechanism hypotheses. Clinical brain scans of 83 patients with brain lesions (67 in the training and 16 in the validation cohort, 65 adults and 18 children) with MOG antibody (n = 26), AQP4 antibody disease (n = 26) and multiple sclerosis (n = 31) recruited from Oxford neuromyelitis optica and multiple sclerosis clinical services were retrospectively and anonymously scored on a set of 29 predefined magnetic resonance imaging features by two independent raters. Principal component analysis was used to perform an overview of patients without a priori knowledge of the diagnosis. Orthogonal partial least squares discriminant analysis was used to build models separating diagnostic groups and identify best classifiers, which were then tested on an independent cohort set. Adults and children with MOG antibody disease frequently had fluffy brainstem lesions, often located in pons and/or adjacent to fourth ventricle. Children across all conditions showed more frequent bilateral, large, brainstem and deep grey matter lesions. MOG antibody disease spontaneously separated from multiple sclerosis but overlapped with AQP4 antibody disease. Multiple sclerosis was discriminated from MOG antibody disease and from AQP4 antibody disease with high predictive values, while MOG antibody disease could not be accurately discriminated from AQP4 antibody disease. Best classifiers between MOG antibody disease and multiple sclerosis were similar in adults and children, and included ovoid lesions adjacent to the body of lateral ventricles, Dawson's fingers, T1 hypointense lesions (multiple sclerosis), fluffy lesions and three lesions or less (MOG antibody). In the validation cohort patients with antibody-mediated conditions were differentiated from multiple sclerosis with high accuracy. Both antibody-mediated conditions can be clearly separated from multiple sclerosis on conventional brain imaging, both in adults and children. The overlap between MOG antibody oligodendrocytopathy and AQP4 antibody astrocytopathy suggests that the primary immune target is not the main substrate for brain lesion characteristics. This is also supported by the clear distinction between multiple sclerosis and MOG antibody disease both considered primary demyelinating conditions. We identify discriminatory features, which may be useful in classifying atypical multiple sclerosis, seronegative neuromyelitis optica spectrum disorders and relapsing acute disseminated encephalomyelitis, and characterizing cohorts for antibody discovery. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Treatment with a neutralising anti-rat interleukin-17 antibody after multiple-trauma reduces lung inflammation.

PubMed

Dai, Heling; Xu, Li; Tang, Yu; Liu, Zhi; Sun, Tiansheng

2015-08-01

It has been well recognised that a deficit of numbers and function of CD4(+)CD25(+)Foxp3(+) cells (Treg) is attributed to the development of autoimmune diseases and inflammatory diseases; additionally, IL-17-producing cells (Th17) have a pro-inflammatory role. The balance between Th17 and Treg may be essential for maintaining immune homeostasis and has long been thought as one of the important factors in the development/prevention of autoimmune diseases and inflammatory diseases. In our previous research, we explored that cytokines (IL-17) and the balance of Treg/Th17 had a significant relevance with tissue (lung) inflammation and injury in acute-phase after multiple-trauma. To more verify whether an imbalance of Treg/Th17 is characteristic of rats suffering from multiple trauma. Using IL-17 monoclonal antibody (IL-17mAb)-treated multiple-trauma rat, we tested the pathogenic role of IL-17 in the development of multiple-trauma. Rat models were treated respectively with IL-17mAb or rat IgG 2A isotype control or phosphate-buffered solution after model was established. Normal rats only received anaesthesia and cannulation were taken as sham. Rats in each group were killed respectively at the end of 1h, 4h, 8h after injection. Collected serum and lung samples for assessment dynamically of MPO, IL-17, IL-6, and TGF-β-mRNA, and cytokine (IL-17, IL-6, TGF-β) and lung tissue for pulmonary histological analysis. Neutralisation of IL-17 with anti-IL-17 can decrease serum IL-17 level and the IL-17-mRNA transcript level in lung, and ameliorate tissue inflammatory, defer disease course. Our data suggest that IL-17 is crucially involved in the pathogenesis of multiple-trauma in rat, IL-17 inhibition might ameliorate the lung inflammation in acute-phase after multiple-trauma. Copyright © 2015 Elsevier Ltd. All rights reserved.

Global stability of a multiple infected compartments model for waterborne diseases

NASA Astrophysics Data System (ADS)

Wang, Yi; Cao, Jinde

2014-10-01

In this paper, mathematical analysis is carried out for a multiple infected compartments model for waterborne diseases, such as cholera, giardia, and rotavirus. The model accounts for both person-to-person and water-to-person transmission routes. Global stability of the equilibria is studied. In terms of the basic reproduction number R0, we prove that, if R0⩽1, then the disease-free equilibrium is globally asymptotically stable and the infection always disappears; whereas if R0>1, there exists a unique endemic equilibrium which is globally asymptotically stable for the corresponding fast-slow system. Numerical simulations verify our theoretical results and present that the decay rate of waterborne pathogens has a significant impact on the epidemic growth rate. Also, we observe numerically that the unique endemic equilibrium is globally asymptotically stable for the whole system. This statement indicates that the present method need to be improved by other techniques.

Therapeutic Efficacy of Suppressing the JAK/STAT Pathway in Multiple Models of EAE1

PubMed Central

Liu, Yudong; Holdbrooks, Andrew T.; De Sarno, Patrizia; Rowse, Amber L.; Yanagisawa, Lora L.; McFarland, Braden C.; Harrington, Laurie E.; Raman, Chander; Sabbaj, Steffanie; Benveniste, Etty N.; Qin, Hongwei

2014-01-01

Pathogenic T helper cells and myeloid cells are involved in the pathogenesis of Multiple Sclerosis (MS) and Experimental Autoimmune Encephalomyelitis (EAE), an animal model of MS. The JAK/STAT pathway is utilized by numerous cytokines for signaling, and is critical for development, regulation and termination of immune responses. Dysregulation of the JAK/STAT pathway has pathological implications in autoimmune and neuroinflammatory diseases. Many of the cytokines involved in MS/EAE, including IL-6, IL-12, IL-23, IFN-γ and GM-CSF, use the JAK/STAT pathway to induce biological responses. Thus, targeting JAKs has implications for treating autoimmune inflammation of the brain. We have utilized AZD1480, a JAK1/2 inhibitor, to investigate the therapeutic potential of inhibiting the JAK/STAT pathway in models of EAE. AZD1480 treatment inhibits disease severity in MOG-induced classical and atypical EAE models by preventing entry of immune cells into the brain, suppressing differentiation of Th1 and Th17 cells, deactivating myeloid cells, inhibiting STAT activation in the brain, and reducing expression of pro-inflammatory cytokines and chemokines. Treatment of SJL/J mice with AZD1480 delays disease onset of PLP-induced relapsing-remitting disease, reduces relapses and diminishes clinical severity. AZD1480 treatment was also effective in reducing ongoing paralysis induced by adoptive transfer of either pathogenic Th1 or Th17 cells. In vivo AZD1480 treatment impairs both the priming and expansion of T-cells, and attenuates antigen-presentation functions of myeloid cells. Inhibition of the JAK/STAT pathway has clinical efficacy in multiple pre-clinical models of MS, suggesting the feasibility of the JAK/STAT pathway as a target for neuroinflammatory diseases. PMID:24323580

SeqSIMLA2_exact: simulate multiple disease sites in large pedigrees with given disease status for diseases with low prevalence.

PubMed

Yao, Po-Ju; Chung, Ren-Hua

2016-02-15

It is difficult for current simulation tools to simulate sequence data in a pre-specified pedigree structure and pre-specified affection status. Previously, we developed a flexible tool, SeqSIMLA2, for simulating sequence data in either unrelated case-control or family samples with different disease and quantitative trait models. Here we extended the tool to efficiently simulate sequences with multiple disease sites in large pedigrees with a given disease status for each pedigree member, assuming that the disease prevalence is low. SeqSIMLA2_exact is implemented with C++ and is available at http://seqsimla.sourceforge.net. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis.

PubMed

Novakovic, A M; Krekels, E H J; Munafo, A; Ueckert, S; Karlsson, M O

2017-01-01

In this study, we report the development of the first item response theory (IRT) model within a pharmacometrics framework to characterize the disease progression in multiple sclerosis (MS), as measured by Expanded Disability Status Score (EDSS). Data were collected quarterly from a 96-week phase III clinical study by a blinder rater, involving 104,206 item-level observations from 1319 patients with relapsing-remitting MS (RRMS), treated with placebo or cladribine. Observed scores for each EDSS item were modeled describing the probability of a given score as a function of patients' (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time, and the model was then extended to cladribine arms to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. The IRT model was able to describe baseline and longitudinal EDSS data on item and total level. The final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of eight items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modeling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner.

Posttraumatic Growth and HIV Disease Progression

ERIC Educational Resources Information Center

Milam, Joel

2006-01-01

The relationship between posttraumatic growth (PTG; perceiving positive changes since diagnosis) and disease status, determined by changes in viral load and CD4 count over time, was examined among 412 people living with HIV. In controlled multiple regression models, PTG was not associated with disease status over time for the entire sample.…

Decision Aids for Multiple-Decision Disease Management as Affected by Weather Input Errors

USDA-ARS?s Scientific Manuscript database

Many disease management decision support systems (DSS) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation or estimation from off-site sources, may affect model calculations and manage...

Animal models of gastrointestinal and liver diseases. Animal models of cystic fibrosis: gastrointestinal, pancreatic, and hepatobiliary disease and pathophysiology

PubMed Central

Olivier, Alicia K.; Gibson-Corley, Katherine N.

2015-01-01

Multiple organ systems, including the gastrointestinal tract, pancreas, and hepatobiliary systems, are affected by cystic fibrosis (CF). Many of these changes begin early in life and are difficult to study in young CF patients. Recent development of novel CF animal models has expanded opportunities in the field to better understand CF pathogenesis and evaluate traditional and innovative therapeutics. In this review, we discuss manifestations of CF disease in gastrointestinal, pancreatic, and hepatobiliary systems of humans and animal models. We also compare the similarities and limitations of animal models and discuss future directions for modeling CF. PMID:25591863

A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa.

PubMed

Roy, Sandip; McElwain, Terry F; Wan, Yan

2011-10-01

Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission. A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community. The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary identification of the network model for brucellosis is achieved using historical data, and the robustness of the obtained model is demonstrated. As a whole, our results indicate that network modeling can aid in designing control policies for zoonotic diseases.

A Network Control Theory Approach to Modeling and Optimal Control of Zoonoses: Case Study of Brucellosis Transmission in Sub-Saharan Africa

PubMed Central

Roy, Sandip; McElwain, Terry F.; Wan, Yan

2011-01-01

Background Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission. Methodology/Principal Findings A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community. Conclusions/Significance The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary identification of the network model for brucellosis is achieved using historical data, and the robustness of the obtained model is demonstrated. As a whole, our results indicate that network modeling can aid in designing control policies for zoonotic diseases. PMID:22022621

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

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

PubMed Central

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

2015-01-01

Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases. PMID:26295344

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

PubMed

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

2015-01-01

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

A small-molecule inhibitor of the NLRP3 inflammasome for the treatment of inflammatory diseases.

PubMed

Coll, Rebecca C; Robertson, Avril A B; Chae, Jae Jin; Higgins, Sarah C; Muñoz-Planillo, Raúl; Inserra, Marco C; Vetter, Irina; Dungan, Lara S; Monks, Brian G; Stutz, Andrea; Croker, Daniel E; Butler, Mark S; Haneklaus, Moritz; Sutton, Caroline E; Núñez, Gabriel; Latz, Eicke; Kastner, Daniel L; Mills, Kingston H G; Masters, Seth L; Schroder, Kate; Cooper, Matthew A; O'Neill, Luke A J

2015-03-01

The NOD-like receptor (NLR) family, pyrin domain-containing protein 3 (NLRP3) inflammasome is a component of the inflammatory process, and its aberrant activation is pathogenic in inherited disorders such as cryopyrin-associated periodic syndrome (CAPS) and complex diseases such as multiple sclerosis, type 2 diabetes, Alzheimer's disease and atherosclerosis. We describe the development of MCC950, a potent, selective, small-molecule inhibitor of NLRP3. MCC950 blocked canonical and noncanonical NLRP3 activation at nanomolar concentrations. MCC950 specifically inhibited activation of NLRP3 but not the AIM2, NLRC4 or NLRP1 inflammasomes. MCC950 reduced interleukin-1β (IL-1β) production in vivo and attenuated the severity of experimental autoimmune encephalomyelitis (EAE), a disease model of multiple sclerosis. Furthermore, MCC950 treatment rescued neonatal lethality in a mouse model of CAPS and was active in ex vivo samples from individuals with Muckle-Wells syndrome. MCC950 is thus a potential therapeutic for NLRP3-associated syndromes, including autoinflammatory and autoimmune diseases, and a tool for further study of the NLRP3 inflammasome in human health and disease.

Systematic Review of Programs Treating High-Need and High-Cost People With Multiple Chronic Diseases or Disabilities in the United States, 2008–2014

PubMed Central

Bleich, Sara N.; Sherrod, Cheryl; Chiang, Anne; Boyd, Cynthia; Wolff, Jennifer; DuGoff, Eva; Salzberg, Claudia; Anderson, Keely; Leff, Bruce

2015-01-01

Introduction Finding ways to provide better and less expensive health care for people with multiple chronic conditions or disability is a pressing concern. The purpose of this systematic review was to evaluate different approaches for caring for this high-need and high-cost population. Methods We searched Medline for articles published from May 31, 2008, through June 10, 2014, for relevant studies. Articles were considered eligible for this review if they met the following criteria: included people with multiple chronic conditions (behavioral or mental health) or disabilities (2 or more); addressed 1 or more of clinical outcomes, health care use and spending, or patient satisfaction; and compared results from an intervention group with a comparison group or baseline measurements. We extracted information on program characteristics, participant characteristics, and significant (positive and negative) clinical findings, patient satisfaction, and health care use outcomes. For each outcome, the number of significant and positive results was tabulated. Results Twenty-seven studies were included across 5 models of care. Of the 3 studies reporting patient satisfaction outcomes, 2 reported significant improvements; both were randomized controlled trials (RCTs). Of the 14 studies reporting clinical outcomes, 12 reported improvements (8 were RCTs). Of the 13 studies reporting health care use and spending outcomes, 12 reported significant improvements (2 were RCTs). Two models of care — care and case management and disease management — reported improvements in all 3 outcomes. For care and case management models, most improvements were related to health care use. For the disease management models, most improvements were related to clinical outcomes. Conclusions Care and case management as well as disease management may be promising models of care for people with multiple chronic conditions or disabilities. More research and consistent methods are needed to understand the most appropriate care for these high-need and high-cost patients. PMID:26564013

Systematic Review of Programs Treating High-Need and High-Cost People With Multiple Chronic Diseases or Disabilities in the United States, 2008-2014.

PubMed

Bleich, Sara N; Sherrod, Cheryl; Chiang, Anne; Boyd, Cynthia; Wolff, Jennifer; DuGoff, Eva; Chang, Eva; Salzberg, Claudia; Anderson, Keely; Leff, Bruce; Anderson, Gerard

2015-11-12

Finding ways to provide better and less expensive health care for people with multiple chronic conditions or disability is a pressing concern. The purpose of this systematic review was to evaluate different approaches for caring for this high-need and high-cost population. We searched Medline for articles published from May 31, 2008, through June 10, 2014, for relevant studies. Articles were considered eligible for this review if they met the following criteria: included people with multiple chronic conditions (behavioral or mental health) or disabilities (2 or more); addressed 1 or more of clinical outcomes, health care use and spending, or patient satisfaction; and compared results from an intervention group with a comparison group or baseline measurements. We extracted information on program characteristics, participant characteristics, and significant (positive and negative) clinical findings, patient satisfaction, and health care use outcomes. For each outcome, the number of significant and positive results was tabulated. Twenty-seven studies were included across 5 models of care. Of the 3 studies reporting patient satisfaction outcomes, 2 reported significant improvements; both were randomized controlled trials (RCTs). Of the 14 studies reporting clinical outcomes, 12 reported improvements (8 were RCTs). Of the 13 studies reporting health care use and spending outcomes, 12 reported significant improvements (2 were RCTs). Two models of care - care and case management and disease management - reported improvements in all 3 outcomes. For care and case management models, most improvements were related to health care use. For the disease management models, most improvements were related to clinical outcomes. Care and case management as well as disease management may be promising models of care for people with multiple chronic conditions or disabilities. More research and consistent methods are needed to understand the most appropriate care for these high-need and high-cost patients.

Transcutaneous photodynamic therapy delays the onset of paralysis in a murine multiple sclerosis model

NASA Astrophysics Data System (ADS)

Hunt, David W. C.; Leong, Simon; Levy, Julia G.; Chan, Agnes H.

1995-03-01

Photodynamic therapy (PDT) using benzoporphyrin derivative (BPD, Verteporfin) and whole body irradiation, can affect the course of adoptively transferred experimental allergic (autoimmune) encephalomyelitis (EAE) in PL mice. Murine EAE is a T cell-mediated autoimmune disease which serves as a model for human multiple sclerosis. Using a novel disease induction protocol, we found that mice characteristically developed EAE within 3 weeks of receipt of myelin basic protein (MBP)-sensitized, in vitro-cultured spleen or lymph node cells. However, if animals were treated with PDT (1 mg BPD/kg bodyweight and exposed to whole body 15 Joules cm2 of LED light) 24 hours after receiving these cells, disease onset time was significantly delayed. PDT-treated mice developed disease symptoms 45 +/- 3 days following cell administration whereas untreated controls were affected within 23 +/- 2 days. In contrast, application of PDT 48 or 120 hours following injection of the pathogenic cells had no significant effect upon the development of EAE. Experiments are in progress to account for the protective effect of PDT in this animal model. These studies should provide evidence on the feasibility of PDT as a treatment for human autoimmune disease.

Integrated defense system overlaps as a disease model: with examples for multiple chemical sensitivity.

PubMed Central

Rowat, S C

1998-01-01

The central nervous, immune, and endocrine systems communicate through multiple common messengers. Over evolutionary time, what may be termed integrated defense system(s) (IDS) have developed to coordinate these communications for specific contexts; these include the stress response, acute-phase response, nonspecific immune response, immune response to antigen, kindling, tolerance, time-dependent sensitization, neurogenic switching, and traumatic dissociation (TD). These IDSs are described and their overlap is examined. Three models of disease production are generated: damage, in which IDSs function incorrectly; inadequate/inappropriate, in which IDS response is outstripped by a changing context; and evolving/learning, in which the IDS learned response to a context is deemed pathologic. Mechanisms of multiple chemical sensitivity (MCS) are developed from several IDS disease models. Model 1A is pesticide damage to the central nervous system, overlapping with body chemical burdens, TD, and chronic zinc deficiency; model 1B is benzene disruption of interleukin-1, overlapping with childhood developmental windows and hapten-antigenic spreading; and model 1C is autoimmunity to immunoglobulin-G (IgG), overlapping with spreading to other IgG-inducers, sudden spreading of inciters, and food-contaminating chemicals. Model 2A is chemical and stress overload, including comparison with the susceptibility/sensitization/triggering/spreading model; model 2B is genetic mercury allergy, overlapping with: heavy metals/zinc displacement and childhood/gestational mercury exposures; and model 3 is MCS as evolution and learning. Remarks are offered on current MCS research. Problems with clinical measurement are suggested on the basis of IDS models. Large-sample patient self-report epidemiology is described as an alternative or addition to clinical biomarker and animal testing. Images Figure 1 Figure 2 Figure 3 Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:9539008

Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Clinical endpoints in the controlled human challenge model for Shigella: A call for standardization and the development of a disease severity score

PubMed Central

Lynen, Amanda; Riddle, Mark S.; Talaat, Kawsar; Sack, David; Gutiérrez, Ramiro L.; McKenzie, Robin; DeNearing, Barbara; Feijoo, Brittany; Kaminski, Robert W.; Taylor, David N.; Kirkpatrick, Beth D.; Bourgeois, A. Louis

2018-01-01

Background Since 1946 the controlled human infection model (CHIM) for Shigella has been used to improve understanding of disease pathogenesis, describe clinical and immunologic responses to infection and as a tool for vaccine development. As the frequency and intent for use in vaccine comparisons increases, standardization of the primary endpoint definition is necessary. Methods Subject-level data were obtained from previously conducted experimental Shigella CHIM studies. Signs and symptoms severity were categorized consistently across all studies. Sign and symptom correlations were estimated and univariate models were utilized to describe the association between stool output and other Shigella-attributable signs and symptoms. Multiple correspondence and hierarchical clustering analyses were performed to describe the co-occurrence of signs and symptoms. A disease score is proposed based on the co-occurrence of these events. Results Data were obtained on 54 subjects receiving 800 to 2000 colony forming units (cfu) of S. flexneri. The median maximum 24 hour stool output was 514 ml (IQR: 300, 998 ml) with a median frequency of 6 (IQR: 4, 9). Subjects reported abdominal pain or cramps (81.5%), headache (66.7%) and anorexia (64.8%), 50.0% had a fever and 27.8% had gross blood in multiple loose stools. Multiple correspondence analyses highlighted co-occurrence of symptoms based on severity. A 3-parameter disease severity score predicted shigellosis endpoints and better differentiated disease spectrum. Conclusion Dichotomous endpoints for Shigella CHIM fail to fully account for disease variability. An ordinal disease score characterizing the breadth of disease severity may enable a better characterization of shigellosis and can decrease sample size requirements. Furthermore, the disease severity score may be a useful tool for portfolio management by enabling prioritization across vaccine candidates with comparable efficacy estimates using dichotomous endpoints. PMID:29590182

Generation of gene-targeted mice using embryonic stem cells derived from a transgenic mouse model of Alzheimer's disease.

PubMed

Yamamoto, Satoshi; Ooshima, Yuki; Nakata, Mitsugu; Yano, Takashi; Matsuoka, Kunio; Watanabe, Sayuri; Maeda, Ryouta; Takahashi, Hideki; Takeyama, Michiyasu; Matsumoto, Yoshio; Hashimoto, Tadatoshi

2013-06-01

Gene-targeting technology using mouse embryonic stem (ES) cells has become the "gold standard" for analyzing gene functions and producing disease models. Recently, genetically modified mice with multiple mutations have increasingly been produced to study the interaction between proteins and polygenic diseases. However, introduction of an additional mutation into mice already harboring several mutations by conventional natural crossbreeding is an extremely time- and labor-intensive process. Moreover, to do so in mice with a complex genetic background, several years may be required if the genetic background is to be retained. Establishing ES cells from multiple-mutant mice, or disease-model mice with a complex genetic background, would offer a possible solution. Here, we report the establishment and characterization of novel ES cell lines from a mouse model of Alzheimer's disease (3xTg-AD mouse, Oddo et al. in Neuron 39:409-421, 2003) harboring 3 mutated genes (APPswe, TauP301L, and PS1M146V) and a complex genetic background. Thirty blastocysts were cultured and 15 stable ES cell lines (male: 11; female: 4) obtained. By injecting these ES cells into diploid or tetraploid blastocysts, we generated germline-competent chimeras. Subsequently, we confirmed that F1 mice derived from these animals showed similar biochemical and behavioral characteristics to the original 3xTg-AD mice. Furthermore, we introduced a gene-targeting vector into the ES cells and successfully obtained gene-targeted ES cells, which were then used to generate knockout mice for the targeted gene. These results suggest that the present methodology is effective for introducing an additional mutation into mice already harboring multiple mutated genes and/or a complex genetic background.

ABBV-105, a selective and irreversible inhibitor of Bruton's Tyrosine Kinase (BTK), is efficacious in multiple preclinical models of inflammation.

PubMed

Goess, Christian; Harris, Christopher M; Murdock, Sara; McCarthy, Richard W; Sampson, Erik; Twomey, Rachel; Mathieu, Suzanne; Mario, Regina; Perham, Matthew; Goedken, Eric R; Long, Andrew J

2018-06-02

Bruton's Tyrosine Kinase (BTK) is a non-receptor tyrosine kinase required for intracellular signaling downstream of multiple immunoreceptors. We evaluated ABBV-105, a covalent BTK inhibitor, using in vitro and in vivo assays to determine potency, selectivity, and efficacy to validate the therapeutic potential of ABBV-105 in inflammatory disease. ABBV-105 potency and selectivity were evaluated in enzymatic and cellular assays. The impact of ABBV-105 on B cell function in vivo was assessed using mechanistic models of antibody production. Efficacy of ABBV-105 in chronic inflammatory disease was evaluated in animal models of arthritis and lupus. Measurement of BTK occupancy was employed as a target engagement biomarker. ABBV-105 irreversibly inhibits BTK, demonstrating superior kinome selectivity and is potent in B cell receptor, Fc receptor, and TLR-9-dependent cellular assays. Oral administration resulted in rapid clearance in plasma, but maintenance of BTK splenic occupancy. ABBV-105 inhibited antibody responses to thymus-independent and thymus-dependent antigens, paw swelling and bone destruction in rat collagen induced arthritis (CIA), and reduced disease in an IFNα-accelerated lupus nephritis model. BTK occupancy in disease models correlated with in vivo efficacy. ABBV-105, a selective BTK inhibitor, demonstrates compelling efficacy in pre-clinical mechanistic models of antibody production and in models of rheumatoid arthritis and lupus.

Preparation of organotypic brain slice cultures for the study of Alzheimer’s disease

PubMed Central

Croft, Cara L.; Noble, Wendy

2018-01-01

Alzheimer's disease, the most common cause of dementia, is a progressive neurodegenerative disorder characterised by amyloid-beta deposits in extracellular plaques, intracellular neurofibrillary tangles of aggregated tau, synaptic dysfunction and neuronal death. There are no cures for AD and current medications only alleviate some disease symptoms. Transgenic rodent models to study Alzheimer’s mimic features of human disease such as age-dependent accumulation of abnormal beta-amyloid and tau, synaptic dysfunction, cognitive deficits and neurodegeneration. These models have proven vital for improving our understanding of the molecular mechanisms underlying AD and for identifying promising therapeutic approaches. However, modelling neurodegenerative disease in animals commonly involves aging animals until they develop harmful phenotypes, often coupled with invasive procedures. In vivo studies are also resource, labour, time and cost intensive. We have developed a novel organotypic brain slice culture model to study Alzheimer’ disease which brings the potential of substantially reducing the number of rodents used in dementia research from an estimated 20,000 per year. We obtain 36 brain slices from each mouse pup, considerably reducing the numbers of animals required to investigate multiple stages of disease. This tractable model also allows the opportunity to modulate multiple pathways in tissues from a single animal. We believe that this model will most benefit dementia researchers in the academic and drug discovery sectors. We validated the slice culture model against aged mice, showing that the molecular phenotype closely mimics that displayed in vivo, albeit in an accelerated timescale. We showed beneficial outcomes following treatment of slices with agents previously shown to have therapeutic effects in vivo, and we also identified new mechanisms of action of other compounds. Thus, organotypic brain slice cultures from transgenic mouse models expressing Alzheimer’s disease-related genes may provide a valid and sensitive replacement for in vivo studies that do not involve behavioural analysis. PMID:29904599

A residency clinic chronic condition management quality improvement project.

PubMed

Halverson, Larry W; Sontheimer, Dan; Duvall, Sharon

2007-02-01

Quality improvement in chronic disease management is a major agenda for improving health and reducing health care costs. A six-component chronic disease management model can help guide this effort. Several characteristics of the "new model" of family medicine described by the Future of Family Medicine (FFM) Project Leadership Committee are promulgated to foster practice changes that improve quality. Our objective was to implement and assess a quality improvement project guided by the components of a chronic disease management model and FFM new model characteristics. Diabetes was selected as a model chronic disease focus. Multiple practice changes were implemented. A mature electronic medical record facilitated data collection and measurement of quality improvement progress. Data from the diabetes registry demonstrates that our efforts have been effective. Significant improvement occurred in five out of six quality indicators. Multidisciplinary teamwork in a model residency practice guided by chronic disease management principles and the FFM new model characteristics can produce significant management improvements in one important chronic disease.

Trehalose upregulates progranulin expression in human and mouse models of GRN haploinsufficiency: a novel therapeutic lead to treat frontotemporal dementia.

PubMed

Holler, Christopher J; Taylor, Georgia; McEachin, Zachary T; Deng, Qiudong; Watkins, William J; Hudson, Kathryn; Easley, Charles A; Hu, William T; Hales, Chadwick M; Rossoll, Wilfried; Bassell, Gary J; Kukar, Thomas

2016-06-24

Progranulin (PGRN) is a secreted growth factor important for neuronal survival and may do so, in part, by regulating lysosome homeostasis. Mutations in the PGRN gene (GRN) are a common cause of frontotemporal lobar degeneration (FTLD) and lead to disease through PGRN haploinsufficiency. Additionally, complete loss of PGRN in humans leads to neuronal ceroid lipofuscinosis (NCL), a lysosomal storage disease. Importantly, Grn-/- mouse models recapitulate pathogenic lysosomal features of NCL. Further, GRN variants that decrease PGRN expression increase the risk of developing Alzheimer's disease (AD) and Parkinson's disease (PD). Together these findings demonstrate that insufficient PGRN predisposes neurons to degeneration. Therefore, compounds that increase PGRN levels are potential therapeutics for multiple neurodegenerative diseases. Here, we performed a cell-based screen of a library of known autophagy-lysosome modulators and identified multiple novel activators of a human GRN promoter reporter including several common mTOR inhibitors and an mTOR-independent activator of autophagy, trehalose. Secondary cellular screens identified trehalose, a natural disaccharide, as the most promising lead compound because it increased endogenous PGRN in all cell lines tested and has multiple reported neuroprotective properties. Trehalose dose-dependently increased GRN mRNA as well as intracellular and secreted PGRN in both mouse and human cell lines and this effect was independent of the transcription factor EB (TFEB). Moreover, trehalose rescued PGRN deficiency in human fibroblasts and neurons derived from induced pluripotent stem cells (iPSCs) generated from GRN mutation carriers. Finally, oral administration of trehalose to Grn haploinsufficient mice significantly increased PGRN expression in the brain. This work reports several novel autophagy-lysosome modulators that enhance PGRN expression and identifies trehalose as a promising therapeutic for raising PGRN levels to treat multiple neurodegenerative diseases.

Modeling oscillatory dynamics in brain microcircuits as a way to help uncover neurological disease mechanisms: A proposal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skinner, F. K.; Department of Medicine; Department of Physiology, University of Toronto Medical Sciences Building, 3rd Floor, 1 King's College Circle, Toronto, Ontario M5S 1A8

There is an undisputed need and requirement for theoretical and computational studies in Neuroscience today. Furthermore, it is clear that oscillatory dynamical output from brain networks is representative of various behavioural states, and it is becoming clear that one could consider these outputs as measures of normal and pathological brain states. Although mathematical modeling of oscillatory dynamics in the context of neurological disease exists, it is a highly challenging endeavour because of the many levels of organization in the nervous system. This challenge is coupled with the increasing knowledge of cellular specificity and network dysfunction that is associated with disease.more » Recently, whole hippocampus in vitro preparations from control animals have been shown to spontaneously express oscillatory activities. In addition, when using preparations derived from animal models of disease, these activities show particular alterations. These preparations present an opportunity to address challenges involved with using models to gain insight because of easier access to simultaneous cellular and network measurements, and pharmacological modulations. We propose that by developing and using models with direct links to experiment at multiple levels, which at least include cellular and microcircuit, a cycling can be set up and used to help us determine critical mechanisms underlying neurological disease. We illustrate our proposal using our previously developed inhibitory network models in the context of these whole hippocampus preparations and show the importance of having direct links at multiple levels.« less

Impaired neurosteroid synthesis in multiple sclerosis

PubMed Central

Noorbakhsh, Farshid; Ellestad, Kristofor K.; Maingat, Ferdinand; Warren, Kenneth G.; Han, May H.; Steinman, Lawrence; Baker, Glen B.

2011-01-01

High-throughput technologies have led to advances in the recognition of disease pathways and their underlying mechanisms. To investigate the impact of micro-RNAs on the disease process in multiple sclerosis, a prototypic inflammatory neurological disorder, we examined cerebral white matter from patients with or without the disease by micro-RNA profiling, together with confirmatory reverse transcription–polymerase chain reaction analysis, immunoblotting and gas chromatography-mass spectrometry. These observations were verified using the in vivo multiple sclerosis model, experimental autoimmune encephalomyelitis. Brains of patients with or without multiple sclerosis demonstrated differential expression of multiple micro-RNAs, but expression of three neurosteroid synthesis enzyme-specific micro-RNAs (miR-338, miR-155 and miR-491) showed a bias towards induction in patients with multiple sclerosis (P < 0.05). Analysis of the neurosteroidogenic pathways targeted by micro-RNAs revealed suppression of enzyme transcript and protein levels in the white matter of patients with multiple sclerosis (P < 0.05). This was confirmed by firefly/Renilla luciferase micro-RNA target knockdown experiments (P < 0.05) and detection of specific micro-RNAs by in situ hybridization in the brains of patients with or without multiple sclerosis. Levels of important neurosteroids, including allopregnanolone, were suppressed in the white matter of patients with multiple sclerosis (P < 0.05). Induction of the murine micro-RNAs, miR-338 and miR-155, accompanied by diminished expression of neurosteroidogenic enzymes and allopregnanolone, was also observed in the brains of mice with experimental autoimmune encephalomyelitis (P < 0.05). Allopregnanolone treatment of the experimental autoimmune encephalomyelitis mouse model limited the associated neuropathology, including neuroinflammation, myelin and axonal injury and reduced neurobehavioral deficits (P < 0.05). These multi-platform studies point to impaired neurosteroidogenesis in both multiple sclerosis and experimental autoimmune encephalomyelitis. The findings also indicate that allopregnanolone and perhaps other neurosteroid-like compounds might represent potential biomarkers or therapies for multiple sclerosis. PMID:21908875

Analysis of underlying and multiple-cause mortality data: the life table methods.

PubMed

Moussa, M A

1987-02-01

The stochastic compartment model concepts are employed to analyse and construct complete and abbreviated total mortality life tables, multiple-decrement life tables for a disease, under the underlying and pattern-of-failure definitions of mortality risk, cause-elimination life tables, cause-elimination effects on saved population through the gain in life expectancy as a consequence of eliminating the mortality risk, cause-delay life tables designed to translate the clinically observed increase in survival time as the population gain in life expectancy that would occur if a treatment protocol was made available to the general population and life tables for disease dependency in multiple-cause data.

76 FR 55071 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-06

..., multiple sclerosis, rheumatoid arthritis, and lupus. Treatments generally include immunosuppressants or... anti-TL1A antibodies that prevent disease in mouse models of rheumatoid arthritis and inflammatory... Arthritis and Musculoskeletal and Skin Diseases is seeking statements of capability or interest from parties...

The network level reproduction number for infectious diseases with both vertical and horizontal transmission.

PubMed

Xue, Ling; Scoglio, Caterina

2013-05-01

A wide range of infectious diseases are both vertically and horizontally transmitted. Such diseases are spatially transmitted via multiple species in heterogeneous environments, typically described by complex meta-population models. The reproduction number, R0, is a critical metric predicting whether the disease can invade the meta-population system. This paper presents the reproduction number for a generic disease vertically and horizontally transmitted among multiple species in heterogeneous networks, where nodes are locations, and links reflect outgoing or incoming movement flows. The metapopulation model for vertically and horizontally transmitted diseases is gradually formulated from two species, two-node network models. We derived an explicit expression of R0, which is the spectral radius of a matrix reduced in size with respect to the original next generation matrix. The reproduction number is shown to be a function of vertical and horizontal transmission parameters, and the lower bound is the reproduction number for horizontal transmission. As an application, the reproduction number and its bounds for the Rift Valley fever zoonosis, where livestock, mosquitoes, and humans are the involved species are derived. By computing the reproduction number for different scenarios through numerical simulations, we found the reproduction number is affected by livestock movement rates only when parameters are heterogeneous across nodes. To summarize, our study contributes the reproduction number for vertically and horizontally transmitted diseases in heterogeneous networks. This explicit expression is easily adaptable to specific infectious diseases, affording insights into disease evolution. Copyright © 2013 Elsevier Inc. All rights reserved.

Positive or negative involvement of heat shock proteins in multiple sclerosis pathogenesis: an overview.

PubMed

Turturici, Giuseppina; Tinnirello, Rosaria; Sconzo, Gabriella; Asea, Alexzander; Savettieri, Giovanni; Ragonese, Paolo; Geraci, Fabiana

2014-12-01

Multiple sclerosis (MS) is the most diffuse chronic inflammatory disease of the central nervous system. Both immune-mediated and neurodegenerative processes apparently play roles in the pathogenesis of this disease. Heat shock proteins (HSPs) are a family of highly evolutionarily conserved proteins; their expression in the nervous system is induced in a variety of pathologic states, including cerebral ischemia, neurodegenerative diseases, epilepsy, and trauma. To date, investigators have observed protective effects of HSPs in a variety of brain disease models (e.g. of Alzheimer disease and Parkinson disease). In contrast, unequivocal data have been obtained for their roles in MS that depend on the HSP family and particularly on their localization (i.e. intracellular or extracellular). This article reviews our current understanding of the involvement of the principal HSP families in MS.

Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

PubMed

Halevy, Tomer; Urbach, Achia

2014-10-24

Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

Using multiple decrement models to estimate risk and morbidity from specific AIDS illnesses. Multicenter AIDS Cohort Study (MACS).

PubMed

Hoover, D R; Peng, Y; Saah, A J; Detels, R R; Day, R S; Phair, J P

A simple non-parametric approach is developed to simultaneously estimate net incidence and morbidity time from specific AIDS illnesses in populations at high risk for death from these illnesses and other causes. The disease-death process has four-stages that can be recast as two sandwiching three-state multiple decrement processes. Non-parametric estimation of net incidence and morbidity time with error bounds are achieved from these sandwiching models through modification of methods from Aalen and Greenwood, and bootstrapping. An application to immunosuppressed HIV-1 infected homosexual men reveals that cytomegalovirus disease, Kaposi's sarcoma and Pneumocystis pneumonia are likely to occur and cause significant morbidity time.

Kidney disease models: tools to identify mechanisms and potential therapeutic targets

PubMed Central

Bao, Yin-Wu; Yuan, Yuan; Chen, Jiang-Hua; Lin, Wei-Qiang

2018-01-01

Acute kidney injury (AKI) and chronic kidney disease (CKD) are worldwide public health problems affecting millions of people and have rapidly increased in prevalence in recent years. Due to the multiple causes of renal failure, many animal models have been developed to advance our understanding of human nephropathy. Among these experimental models, rodents have been extensively used to enable mechanistic understanding of kidney disease induction and progression, as well as to identify potential targets for therapy. In this review, we discuss AKI models induced by surgical operation and drugs or toxins, as well as a variety of CKD models (mainly genetically modified mouse models). Results from recent and ongoing clinical trials and conceptual advances derived from animal models are also explored. PMID:29515089

Managing Disease Risks from Trade: Strategic Behavior with Many Choices and Price Effects.

PubMed

Chitchumnong, Piyayut; Horan, Richard D

2018-03-16

An individual's infectious disease risks, and hence the individual's incentives for risk mitigation, may be influenced by others' risk management choices. If so, then there will be strategic interactions among individuals, whereby each makes his or her own risk management decisions based, at least in part, on the expected decisions of others. Prior work has shown that multiple equilibria could arise in this setting, with one equilibrium being a coordination failure in which individuals make too few investments in protection. However, these results are largely based on simplified models involving a single management choice and fixed prices that may influence risk management incentives. Relaxing these assumptions, we find strategic interactions influence, and are influenced by, choices involving multiple management options and market price effects. In particular, we find these features can reduce or eliminate concerns about multiple equilibria and coordination failure. This has important policy implications relative to simpler models.

Fat-soluble vitamins as disease modulators in multiple sclerosis.

PubMed

Torkildsen, Ø; Løken-Amsrud, K I; Wergeland, S; Myhr, K-M; Holmøy, T

2013-01-01

Fat-soluble vitamins (A, D, E and K) have properties that could be relevant as modulators of disease activity in multiple sclerosis (MS). We performed a systematic search on PubMed and Medline up to May 2012, using the search strings 'vitamin A', 'retinol', 'retinal', 'carotenoids', 'vitamin D', 'vitamin E', 'alpha-tocopherol', 'vitamin K' in conjunction with 'multiple sclerosis', 'animal model' and 'experimental autoimmune encephalitis (EAE)'. In addition, the reference lists of the publications identified were examined for further citations of relevance. There is comprehensive evidence from epidemiological, observational, and experimental studies that vitamin D may be beneficial in MS. Results from small-scale clinical studies are inconclusive, and large-scale, adequately powered, randomized, controlled trials are still lacking. For vitamin D, Oxford Centre for Evidence-Based Medicine level 2c evidence exists for a positive therapeutic effect. Evidence from animal models indicates that all the examined fat-soluble vitamins could have potential as modulators of disease activity in MS. For vitamin A and E, level 4 and 5 evidence exists for a modulatory effect in MS; for vitamin K, too few studies have been conducted to indicate an effect in humans. Vitamin D is a promising candidate as modulator of disease activity in MS, and controlled studies are currently being conducted. All the fat-soluble vitamins have, however, been demonstrated to be effective in different animal models for the disease, and vitamin A and E have biological properties that could be relevant for MS pathogenesis. Thus, vitamin A and E seem to be promising candidates for future case-control and cohort studies. © 2012 John Wiley & Sons A/S.

Diverse ways of perturbing the human arachidonic acid metabolic network to control inflammation.

PubMed

Meng, Hu; Liu, Ying; Lai, Luhua

2015-08-18

Inflammation and other common disorders including diabetes, cardiovascular disease, and cancer are often the result of several molecular abnormalities and are not likely to be resolved by a traditional single-target drug discovery approach. Though inflammation is a normal bodily reaction, uncontrolled and misdirected inflammation can cause inflammatory diseases such as rheumatoid arthritis and asthma. Nonsteroidal anti-inflammatory drugs including aspirin, ibuprofen, naproxen, or celecoxib are commonly used to relieve aches and pains, but often these drugs have undesirable and sometimes even fatal side effects. To facilitate safer and more effective anti-inflammatory drug discovery, a balanced treatment strategy should be developed at the biological network level. In this Account, we focus on our recent progress in modeling the inflammation-related arachidonic acid (AA) metabolic network and subsequent multiple drug design. We first constructed a mathematical model of inflammation based on experimental data and then applied the model to simulate the effects of commonly used anti-inflammatory drugs. Our results indicated that the model correctly reproduced the established bleeding and cardiovascular side effects. Multitarget optimal intervention (MTOI), a Monte Carlo simulated annealing based computational scheme, was then developed to identify key targets and optimal solutions for controlling inflammation. A number of optimal multitarget strategies were discovered that were both effective and safe and had minimal associated side effects. Experimental studies were performed to evaluate these multitarget control solutions further using different combinations of inhibitors to perturb the network. Consequently, simultaneous control of cyclooxygenase-1 and -2 and leukotriene A4 hydrolase, as well as 5-lipoxygenase and prostaglandin E2 synthase were found to be among the best solutions. A single compound that can bind multiple targets presents advantages including low risk of drug-drug interactions and robustness regarding concentration fluctuations. Thus, we developed strategies for multiple-target drug design and successfully discovered several series of multiple-target inhibitors. Optimal solutions for a disease network often involve mild but simultaneous interventions of multiple targets, which is in accord with the philosophy of traditional Chinese medicine (TCM). To this end, our AA network model can aptly explain TCM anti-inflammatory herbs and formulas at the molecular level. We also aimed to identify activators for several enzymes that appeared to have increased activity based on MTOI outcomes. Strategies were then developed to predict potential allosteric sites and to discover enzyme activators based on our hypothesis that combined treatment with the projected activators and inhibitors could balance different AA network pathways, control inflammation, and reduce associated adverse effects. Our work demonstrates that the integration of network modeling and drug discovery can provide novel solutions for disease control, which also calls for new developments in drug design concepts and methodologies. With the rapid accumulation of quantitative data and knowledge of the molecular networks of disease, we can expect an increase in the development and use of quantitative disease models to facilitate efficient and safe drug discovery.

A selective and potent CXCR3 antagonist SCH 546738 attenuates the development of autoimmune diseases and delays graft rejection

PubMed Central

2012-01-01

Background The CXCR3 receptor and its three interferon-inducible ligands (CXCL9, CXCL10 and CXCL11) have been implicated as playing a central role in directing a Th1 inflammatory response. Recent studies strongly support that the CXCR3 receptor is a very attractive therapeutic target for treating autoimmune diseases, such as rheumatoid arthritis, multiple sclerosis and psoriasis, and to prevent transplant rejection. We describe here the in vitro and in vivo pharmacological characterizations of a novel and potent small molecule CXCR3 antagonist, SCH 546738. Results In this study, we evaluated in vitro pharmacological properties of SCH 546738 by radioligand receptor binding and human activated T cell chemotaxis assays. In vivo efficacy of SCH 546738 was determined by mouse collagen-induced arthritis, rat and mouse experimental autoimmune encephalomyelitis, and rat cardiac transplantation models. We show that SCH 546738 binds to human CXCR3 with a high affinity of 0.4 nM. In addition, SCH 546738 displaces radiolabeled CXCL10 and CXCL11 from human CXCR3 with IC50 ranging from 0.8 to 2.2 nM in a non-competitive manner. SCH 546738 potently and specifically inhibits CXCR3-mediated chemotaxis in human activated T cells with IC90 about 10 nM. SCH 546738 attenuates the disease development in mouse collagen-induced arthritis model. SCH 546738 also significantly reduces disease severity in rat and mouse experimental autoimmune encephalomyelitis models. Furthermore, SCH 546738 alone achieves dose-dependent prolongation of rat cardiac allograft survival. Most significantly, SCH 546738 in combination with CsA supports permanent engraftment. Conclusions SCH 546738 is a novel, potent and non-competitive small molecule CXCR3 antagonist. It is efficacious in multiple preclinical disease models. These results demonstrate that therapy with CXCR3 antagonists may serve as a new strategy for treatment of autoimmune diseases, including rheumatoid arthritis and multiple sclerosis, and to prevent transplant rejection. PMID:22233170

A small molecule inhibitior of the NLRP3 inflammasome is a potential therapeutic for inflammatory diseases

PubMed Central

Coll, Rebecca C.; Robertson, Avril A. B.; Chae, Jae Jin; Higgins, Sarah C.; Muñoz-Planillo, Raúl; Inserra, Marco C.; Vetter, Irina; Dungan, Lara S.; Monks, Brian G.; Stutz, Andrea; Croker, Daniel E.; Butler, Mark S.; Haneklaus, Moritz; Sutton, Caroline E.; Núñez, Gabriel; Latz, Eicke; Kastner, Daniel L.; Mills, Kingston H. G.; Masters, Seth L.; Schroder, Kate; Cooper, Matthew A.; O’Neill, Luke A. J.

2015-01-01

The NLRP3 inflammasome is a component of the inflammatory process and its aberrant activation is pathogenic in inherited disorders such as the cryopyrin associated periodic syndromes (CAPS) and complex diseases such as multiple sclerosis, type 2 diabetes and atherosclerosis. We describe the development of MCC950, a potent, selective, small molecule inhibitor of NLRP3. MCC950 blocks canonical and non-canonical NLRP3 activation at nanomolar concentrations. MCC950 specifically inhibits NLRP3 but not AIM2, NLRC4 or NLRP1 activation. MCC950 reduces Interleukin-1p (IL-1β) production in vivo and attenuates the severity of experimental autoimmune encephalomyelitis (EAE), a disease model of multiple sclerosis. Furthermore, MCC950 treatment rescues neonatal lethality in a mouse model of CAPS and is active in ex vivo samples from individuals with Muckle-Wells syndrome. MCC950 is thus a potential therapeutic for NLRP3-associated syndromes, including autoinflammatory and autoimmune diseases, and a tool for the further study of the NLRP3 inflammasome in human health and disease. PMID:25686105

Neuroprotection in a Novel Mouse Model of Multiple Sclerosis

PubMed Central

Lidster, Katie; Jackson, Samuel J.; Ahmed, Zubair; Munro, Peter; Coffey, Pete; Giovannoni, Gavin; Baker, Mark D.; Baker, David

2013-01-01

Multiple sclerosis is an immune-mediated, demyelinating and neurodegenerative disease that currently lacks any neuroprotective treatments. Innovative neuroprotective trial designs are required to hasten the translational process of drug development. An ideal target to monitor the efficacy of strategies aimed at treating multiple sclerosis is the visual system, which is the most accessible part of the human central nervous system. A novel C57BL/6 mouse line was generated that expressed transgenes for a myelin oligodendrocyte glycoprotein-specific T cell receptor and a retinal ganglion cell restricted-Thy1 promoter-controlled cyan fluorescent protein. This model develops spontaneous or induced optic neuritis, in the absence of paralytic disease normally associated with most rodent autoimmune models of multiple sclerosis. Demyelination and neurodegeneration could be monitored longitudinally in the living animal using electrophysiology, visual sensitivity, confocal scanning laser ophthalmoscopy and optical coherence tomography all of which are relevant to human trials. This model offers many advantages, from a 3Rs, economic and scientific perspective, over classical experimental autoimmune encephalomyelitis models that are associated with substantial suffering of animals. Optic neuritis in this model led to inflammatory damage of axons in the optic nerve and subsequent loss of retinal ganglion cells in the retina. This was inhibited by the systemic administration of a sodium channel blocker (oxcarbazepine) or intraocular treatment with siRNA targeting caspase-2. These novel approaches have relevance to the future treatment of neurodegeneration of MS, which has so far evaded treatment. PMID:24223903

A bidirectional association between the gut microbiota and CNS disease in a biphasic murine model of multiple sclerosis.

PubMed

Colpitts, Sara L; Kasper, Eli J; Keever, Abigail; Liljenberg, Caleb; Kirby, Trevor; Magori, Krisztian; Kasper, Lloyd H; Ochoa-Repáraz, Javier

2017-11-02

The gut microbiome plays an important role in the development of inflammatory disease as shown using experimental models of central nervous system (CNS) demyelination. Gut microbes influence the response of regulatory immune cell populations in the gut-associated lymphoid tissue (GALT), which drive protection in acute and chronic experimental autoimmune encephalomyelitis (EAE). Recent observations suggest that communication between the host and the gut microbiome is bidirectional. We hypothesized that the gut microbiota differs between the acute inflammatory and chronic progressive stages of a murine model of secondary-progressive multiple sclerosis (SP-MS). This non-obese diabetic (NOD) model of EAE develops a biphasic pattern of disease that more closely resembles the human condition when transitioning from relapsing-remitting (RR)-MS to SP-MS. We compared the gut microbiome of NOD mice with either mild or severe disease to that of non-immunized control mice. We found that the mice which developed a severe secondary form of EAE harbored a dysbiotic gut microbiome when compared with the healthy control mice. Furthermore, we evaluated whether treatment with a cocktail of broad-spectrum antibiotics would modify the outcome of the progressive stage of EAE in the NOD model. Our results indicated reduced mortality and clinical disease severity in mice treated with antibiotics compared with untreated mice. Our findings support the hypothesis that there are reciprocal effects between experimental CNS inflammatory demyelination and modification of the microbiome providing a foundation for the establishment of early therapeutic interventions targeting the gut microbiome that could potentially limit disease progression.

Use of model organism and disease databases to support matchmaking for human disease gene discovery.

PubMed

Mungall, Christopher J; Washington, Nicole L; Nguyen-Xuan, Jeremy; Condit, Christopher; Smedley, Damian; Köhler, Sebastian; Groza, Tudor; Shefchek, Kent; Hochheiser, Harry; Robinson, Peter N; Lewis, Suzanna E; Haendel, Melissa A

2015-10-01

The Matchmaker Exchange application programming interface (API) allows searching a patient's genotypic or phenotypic profiles across clinical sites, for the purposes of cohort discovery and variant disease causal validation. This API can be used not only to search for matching patients, but also to match against public disease and model organism data. This public disease data enable matching known diseases and variant-phenotype associations using phenotype semantic similarity algorithms developed by the Monarch Initiative. The model data can provide additional evidence to aid diagnosis, suggest relevant models for disease mechanism and treatment exploration, and identify collaborators across the translational divide. The Monarch Initiative provides an implementation of this API for searching multiple integrated sources of data that contextualize the knowledge about any given patient or patient family into the greater biomedical knowledge landscape. While this corpus of data can aid diagnosis, it is also the beginning of research to improve understanding of rare human diseases. © 2015 WILEY PERIODICALS, INC.

Global and 3D Spatial Assessment of Neuroinflammation in Rodent Models of Multiple Sclerosis

PubMed Central

Gupta, Shashank; Utoft, Regine; Hasseldam, Henrik; Schmidt-Christensen, Anja; Hannibal, Tine Dahlbaek; Hansen, Lisbeth; Fransén-Pettersson, Nina; Agarwal-Gupta, Noopur; Rozell, Björn; Andersson, Åsa; Holmberg, Dan

2013-01-01

Multiple Sclerosis (MS) is a progressive autoimmune inflammatory and demyelinating disease of the central nervous system (CNS). T cells play a key role in the progression of neuroinflammation in MS and also in the experimental autoimmune encephalomyelitis (EAE) animal models for the disease. A technology for quantitative and 3 dimensional (3D) spatial assessment of inflammation in this and other CNS inflammatory conditions is much needed. Here we present a procedure for 3D spatial assessment and global quantification of the development of neuroinflammation based on Optical Projection Tomography (OPT). Applying this approach to the analysis of rodent models of MS, we provide global quantitative data of the major inflammatory component as a function of the clinical course. Our data demonstrates a strong correlation between the development and progression of neuroinflammation and clinical disease in several mouse and a rat model of MS refining the information regarding the spatial dynamics of the inflammatory component in EAE. This method provides a powerful tool to investigate the effect of environmental and genetic forces and for assessing the therapeutic effects of drug therapy in animal models of MS and other neuroinflammatory/neurodegenerative disorders. PMID:24124545

Multivariate Bayesian modeling of known and unknown causes of events--an application to biosurveillance.

PubMed

Shen, Yanna; Cooper, Gregory F

2012-09-01

This paper investigates Bayesian modeling of known and unknown causes of events in the context of disease-outbreak detection. We introduce a multivariate Bayesian approach that models multiple evidential features of every person in the population. This approach models and detects (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A contribution of this paper is that it introduces a multivariate Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has general applicability in domains where the space of known causes is incomplete. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Anti-inflammatory properties of methylthioadenosine in experimental colitis

USDA-ARS?s Scientific Manuscript database

The methionine (Met) metabolic cycle is critical for normal cell functions. Met cycle disruption has been implicated in disease, such as alcoholic liver disease (ALD) and multiple sclerosis (MS). Studies in animal models of ALD and MS have shown that the Met metabolite methylthioadenosine (MTA) has ...

Behavioural change models for infectious disease transmission: a systematic review (2010–2015)

PubMed Central

2016-01-01

We review behavioural change models (BCMs) for infectious disease transmission in humans. Following the Cochrane collaboration guidelines and the PRISMA statement, our systematic search and selection yielded 178 papers covering the period 2010–2015. We observe an increasing trend in published BCMs, frequently coupled to (re)emergence events, and propose a categorization by distinguishing how information translates into preventive actions. Behaviour is usually captured by introducing information as a dynamic parameter (76/178) or by introducing an economic objective function, either with (26/178) or without (37/178) imitation. Approaches using information thresholds (29/178) and exogenous behaviour formation (16/178) are also popular. We further classify according to disease, prevention measure, transmission model (with 81/178 population, 6/178 metapopulation and 91/178 individual-level models) and the way prevention impacts transmission. We highlight the minority (15%) of studies that use any real-life data for parametrization or validation and note that BCMs increasingly use social media data and generally incorporate multiple sources of information (16/178), multiple types of information (17/178) or both (9/178). We conclude that individual-level models are increasingly used and useful to model behaviour changes. Despite recent advancements, we remain concerned that most models are purely theoretical and lack representative data and a validation process. PMID:28003528

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus

PubMed Central

Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

2016-01-01

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector’s life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis’ life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector–based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector. PMID:27159134

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus.

PubMed

Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

2016-01-01

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.

Evidence of major genes for resistance to bacterial cold-water disease in rainbow trout using mixed inheritance multiple-threshold models and Bayesian segregation analysis

USDA-ARS?s Scientific Manuscript database

PURPOSE: Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture, and in 2005, a rainbow trout breeding program was initiated at the NCCCWA to select for increased disease survival. The main objectives of this study were to determine the mode of inheritance of di...

Prenatal programming of pulmonary hypertension induced by chronic hypoxia or ductal ligation in sheep.

PubMed

Papamatheakis, Demosthenes G; Chundu, Madalitso; Blood, Arlin B; Wilson, Sean M

2013-12-01

Pulmonary hypertension of the newborn is caused by a spectrum of functional and structural abnormalities of the cardiopulmonary circuit. The existence of multiple etiologies and an incomplete understanding of the mechanisms of disease progression have hindered the development of effective therapies. Animal models offer a means of gaining a better understanding of the fundamental basis of the disease. To that effect, a number of experimental animal models are being used to generate pulmonary hypertension in the fetus and newborn. In this review, we compare the mechanisms associated with pulmonary hypertension caused by two such models: in utero ligation of the ductus arteriosus and chronic perinatal hypoxia in sheep fetuses and newborns. In this manner, we make direct comparisons between ductal ligation and chronic hypoxia with respect to the associated mechanisms of disease, since multiple studies have been performed with both models in a single species. We present evidence that the mechanisms associated with pulmonary hypertension are dependent on the type of stress to which the fetus is subjected. Such an analysis allows for a more thorough evaluation of the disease etiology, which can help focus clinical treatments. The final part of the review provides a clinical appraisal of current treatment strategies and lays the foundation for developing individualized therapies that depend on the causative factors.

Dynamics of multiple infection and within-host competition by the anther-smut pathogen.

PubMed

Hood, M E

2003-07-01

Infection of one host by multiple pathogen genotypes represents an important area of pathogen ecology and evolution that lacks a broad empirical foundation. Multiple infection of Silene latifolia by Microbotryum violaceum was studied under field and greenhouse conditions using the natural polymorphism for mating-type bias as a marker. Field transmission resulted in frequent multiple infection, and each stem of the host was infected independently. Within-host diversity of infections equaled that of nearby inoculum sources by the end of the growing season. The number of diseased stems per plant was positively correlated with multiple infection and with overwintering mortality. As a result, multiply infected plants were largely purged from the population, and there was lower within-host pathogen diversity in the second season. However, among plants with a given number of diseased stems, multiply infected plants had a lower risk of overwintering mortality. Following simultaneous and sequential inoculation, strong competitive exclusion was demonstrated, and the first infection had a significant advantage. Dynamics of multiple infection initially included components of coinfection models for virulence evolution and then components of superinfection models after systemic colonization. Furthermore, there was evidence for an advantage of genotypes with mating-type bias, which may contribute to maintenance of this polymorphism in natural populations.

Patient decision-making related to antirheumatic drugs in rheumatoid arthritis: the importance of patient trust of physician.

PubMed

Martin, Richard W; Head, Andrew J; René, Jonathan; Swartz, Timothy J; Fiechtner, Justus J; McIntosh, Barbara A; Holmes-Rovner, Margaret

2008-04-01

To explore how rheumatoid arthritis (RA) antirheumatic drug-specific knowledge and numeric literacy, patient trust in physician, and demographic and disease-related factors relate to the confidence of patient decision-making related to disease modifying antirheumatic drugs (DMARD). Data were analyzed from 628 randomly selected patients with RA receiving care in community rheumatology practices, who responded to a multicenter, cross-sectional mail survey. We used multiple regression models to predict patient confidence in DMARD decision-making related to their most recently initiated DMARD. Significant positive correlation was found between confidence in DMARD decision and trust in physician, DMARD-specific knowledge, and disease duration, but not risk-related numeric literacy, sex, or education. Negative correlations were found with disease severity and current bother with DMARD side effects. A multiple linear regression model of confidence in DMARD decision had an overall R = 0.788, R2 = 0.620 (p < 0.001). The 4 dependent variables contributing significantly to the model were female sex, Medicaid insurance status, satisfaction with RA disease control, and trust in physician, with standardized beta = 0.077, -0.089, 0.147, and 0.687, respectively. In this sample of community patients with RA, the patient trust in physician had substantially greater effect on confidence in DMARD decision than DMARD-specific knowledge, disease-related factors, or demographic characteristics.

Immunopathological Patterns from EAE and Theiler’s Virus Infection: Is Multiple Sclerosis a Homogenous 1-stage or Heterogenous 2-stage Disease?

PubMed Central

Martinez, Nicholas E.; Sato, Fumitaka; Omura, Seiichi; Minagar, Alireza; Alexander, J. Steven; Tsunoda, Ikuo

2012-01-01

Multiple sclerosis (MS) is a disease which can present in different clinical courses. The most common form of MS is the relapsing-remitting (RR) course, which in many cases evolves into secondary progressive (SP) disease. Autoimmune models such as experimental autoimmune encephalomyelitis (EAE) have been developed to represent the various clinical forms of MS. These models along with clinico-pathological evidence obtained from MS patients have allowed us to propose ‘1-stage’ and ‘2-stage’ disease theories to explain the transition in the clinical course of MS from RR to SP. Relapses in MS are associated with pro-inflammatory T helper (Th) 1/Th17 immune responses, while remissions are associated with anti-inflammatory Th2/regulatory T (Treg) immune responses. Based on the ‘1-stage disease’ theory, the transition from RR to SP disease occurs when the inflammatory immune response overwhelms the anti-inflammatory immune response. The ‘2-stage disease’ theory proposes that the transition from RR to SP-MS occurs when the Th2 response or some other responses overwhelm the inflammatory response resulting in the sustained production of anti-myelin antibodies, which cause continuing demyelination, neurodegeneration, and axonal loss. The Theiler’s virus model is also a 2-stage disease, where axonal degeneration precedes demyelination during the first stage, followed by inflammatory demyelination during the second stage. PMID:22633747

Women Confronting the Reality of Multiple Sclerosis: A Qualitative Model of Self-Healing

ERIC Educational Resources Information Center

Romagosa, Carol J.

2010-01-01

Multiple sclerosis (MS) is a chronic debilitating disease that has an uncertain course. Although uncertainty is a universal experience in chronic illness, uncertainty in MS is especially threatening to psychological well-being. Chronic illness, including conditions of disability, is one of our greatest health care problems as society ages. Never…

Advances and Challenges in Genomic Selection for Disease Resistance.

PubMed

Poland, Jesse; Rutkoski, Jessica

2016-08-04

Breeding for disease resistance is a central focus of plant breeding programs, as any successful variety must have the complete package of high yield, disease resistance, agronomic performance, and end-use quality. With the need to accelerate the development of improved varieties, genomics-assisted breeding is becoming an important tool in breeding programs. With marker-assisted selection, there has been success in breeding for disease resistance; however, much of this work and research has focused on identifying, mapping, and selecting for major resistance genes that tend to be highly effective but vulnerable to breakdown with rapid changes in pathogen races. In contrast, breeding for minor-gene quantitative resistance tends to produce more durable varieties but is a more challenging breeding objective. As the genetic architecture of resistance shifts from single major R genes to a diffused architecture of many minor genes, the best approach for molecular breeding will shift from marker-assisted selection to genomic selection. Genomics-assisted breeding for quantitative resistance will therefore necessitate whole-genome prediction models and selection methodology as implemented for classical complex traits such as yield. Here, we examine multiple case studies testing whole-genome prediction models and genomic selection for disease resistance. In general, whole-genome models for disease resistance can produce prediction accuracy suitable for application in breeding. These models also largely outperform multiple linear regression as would be applied in marker-assisted selection. With the implementation of genomic selection for yield and other agronomic traits, whole-genome marker profiles will be available for the entire set of breeding lines, enabling genomic selection for disease at no additional direct cost. In this context, the scope of implementing genomics selection for disease resistance, and specifically for quantitative resistance and quarantined pathogens, becomes a tractable and powerful approach in breeding programs.

The mechanisms of sirtuin 2-mediated exacerbation of alpha-synuclein toxicity in models of Parkinson disease

USDA-ARS?s Scientific Manuscript database

Sirtuin genes have been associated with aging and are known to affect multiple cellular pathways. Sirtuin 2 was previously shown to modulate proteotoxicity associated with age-associated neurodegenerative disorders such as Alzheimer and Parkinson disease (PD). However, the precise molecular mechanis...

Dietary glutamate reduces systemic but not intestinal leucine oxidation in protein malnourished piglets

USDA-ARS?s Scientific Manuscript database

The methionine (Met) metabolic cycle is critical for normal cell functions. Met cycle disruption has been implicated in disease, such as alcoholic liver disease (ALD) and multiple sclerosis (MS). Studies in animal models of ALD and MS have shown that the Met metabolite methylthioadenosine (MTA) has ...

Epidemiology and population biology of pseudoperonospora cubensis: a model system for management of downy mildews

USDA-ARS?s Scientific Manuscript database

The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of disease outbreaks. Dispersal potential of th...

Rat Models of Cardiovascular Disease Demonstrate Distinctive Pulmonary Gene Expressions for Vascular Response Genes: Impact of Ozone Exposure

EPA Science Inventory

Comparative gene expression profiling of multiple tissues from rat strains with genetic predisposition to diverse cardiovascular diseases (CVD) can help decode the transcriptional program that governs organ-specific functions. We examined expressions of CVD genes in the lungs of ...

Modulation of Multiple Sclerosis and Its Animal Model Experimental Autoimmune Encephalomyelitis by Food and Gut Microbiota

PubMed Central

van den Hoogen, Ward J.; Laman, Jon D.; ’t Hart, Bert A.

2017-01-01

Multiple sclerosis (MS) is an autoimmune neurological disease characterized by chronic inflammation of the central nervous system (CNS), leading to demyelination, axonal damage, and symptoms such as fatigue and disability. Although the cause of MS is not known, the infiltration of peripherally activated immune cells into the CNS has a key pathogenic role. Accumulating evidence supports an important role of diet and gut microbiota in immune-mediated diseases. Preclinical as well as clinical studies suggest a role for gut microbiota and dietary components in MS. Here, we review these recent studies on gut microbiota and dietary interventions in MS and its animal model experimental autoimmune encephalomyelitis. We also propose directions for future research. PMID:28928747

Relationship between urban sprawl and physical activity, obesity, and morbidity - update and refinement.

PubMed

Ewing, Reid; Meakins, Gail; Hamidi, Shima; Nelson, Arthur C

2014-03-01

This study aims to model multiple health outcomes and behaviors in terms of the updated, refined, and validated county compactness/sprawl measures. Multiple health outcomes and behaviors are modeled using multi-level analysis. After controlling for observed confounding influences, both original and new compactness measures are negatively related to BMI, obesity, heart disease, high blood pressure, and diabetes. Indices are not significantly related to physical activity, perhaps because physical activity is not defined broadly to include active travel to work, shopping, and other destinations. Developing urban and suburban areas in a more compact manner may have some salutary effect on obesity and chronic disease trends. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

DOE PAGES

Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas; ...

2016-11-14

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection andmore » Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.« less

Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection andmore » Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.« less

Plasma amino acid profile associated with fatty liver disease and co-occurrence of metabolic risk factors.

PubMed

Yamakado, Minoru; Tanaka, Takayuki; Nagao, Kenji; Imaizumi, Akira; Komatsu, Michiharu; Daimon, Takashi; Miyano, Hiroshi; Tani, Mizuki; Toda, Akiko; Yamamoto, Hiroshi; Horimoto, Katsuhisa; Ishizaka, Yuko

2017-11-03

Fatty liver disease (FLD) increases the risk of diabetes, cardiovascular disease, and steatohepatitis, which leads to fibrosis, cirrhosis, and hepatocellular carcinoma. Thus, the early detection of FLD is necessary. We aimed to find a quantitative and feasible model for discriminating the FLD, based on plasma free amino acid (PFAA) profiles. We constructed models of the relationship between PFAA levels in 2,000 generally healthy Japanese subjects and the diagnosis of FLD by abdominal ultrasound scan by multiple logistic regression analysis with variable selection. The performance of these models for FLD discrimination was validated using an independent data set of 2,160 subjects. The generated PFAA-based model was able to identify FLD patients. The area under the receiver operating characteristic curve for the model was 0.83, which was higher than those of other existing liver function-associated markers ranging from 0.53 to 0.80. The value of the linear discriminant in the model yielded the adjusted odds ratio (with 95% confidence intervals) for a 1 standard deviation increase of 2.63 (2.14-3.25) in the multiple logistic regression analysis with known liver function-associated covariates. Interestingly, the linear discriminant values were significantly associated with the progression of FLD, and patients with nonalcoholic steatohepatitis also exhibited higher values.

Epidemic Forecasting is Messier Than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast

PubMed Central

Moran, Kelly R.; Fairchild, Geoffrey; Generous, Nicholas; Hickmann, Kyle; Osthus, Dave; Priedhorsky, Reid; Hyman, James; Del Valle, Sara Y.

2016-01-01

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection and Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. We conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting. PMID:28830111

Data-driven model for the assessment of Mycobacterium tuberculosis transmission in evolving demographic structures

PubMed Central

Arregui, Sergio; Marinova, Dessislava; Sanz, Joaquín

2018-01-01

In the case of tuberculosis (TB), the capabilities of epidemic models to produce quantitatively robust forecasts are limited by multiple hindrances. Among these, understanding the complex relationship between disease epidemiology and populations’ age structure has been highlighted as one of the most relevant. TB dynamics depends on age in multiple ways, some of which are traditionally simplified in the literature. That is the case of the heterogeneities in contact intensity among different age strata that are common to all airborne diseases, but still typically neglected in the TB case. Furthermore, while demographic structures of many countries are rapidly aging, demographic dynamics are pervasively ignored when modeling TB spreading. In this work, we present a TB transmission model that incorporates country-specific demographic prospects and empirical contact data around a data-driven description of TB dynamics. Using our model, we find that the inclusion of demographic dynamics is followed by an increase in the burden levels predicted for the next decades in the areas of the world that are most hit by the disease today. Similarly, we show that considering realistic patterns of contacts among individuals in different age strata reshapes the transmission patterns reproduced by the models, a result with potential implications for the design of age-focused epidemiological interventions. PMID:29563223

The Existence and Stability Analysis of the Equilibria in Dengue Disease Infection Model

NASA Astrophysics Data System (ADS)

Anggriani, N.; Supriatna, A. K.; Soewono, E.

2015-06-01

In this paper we formulate an SIR (Susceptible - Infective - Recovered) model of Dengue fever transmission with constant recruitment. We found a threshold parameter K0, known as the Basic Reproduction Number (BRN). This model has two equilibria, disease-free equilibrium and endemic equilibrium. By constructing suitable Lyapunov function, we show that the disease- free equilibrium is globally asymptotic stable whenever BRN is less than one and when it is greater than one, the endemic equilibrium is globally asymptotic stable. Numerical result shows the dynamic of each compartment together with effect of multiple bio-agent intervention as a control to the dengue transmission.

Phenotype–genotype correlation in Hirschsprung disease is illuminated by comparative analysis of the RET protein sequence

PubMed Central

Kashuk, Carl S.; Stone, Eric A.; Grice, Elizabeth A.; Portnoy, Matthew E.; Green, Eric D.; Sidow, Arend; Chakravarti, Aravinda; McCallion, Andrew S.

2005-01-01

The ability to discriminate between deleterious and neutral amino acid substitutions in the genes of patients remains a significant challenge in human genetics. The increasing availability of genomic sequence data from multiple vertebrate species allows inclusion of sequence conservation and physicochemical properties of residues to be used for functional prediction. In this study, the RET receptor tyrosine kinase serves as a model disease gene in which a broad spectrum (≥116) of disease-associated mutations has been identified among patients with Hirschsprung disease and multiple endocrine neoplasia type 2. We report the alignment of the human RET protein sequence with the orthologous sequences of 12 non-human vertebrates (eight mammalian, one avian, and three teleost species), their comparative analysis, the evolutionary topology of the RET protein, and predicted tolerance for all published missense mutations. We show that, although evolutionary conservation alone provides significant information to predict the effect of a RET mutation, a model that combines comparative sequence data with analysis of physiochemical properties in a quantitative framework provides far greater accuracy. Although the ability to discern the impact of a mutation is imperfect, our analyses permit substantial discrimination between predicted functional classes of RET mutations and disease severity even for a multigenic disease such as Hirschsprung disease. PMID:15956201

Mouse models rarely mimic the transcriptome of human neurodegenerative diseases: A systematic bioinformatics-based critique of preclinical models.

PubMed

Burns, Terry C; Li, Matthew D; Mehta, Swapnil; Awad, Ahmed J; Morgan, Alexander A

2015-07-15

Translational research for neurodegenerative disease depends intimately upon animal models. Unfortunately, promising therapies developed using mouse models mostly fail in clinical trials, highlighting uncertainty about how well mouse models mimic human neurodegenerative disease at the molecular level. We compared the transcriptional signature of neurodegeneration in mouse models of Alzheimer׳s disease (AD), Parkinson׳s disease (PD), Huntington׳s disease (HD) and amyotrophic lateral sclerosis (ALS) to human disease. In contrast to aging, which demonstrated a conserved transcriptome between humans and mice, only 3 of 19 animal models showed significant enrichment for gene sets comprising the most dysregulated up- and down-regulated human genes. Spearman׳s correlation analysis revealed even healthy human aging to be more closely related to human neurodegeneration than any mouse model of AD, PD, ALS or HD. Remarkably, mouse models frequently upregulated stress response genes that were consistently downregulated in human diseases. Among potential alternate models of neurodegeneration, mouse prion disease outperformed all other disease-specific models. Even among the best available animal models, conserved differences between mouse and human transcriptomes were found across multiple animal model versus human disease comparisons, surprisingly, even including aging. Relative to mouse models, mouse disease signatures demonstrated consistent trends toward preserved mitochondrial function protein catabolism, DNA repair responses, and chromatin maintenance. These findings suggest a more complex and multifactorial pathophysiology in human neurodegeneration than is captured through standard animal models, and suggest that even among conserved physiological processes such as aging, mice are less prone to exhibit neurodegeneration-like changes. This work may help explain the poor track record of mouse-based translational therapies for neurodegeneration and provides a path forward to critically evaluate and improve animal models of human disease. Copyright © 2015 Elsevier B.V. All rights reserved.

Amelioration of ongoing experimental autoimmune encephalomyelitis with fluoxetine.

PubMed

Bhat, Roopa; Mahapatra, Sidharth; Axtell, Robert C; Steinman, Lawrence

2017-12-15

In patients with multiple sclerosis, the selective serotonin reuptake inhibitor, fluoxetine, resulted in less acute disease activity. We tested the immune modulating effects of fluoxetine in a mouse model of multiple sclerosis, i.e. experimental autoimmune encephalomyelitis (EAE). We show that fluoxetine delayed the onset of disease and reduced clinical paralysis in mice with established disease. Fluoxetine had abrogating effects on proliferation of immune cells and inflammatory cytokine production by both antigen-presenting cells and T cells. Specifically, in CD 4 T cells, fluoxetine increased Fas-induced apoptosis. We conclude that fluoxetine possesses immune-modulating effects resulting in the amelioration of symptoms in EAE. Copyright © 2017 Elsevier B.V. All rights reserved.

A Reaction-Diffusion Model of Vector-Borne Disease with Periodic Delays

NASA Astrophysics Data System (ADS)

Wu, Ruiwen; Zhao, Xiao-Qiang

2018-06-01

A vector-borne disease is caused by a range of pathogens and transmitted to hosts through vectors. To investigate the multiple effects of the spatial heterogeneity, the temperature sensitivity of extrinsic incubation period and intrinsic incubation period, and the seasonality on disease transmission, we propose a nonlocal reaction-diffusion model of vector-borne disease with periodic delays. We introduce the basic reproduction number R_0 for this model and then establish a threshold-type result on its global dynamics in terms of R_0 . In the case where all the coefficients are constants, we also prove the global attractivity of the positive constant steady state when R_0>1 . Numerically, we study the malaria transmission in Maputo Province, Mozambique.

A Tol2 Gateway-Compatible Toolbox for the Study of the Nervous System and Neurodegenerative Disease.

PubMed

Don, Emily K; Formella, Isabel; Badrock, Andrew P; Hall, Thomas E; Morsch, Marco; Hortle, Elinor; Hogan, Alison; Chow, Sharron; Gwee, Serene S L; Stoddart, Jack J; Nicholson, Garth; Chung, Roger; Cole, Nicholas J

2017-02-01

Currently there is a lack in fundamental understanding of disease progression of most neurodegenerative diseases, and, therefore, treatments and preventative measures are limited. Consequently, there is a great need for adaptable, yet robust model systems to both investigate elementary disease mechanisms and discover effective therapeutics. We have generated a Tol2 Gateway-compatible toolbox to study neurodegenerative disorders in zebrafish, which includes promoters for astrocytes, microglia and motor neurons, multiple fluorophores, and compatibility for the introduction of genes of interest or disease-linked genes. This toolbox will advance the rapid and flexible generation of zebrafish models to discover the biology of the nervous system and the disease processes that lead to neurodegeneration.

Upper Extremity Function in Multiple Sclerosis Patients With Advanced Disability Treated With Ocrevus

ClinicalTrials.gov

2018-06-18

Multiple Sclerosis; Pathologic Processes; Demyelinating Diseases; Demyelinating Autoimmune Diseases; Nervous System Diseases; Autoimmune Diseases; Immune System Diseases; Primary Progressive Multiple Sclerosis; Relapsing Remitting Multiple Sclerosis

A longitudinal model for disease progression was developed and applied to multiple sclerosis

PubMed Central

Lawton, Michael; Tilling, Kate; Robertson, Neil; Tremlett, Helen; Zhu, Feng; Harding, Katharine; Oger, Joel; Ben-Shlomo, Yoav

2015-01-01

Objectives To develop a model of disease progression using multiple sclerosis (MS) as an exemplar. Study Design and Settings Two observational cohorts, the University of Wales MS (UoWMS), UK (1976), and British Columbia MS (BCMS) database, Canada (1980), with longitudinal disability data [the Expanded Disability Status Scale (EDSS)] were used; individuals potentially eligible for MS disease-modifying drugs treatments, but who were unexposed, were selected. Multilevel modeling was used to estimate the EDSS trajectory over time in one data set and validated in the other; challenges addressed included the choice and function of time axis, complex observation-level variation, adjustments for MS relapses, and autocorrelation. Results The best-fitting model for the UoWMS cohort (404 individuals, and 2,290 EDSS observations) included a nonlinear function of time since onset. Measurement error decreased over time and ad hoc methods reduced autocorrelation and the effect of relapse. Replication within the BCMS cohort (978 individuals and 7,335 EDSS observations) led to a model with similar time (years) coefficients, time [0.22 (95% confidence interval {CI}: 0.19, 0.26), 0.16 (95% CI: 0.10, 0.22)] and log time [−0.13 (95% CI: −0.39, 0.14), −0.15 (95% CI: −0.70, 0.40)] for BCMS and UoWMS, respectively. Conclusion It is possible to develop robust models of disability progression for chronic disease. However, explicit validation is important given the complex methodological challenges faced. PMID:26071892

Epidemic Forecasting is Messier Than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast.

PubMed

Moran, Kelly R; Fairchild, Geoffrey; Generous, Nicholas; Hickmann, Kyle; Osthus, Dave; Priedhorsky, Reid; Hyman, James; Del Valle, Sara Y

2016-12-01

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection and Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. We conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting. 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.

Medicare capitation model, functional status, and multiple comorbidities: model accuracy

PubMed Central

Noyes, Katia; Liu, Hangsheng; Temkin-Greener, Helena

2012-01-01

Objective This study examined financial implications of CMS-Hierarchical Condition Categories (HCC) risk-adjustment model on Medicare payments for individuals with comorbid chronic conditions. Study Design The study used 1992-2000 data from the Medicare Current Beneficiary Survey and corresponding Medicare claims. The pairs of comorbidities were formed based on the prior evidence about possible synergy between these conditions and activities of daily living (ADL) deficiencies and included heart disease and cancer, lung disease and cancer, stroke and hypertension, stroke and arthritis, congestive heart failure (CHF) and osteoporosis, diabetes and coronary artery disease, CHF and dementia. Methods For each beneficiary, we calculated the actual Medicare cost ratio as the ratio of the individual’s annualized costs to the mean annual Medicare cost of all people in the study. The actual Medicare cost ratios, by ADLs, were compared to the HCC ratios under the CMS-HCC payment model. Using multivariate regression models, we tested whether having the identified pairs of comorbidities affects the accuracy of CMS-HCC model predictions. Results The CMS-HCC model underpredicted Medicare capitation payments for patients with hypertension, lung disease, congestive heart failure and dementia. The difference between the actual costs and predicted payments was partially explained by beneficiary functional status and less than optimal adjustment for these chronic conditions. Conclusions Information about beneficiary functional status should be incorporated in reimbursement models since underpaying providers for caring for population with multiple comorbidities may provide severe disincentives for managed care plans to enroll such individuals and to appropriately manage their complex and costly conditions. PMID:18837646

Stargardt disease: clinical features, molecular genetics, animal models and therapeutic options

PubMed Central

Tanna, Preena; Strauss, Rupert W; Fujinami, Kaoru; Michaelides, Michel

2017-01-01

Stargardt disease (STGD1; MIM 248200) is the most prevalent inherited macular dystrophy and is associated with disease-causing sequence variants in the gene ABCA4. Significant advances have been made over the last 10 years in our understanding of both the clinical and molecular features of STGD1, and also the underlying pathophysiology, which has culminated in ongoing and planned human clinical trials of novel therapies. The aims of this review are to describe the detailed phenotypic and genotypic characteristics of the disease, conventional and novel imaging findings, current knowledge of animal models and pathogenesis, and the multiple avenues of intervention being explored. PMID:27491360

An application of Mean Escape Time and metapopulation on forestry catastrophe insurance

NASA Astrophysics Data System (ADS)

Li, Jiangcheng; Zhang, Chunmin; Liu, Jifa; Li, Zhen; Yang, Xuan

2018-04-01

A forestry catastrophe insurance model due to forestry pest infestations and disease epidemics is developed by employing metapopulation dynamics and statistics properties of Mean Escape Time (MET). The probability of outbreak of forestry catastrophe loss and the catastrophe loss payment time with MET are respectively investigated. Forestry loss data in China is used for model simulation. Experimental results are concluded as: (1) The model with analytical results is shown to be a better fit; (2) Within the condition of big area of patches and structure of patches, high system factor, low extinction rate, high multiplicative noises, and additive noises with a high cross-correlated strength range, an outbreak of forestry catastrophe loss or catastrophe loss payment due to forestry pest infestations and disease epidemics could occur; (3) An optimal catastrophe loss payment time MET due to forestry pest infestations and disease epidemics can be identified by taking proper value of multiplicative noises and limits the additive noises on a low range of value, and cross-correlated strength at a high range of value.

Specificity, cross-talk and adaptation in Interferon signaling

NASA Astrophysics Data System (ADS)

Zilman, Anton

Innate immune system is the first line of defense of higher organisms against pathogens. It coordinates the behavior of millions of cells of multiple types, achieved through numerous signaling molecules. This talk focuses on the signaling specificity of a major class of signaling molecules - Type I Interferons - which are also used therapeutically in the treatment of a number of diseases, such as Hepatitis C, multiple sclerosis and some cancers. Puzzlingly, different Interferons act through the same cell surface receptor but have different effects on the target cells. They also exhibit a strange pattern of temporal cross-talk resulting in a serious clinical problem - loss of response to Interferon therapy. We combined mathematical modeling with quantitative experiments to develop a quantitative model of specificity and adaptation in the Interferon signaling pathway. The model resolves several outstanding experimental puzzles and directly affects the clinical use of Type I Interferons in treatment of viral hepatitis and other diseases.

Inducible and reversible phenotypes in a novel mouse model of Friedreich’s Ataxia

PubMed Central

Gao, Kun; Swarup, Vivek; Versano, Revital; Dong, Hongmei; Jordan, Maria C

2017-01-01

Friedreich's ataxia (FRDA), the most common inherited ataxia, is caused by recessive mutations that reduce the levels of frataxin (FXN), a mitochondrial iron binding protein. We developed an inducible mouse model of Fxn deficiency that enabled us to control the onset and progression of disease phenotypes by the modulation of Fxn levels. Systemic knockdown of Fxn in adult mice led to multiple phenotypes paralleling those observed in human patients across multiple organ systems. By reversing knockdown after clinical features appear, we were able to determine to what extent observed phenotypes represent reversible cellular dysfunction. Remarkably, upon restoration of near wild-type FXN levels, we observed significant recovery of function, associated pathology and transcriptomic dysregulation even after substantial motor dysfunction and pathology were observed. This model will be of broad utility in therapeutic development and in refining our understanding of the relative contribution of reversible cellular dysfunction at different stages in disease. PMID:29257745

Predictors of Employment Status for People with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Rumrill, Phillip D.; Fitzgerald, Shawn M.

2004-01-01

This study examined the relevance of the disease-and-demographics model for explaining the employment outcomes of adults with multiple sclerosis (MS). Participating in a national survey of their employment concerns, 1,310 adults with MS provided data for the study (274 men, 21%; 1,020 women, 78%; 16 participants did not identify their gender).…

Potential use of multiple surveillance data in the forecast of hospital admissions

PubMed Central

Lau, Eric H.Y.; Ip, Dennis K.M.; Cowling, Benjamin J.

2013-01-01

Objective This paper describes the potential use of multiple influenza surveillance data to forecast hospital admissions for respiratory diseases. Introduction A sudden surge in hospital admissions in public hospital during influenza peak season has been a challenge to healthcare and manpower planning. In Hong Kong, the timing of influenza peak seasons are variable and early short-term indication of possible surge may facilitate preparedness which could be translated into strategies such as early discharge or reallocation of extra hospital beds. In this study we explore the potential use of multiple routinely collected syndromic data in the forecast of hospital admissions. Methods A multivariate dynamic linear time series model was fitted to multiple syndromic data including influenza-like illness (ILI) rates among networks of public and private general practitioners (GP), and school absenteeism rates, plus drop-in fever count data from designated flu clinics (DFC) that were created during the pandemic. The latent process derived from the model has been used as a measure of the influenza activity [1]. We compare the cross-correlations between estimated influenza level based on multiple surveillance data and GP ILI data, versus accident and emergency hospital admissions with principal diagnoses of respiratory diseases and pneumonia & influenza (P&I). Results The estimated influenza activity has higher cross-correlation with respiratory and P&I admissions (ρ=0.66 and 0.73 respectively) compared to that of GP ILI rates (Table 1). Cross correlations drop distinctly after lag 2 for both estimated influenza activity and GP ILI rates. Conclusions The use of a multivariate method to integrate information from multiple sources of influenza surveillance data may have the potential to improve forecasting of admission surge of respiratory diseases.

The Bordetella bronchiseptica type III secretion system is required for persistence and disease severity but not transmission in swine

USDA-ARS?s Scientific Manuscript database

Bordetella bronchiseptica is pervasive in swine populations and plays multiple roles in respiratory disease. Most studies addressing virulence factors of B. bronchiseptica utilize isolates derived from hosts other than pigs in conjunction with rodent infection models. Based on previous in vivo mouse...

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

Intestinal microbiota in primary sclerosing cholangitis.

PubMed

Hov, Johannes R; Kummen, Martin

2017-03-01

Alterations of the gut-liver axis have been linked to the pathogenesis of primary sclerosing cholangitis (PSC) since the disease was first described. The purpose of this review is to discuss multiple recent studies on the intestinal microbiota in human PSC and experimental models of this disease. Data are available from eight cross-sectional studies of human PSC, which include a variable number of patients (n = 11-85), material (mucosal or fecal), and microbiota profiling methodology. Despite the heterogeneity of the studies, a pattern of differences is observed that could represent a theme or signature of the PSC gut microbiota, characterized by low diversity and with alterations in multiple bacterial taxa. In experimental models of PSC, re-derivation of animals into germ-free facilities may either aggravate or attenuate the disease, depending on host genetics and putative disease mechanisms (e.g., fibrotic or immune-driven processes, respectively). The present data provide a strong rationale to explore the functional consequences of the observed gut microbial alterations and their influence on the pathogenesis in PSC. Studies of gut microbiota as biomarker and treatment target may potentially also lead to early translation into clinical practice.

Omics analysis of mouse brain models of human diseases.

PubMed

Paban, Véronique; Loriod, Béatrice; Villard, Claude; Buee, Luc; Blum, David; Pietropaolo, Susanna; Cho, Yoon H; Gory-Faure, Sylvie; Mansour, Elodie; Gharbi, Ali; Alescio-Lautier, Béatrice

2017-02-05

The identification of common gene/protein profiles related to brain alterations, if they exist, may indicate the convergence of the pathogenic mechanisms driving brain disorders. Six genetically engineered mouse lines modelling neurodegenerative diseases and neuropsychiatric disorders were considered. Omics approaches, including transcriptomic and proteomic methods, were used. The gene/protein lists were used for inter-disease comparisons and further functional and network investigations. When the inter-disease comparison was performed using the gene symbol identifiers, the number of genes/proteins involved in multiple diseases decreased rapidly. Thus, no genes/proteins were shared by all 6 mouse models. Only one gene/protein (Gfap) was shared among 4 disorders, providing strong evidence that a common molecular signature does not exist among brain diseases. The inter-disease comparison of functional processes showed the involvement of a few major biological processes indicating that brain diseases of diverse aetiologies might utilize common biological pathways in the nervous system, without necessarily involving similar molecules. Copyright © 2016 Elsevier B.V. All rights reserved.

Fetal Substance Exposure and Cumulative Environmental Risk in an African American Cohort

ERIC Educational Resources Information Center

Yumoto, Chie; Jacobson, Sandra W.; Jacobson, Joseph L.

2008-01-01

Two models of vulnerability to socioenvironmental risk were examined in 337 African American children (M = 7.8 years) recruited to overrepresent prenatal alcohol or cocaine exposure: The cumulative risk model predicted synergistic effects from exposure to multiple risk factors, and the fetal patterning of disease model predicted that prenatal…

Agent Orange exposure and prevalence of self-reported diseases in Korean Vietnam veterans.

PubMed

Yi, Sang-Wook; Ohrr, Heechoul; Hong, Jae-Seok; Yi, Jee-Jeon

2013-09-01

The aim of this study was to evaluate the association between Agent Orange exposure and self-reported diseases in Korean Vietnam veterans. A postal survey of 114 562 Vietnam veterans was conducted. The perceived exposure to Agent Orange was assessed by a 6-item questionnaire. Two proximity-based Agent Orange exposure indices were constructed using division/brigade-level and battalion/company-level unit information. Adjusted odds ratios (ORs) for age and other confounders were calculated using a logistic regression model. The prevalence of all self-reported diseases showed monotonically increasing trends as the levels of perceived self-reported exposure increased. The ORs for colon cancer (OR, 1.13), leukemia (OR, 1.56), hypertension (OR, 1.03), peripheral vasculopathy (OR, 1.07), enterocolitis (OR, 1.07), peripheral neuropathy (OR, 1.07), multiple nerve palsy (OR, 1.14), multiple sclerosis (OR, 1.24), skin diseases (OR, 1.05), psychotic diseases (OR, 1.07) and lipidemia (OR, 1.05) were significantly elevated for the high exposure group in the division/brigade-level proximity-based exposure analysis, compared to the low exposure group. The ORs for cerebral infarction (OR, 1.08), chronic bronchitis (OR, 1.05), multiple nerve palsy (OR, 1.07), multiple sclerosis (OR, 1.16), skin diseases (OR, 1.05), and lipidemia (OR, 1.05) were significantly elevated for the high exposure group in the battalion/company-level analysis. Korean Vietnam veterans with high exposure to Agent Orange experienced a higher prevalence of several self-reported chronic diseases compared to those with low exposure by proximity-based exposure assessment. The strong positive associations between perceived self-reported exposure and all self-reported diseases should be evaluated with discretion because the likelihood of reporting diseases was directly related to the perceived intensity of Agent Orange exposure.

A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission

PubMed Central

Parker, Jon; Epstein, Joshua M.

2013-01-01

The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability. PMID:24465120

Reducing Disease Activity in Animal Models of MS by Activation of the Protective Arm of the Renin-Angiotensin System

DTIC Science & Technology

2015-10-01

patients, there is little evidence for a role of ACE2/A( 1 -7)/Mas axis, only a solitary assessment showing decreased ACE2 levels in the CSF of MS...project? Major Goals (Year 1 ): 1 : Measure levels of RAS components in the spinal cord of mice with EAE (animal model of MS) prior to, and at multiple...AWARD NUMBER: W81XWH-14- 1 -0523 TITLE: Reducing Disease Activity in Animal Models of MS by Activation of the Protective Arm of the Renin

Fruitful research: drug target discovery for neurodegenerative diseases in Drosophila.

PubMed

Konsolaki, Mary

2013-12-01

Although vertebrate model systems have obvious advantages in the study of human disease, invertebrate organisms have contributed enormously to this field as well. The conservation of genome structure and physiology among organisms poses unexpected peculiarities, and the redundancy in certain gene families or the presence of polymorphisms that can slightly alter gene expression can, in certain instances, bring invertebrate systems, such as Drosophila, closer to humans than mice and vice versa. This necessitates the analysis of disease pathways in multiple model organisms. The author highlights findings from Drosophila models of neurodegenerative diseases that have occurred in the past few years. She also highlights and discusses various molecular, genetic and genomic tools used in flies, as well as methods for generating disease models. Finally, the author describes Drosophila models of Alzheimer's, Parkinson's tri-nucleotide repeat diseases, and Fragile X syndrome and summarizes insights in disease mechanisms that have been discovered directly in fly models. Full genome genetic screens in Drosophila can lead to the rapid identification of drug target candidates that can be subsequently validated in a vertebrate system. In addition, the Drosophila models of neurodegeneration may often show disease phenotypes that are absent in equivalent mouse models. The author believes that the extensive contribution of Drosophila to both new disease drug target discovery, in addition to target validation, makes them indispensible to drug discovery and development.

Variations in diet cause alterations in microbiota and metabolites that follow changes in disease severity in a multiple sclerosis model.

PubMed

Libbey, J E; Sanchez, J M; Doty, D J; Sim, J T; Cusick, M F; Cox, J E; Fischer, K F; Round, J L; Fujinami, R S

2018-04-25

Multiple sclerosis (MS) is a metabolically demanding disease involving immune-mediated destruction of myelin in the central nervous system. We previously demonstrated a significant alteration in disease course in the experimental autoimmune encephalomyelitis (EAE) preclinical model of MS due to diet. Based on the established crosstalk between metabolism and gut microbiota, we took an unbiased sampling of microbiota, in the stool, and metabolites, in the serum and stool, from mice (Mus musculus) on the two different diets, the Teklad global soy protein-free extruded rodent diet (irradiated diet) and the Teklad sterilisable rodent diet (autoclaved diet). Within the microbiota, the genus Lactobacillus was found to be inversely correlated with EAE severity. Therapeutic treatment with Lactobacillus paracasei resulted in a significant reduction in the incidence of disease, clinical scores and the amount of weight loss in EAE mice. Within the metabolites, we identified shifts in glycolysis and the tricarboxylic acid cycle that may explain the differences in disease severity between the different diets in EAE. This work begins to elucidate the relationship between diet, microbiota and metabolism in the EAE preclinical model of MS and identifies targets for further study with the goal to more specifically probe the complex metabolic interaction at play in EAE that may have translational relevance to MS patients.

Combining Early Coagulation and Inflammatory Status Improves Prediction of Mortality in Burned and Nonburned Trauma Patients

DTIC Science & Technology

2008-02-01

clinician to distinguish between the effects of treatment and the effects of disease. Several different prediction models for multiple or- gan failure...treat- ment protocols and allow a clinician to distinguish the effect of treatment from effect of disease. In this study, our model predicted in...TNF produces a decrease in protein C activation by down regulating the expression of endothelial cell protein C receptor and thrombomodulin, both of

Homozygous parent affected sib pair method for detecting disease predisposing variants: application to insulin dependent diabetes mellitus.

PubMed

Robinson, W P; Barbosa, J; Rich, S S; Thomson, G

1993-01-01

For complex genetic diseases involving incomplete penetrance, genetic heterogeneity, and multiple disease genes, it is often difficult to determine the molecular variant(s) responsible for the disease pathogenesis. Linkage and association studies may help identify genetic regions and molecular variants suspected of being directly responsible for disease predisposition or protection, but, especially for complex diseases, they are less useful for determining when a predisposing molecular variant has been identified. In this paper, we expand upon the simple concept that if a genetic factor predisposing to disease has been fully identified, then a parent homozygous for this factor should transmit either of his/her copies at random to any affected children. Closely linked markers are used to determine identity by descent values in affected sib pairs from a parent homozygous for a putative disease predisposing factor. The expected deviation of haplotype sharing from 50%, when not all haplotypes carrying this factor are in fact equally predisposing, has been algebraically determined for a single locus general disease model. Equations to determine expected sharing for multiple disease alleles or multiple disease locus models have been formulated. The recessive case is in practice limiting and therefore can be used to estimate the maximum proportion of putative susceptibility haplotypes which are in fact predisposing to disease when the mode of inheritance of a disease is unknown. This method has been applied to 27 DR3/DR3 parents and 50 DR4/DR4 parents who have at least 2 children affected with insulin dependent diabetes mellitus (IDDM). The transmission of both DR3 and DR4 haplotypes is statistically different from 50% (P < 0.05 and P < 0.001, respectively). An upper estimate for the proportion of DR3 haplotypes associated with a high IDDM susceptibility is 49%, and for DR4 haplotypes 38%. Our results show that the joint presence of non-Asp at DQ beta position 57 and Arg at DQ alpha position 52, which has been proposed as a strong IDDM predisposing factor, is insufficient to explain the HLA component of IDDM predisposition.

Animal models of Parkinson's disease: limits and relevance to neuroprotection studies.

PubMed

Bezard, Erwan; Yue, Zhenyu; Kirik, Deniz; Spillantini, Maria Grazia

2013-01-01

Over the last two decades, significant strides has been made toward acquiring a better knowledge of both the etiology and pathogenesis of Parkinson's disease (PD). Experimental models are of paramount importance to obtain greater insights into the pathogenesis of the disease. Thus far, neurotoxin-based animal models have been the most popular tools employed to produce selective neuronal death in both in vitro and in vivo systems. These models have been commonly referred to as the pathogenic models. The current trend in modeling PD revolves around what can be called the disease gene-based models or etiologic models. The value of utilizing multiple models with a different mechanism of insult rests on the premise that dopamine-producing neurons die by stereotyped cascades that can be activated by a range of insults, from neurotoxins to downregulation and overexpression of disease-related genes. In this position article, we present the relevance of both pathogenic and etiologic models as well as the concept of clinically relevant designs that, we argue, should be utilized in the preclinical development phase of new neuroprotective therapies before embarking into clinical trials. Copyright © 2013 Movement Disorders Society.

Mathematical analysis of a multiple strain, multi-locus-allele system for antigenically variable infectious diseases revisited.

PubMed

Cherif, Alhaji

2015-09-01

Many important pathogens such as HIV/AIDS, influenza, malaria, dengue and meningitis generally exist in phenotypically distinct serotypes that compete for hosts. Models used to study these diseases appear as meta-population systems. Herein, we revisit one of the multiple strain models that have been used to investigate the dynamics of infectious diseases with co-circulating serotypes or strains, and provide analytical results underlying the numerical investigations. In particular, we establish the necessary conditions for the local asymptotic stability of the steady states and for the existence of oscillatory behaviors via Hopf bifurcation. In addition, we show that the existence of discrete antigenic forms among pathogens can either fully or partially self-organize, where (i) strains exhibit no strain structures and coexist or (ii) antigenic variants sort into non-overlapping or minimally overlapping clusters that either undergo the principle of competitive exclusion exhibiting discrete strain structures, or co-exist cyclically. Copyright © 2015. Published by Elsevier Inc.

Iron deposition and inflammation in multiple sclerosis. Which one comes first?

PubMed Central

2011-01-01

Whether iron deposition is an epiphenomenon of the multiple sclerosis (MS) disease process or may play a primary role in triggering inflammation and disease development remains unclear at this time, and should be studied at the early stages of disease pathogenesis. However, it is difficult to study the relationship between iron deposition and inflammation in early MS due to the delay between the onset of symptoms and diagnosis, and the poor availability of tissue specimens. In a recent article published in BMC Neuroscience, Williams et al. investigated the relationship between inflammation and iron deposition using an original animal model labeled as "cerebral experimental autoimmune encephalomyelitis", which develops CNS perivascular iron deposits. However, the relative contribution of iron deposition vs. inflammation in the pathogenesis and progression of MS remains unknown. Further studies should establish the association between inflammation, reduced blood flow, iron deposition, microglia activation and neurodegeneration. Creating a representative animal model that can study independently such relationship will be the key factor in this endeavor. PMID:21699686

Interleukin 35 and Hepatocyte Growth Factor; as a novel combined immune gene therapy for Multiple Sclerosis disease.

PubMed

Moghadam, Samira; Erfanmanesh, Maryam; Esmaeilzadeh, Abdolreza

2017-11-01

An autoimmune demyelination disease of the Central Nervous System, Multiple Sclerosis, is a chronic inflammation which mostly involves young adults. Suffering people face functional loss with a severe pain. Most current MS treatments are focused on the immune response suppression. Approved drugs suppress the inflammatory process, but factually, there is no definite cure for Multiple Sclerosis. Recently developed knowledge has demonstrated that gene and cell therapy as a hopeful approach in tissue regeneration. The authors propose a novel combined immune gene therapy for Multiple Sclerosis treatment using anti-inflammatory and remyelination of Interleukine-35 and Hepatocyte Growth Factor properties, respectively. In this hypothesis Interleukine-35 and Hepatocyte Growth Factor introduce to Mesenchymal Stem Cells of EAE mouse model via an adenovirus based vector. It is expected that Interleukine-35 and Hepatocyte Growth Factor genes expressed from MSCs could effectively perform in immunotherapy of Multiple Sclerosis. Copyright © 2017. Published by Elsevier Ltd.

Family-Based Rare Variant Association Analysis: A Fast and Efficient Method of Multivariate Phenotype Association Analysis.

PubMed

Wang, Longfei; Lee, Sungyoung; Gim, Jungsoo; Qiao, Dandi; Cho, Michael; Elston, Robert C; Silverman, Edwin K; Won, Sungho

2016-09-01

Family-based designs have been repeatedly shown to be powerful in detecting the significant rare variants associated with human diseases. Furthermore, human diseases are often defined by the outcomes of multiple phenotypes, and thus we expect multivariate family-based analyses may be very efficient in detecting associations with rare variants. However, few statistical methods implementing this strategy have been developed for family-based designs. In this report, we describe one such implementation: the multivariate family-based rare variant association tool (mFARVAT). mFARVAT is a quasi-likelihood-based score test for rare variant association analysis with multiple phenotypes, and tests both homogeneous and heterogeneous effects of each variant on multiple phenotypes. Simulation results show that the proposed method is generally robust and efficient for various disease models, and we identify some promising candidate genes associated with chronic obstructive pulmonary disease. The software of mFARVAT is freely available at http://healthstat.snu.ac.kr/software/mfarvat/, implemented in C++ and supported on Linux and MS Windows. © 2016 WILEY PERIODICALS, INC.

Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies

PubMed Central

Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

2016-01-01

Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K-means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups. PMID:27330233

Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies.

PubMed

Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K -means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups.

Bioerodible System for Sequential Release of Multiple Drugs

PubMed Central

Sundararaj, Sharath C.; Thomas, Mark V.; Dziubla, Thomas D.; Puleo, David A.

2013-01-01

Because many complex physiological processes are controlled by multiple biomolecules, comprehensive treatment of certain disease conditions may be more effectively achieved by administration of more than one type of drug. Thus, the objective of the present research was to develop a multilayered, polymer-based system for sequential delivery of multiple drugs. The polymers used were cellulose acetate phthalate (CAP) complexed with Pluronic F-127 (P). After evaluating morphology of the resulting CAPP system, in vitro release of small molecule drugs and a model protein was studied from both single and multilayered devices. Drug release from single-layered CAPP films followed zero-order kinetics related to surface erosion of the association polymer. Release studies from multilayered CAPP devices showed the possibility of achieving intermittent release of one type of drug as well as sequential release of more than one type of drug. Mathematical modeling accurately predicted the release profiles for both single layer and multilayered devices. The present CAPP association polymer-based multilayer devices can be used for localized, sequential delivery of multiple drugs for the possible treatment of complex disease conditions, and perhaps for tissue engineering applications, that require delivery of more than one type of biomolecule. PMID:24096151

A model to evaluate quality and effectiveness of disease management.

PubMed

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.

The hygiene theory harnessing helminths and their ova to treat autoimmunity.

PubMed

Ben-Ami Shor, Dana; Harel, Michal; Eliakim, Rami; Shoenfeld, Yehuda

2013-10-01

The incidence of autoimmune diseases is increasing in Western countries, possibly due to the improved sanitary conditions and reduced exposure to infections in childhood (the hygiene hypothesis). There is an ongoing debate whether infection prevents or precipitates autoimmune diseases. Various helminths species used in several animal models were shown to limit inflammatory activity in a variety of diseases including inflammatory bowel disease, multiple sclerosis, type 1 diabetes, rheumatoid arthritis, and systemic lupus erythematosus. At present the scientific data is based mostly on experimental animal models; however, there is an increasing body of evidence in a number of clinical trials being conducted. Herein we review several clinical trials evaluating the anti-inflammatory effects of helminths and assessing their association with different autoimmune diseases, including inflammatory bowel disease, multiple sclerosis, and autoimmune liver diseases. We also describe the common pathways by which helminths induce immune modulation and the key changes observed in the host immune system following exposure to helminths. These common pathways include the inhibition of IFN-γ and IL-17 production, promotion of IL-4, IL-10 and TGF-β release, induction of CD4(+) T cell FoxP3(+) expression, and generation of regulatory macrophages, dendritic cells, and B cells. Helminths products are becoming significant candidates for anti-inflammatory agents in this context. However, further research is needed for synthetic analogues of helminths' potent products that mimic the parasite-mediated immunomodulation effect.

Disease spread across multiple scales in a spatial hierarchy: effect of host spatial structure and of inoculum quantity and distribution.

PubMed

Gosme, Marie; Lucas, Philippe

2009-07-01

Spatial patterns of both the host and the disease influence disease spread and crop losses. Therefore, the manipulation of these patterns might help improve control strategies. Considering disease spread across multiple scales in a spatial hierarchy allows one to capture important features of epidemics developing in space without using explicitly spatialized variables. Thus, if the system under study is composed of roots, plants, and planting hills, the effect of host spatial pattern can be studied by varying the number of plants per planting hill. A simulation model based on hierarchy theory was used to simulate the effects of large versus small planting hills, low versus high level of initial infections, and aggregated versus uniform distribution of initial infections. The results showed that aggregating the initially infected plants always resulted in slower epidemics than spreading out the initial infections uniformly. Simulation results also showed that, in most cases, disease epidemics were slower in the case of large host aggregates (100 plants/hill) than with smaller aggregates (25 plants/hill), except when the initially infected plants were both numerous and spread out uniformly. The optimal strategy for disease control depends on several factors, including initial conditions. More importantly, the model offers a framework to account for the interplay between the spatial characteristics of the system, rates of infection, and aggregation of the disease.

Accounting for disease modifying therapy in models of clinical progression in multiple sclerosis.

PubMed

Healy, Brian C; Engler, David; Gholipour, Taha; Weiner, Howard; Bakshi, Rohit; Chitnis, Tanuja

2011-04-15

Identifying predictors of clinical progression in patients with relapsing-remitting multiple sclerosis (RRMS) is complicated in the era of disease modifying therapy (DMT) because patients follow many different DMT regimens. To investigate predictors of progression in a treated RRMS sample, a cohort of RRMS patients was prospectively followed in the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB). Enrollment criteria were exposure to either interferon-β (IFN-β, n=164) or glatiramer acetate (GA, n=114) for at least 6 months prior to study entry. Baseline demographic and clinical features were used as candidate predictors of longitudinal clinical change on the Expanded Disability Status Scale (EDSS). We compared three approaches to account for DMT effects in statistical modeling. In all approaches, we analyzed all patients together and stratified based on baseline DMT. Model 1 used all available longitudinal EDSS scores, even those after on-study DMT changes. Model 2 used only clinical observations prior to changing DMT. Model 3 used causal statistical models to identify predictors of clinical change. When all patients were considered using Model 1, patients with a motor symptom as the first relapse had significantly larger change in EDSS scores during follow-up (p=0.04); none of the other clinical or demographic variables significantly predicted change. In Models 2 and 3, results were generally unchanged. DMT modeling choice had a modest impact on the variables classified as predictors of EDSS score change. Importantly, however, interpretation of these predictors is dependent upon modeling choice. Copyright © 2011 Elsevier B.V. All rights reserved.

A systems pharmacology-oriented discovery of a new therapeutic use of the TCM formula Liuweiwuling for liver failure.

PubMed

Wang, Jia-Bo; Cui, He-Rong; Wang, Rui-Lin; Zhang, Cong-En; Niu, Ming; Bai, Zhao-Fang; Xu, Gen-Hua; Li, Peng-Yan; Jiang, Wen-Yan; Han, Jing-Jing; Ma, Xiao; Cai, Guang-Ming; Li, Rui-Sheng; Zhang, Li-Ping; Xiao, Xiao-He

2018-04-04

Multiple components of traditional Chinese medicine (TCM) formulae determine their treatment targets for multiple diseases as opposed to a particular disease. However, discovering the unexplored therapeutic potential of a TCM formula remains challenging and costly. Inspired by the drug repositioning methodology, we propose an integrated strategy to feasibly identify new therapeutic uses for a formula composed of six herbs, Liuweiwuling. First, we developed a comprehensive systems approach to enrich drug compound-liver disease networks to analyse the major predicted diseases of Liuweiwuling and discover its potential effect on liver failure. The underlying mechanisms were subsequently predicted to mainly attribute to a blockade of hepatocyte apoptosis via a synergistic combination of multiple effects. Next, a classical pharmacology experiment was designed to validate the effects of Liuweiwuling on different models of fulminant liver failure induced by D-galactosamine/lipopolysaccharide (GalN/LPS) or thioacetamide (TAA). The results indicated that pretreatment with Liuweiwuling restored liver function and reduced lethality induced by GalN/LPS or TAA in a dose-dependent manner, which was partially attributable to the abrogation of hepatocyte apoptosis by multiple synergistic effects. In summary, the integrated strategy discussed in this paper may provide a new approach for the more efficient discovery of new therapeutic uses for TCM formulae.

Patients’ Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test

PubMed Central

Dou, Kaili; Yu, Ping; Liu, Fang; Guan, YingPing; Li, Zhenye; Ji, Yumeng; Du, Ningkai; Lu, Xudong; Duan, Huilong

2017-01-01

Background Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. Objective The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients’ acceptance of smartphone health technology for chronic disease management. Methods Multiple theories and factors that may influence patients’ acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients’ acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients’ actual use of a smartphone health app. The partial least square method was used to test the theoretical model. Results The model accounted for .412 of the variance in patients’ intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients’ smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients’ intentions to use the technology. Age and gender had no significant influence on patients’ acceptance of smartphone technology. The study also confirmed the positive relationship between intention to use and actual use of smartphone health apps for chronic disease management. Conclusions This study developed a theoretical model to predict patients’ acceptance of smartphone health technology for chronic disease management. Although resistance to change is a significant barrier to technology acceptance, careful management of doctor-patient relationship, and raising patients’ awareness of the negative effect of chronic disease can negate the effect of resistance and encourage acceptance and use of smartphone health technology to support chronic disease management for patients in the community. PMID:29212629

Using a Simulation to Illustrate Crosscutting Concepts through a Disease Model

ERIC Educational Resources Information Center

Bokor, Julie; Darwiche, Houda; Joseph, Drew

2015-01-01

Using Pompe disease as a context affords the opportunity for students to consider multiple biological concepts and embraces the Next Generation Science Standards Disciplinary Core Ideas Structure and Function (LS1.A) and Inheritance of Traits (LS3.A) as well as Crosscutting Concepts Structure and Function and Cause and Effect. These crosscutting…

Bovine respiratory disease model based on dual infections with infection with bovine viral diarrhea virus and bovine corona virus

USDA-ARS?s Scientific Manuscript database

Bovine respiratory disease complex (BRDC) is the leading cause of economic loss in the U.S. cattle industry. BRDC likely results from simultaneous or sequential infections with multiple pathogens including both viruses and bacteria. Bovine viral diarrhea virus (BVDV) and bovine corona virus (BoCV...

In Silico Investigations of the Anti-Catabolic Effects of Pamidronate and Denosumab on Multiple Myeloma-Induced Bone Disease

PubMed Central

Wang, Yan; Lin, Bo

2012-01-01

It is unclear whether the new anti-catabolic agent denosumab represents a viable alternative to the widely used anti-catabolic agent pamidronate in the treatment of Multiple Myeloma (MM)-induced bone disease. This lack of clarity primarily stems from the lack of sufficient clinical investigations, which are costly and time consuming. However, in silico investigations require less time and expense, suggesting that they may be a useful complement to traditional clinical investigations. In this paper, we aim to (i) develop integrated computational models that are suitable for investigating the effects of pamidronate and denosumab on MM-induced bone disease and (ii) evaluate the responses to pamidronate and denosumab treatments using these integrated models. To achieve these goals, pharmacokinetic models of pamidronate and denosumab are first developed and then calibrated and validated using different clinical datasets. Next, the integrated computational models are developed by incorporating the simulated transient concentrations of pamidronate and denosumab and simulations of their actions on the MM-bone compartment into the previously proposed MM-bone model. These integrated models are further calibrated and validated by different clinical datasets so that they are suitable to be applied to investigate the responses to the pamidronate and denosumab treatments. Finally, these responses are evaluated by quantifying the bone volume, bone turnover, and MM-cell density. This evaluation identifies four denosumab regimes that potentially produce an overall improved bone-related response compared with the recommended pamidronate regime. This in silico investigation supports the idea that denosumab represents an appropriate alternative to pamidronate in the treatment of MM-induced bone disease. PMID:23028650

Bi-level Multi-Source Learning for Heterogeneous Block-wise Missing Data

PubMed Central

Xiang, Shuo; Yuan, Lei; Fan, Wei; Wang, Yalin; Thompson, Paul M.; Ye, Jieping

2013-01-01

Bio-imaging technologies allow scientists to collect large amounts of high-dimensional data from multiple heterogeneous sources for many biomedical applications. In the study of Alzheimer's Disease (AD), neuroimaging data, gene/protein expression data, etc., are often analyzed together to improve predictive power. Joint learning from multiple complementary data sources is advantageous, but feature-pruning and data source selection are critical to learn interpretable models from high-dimensional data. Often, the data collected has block-wise missing entries. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), most subjects have MRI and genetic information, but only half have cerebrospinal fluid (CSF) measures, a different half has FDG-PET; only some have proteomic data. Here we propose how to effectively integrate information from multiple heterogeneous data sources when data is block-wise missing. We present a unified “bi-level” learning model for complete multi-source data, and extend it to incomplete data. Our major contributions are: (1) our proposed models unify feature-level and source-level analysis, including several existing feature learning approaches as special cases; (2) the model for incomplete data avoids imputing missing data and offers superior performance; it generalizes to other applications with block-wise missing data sources; (3) we present efficient optimization algorithms for modeling complete and incomplete data. We comprehensively evaluate the proposed models including all ADNI subjects with at least one of four data types at baseline: MRI, FDG-PET, CSF and proteomics. Our proposed models compare favorably with existing approaches. PMID:23988272

Bi-level multi-source learning for heterogeneous block-wise missing data.

PubMed

Xiang, Shuo; Yuan, Lei; Fan, Wei; Wang, Yalin; Thompson, Paul M; Ye, Jieping

2014-11-15

Bio-imaging technologies allow scientists to collect large amounts of high-dimensional data from multiple heterogeneous sources for many biomedical applications. In the study of Alzheimer's Disease (AD), neuroimaging data, gene/protein expression data, etc., are often analyzed together to improve predictive power. Joint learning from multiple complementary data sources is advantageous, but feature-pruning and data source selection are critical to learn interpretable models from high-dimensional data. Often, the data collected has block-wise missing entries. In the Alzheimer's Disease Neuroimaging Initiative (ADNI), most subjects have MRI and genetic information, but only half have cerebrospinal fluid (CSF) measures, a different half has FDG-PET; only some have proteomic data. Here we propose how to effectively integrate information from multiple heterogeneous data sources when data is block-wise missing. We present a unified "bi-level" learning model for complete multi-source data, and extend it to incomplete data. Our major contributions are: (1) our proposed models unify feature-level and source-level analysis, including several existing feature learning approaches as special cases; (2) the model for incomplete data avoids imputing missing data and offers superior performance; it generalizes to other applications with block-wise missing data sources; (3) we present efficient optimization algorithms for modeling complete and incomplete data. We comprehensively evaluate the proposed models including all ADNI subjects with at least one of four data types at baseline: MRI, FDG-PET, CSF and proteomics. Our proposed models compare favorably with existing approaches. © 2013 Elsevier Inc. All rights reserved.

Measurement of the permeability, perfusion, and histogram characteristics in relapsing-remitting multiple sclerosis using dynamic contrast-enhanced MRI with extended Tofts linear model.

PubMed

Yin, Ping; Xiong, Hua; Liu, Yi; Sah, Shambhu K; Zeng, Chun; Wang, Jingjie; Li, Yongmei; Hong, Nan

2018-01-01

To investigate the application value of using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with extended Tofts linear model for relapsing-remitting multiple sclerosis (RRMS) and its correlation with expanded disability status scale (EDSS) scores and disease duration. Thirty patients with multiple sclerosis (MS) underwent conventional magnetic resonance imaging (MRI) and DCE-MRI with a 3.0 Tesla MR scanner. An extended Tofts linear model was used to quantitatively measure MR imaging biomarkers. The histogram parameters and correlation among imaging biomarkers, EDSS scores, and disease duration were also analyzed. The MR imaging biomarkers volume transfer constant (K trans ), volume of the extravascular extracellular space per unit volume of tissue (Ve), fractional plasma volume (V p ), cerebral blood flow (CBF), and cerebral blood volume (CBV) of contrast-enhancing (CE) lesions were significantly higher (P < 0.05) than those of nonenhancing (NE) lesions and normal-appearing white matter (NAWM) regions. The skewness of Ve value in CE lesions was more close to normal distribution. There was no significant correlation among the biomarkers with the EDSS scores and disease duration (P > 0.05). Our study demonstrates that the DCE-MRI with the extended Tofts linear model can measure the permeability and perfusion characteristic in MS lesions and in NAWM regions. The K trans , Ve, Vp, CBF, and CBV of CE lesions were significantly higher than that of NE lesions. The skewness of Ve value in CE lesions was more close to normal distribution, indicating that the histogram can be helpful to distinguish the pathology of MS lesions.

Association of Climatic Variability, Vector Population and Malarial Disease in District of Visakhapatnam, India: A Modeling and Prediction Analysis.

PubMed

Srimath-Tirumula-Peddinti, Ravi Chandra Pavan Kumar; Neelapu, Nageswara Rao Reddy; Sidagam, Naresh

2015-01-01

Malarial incidence, severity, dynamics and distribution of malaria are strongly determined by climatic factors, i.e., temperature, precipitation, and relative humidity. The objectives of the current study were to analyse and model the relationships among climate, vector and malaria disease in district of Visakhapatnam, India to understand malaria transmission mechanism (MTM). Epidemiological, vector and climate data were analysed for the years 2005 to 2011 in Visakhapatnam to understand the magnitude, trends and seasonal patterns of the malarial disease. Statistical software MINITAB ver. 14 was used for performing correlation, linear and multiple regression analysis. Perennial malaria disease incidence and mosquito population was observed in the district of Visakhapatnam with peaks in seasons. All the climatic variables have a significant influence on disease incidence as well as on mosquito populations. Correlation coefficient analysis, seasonal index and seasonal analysis demonstrated significant relationships among climatic factors, mosquito population and malaria disease incidence in the district of Visakhapatnam, India. Multiple regression and ARIMA (I) models are best suited models for modeling and prediction of disease incidences and mosquito population. Predicted values of average temperature, mosquito population and malarial cases increased along with the year. Developed MTM algorithm observed a major MTM cycle following the June to August rains and occurring between June to September and minor MTM cycles following March to April rains and occurring between March to April in the district of Visakhapatnam. Fluctuations in climatic factors favored an increase in mosquito populations and thereby increasing the number of malarial cases. Rainfall, temperatures (20°C to 33°C) and humidity (66% to 81%) maintained a warmer, wetter climate for mosquito growth, parasite development and malaria transmission. Changes in climatic factors influence malaria directly by modifying the behaviour and geographical distribution of vectors and by changing the length of the life cycle of the parasite.

Association of Climatic Variability, Vector Population and Malarial Disease in District of Visakhapatnam, India: A Modeling and Prediction Analysis

PubMed Central

Srimath-Tirumula-Peddinti, Ravi Chandra Pavan Kumar; Neelapu, Nageswara Rao Reddy; Sidagam, Naresh

2015-01-01

Background Malarial incidence, severity, dynamics and distribution of malaria are strongly determined by climatic factors, i.e., temperature, precipitation, and relative humidity. The objectives of the current study were to analyse and model the relationships among climate, vector and malaria disease in district of Visakhapatnam, India to understand malaria transmission mechanism (MTM). Methodology Epidemiological, vector and climate data were analysed for the years 2005 to 2011 in Visakhapatnam to understand the magnitude, trends and seasonal patterns of the malarial disease. Statistical software MINITAB ver. 14 was used for performing correlation, linear and multiple regression analysis. Results/Findings Perennial malaria disease incidence and mosquito population was observed in the district of Visakhapatnam with peaks in seasons. All the climatic variables have a significant influence on disease incidence as well as on mosquito populations. Correlation coefficient analysis, seasonal index and seasonal analysis demonstrated significant relationships among climatic factors, mosquito population and malaria disease incidence in the district of Visakhapatnam, India. Multiple regression and ARIMA (I) models are best suited models for modeling and prediction of disease incidences and mosquito population. Predicted values of average temperature, mosquito population and malarial cases increased along with the year. Developed MTM algorithm observed a major MTM cycle following the June to August rains and occurring between June to September and minor MTM cycles following March to April rains and occurring between March to April in the district of Visakhapatnam. Fluctuations in climatic factors favored an increase in mosquito populations and thereby increasing the number of malarial cases. Rainfall, temperatures (20°C to 33°C) and humidity (66% to 81%) maintained a warmer, wetter climate for mosquito growth, parasite development and malaria transmission. Conclusions/Significance Changes in climatic factors influence malaria directly by modifying the behaviour and geographical distribution of vectors and by changing the length of the life cycle of the parasite. PMID:26110279

Multiple imputation for estimating the risk of developing dementia and its impact on survival.

PubMed

Yu, Binbing; Saczynski, Jane S; Launer, Lenore

2010-10-01

Dementia, Alzheimer's disease in particular, is one of the major causes of disability and decreased quality of life among the elderly and a leading obstacle to successful aging. Given the profound impact on public health, much research has focused on the age-specific risk of developing dementia and the impact on survival. Early work has discussed various methods of estimating age-specific incidence of dementia, among which the illness-death model is popular for modeling disease progression. In this article we use multiple imputation to fit multi-state models for survival data with interval censoring and left truncation. This approach allows semi-Markov models in which survival after dementia depends on onset age. Such models can be used to estimate the cumulative risk of developing dementia in the presence of the competing risk of dementia-free death. Simulations are carried out to examine the performance of the proposed method. Data from the Honolulu Asia Aging Study are analyzed to estimate the age-specific and cumulative risks of dementia and to examine the effect of major risk factors on dementia onset and death.

Rodent Models of Experimental Endometriosis: Identifying Mechanisms of Disease and Therapeutic Targets

PubMed Central

Bruner-Tran, Kaylon L.; Mokshagundam, Shilpa; Herington, Jennifer L.; Ding, Tianbing; Osteen, Kevin G.

2018-01-01

Background: Although it has been more than a century since endometriosis was initially described in the literature, understanding the etiology and natural history of the disease has been challenging. However, the broad utility of murine and rat models of experimental endometriosis has enabled the elucidation of a number of potentially targetable processes which may otherwise promote this disease. Objective: To review a variety of studies utilizing rodent models of endometriosis to illustrate their utility in examining mechanisms associated with development and progression of this disease. Results: Use of rodent models of endometriosis has provided a much broader understanding of the risk factors for the initial development of endometriosis, the cellular pathology of the disease and the identification of potential therapeutic targets. Conclusion: Although there are limitations with any animal model, the variety of experimental endometriosis models that have been developed has enabled investigation into numerous aspects of this disease. Thanks to these models, our under-standing of the early processes of disease development, the role of steroid responsiveness, inflammatory processes and the peritoneal environment has been advanced. More recent models have begun to shed light on how epigenetic alterations con-tribute to the molecular basis of this disease as well as the multiple comorbidities which plague many patients. Continued de-velopments of animal models which aid in unraveling the mechanisms of endometriosis development provide the best oppor-tunity to identify therapeutic strategies to prevent or regress this enigmatic disease.

Modeling the combined influence of host dispersal and waterborne fate and transport on pathogen spread in complex landscapes

PubMed Central

Lu, Ding; McDowell, Julia Z.; Davis, George M.; Spear, Robert C.; Remais, Justin V.

2012-01-01

Environmental models, often applied to questions on the fate and transport of chemical hazards, have recently become important in tracing certain environmental pathogens to their upstream sources of contamination. These tools, such as first order decay models applied to contaminants in surface waters, offer promise for quantifying the fate and transport of pathogens with multiple environmental stages and/or multiple hosts, in addition to those pathogens whose environmental stages are entirely waterborne. Here we consider the fate and transport capabilities of the human schistosome Schistosoma japonicum, which exhibits two waterborne stages and is carried by an amphibious intermediate snail host. We present experimentally-derived dispersal estimates for the intermediate snail host and fate and transport estimates for the passive downstream diffusion of cercariae, the waterborne, human-infective parasite stage. Using a one dimensional advective transport model exhibiting first-order decay, we simulate the added spatial reach and relative increase in cercarial concentrations that dispersing snail hosts contribute to downstream sites. Simulation results suggest that snail dispersal can substantially increase the concentrations of cercariae reaching downstream locations, relative to no snail dispersal, effectively putting otherwise isolated downstream sites at increased risk of exposure to cercariae from upstream sources. The models developed here can be applied to other infectious diseases with multiple life-stages and hosts, and have important implications for targeted ecological control of disease spread. PMID:23162675

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

PubMed

Tran, Phoebe; Waller, Lance

2015-01-01

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

Combined influence of multiple climatic factors on the incidence of bacterial foodborne diseases.

PubMed

Park, Myoung Su; Park, Ki Hwan; Bahk, Gyung Jin

2018-01-01

Information regarding the relationship between the incidence of foodborne diseases (FBD) and climatic factors is useful in designing preventive strategies for FBD based on anticipated future climate change. To better predict the effect of climate change on foodborne pathogens, the present study investigated the combined influence of multiple climatic factors on bacterial FBD incidence in South Korea. During 2011-2015, the relationships between 8 climatic factors and the incidences of 13 bacterial FBD, were determined based on inpatient stays, on a monthly basis using the Pearson correlation analyses, multicollinearity tests, principal component analysis (PCA), and the seasonal autoregressive integrated moving average (SARIMA) modeling. Of the 8 climatic variables, the combination of temperature, relative humidity, precipitation, insolation, and cloudiness was significantly associated with salmonellosis (P<0.01), vibriosis (P<0.05), and enterohemorrhagic Escherichia coli O157:H7 infection (P<0.01). The combined effects of snowfall, wind speed, duration of sunshine, and cloudiness were not significant for these 3 FBD. Other FBD, including campylobacteriosis, were not significantly associated with any combination of climatic factors. These findings indicate that the relationships between multiple climatic factors and bacterial FBD incidence can be valuable for the development of prediction models for future patterns of diseases in response to changes in climate. Copyright © 2017 Elsevier B.V. All rights reserved.

Vector-Borne Pathogen and Host Evolution in a Structured Immuno-Epidemiological System.

PubMed

Gulbudak, Hayriye; Cannataro, Vincent L; Tuncer, Necibe; Martcheva, Maia

2017-02-01

Vector-borne disease transmission is a common dissemination mode used by many pathogens to spread in a host population. Similar to directly transmitted diseases, the within-host interaction of a vector-borne pathogen and a host's immune system influences the pathogen's transmission potential between hosts via vectors. Yet there are few theoretical studies on virulence-transmission trade-offs and evolution in vector-borne pathogen-host systems. Here, we consider an immuno-epidemiological model that links the within-host dynamics to between-host circulation of a vector-borne disease. On the immunological scale, the model mimics antibody-pathogen dynamics for arbovirus diseases, such as Rift Valley fever and West Nile virus. The within-host dynamics govern transmission and host mortality and recovery in an age-since-infection structured host-vector-borne pathogen epidemic model. By considering multiple pathogen strains and multiple competing host populations differing in their within-host replication rate and immune response parameters, respectively, we derive evolutionary optimization principles for both pathogen and host. Invasion analysis shows that the [Formula: see text] maximization principle holds for the vector-borne pathogen. For the host, we prove that evolution favors minimizing case fatality ratio (CFR). These results are utilized to compute host and pathogen evolutionary trajectories and to determine how model parameters affect evolution outcomes. We find that increasing the vector inoculum size increases the pathogen [Formula: see text], but can either increase or decrease the pathogen virulence (the host CFR), suggesting that vector inoculum size can contribute to virulence of vector-borne diseases in distinct ways.

Tissue Chips to aid drug development and modeling for rare diseases

PubMed Central

Low, Lucie A.; Tagle, Danilo A.

2016-01-01

Introduction The technologies used to design, create and use microphysiological systems (MPS, “tissue chips” or “organs-on-chips”) have progressed rapidly in the last 5 years, and validation studies of the functional relevance of these platforms to human physiology, and response to drugs for individual model organ systems, are well underway. These studies are paving the way for integrated multi-organ systems that can model diseases and predict drug efficacy and toxicology of multiple organs in real-time, improving the potential for diagnostics and development of novel treatments of rare diseases in the future. Areas covered This review will briefly summarize the current state of tissue chip research and highlight model systems where these microfabricated (or bioengineered) devices are already being used to screen therapeutics, model disease states, and provide potential treatments in addition to helping elucidate the basic molecular and cellular phenotypes of rare diseases. Expert opinion Microphysiological systems hold great promise and potential for modeling rare disorders, as well as for their potential use to enhance the predictive power of new drug therapeutics, plus potentially increase the statistical power of clinical trials while removing the inherent risks of these trials in rare disease populations. PMID:28626620

A conceptual disease model for adult Pompe disease.

PubMed

Kanters, Tim A; Redekop, W Ken; Rutten-Van Mölken, Maureen P M H; Kruijshaar, Michelle E; Güngör, Deniz; van der Ploeg, Ans T; Hakkaart, Leona

2015-09-15

Studies in orphan diseases are, by nature, confronted with small patient populations, meaning that randomized controlled trials will have limited statistical power. In order to estimate the effectiveness of treatments in orphan diseases and extrapolate effects into the future, alternative models might be needed. The purpose of this study is to develop a conceptual disease model for Pompe disease in adults (an orphan disease). This conceptual model describes the associations between the most important levels of health concepts for Pompe disease in adults, from biological parameters via physiological parameters, symptoms and functional indicators to health perceptions and final health outcomes as measured in terms of health-related quality of life. The structure of the Wilson-Cleary health outcomes model was used as a blueprint, and filled with clinically relevant aspects for Pompe disease based on literature and expert opinion. Multiple observations per patient from a Dutch cohort study in untreated patients were used to quantify the relationships between the different levels of health concepts in the model by means of regression analyses. Enzyme activity, muscle strength, respiratory function, fatigue, level of handicap, general health perceptions, mental and physical component scales and utility described the different levels of health concepts in the Wilson-Cleary model for Pompe disease. Regression analyses showed that functional status was affected by fatigue, muscle strength and respiratory function. Health perceptions were affected by handicap. In turn, self-reported quality of life was affected by health perceptions. We conceptualized a disease model that incorporated the mechanisms believed to be responsible for impaired quality of life in Pompe disease. The model provides a comprehensive overview of various aspects of Pompe disease in adults, which can be useful for both clinicians and policymakers to support their multi-faceted decision making.

MitoQ, a mitochondria-targeted antioxidant, delays disease progression and alleviates pathogenesis in an experimental autoimmune encephalomyelitis mouse model of multiple sclerosis

PubMed Central

Mao, Peizhong; Manczak, Maria; Shirendeb, Ulziibat P.; Reddy, P. Hemachandra

2013-01-01

Oxidative stress and mitochondrial dysfunction are involved in the progression and pathogenesis of multiple sclerosis (MS). MitoQ is a mitochondria-targeted antioxidant that has a neuroprotective role in several mitochondrial and neurodegenerative diseases, including Alzheimer’s disease and Parkinson’s disease. Here we sought to determine the possible effects of a systematic administration of MitoQ as a therapy, using an experimental autoimmune encephalomyelitis (EAE) mouse model. We studied the beneficial effects of MitoQ in EAE mice that mimic MS like symptoms by treating EAE mice with MitoQ and pretreated C57BL6 mice MitoQ plus EAE induction. We found that pretreatment and treatment of EAE mice with MitoQ reduced neurological disabilities associated with EAE. We also found that both pretreatment and treatment of the EAE mice with MitoQ significantly suppressed inflammatory markers of EAE, including the inhibition of inflammatory cytokines and chemokines. MitoQ treatments reduced neuronal cell loss in the spinal cord, a factor underlying motor disability in EAE mice. The neuroprotective role of MitoQ was confirmed by a neuron-glia co-culture system designed to mimic the mechanism of MS and EAE in vitro. We found that axonal inflammation and oxidative stress are associated with impaired behavioral functions in the EAE mouse model and that treatment with MitoQ can exert protective effects on neurons and reduce axonal inflammation and oxidative stress. These protective effects are likely via multiple mechanisms, including the attenuation of the robust immune response. These results suggest that MitoQ may be a new candidate for the treatment of MS. PMID:24055980

MitoQ, a mitochondria-targeted antioxidant, delays disease progression and alleviates pathogenesis in an experimental autoimmune encephalomyelitis mouse model of multiple sclerosis.

PubMed

Mao, Peizhong; Manczak, Maria; Shirendeb, Ulziibat P; Reddy, P Hemachandra

2013-12-01

Oxidative stress and mitochondrial dysfunction are involved in the progression and pathogenesis of multiple sclerosis (MS). MitoQ is a mitochondria-targeted antioxidant that has a neuroprotective role in several mitochondrial and neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease. Here we sought to determine the possible effects of a systematic administration of MitoQ as a therapy, using an experimental autoimmune encephalomyelitis (EAE) mouse model. We studied the beneficial effects of MitoQ in EAE mice that mimic MS like symptoms by treating EAE mice with MitoQ and pretreated C57BL6 mice with MitoQ plus EAE induction. We found that pretreatment and treatment of EAE mice with MitoQ reduced neurological disabilities associated with EAE. We also found that both pretreatment and treatment of the EAE mice with MitoQ significantly suppressed inflammatory markers of EAE, including the inhibition of inflammatory cytokines and chemokines. MitoQ treatments reduced neuronal cell loss in the spinal cord, a factor underlying motor disability in EAE mice. The neuroprotective role of MitoQ was confirmed by a neuron-glia co-culture system designed to mimic the mechanism of MS and EAE in vitro. We found that axonal inflammation and oxidative stress are associated with impaired behavioral functions in the EAE mouse model and that treatment with MitoQ can exert protective effects on neurons and reduce axonal inflammation and oxidative stress. These protective effects are likely via multiple mechanisms, including the attenuation of the robust immune response. These results suggest that MitoQ may be a new candidate for the treatment of MS. © 2013.

Trends in Mortality After Primary Cytoreductive Surgery for Ovarian Cancer: A Systematic Review and Metaregression of Randomized Clinical Trials and Observational Studies.

PubMed

Di Donato, Violante; Kontopantelis, Evangelos; Aletti, Giovanni; Casorelli, Assunta; Piacenti, Ilaria; Bogani, Giorgio; Lecce, Francesca; Benedetti Panici, Pierluigi

2017-06-01

Primary cytoreductive surgery (PDS) followed by platinum-based chemotherapy is the cornerstone of treatment and the absence of residual tumor after PDS is universally considered the most important prognostic factor. The aim of the present analysis was to evaluate trend and predictors of 30-day mortality in patients undergoing primary cytoreduction for ovarian cancer. Literature was searched for records reporting 30-day mortality after PDS. All cohorts were rated for quality. Simple and multiple Poisson regression models were used to quantify the association between 30-day mortality and the following: overall or severe complications, proportion of patients with stage IV disease, median age, year of publication, and weighted surgical complexity index. Using the multiple regression model, we calculated the risk of perioperative mortality at different levels for statistically significant covariates of interest. Simple regression identified median age and proportion of patients with stage IV disease as statistically significant predictors of 30-day mortality. When included in the multiple Poisson regression model, both remained statistically significant, with an incidence rate ratio of 1.087 for median age and 1.017 for stage IV disease. Disease stage was a strong predictor, with the risk estimated to increase from 2.8% (95% confidence interval 2.02-3.66) for stage III to 16.1% (95% confidence interval 6.18-25.93) for stage IV, for a cohort with a median age of 65 years. Metaregression demonstrated that increased age and advanced clinical stage were independently associated with an increased risk of mortality, and the combined effects of both factors greatly increased the risk.

Speech and pause characteristics associated with voluntary rate reduction in Parkinson's disease and Multiple Sclerosis.

PubMed

Tjaden, Kris; Wilding, Greg

2011-01-01

The primary purpose of this study was to investigate how speakers with Parkinson's disease (PD) and Multiple Sclerosis (MS) accomplish voluntary reductions in speech rate. A group of talkers with no history of neurological disease was included for comparison. This study was motivated by the idea that knowledge of how speakers with dysarthria voluntarily accomplish a reduced speech rate would contribute toward a descriptive model of speaking rate change in dysarthria. Such a model has the potential to assist in identifying rate control strategies to receive focus in clinical treatment programs and also would advance understanding of global speech timing in dysarthria. All speakers read a passage in Habitual and Slow conditions. Speech rate, articulation rate, pause duration, and pause frequency were measured. All speaker groups adjusted articulation time as well as pause time to reduce overall speech rate. Group differences in how voluntary rate reduction was accomplished were primarily one of quantity or degree. Overall, a slower-than-normal rate was associated with a reduced articulation rate, shorter speech runs that included fewer syllables, and longer more frequent pauses. Taken together, these results suggest that existing skills or strategies used by patients should be emphasized in dysarthria training programs focusing on rate reduction. Results further suggest that a model of voluntary speech rate reduction based on neurologically normal speech shows promise as being applicable for mild to moderate dysarthria. The reader will be able to: (1) describe the importance of studying voluntary adjustments in speech rate in dysarthria, (2) discuss how speakers with Parkinson's disease and Multiple Sclerosis adjust articulation time and pause time to slow speech rate. Copyright © 2011 Elsevier Inc. All rights reserved.

Sustaining self-management in diabetes mellitus.

PubMed

Mitchell-Brown, Fay

2014-01-01

Successful management of diabetes depends on the individual's ability to manage and control symptoms. Self-management of diabetes is believed to play a significant role in achieving positive outcomes for patients. Adherence to self-management behaviors supports high-quality care, which reduces and delays disease complications, resulting in improved quality of life. Because self-management is so important to diabetes management and involves a lifelong commitment for all patients, health care providers should actively promote ways to maintain and sustain behavior change that support adherence to self-management. A social ecological model of behavior change (McLeroy, Bibeau, Steckler, & Glanz, 1988) helps practitioners provide evidence-based care and optimizes patients' clinical outcomes. This model supports self-management behaviors through multiple interacting interventions that can help sustain behavior change. Diabetes is a complex chronic disease; successful management must use multiple-level interventions.

Marginal Structural Cox Models for Estimating the Association Between β-Interferon Exposure and Disease Progression in a Multiple Sclerosis Cohort

PubMed Central

Karim, Mohammad Ehsanul; Gustafson, Paul; Petkau, John; Zhao, Yinshan; Shirani, Afsaneh; Kingwell, Elaine; Evans, Charity; van der Kop, Mia; Oger, Joel; Tremlett, Helen

2014-01-01

Longitudinal observational data are required to assess the association between exposure to β-interferon medications and disease progression among relapsing-remitting multiple sclerosis (MS) patients in the “real-world” clinical practice setting. Marginal structural Cox models (MSCMs) can provide distinct advantages over traditional approaches by allowing adjustment for time-varying confounders such as MS relapses, as well as baseline characteristics, through the use of inverse probability weighting. We assessed the suitability of MSCMs to analyze data from a large cohort of 1,697 relapsing-remitting MS patients in British Columbia, Canada (1995–2008). In the context of this observational study, which spanned more than a decade and involved patients with a chronic yet fluctuating disease, the recently proposed “normalized stabilized” weights were found to be the most appropriate choice of weights. Using this model, no association between β-interferon exposure and the hazard of disability progression was found (hazard ratio = 1.36, 95% confidence interval: 0.95, 1.94). For sensitivity analyses, truncated normalized unstabilized weights were used in additional MSCMs and to construct inverse probability weight-adjusted survival curves; the findings did not change. Additionally, qualitatively similar conclusions from approximation approaches to the weighted Cox model (i.e., MSCM) extend confidence in the findings. PMID:24939980

Prediction of Coronary Artery Disease Risk Based on Multiple Longitudinal Biomarkers

PubMed Central

Yang, Lili; Yu, Menggang; Gao, Sujuan

2016-01-01

In the last decade, few topics in the area of cardiovascular disease (CVD) research have received as much attention as risk prediction. One of the well documented risk factors for CVD is high blood pressure (BP). Traditional CVD risk prediction models consider BP levels measured at a single time and such models form the basis for current clinical guidelines for CVD prevention. However, in clinical practice, BP levels are often observed and recorded in a longitudinal fashion. Information on BP trajectories can be powerful predictors for CVD events. We consider joint modeling of time to coronary artery disease and individual longitudinal measures of systolic and diastolic BPs in a primary care cohort with up to 20 years of follow-up. We applied novel prediction metrics to assess the predictive performance of joint models. Predictive performances of proposed joint models and other models were assessed via simulations and illustrated using the primary care cohort. PMID:26439685

Bivalent compound 17MN exerts neuroprotection through interaction at multiple sites in a cellular model of Alzheimer’s disease

PubMed Central

Liu, Kai; Chojnacki, Jeremy E.; Wade, Emily E.; Saathoff, John M.; Lesnefsky, Edward J.; Chen, Qun; Zhang, Shijun

2016-01-01

Multiple pathogenic factors have been suggested in playing a role in the development of Alzheimer’s disease (AD). The multifactorial nature of AD also suggests the potential use of compounds with polypharmacology as effective disease-modifying agents. Recently, we have developed a bivalent strategy to include cell membrane anchorage into the molecular design. Our results demonstrated that the bivalent compounds exhibited multifunctional properties and potent neuroprotection in a cellular AD model. Herein, we report the mechanistic exploration of one of the representative bivalent compounds, 17MN, in MC65 cells. Our results established that MC65 cells die through a necroptotic mechanism upon the removal of tetracycline (TC). Furthermore, we have shown that mitochondrial membrane potential (MMP) and cytosolic Ca2+ levels are increased upon removal of TC. Our bivalent compound 17MN can reverse such changes and protect MC65 cells from TC removal induced cytotoxicity. The results also suggest that 17MN may function between the Aβ species and RIPK1 in producing its neuroprotection. Colocalization studies employing a fluorescent analog of 17MN and confocal microscopy demonstrated the interactions of 17MN with both mitochondria and endoplasmic reticulum (ER), thus suggesting that 17MN exerts its neuroprotection via a multiple-site mechanism in MC65 cells. Collectively, these results strongly support our original design rationale of bivalent compounds and encourage further optimization of this bivalent strategy to develop more potent analogs as novel disease-modifying agents for AD. PMID:26401780

Understanding disease processes in multiple sclerosis through magnetic resonance imaging studies in animal models

PubMed Central

Nathoo, Nabeela; Yong, V. Wee; Dunn, Jeff F.

2014-01-01

There are exciting new advances in multiple sclerosis (MS) resulting in a growing understanding of both the complexity of the disorder and the relative involvement of grey matter, white matter and inflammation. Increasing need for preclinical imaging is anticipated, as animal models provide insights into the pathophysiology of the disease. Magnetic resonance (MR) is the key imaging tool used to diagnose and to monitor disease progression in MS, and thus will be a cornerstone for future research. Although gadolinium-enhancing and T2 lesions on MRI have been useful for detecting MS pathology, they are not correlative of disability. Therefore, new MRI methods are needed. Such methods require validation in animal models. The increasing necessity for MRI of animal models makes it critical and timely to understand what research has been conducted in this area and what potential there is for use of MRI in preclinical models of MS. Here, we provide a review of MRI and magnetic resonance spectroscopy (MRS) studies that have been carried out in animal models of MS that focus on pathology. We compare the MRI phenotypes of animals and patients and provide advice on how best to use animal MR studies to increase our understanding of the linkages between MR and pathology in patients. This review describes how MRI studies of animal models have been, and will continue to be, used in the ongoing effort to understand MS. PMID:24936425

Dietary Phosphorus Intake and the Kidney

PubMed Central

Chang, Alex R.; Anderson, Cheryl

2017-01-01

Although phosphorus is an essential nutrient required for multiple physiological functions, recent research raises concerns that high phosphorus intake could have detrimental effects on health. Phosphorus is abundant in the food supply of developed countries, occurring naturally in protein-rich foods and as an additive in processed foods. High phosphorus intake can cause vascular and renal calcification, renal tubular injury, and premature death in multiple animal models. Small studies in human suggest that high phosphorus intake may result in positive phosphorus balance and correlate with renal calcification and albuminuria. Although serum phosphorus is strongly associated with cardiovascular disease, progression of kidney disease, and death, limited data exist linking high phosphorus intake directly to adverse clinical outcomes. Further prospective studies are needed to determine whether phosphorus intake is a modifiable risk factor for kidney disease. PMID:28613982

Dantrolene, a treatment for Alzheimer disease?

PubMed

Liang, Li; Wei, Huafeng

2015-01-01

Alzheimer disease (AD) is a fatal progressive disease and the most common form of dementia without effective treatments. Previous studies support that the disruption of endoplasmic reticulum Ca through overactivation of ryanodine receptors plays an important role in the pathogenesis of AD. Normalization of intracellular Ca homeostasis could be an effective strategy for AD therapies. Dantrolene, an antagonist of ryanodine receptors and an FDA-approved drug for clinical treatment of malignant hyperthermia and muscle spasms, exhibits neuroprotective effects in multiple models of neurodegenerative disorders. Recent preclinical studies consistently support the therapeutic effects of dantrolene in various types of AD animal models and were summarized in the current review.

Protective effects of fisetin and other berry flavonoids in Parkinson's disease.

PubMed

Maher, Pamela

2017-09-20

Parkinson's disease (PD) is an age-associated degenerative disease of the midbrain that results from the loss of dopaminergic neurons in the substantia nigra. It initially presents as a movement disorder with cognitive and other behavioral problems appearing later in the progression of the disease. Current therapies for PD only delay the onset or reduce the motor symptoms. There are no treatments to stop the nerve cell death or to cure the disease. It is becoming increasingly clear that neurological diseases such as PD are multi-factorial involving disruptions in multiple cellular systems. Thus, it is unlikely that modulating only a single factor will be effective at either preventing disease development or slowing disease progression. A better approach is to identify small molecules that have multiple biological activities relevant to the maintenance of brain function. Flavonoids are polyphenolic compounds that are widely distributed in fruits and vegetables and therefore regularly consumed in the human diet. While flavonoids were historically characterized on the basis of their antioxidant and free radical scavenging effects, more recent studies have shown that flavonoids have a wide range of activities that could make them particularly effective as agents for the treatment of PD. In this article, the multiple physiological benefits of flavonoids in the context of PD are first reviewed. Then, the evidence for the beneficial effects of the flavonol fisetin in models of PD are discussed. These results, coupled with the known actions of fisetin, suggest that it could reduce the impact of PD on brain function.

A fast and high performance multiple data integration algorithm for identifying human disease genes

PubMed Central

2015-01-01

Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620

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

PubMed Central

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

2015-01-01

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. PMID:25843376

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

PubMed

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.

Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

PubMed

Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

2013-01-01

DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

Experimental anti-GBM nephritis as an analytical tool for studying spontaneous lupus nephritis.

PubMed

Du, Yong; Fu, Yuyang; Mohan, Chandra

2008-01-01

Systemic lupus erythematosus (SLE) is an autoimmune disease that results in immune-mediated damage to multiple organs. Among these, kidney involvement is the most common and fatal. Spontaneous lupus nephritis (SLN) in mouse models has provided valuable insights into the underlying mechanisms of human lupus nephritis. However, SLN in mouse models takes 6-12 months to manifest; hence there is clearly the need for a mouse model that can be used to unveil the pathogenic processes that lead to immune nephritis over a shorter time frame. In this article more than 25 different molecules are reviewed that have been studied both in the anti-glomerular basement membrane (anti-GBM) model and in SLN and it was found that these molecules influence both diseases in a parallel fashion, suggesting that the two disease settings share common molecular mechanisms. Based on these observations, the authors believe the experimental anti-GBM disease model might be one of the best tools currently available for uncovering the downstream molecular mechanisms leading to SLN.

Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

PubMed Central

Yamakado, Minoru; Nagao, Kenji; Imaizumi, Akira; Tani, Mizuki; Toda, Akiko; Tanaka, Takayuki; Jinzu, Hiroko; Miyano, Hiroshi; Yamamoto, Hiroshi; Daimon, Takashi; Horimoto, Katsuhisa; Ishizaka, Yuko

2015-01-01

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

Treatment of a multiple sclerosis animal model by a novel nanodrop formulation of a natural antioxidant

PubMed Central

Binyamin, Orli; Larush, Liraz; Frid, Kati; Keller, Guy; Friedman-Levi, Yael; Ovadia, Haim; Abramsky, Oded; Magdassi, Shlomo; Gabizon, Ruth

2015-01-01

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system and is associated with demyelination, neurodegeneration, and sensitivity to oxidative stress. In this work, we administered a nanodroplet formulation of pomegranate seed oil (PSO), denominated Nano-PSO, to mice induced for experimental autoimmune encephalomyelitis (EAE), an established model of MS. PSO comprises high levels of punicic acid, a unique polyunsaturated fatty acid considered as one of the strongest natural antioxidants. We show here that while EAE-induced mice treated with natural PSO presented some reduction in disease burden, this beneficial effect increased significantly when EAE mice were treated with Nano-PSO of specific size nanodroplets at much lower concentrations of the oil. Pathological examinations revealed that Nano-PSO administration dramatically reduced demyelination and oxidation of lipids in the brains of the affected animals, which are hallmarks of this severe neurological disease. We propose that novel formulations of natural antioxidants such as Nano-PSO may be considered for the treatment of patients suffering from demyelinating diseases. On the mechanistic side, our results demonstrate that lipid oxidation may be a seminal feature in both demyelination and neurodegeneration. PMID:26648720

Novel test of motor and other dysfunctions in mouse neurological disease models.

PubMed

Barth, Albert M I; Mody, Istvan

2014-01-15

Just like human neurological disorders, corresponding mouse models present multiple deficiencies. Estimating disease progression or potential treatment effectiveness in such models necessitates the use of time consuming and multiple tests usually requiring a large number of scarcely available genetically modified animals. Here we present a novel and simple single camera arrangement and analysis software for detailed motor function evaluation in mice walking on a wire mesh that provides complex 3D information (instantaneous position, speed, distance traveled, foot fault depth, duration, location, relationship to speed of movement, etc.). We investigated 3 groups of mice with various neurological deficits: (1) unilateral motor cortical stroke; (2) effects of moderate ethanol doses; and (3) aging (96-99 weeks old). We show that post stroke recovery can be divided into separate stages based on strikingly different characteristics of motor function deficits, some resembling the human motor neglect syndrome. Mice treated with moderate dose of alcohol and aged mice showed specific motor and exploratory deficits. Other tests rely either partially or entirely on manual video analysis introducing a significant subjective component into the analysis, and analyze a single aspect of motor function. Our novel experimental approach provides qualitatively new, complex information about motor impairments and locomotor/exploratory activity. It should be useful for the detailed characterization of a broad range of human neurological disease models in mice, and for the more accurate assessment of disease progression or treatment effectiveness. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

PubMed

Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V

2013-09-01

Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.

Influence of laser irradiation on demyelination of nervous fibers

NASA Astrophysics Data System (ADS)

Melnik, Nataly O.; Plaksij, Yu. S.; Mamilov, Serge A.

2000-11-01

Problem demyelinating diseases from actual in modern of neurology. Main disease of this group - multiple sclerosis, which morphological manifestation is the process demyelineation - disintegration of myelin, which covers axial cylinders of nervous filaments. The outcome of such damage is violation of realization of nervous impulses, dissonance of implement and coordination functions. Most typical the feature of a multiple sclerosis is origin of repeated remissions, which compact with indication remyelination. In development of disease the large role is played by modifications of immunological of a reactivity of an organism. The purpose of the title is development of new methods of treatment of a multiple sclerosis because of lasertherapy. For thsi purpose the influence of a laser exposure on demyelination and remyelination processes will be investigated, is investigated pathological fabrics at microscopic and submicroscopic levels. The study of proceses demyelination and remyelination will be conducted on experimental animals (rats), which are sick experimental allergic encephalomyelitis (EAE), that is the most adequate model of a multiple sclerosis. The patients' EAE animals will be subjected to treatment by a laser exposure. For want of it there will be determinate optimum lengths of waves, dozes and modes of laser radiation.

Merits and complexities of modeling multiple sclerosis in non-human primates: implications for drug discovery.

PubMed

't Hart, Bert A; Laman, Jon D; Kap, Yolanda S

2018-05-01

The translation of scientific discoveries made in animal models into effective treatments for patients often fails, indicating that currently used disease models in preclinical research are insufficiently predictive for clinical success. An often-used model in the preclinical research of autoimmune neurological diseases, multiple sclerosis in particular, is experimental autoimmune encephalomyelitis (EAE). Most EAE models are based on genetically susceptible inbred/SPF mouse strains used at adolescent age (10-12 weeks), which lack exposure to genetic and microbial factors which shape the human immune system. Areas covered: Herein, the authors ask whether an EAE model in adult non-human primates from an outbred conventionally-housed colony could help bridge the translational gap between rodent EAE models and MS patients. Particularly, the authors discuss a novel and translationally relevant EAE model in common marmosets (Callithrix jacchus) that shares remarkable pathological similarity with MS. Expert opinion: The MS-like pathology in this model is caused by the interaction of effector memory T cells with B cells infected with the γ1-herpesvirus (CalHV3), both present in the pathogen-educated marmoset immune repertoire. The authors postulate that depletion of only the small subset (<0.05%) of CalHV3-infected B cells may be sufficient to limit chronic inflammatory demyelination.

Pharmacokinetic/pharmacodynamic modelling approaches in paediatric infectious diseases and immunology☆

PubMed Central

Barker, Charlotte I.S.; Germovsek, Eva; Hoare, Rollo L.; Lestner, Jodi M.; Lewis, Joanna; Standing, Joseph F.

2014-01-01

Pharmacokinetic/pharmacodynamic (PKPD) modelling is used to describe and quantify dose–concentration–effect relationships. Within paediatric studies in infectious diseases and immunology these methods are often applied to developing guidance on appropriate dosing. In this paper, an introduction to the field of PKPD modelling is given, followed by a review of the PKPD studies that have been undertaken in paediatric infectious diseases and immunology. The main focus is on identifying the methodological approaches used to define the PKPD relationship in these studies. The major findings were that most studies of infectious diseases have developed a PK model and then used simulations to define a dose recommendation based on a pre-defined PD target, which may have been defined in adults or in vitro. For immunological studies much of the modelling has focused on either PK or PD, and since multiple drugs are usually used, delineating the relative contributions of each is challenging. The use of dynamical modelling of in vitro antibacterial studies, and paediatric HIV mechanistic PD models linked with the PK of all drugs, are emerging methods that should enhance PKPD-based recommendations in the future. PMID:24440429

Training the Next Generation of Scientists: System Dynamics Modeling of Chagas Disease (American Trypanosomiasis) transmission.

NASA Astrophysics Data System (ADS)

Goff, P.; Hulse, A.; Harder, H. R.; Pierce, L. A.; Rizzo, D.; Hanley, J.; Orantes, L.; Stevens, L.; Justi, S.; Monroy, C.

2015-12-01

A computational simulation has been designed as an investigative case study by high school students to introduce system dynamics modeling into high school curriculum. This case study approach leads users through the forensics necessary to diagnose an unknown disease in a Central American village. This disease, Chagas, is endemic to 21 Latin American countries. The CDC estimates that of the 110 million people living in areas with the disease, 8 million are infected, with as many as 300,000 US cases. Chagas is caused by the protozoan parasite, Trypanosoma cruzi, and is spread via blood feeding insect (vectors), that feed on vertebrates and live in crevasses in the walls and roofs of adobe homes. One-third of the infected people will develop chronic Chagas who are asymptomatic for years before their heart or GI tract become enlarged resulting in death. The case study has three parts. Students play the role of WHO field investigators and work collaboratively to: 1) use genetics to identify the host(s) and vector of the disease 2) use a STELLA™ SIR (Susceptible, Infected, Recovered) system dynamics model to study Chagas at the village scale and 3) develop management strategies. The simulations identify mitigation strategies known as Ecohealth Interventions (e.g., home improvements using local materials) to help stakeholders test and compare multiple optima. High school students collaborated with researchers from the University of Vermont, Loyola University and Universidad de San Carlos, Guatemala, working in labs, interviewing researchers, and incorporating mulitple field data as part of a NSF-funded multiyear grant. The model displays stable equilibria of hosts, vectors, and disease-states. Sensitivity analyses show measures of household condition and presence of vertebrates were significant leverage points, supporting other findings by the University research team. The village-scale model explores multiple solutions to disease mitigation for the purpose of producing students who can think long-term, better understand feedbacks, and anticipate unexpected consequences associated with non-linear systems. This case study enables high school teachers to incorporate ongoing research, systems modeling, and engineering design, three core goals Next Generation Science Standards and STEM initiatives.

Older age, higher perceived disability and depressive symptoms predict the amount and severity of work-related difficulties in persons with multiple sclerosis.

PubMed

Raggi, Alberto; Giovannetti, Ambra Mara; Schiavolin, Silvia; Brambilla, Laura; Brenna, Greta; Confalonieri, Paolo Agostino; Cortese, Francesca; Frangiamore, Rita; Leonardi, Matilde; Mantegazza, Renato Emilio; Moscatelli, Marco; Ponzio, Michela; Torri Clerici, Valentina; Zaratin, Paola; De Torres, Laura

2018-04-16

This cross-sectional study aims to identify the predictors of work-related difficulties in a sample of employed persons with multiple sclerosis as addressed with the Multiple Sclerosis Questionnaire for Job Difficulties. Hierarchical linear regression analysis was conducted to identify predictors of work difficulties: predictors included demographic variables (age, formal education), disease duration and severity, perceived disability and psychological variables (cognitive dysfunction, depression and anxiety). The targets were the questionnaire's overall score and its six subscales. A total of 177 participants (108 females, aged 21-63) were recruited. Age, perceived disability and depression were direct and significant predictors of the questionnaire total score, and the final model explained 43.7% of its variation. The models built on the questionnaire's subscales show that perceived disability and depression were direct and significant predictors of most of its subscales. Our results show that, among patients with multiple sclerosis, those who were older, with higher perceived disability and higher depression symptoms have more and more severe work-related difficulties. The Multiple Sclerosis Questionnaire for Job Difficulties can be fruitfully exploited to plan tailored actions to limit the likelihood of near-future job loss in persons of working age with multiple sclerosis. Implications for rehabilitation Difficulties with work are common among people with multiple sclerosis and are usually addressed in terms of unemployment or job loss. The Multiple Sclerosis Questionnaire for Job Difficulties is a disease-specific questionnaire developed to address the amount and severity of work-related difficulties. We found that work-related difficulties were associated to older age, higher perceived disability and depressive symptoms. Mental health issues and perceived disability should be consistently included in future research targeting work-related difficulties.

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

Flowers, Elena; Froelicher, Erika Sivarajan; Aouizerat, Bradley E.

2011-01-01

Background Historically, models to describe disease were exclusively nature-based or nurture-based. Current theoretical models for complex conditions such as cardiovascular disease acknowledge the importance of both biologic and non-biologic contributors to disease. A critical feature is the occurrence of interactions between numerous risk factors for disease. The interaction between genetic (i.e. biologic, nature) and environmental (i.e. non-biologic, nurture) causes of disease is an important mechanism for understanding both the etiology and public health impact of cardiovascular disease. Objectives The purpose of this paper is to describe theoretical underpinnings of gene-environment interactions, models of interaction, methods for studying gene-environment interactions, and the related concept of interactions between epigenetic mechanisms and the environment. Discussion Advances in methods for measurement of genetic predictors of disease have enabled an increasingly comprehensive understanding of the causes of disease. In order to fully describe the effects of genetic predictors of disease, it is necessary to place genetic predictors within the context of known environmental risk factors. The additive or multiplicative effect of the interaction between genetic and environmental risk factors is often greater than the contribution of either risk factor alone. PMID:21684212

Minocycline: far beyond an antibiotic

PubMed Central

Garrido-Mesa, N; Zarzuelo, A; Gálvez, J

2013-01-01

Minocycline is a second-generation, semi-synthetic tetracycline that has been in therapeutic use for over 30 years because of its antibiotic properties against both gram-positive and gram-negative bacteria. It is mainly used in the treatment of acne vulgaris and some sexually transmitted diseases. Recently, it has been reported that tetracyclines can exert a variety of biological actions that are independent of their anti-microbial activity, including anti-inflammatory and anti-apoptotic activities, and inhibition of proteolysis, angiogenesis and tumour metastasis. These findings specifically concern to minocycline as it has recently been found to have multiple non-antibiotic biological effects that are beneficial in experimental models of various diseases with an inflammatory basis, including dermatitis, periodontitis, atherosclerosis and autoimmune disorders such as rheumatoid arthritis and inflammatory bowel disease. Of note, minocycline has also emerged as the most effective tetracycline derivative at providing neuroprotection. This effect has been confirmed in experimental models of ischaemia, traumatic brain injury and neuropathic pain, and of several neurodegenerative conditions including Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, Alzheimer's disease, multiple sclerosis and spinal cord injury. Moreover, other pre-clinical studies have shown its ability to inhibit malignant cell growth and activation and replication of human immunodeficiency virus, and to prevent bone resorption. Considering the above-mentioned findings, this review will cover the most important topics in the pharmacology of minocycline to date, supporting its evaluation as a new therapeutic approach for many of the diseases described herein. PMID:23441623

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

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

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

Validating the use of a luciferase labeled breast cancer cell line, MDA435LCC6, as a means to monitor tumor progression and to assess the therapeutic activity of an established anticancer drug, docetaxel (Dt) alone or in combination with the ILK inhibitor, QLT0267

PubMed Central

Anantha, Malathi; Warburton, Corinna; Waterhouse, Dawn; Yan, Hong; Yang, Young-joo; Strut, Dita; Osooly, Maryam; Masin, Dana; Bally, Marcel B

2011-01-01

A significant issue in drug efficacy studies is animal study design. Here we hypothesize that when evaluating new or existing therapeutics for the treatment of cancer, the location of disease burden will influence drug efficacy. To study this, female NCr nude mice were inoculated with luciferase-positive human breast cancer cells (LCC6WT-luc) orthotopically (o.t.), intraperitoneally (i.p.) or intracardiacly (i.c.) to create localized, ascites or disseminated disease, respectively. Tumor development was monitored using bioluminescence imaging. Docetaxel (Dt) pharmacokinetics and distribution to sites of tumor growth were determined. Disease progression was followed in animals treated with Dt alone and in combination with QLT0267, an integrin linked kinase inhibitor. Tumor related morbidity was most rapid when cells were inoculated i.c., where disease progression was observed in brain, ovaries, adrenal glands and lungs. Dt pharmacokinetics were comparable regardless of the model used (mean plasma AUC0–24 hrs 482.6 ng/ml*hr), however, Dt levels were lowest in those tissues developing disease following i.c. cell injection. Treatment with low dose Dt (5 mg/kg) increased overall survival and reduced tumor cell growth in all three models but the activity was greatest in mice with orthotopic tumors. Higher doses of Dt (15 mg/kg) was able to prolong survival in animals bearing i.p. tumors but not i.c. tumors. Addition of QLT0267 provided no added benefit above Dt alone in the disseminated model. These studies highlight a need for more comprehensive in vivo efficacy studies designed to assess multiple disease models and multiple endpoints, focusing analysis of drug parameters on the most chemoresistant disease. PMID:21358264

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

PubMed

Whiteaker, Jeffrey R; Zhang, Heidi; Zhao, Lei; Wang, Pei; Kelly-Spratt, Karen S; Ivey, Richard G; Piening, Brian D; Feng, Li-Chia; Kasarda, Erik; Gurley, Kay E; Eng, Jimmy K; Chodosh, Lewis A; Kemp, Christopher J; McIntosh, Martin W; Paulovich, Amanda G

2007-10-01

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

Thermoneutral housing exacerbates non-alcoholic fatty liver disease in mice and allows for sex-independent disease modeling

PubMed Central

Giles, Daniel A; Moreno-Fernandez, Maria E; Stankiewicz, Traci E; Graspeuntner, Simon; Cappelletti, Monica; Wu, David; Mukherjee, Rajib; Chan, Calvin C; Lawson, Matthew J; Klarquist, Jared; Sünderhauf, Annika; Softic, Samir; Kahn, C Ronald; Stemmer, Kerstin; Iwakura, Yoichiro; Aronow, Bruce J; Karns, Rebekah; Steinbrecher, Kris A; Karp, Christopher L; Sheridan, Rachel; Shanmukhappa, Shiva K; Reynaud, Damien; Haslam, David B; Sina, Christian; Rupp, Jan; Hogan, Simon P; Divanovic, Senad

2017-01-01

Non-alcoholic fatty liver disease (NAFLD), a common prelude to cirrhosis and hepatocellular carcinoma, is the most common chronic liver disease worldwide. Defining the molecular mechanisms underlying the pathogenesis of NAFLD has been hampered by a lack of animal models that closely recapitulate the severe end of the human disease spectrum, including bridging hepatic fibrosis. Here, we demonstrate that a novel experimental model employing thermoneutral housing, as opposed to standard housing, resulted in lower stress-driven production of corticosterone, augmented mouse proinflammatory immune responses and markedly exacerbated high fat diet (HFD)-induced NAFLD pathogenesis. Disease exacerbation at thermoneutrality was conserved across multiple mouse strains and was associated with augmented intestinal permeability, an altered microbiome and activation of inflammatory pathways associated with human disease. Depletion of Gram-negative microbiota, hematopoietic cell deletion of Toll-like receptor 4 (TLR4) and inactivation of the interleukin-17 (IL-17) axis resulted in altered immune responsiveness and protection from thermoneutral housing-driven NAFLD amplification. Finally, female mice, typically resistant to HFD-induced obesity and NAFLD, develop full-blown disease at thermoneutrality. Thus, thermoneutral housing provides a sex-independent model of exacerbated NAFLD in mice and represents a novel approach for interrogation of the cellular and molecular mechanisms underlying disease pathogenesis. PMID:28604704

A compound chimeric antigen receptor strategy for targeting multiple myeloma.

PubMed

Chen, K H; Wada, M; Pinz, K G; Liu, H; Shuai, X; Chen, X; Yan, L E; Petrov, J C; Salman, H; Senzel, L; Leung, E L H; Jiang, X; Ma, Y

2018-02-01

Current clinical outcomes using chimeric-antigen receptors (CARs) against multiple myeloma show promise in the eradication of bulk disease. However, these anti-BCMA (CD269) CARs observe relapse as a common phenomenon after treatment due to the reemergence of either antigen-positive or -negative cells. Hence, the development of improvements in CAR design to target antigen loss and increase effector cell persistency represents a critical need. Here, we report on the anti-tumor activity of a CAR T-cell possessing two complete and independent CAR receptors against the multiple myeloma antigens BCMA and CS1. We determined that the resulting compound CAR (cCAR) T-cell possesses consistent, potent and directed cytotoxicity against each target antigen population. Using multiple mouse models of myeloma and mixed cell populations, we are further able to show superior in vivo survival by directed cytotoxicity against multiple populations compared to a single-expressing CAR T-cell. These findings indicate that compound targeting of BCMA and CS1 on myeloma cells can potentially be an effective strategy for augmenting the response against myeloma bulk disease and for initiation of broader coverage CAR therapy.

CFH Variants Affect Structural and Functional Brain Changes and Genetic Risk of Alzheimer's Disease.

PubMed

Zhang, Deng-Feng; Li, Jin; Wu, Huan; Cui, Yue; Bi, Rui; Zhou, He-Jiang; Wang, Hui-Zhen; Zhang, Chen; Wang, Dong; Kong, Qing-Peng; Li, Tao; Fang, Yiru; Jiang, Tianzi; Yao, Yong-Gang

2016-03-01

The immune response is highly active in Alzheimer's disease (AD). Identification of genetic risk contributed by immune genes to AD may provide essential insight for the prognosis, diagnosis, and treatment of this neurodegenerative disease. In this study, we performed a genetic screening for AD-related top immune genes identified in Europeans in a Chinese cohort, followed by a multiple-stage study focusing on Complement Factor H (CFH) gene. Effects of the risk SNPs on AD-related neuroimaging endophenotypes were evaluated through magnetic resonance imaging scan, and the effects on AD cerebrospinal fluid biomarkers (CSF) and CFH expression changes were measured in aged and AD brain tissues and AD cellular models. Our results showed that the AD-associated top immune genes reported in Europeans (CR1, CD33, CLU, and TREML2) have weak effects in Chinese, whereas CFH showed strong effects. In particular, rs1061170 (P(meta)=5.0 × 10(-4)) and rs800292 (P(meta)=1.3 × 10(-5)) showed robust associations with AD, which were confirmed in multiple world-wide sample sets (4317 cases and 16 795 controls). Rs1061170 (P=2.5 × 10(-3)) and rs800292 (P=4.7 × 10(-4)) risk-allele carriers have an increased entorhinal thickness in their young age and a higher atrophy rate as the disease progresses. Rs800292 risk-allele carriers have higher CSF tau and Aβ levels and severe cognitive decline. CFH expression level, which was affected by the risk-alleles, was increased in AD brains and cellular models. These comprehensive analyses suggested that CFH is an important immune factor in AD and affects multiple pathological changes in early life and during disease progress.

Performance measurement for people with multiple chronic conditions: conceptual model.

PubMed

Giovannetti, Erin R; Dy, Sydney; Leff, Bruce; Weston, Christine; Adams, Karen; Valuck, Tom B; Pittman, Aisha T; Blaum, Caroline S; McCann, Barbara A; Boyd, Cynthia M

2013-10-01

Improving quality of care for people with multiple chronic conditions (MCCs) requires performance measures reflecting the heterogeneity and scope of their care. Since most existing measures are disease specific, performance measures must be refined and new measures must be developed to address the complexity of care for those with MCCs. To describe development of the Performance Measurement for People with Multiple Chronic Conditions (PM-MCC) conceptual model. Framework development and a national stakeholder panel. We used reviews of existing conceptual frameworks of performance measurement, review of the literature on MCCs, input from experts in the multistakeholder Steering Committee, and public comment. The resulting model centers on the patient and family goals and preferences for care in the context of multiple care sites and providers, the type of care they are receiving, and the national priority domains for healthcare quality measurement. This model organizes measures into a comprehensive framework and identifies areas where measures are lacking. In this context, performance measures can be prioritized and implemented at different levels, in the context of patients' overall healthcare needs.

The properties of the anti-tumor model with coupling non-Gaussian noise and Gaussian colored noise

NASA Astrophysics Data System (ADS)

Guo, Qin; Sun, Zhongkui; Xu, Wei

2016-05-01

The anti-tumor model with correlation between multiplicative non-Gaussian noise and additive Gaussian-colored noise has been investigated in this paper. The behaviors of the stationary probability distribution demonstrate that the multiplicative non-Gaussian noise plays a dual role in the development of tumor and an appropriate additive Gaussian colored noise can lead to a minimum of the mean value of tumor cell population. The mean first passage time is calculated to quantify the effects of noises on the transition time of tumors between the stable states. An increase in both the non-Gaussian noise intensity and the departure from the Gaussian noise can accelerate the transition from the disease state to the healthy state. On the contrary, an increase in cross-correlated degree will slow down the transition. Moreover, the correlation time can enhance the stability of the disease state.

Interaction Studies of Withania Somnifera's Key Metabolite Withaferin A with Different Receptors Assoociated with Cardiovascular Disease.

PubMed

Ravindran, Rekha; Sharma, Nitika; Roy, Sujata; Thakur, Ashoke R; Ganesh, Subhadra; Kumar, Sriram; Devi, Jamuna; Rajkumar, Johanna

2015-01-01

Withania somnifera commonly known as Ashwagandha in India is used in many herbal formulations to treat various cardiovascular diseases. The key metabolite of this plant, Withaferin A was analyzed for its molecular mechanism through docking studies on different targets of cardiovascular disease. Six receptor proteins associated with cardiovascular disease were selected and interaction studies were performed with Withaferin A using AutoDock Vina. CORINA was used to model the small molecules and HBAT to compute the hydrogen bonding. Among the six targets, β1- adrenergic receptors, HMG-CoA and Angiotensinogen-converting enzyme showed significant interaction with Withaferin A. Pharmacophore modeling was done using PharmaGist to understand the pharmacophoric potential of Withaferin A. Clustering of Withaferin A with different existing drug molecules for cardiovascular disease was performed with ChemMine based on structural similarity and physicochemical properties. The ability of natural active component, Withaferin A to interact with different receptors associated with cardiovascular disease was elucidated with various modeling techniques. These studies conclusively revealed Withaferin A as a potent lead compound against multiple targets associated with cardiovascular disease.

Neuropathic pain in a Fabry disease rat model

PubMed Central

Miller, James J.; Aoki, Kazuhiro; Murphy, Carly A.; O’Hara, Crystal L.; Tiemeyer, Michael; Stucky, Cheryl L.; Dahms, Nancy M.

2018-01-01

Fabry disease, the most common lysosomal storage disease, affects multiple organs and results in a shortened life span. This disease is caused by a deficiency of the lysosomal enzyme α-galactosidase A, which leads to glycosphingolipid accumulation in many cell types. Neuropathic pain is an early and severely debilitating symptom in patients with Fabry disease, but the cellular and molecular mechanisms that cause the pain are unknown. We generated a rat model of Fabry disease, the first nonmouse model to our knowledge. Fabry rats had substantial serum and tissue accumulation of α-galactosyl glycosphingolipids and had pronounced mechanical pain behavior. Additionally, Fabry rat dorsal root ganglia displayed global N-glycan alterations, sensory neurons were laden with inclusions, and sensory neuron somata exhibited prominent sensitization to mechanical force. We found that the cation channel transient receptor potential ankyrin 1 (TRPA1) is sensitized in Fabry rat sensory neurons and that TRPA1 antagonism reversed the behavioral mechanical sensitization. This study points toward TRPA1 as a potentially novel target to treat the pain experienced by patients with Fabry disease. PMID:29563343

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

PubMed

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.

The Role of C-Peptide as Marker of Cardiometabolic Risk in Women With Polycystic Ovary Syndrome: A Controlled Study

PubMed Central

de Medeiros, Sebastiao Freitas; Angelo, Laura Camila Antunes; de Medeiros, Matheus Antonio Souto; Banhara, Camila Regis; Barbosa, Bruna Barcelo; Yamamoto, Marcia Marly Winck

2018-01-01

Background The aim of this study was to examine the role of C-peptide as a biological marker of cardiometabolic risk in polycystic ovary syndrome (PCOS). Methods This case-control study enrolled 385 PCOS patients and 240 normal cycling women. Anthropometric and clinical variables were taken at first visit. Fasting C-peptide, glucose, lipids, and hormone measurements were performed. Simple and multiple correlations between C-peptide and other variables associated with dysmetabolism and cardiovascular disease were examined. Results C-peptide was well correlated with several anthropometric, metabolic, and endocrine parameters. In PCOS patients, stepwise multiple regression including C-peptide as the criterion variable and other predictors of cardiovascular disease risk provided a significant model in which the fasting C-peptide/glucose ratio, glucose, body weight, and free estrogen index (FEI) were retained (adjusted R2 = 0.988, F = 7.161, P = 0.008). Conclusion C-peptide levels alone or combined with C-peptide/glucose ratio, glucose, body weight, and FEI provided a significant model to identify PCOS patients with higher risk of future cardiometabolic diseases. PMID:29416587

Towards a 21st century roadmap for biomedical research and ...

EPA Pesticide Factsheets

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies and the corporate and NGO sectors, this consensus report analyses, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathways-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this. To discover and develop new therapies, we need 21-century roadmaps for biomedical research based on multiscale human disease pathways, and supported by policy and funding strategies that prioritise human relevance.

Multiple templates-based homology modeling enhances structure quality of AT1 receptor: validation by molecular dynamics and antagonist docking.

PubMed

Sokkar, Pandian; Mohandass, Shylajanaciyar; Ramachandran, Murugesan

2011-07-01

We present a comparative account on 3D-structures of human type-1 receptor (AT1) for angiotensin II (AngII), modeled using three different methodologies. AngII activates a wide spectrum of signaling responses via the AT1 receptor that mediates physiological control of blood pressure and diverse pathological actions in cardiovascular, renal, and other cell types. Availability of 3D-model of AT1 receptor would significantly enhance the development of new drugs for cardiovascular diseases. However, templates of AT1 receptor with low sequence similarity increase the complexity in straightforward homology modeling, and hence there is a need to evaluate different modeling methodologies in order to use the models for sensitive applications such as rational drug design. Three models were generated for AT1 receptor by, (1) homology modeling with bovine rhodopsin as template, (2) homology modeling with multiple templates and (3) threading using I-TASSER web server. Molecular dynamics (MD) simulation (15 ns) of models in explicit membrane-water system, Ramachandran plot analysis and molecular docking with antagonists led to the conclusion that multiple template-based homology modeling outweighs other methodologies for AT1 modeling.

Patients' Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test.

PubMed

Dou, Kaili; Yu, Ping; Deng, Ning; Liu, Fang; Guan, YingPing; Li, Zhenye; Ji, Yumeng; Du, Ningkai; Lu, Xudong; Duan, Huilong

2017-12-06

Chronic disease patients often face multiple challenges from difficult comorbidities. Smartphone health technology can be used to help them manage their conditions only if they accept and use the technology. The aim of this study was to develop and test a theoretical model to predict and explain the factors influencing patients' acceptance of smartphone health technology for chronic disease management. Multiple theories and factors that may influence patients' acceptance of smartphone health technology have been reviewed. A hybrid theoretical model was built based on the technology acceptance model, dual-factor model, health belief model, and the factors identified from interviews that might influence patients' acceptance of smartphone health technology for chronic disease management. Data were collected from patient questionnaire surveys and computer log records about 157 hypertensive patients' actual use of a smartphone health app. The partial least square method was used to test the theoretical model. The model accounted for .412 of the variance in patients' intention to adopt the smartphone health technology. Intention to use accounted for .111 of the variance in actual use and had a significant weak relationship with the latter. Perceived ease of use was affected by patients' smartphone usage experience, relationship with doctor, and self-efficacy. Although without a significant effect on intention to use, perceived ease of use had a significant positive influence on perceived usefulness. Relationship with doctor and perceived health threat had significant positive effects on perceived usefulness, countering the negative influence of resistance to change. Perceived usefulness, perceived health threat, and resistance to change significantly predicted patients' intentions to use the technology. Age and gender had no significant influence on patients' acceptance of smartphone technology. The study also confirmed the positive relationship between intention to use and actual use of smartphone health apps for chronic disease management. This study developed a theoretical model to predict patients' acceptance of smartphone health technology for chronic disease management. Although resistance to change is a significant barrier to technology acceptance, careful management of doctor-patient relationship, and raising patients' awareness of the negative effect of chronic disease can negate the effect of resistance and encourage acceptance and use of smartphone health technology to support chronic disease management for patients in the community. ©Kaili Dou, Ping Yu, Ning Deng, Fang Liu, YingPing Guan, Zhenye Li, Yumeng Ji, Ningkai Du, Xudong Lu, Huilong Duan. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 06.12.2017.

Helminthic therapy: using worms to treat immune-mediated disease.

PubMed

Elliott, David E; Weinstock, Joel V

2009-01-01

There is an epidemic of immune-mediated disease in highly-developed industrialized countries. Such diseases, like inflammatory bowel disease, multiple sclerosis and asthma increase in prevalence as populations adopt modern hygienic practices. These practices prevent exposure to parasitic worms (helminths). Epidemiologic studies suggest that people who carry helminths have less immune-mediated disease. Mice colonized with helminths are protected from disease in models of colitis, encephalitis, Type 1 diabetes and asthma. Clinical trials show that exposure to helminths reduce disease activity in patients with ulcerative colitis or Crohn's disease. This chapter reviews some of the work showing that colonization with helminths alters immune responses, against dysregulated inflammation. These helminth-host immune interactions have potentially important implications for the treatment of immune-mediated diseases.

A conceptual framework for a long-term economic model for the treatment of attention-deficit/hyperactivity disorder.

PubMed

Nagy, Balázs; Setyawan, Juliana; Coghill, David; Soroncz-Szabó, Tamás; Kaló, Zoltán; Doshi, Jalpa A

2017-06-01

Models incorporating long-term outcomes (LTOs) are not available to assess the health economic impact of attention-deficit/hyperactivity disorder (ADHD). Develop a conceptual modelling framework capable of assessing long-term economic impact of ADHD therapies. Literature was reviewed; a conceptual structure for the long-term model was outlined with attention to disease characteristics and potential impact of treatment strategies. The proposed model has four layers: i) multi-state short-term framework to differentiate between ADHD treatments; ii) multiple states being merged into three core health states associated with LTOs; iii) series of sub-models in which particular LTOs are depicted; iv) outcomes collected to be either used directly for economic analyses or translated into other relevant measures. This conceptual model provides a framework to assess relationships between short- and long-term outcomes of the disease and its treatment, and to estimate the economic impact of ADHD treatments throughout the course of the disease.

A method for detecting IBD regions simultaneously in multiple individuals—with applications to disease genetics

PubMed Central

Moltke, Ida; Albrechtsen, Anders; Hansen, Thomas v.O.; Nielsen, Finn C.; Nielsen, Rasmus

2011-01-01

All individuals in a finite population are related if traced back long enough and will, therefore, share regions of their genomes identical by descent (IBD). Detection of such regions has several important applications—from answering questions about human evolution to locating regions in the human genome containing disease-causing variants. However, IBD regions can be difficult to detect, especially in the common case where no pedigree information is available. In particular, all existing non-pedigree based methods can only infer IBD sharing between two individuals. Here, we present a new Markov Chain Monte Carlo method for detection of IBD regions, which does not rely on any pedigree information. It is based on a probabilistic model applicable to unphased SNP data. It can take inbreeding, allele frequencies, genotyping errors, and genomic distances into account. And most importantly, it can simultaneously infer IBD sharing among multiple individuals. Through simulations, we show that the simultaneous modeling of multiple individuals makes the method more powerful and accurate than several other non-pedigree based methods. We illustrate the potential of the method by applying it to data from individuals with breast and/or ovarian cancer, and show that a known disease-causing mutation can be mapped to a 2.2-Mb region using SNP data from only five seemingly unrelated affected individuals. This would not be possible using classical linkage mapping or association mapping. PMID:21493780

Innovations in Clinical Trial Design in the Era of Molecular Profiling.

PubMed

Wulfkuhle, Julia D; Spira, Alexander; Edmiston, Kirsten H; Petricoin, Emanuel F

2017-01-01

Historically, cancer has been studied, and therapeutic agents have been evaluated based on organ site, clinical staging, and histology. The science of molecular profiling has expanded our knowledge of cancer at the cellular and molecular level such that numerous subtypes are being described based on biomarker expression and genetic mutations rather than traditional classifications of the disease. Drug development has experienced a concomitant revolution in response to this knowledge with many new targeted therapeutic agents becoming available, and this has necessitated an evolution in clinical trial design. The traditional, large phase II and phase III adjuvant trial models need to be replaced with smaller, shorter, and more focused trials. These trials need to be more efficient and adaptive in order to quickly assess the efficacy of new agents and develop new companion diagnostics. We are now seeing a substantial shift from the traditional multiphase trial model to an increase in phase II adjuvant and neoadjuvant trials in earlier-stage disease incorporating surrogate endpoints for long-term survival to assess efficacy of therapeutic agents in shorter time frames. New trial designs have emerged with capabilities to assess more efficiently multiple disease types, multiple molecular subtypes, and multiple agents simultaneously, and regulatory agencies have responded by outlining new pathways for accelerated drug approval that can help bring effective targeted therapeutic agents to the clinic more quickly for patients in need.

The power to detect linkage in complex disease by means of simple LOD-score analyses.

PubMed Central

Greenberg, D A; Abreu, P; Hodge, S E

1998-01-01

Maximum-likelihood analysis (via LOD score) provides the most powerful method for finding linkage when the mode of inheritance (MOI) is known. However, because one must assume an MOI, the application of LOD-score analysis to complex disease has been questioned. Although it is known that one can legitimately maximize the maximum LOD score with respect to genetic parameters, this approach raises three concerns: (1) multiple testing, (2) effect on power to detect linkage, and (3) adequacy of the approximate MOI for the true MOI. We evaluated the power of LOD scores to detect linkage when the true MOI was complex but a LOD score analysis assumed simple models. We simulated data from 14 different genetic models, including dominant and recessive at high (80%) and low (20%) penetrances, intermediate models, and several additive two-locus models. We calculated LOD scores by assuming two simple models, dominant and recessive, each with 50% penetrance, then took the higher of the two LOD scores as the raw test statistic and corrected for multiple tests. We call this test statistic "MMLS-C." We found that the ELODs for MMLS-C are >=80% of the ELOD under the true model when the ELOD for the true model is >=3. Similarly, the power to reach a given LOD score was usually >=80% that of the true model, when the power under the true model was >=60%. These results underscore that a critical factor in LOD-score analysis is the MOI at the linked locus, not that of the disease or trait per se. Thus, a limited set of simple genetic models in LOD-score analysis can work well in testing for linkage. PMID:9718328

The power to detect linkage in complex disease by means of simple LOD-score analyses.

PubMed

Greenberg, D A; Abreu, P; Hodge, S E

1998-09-01

Maximum-likelihood analysis (via LOD score) provides the most powerful method for finding linkage when the mode of inheritance (MOI) is known. However, because one must assume an MOI, the application of LOD-score analysis to complex disease has been questioned. Although it is known that one can legitimately maximize the maximum LOD score with respect to genetic parameters, this approach raises three concerns: (1) multiple testing, (2) effect on power to detect linkage, and (3) adequacy of the approximate MOI for the true MOI. We evaluated the power of LOD scores to detect linkage when the true MOI was complex but a LOD score analysis assumed simple models. We simulated data from 14 different genetic models, including dominant and recessive at high (80%) and low (20%) penetrances, intermediate models, and several additive two-locus models. We calculated LOD scores by assuming two simple models, dominant and recessive, each with 50% penetrance, then took the higher of the two LOD scores as the raw test statistic and corrected for multiple tests. We call this test statistic "MMLS-C." We found that the ELODs for MMLS-C are >=80% of the ELOD under the true model when the ELOD for the true model is >=3. Similarly, the power to reach a given LOD score was usually >=80% that of the true model, when the power under the true model was >=60%. These results underscore that a critical factor in LOD-score analysis is the MOI at the linked locus, not that of the disease or trait per se. Thus, a limited set of simple genetic models in LOD-score analysis can work well in testing for linkage.

Dynamics of tuberculosis transmission with exogenous reinfections and endogenous reactivation

NASA Astrophysics Data System (ADS)

Khajanchi, Subhas; Das, Dhiraj Kumar; Kar, Tapan Kumar

2018-05-01

We propose and analyze a mathematical model for tuberculosis (TB) transmission to study the role of exogenous reinfection and endogenous reactivation. The model exhibits two equilibria: a disease free and an endemic equilibria. We observe that the TB model exhibits transcritical bifurcation when basic reproduction number R0 = 1. Our results demonstrate that the disease transmission rate β and exogenous reinfection rate α plays an important role to change the qualitative dynamics of TB. The disease transmission rate β give rises to the possibility of backward bifurcation for R0 < 1, and hence the existence of multiple endemic equilibria one of which is stable and another one is unstable. Our analysis suggests that R0 < 1 may not be sufficient to completely eliminate the disease. We also investigate that our TB transmission model undergoes Hopf-bifurcation with respect to the contact rate β and the exogenous reinfection rate α. We conducted some numerical simulations to support our analytical findings.

Role of FGF/FGFR signaling in skeletal development and homeostasis: learning from mouse models

PubMed Central

Su, Nan; Jin, Min; Chen, Lin

2014-01-01

Fibroblast growth factor (FGF)/fibroblast growth factor receptor (FGFR) signaling plays essential roles in bone development and diseases. Missense mutations in FGFs and FGFRs in humans can cause various congenital bone diseases, including chondrodysplasia syndromes, craniosynostosis syndromes and syndromes with dysregulated phosphate metabolism. FGF/FGFR signaling is also an important pathway involved in the maintenance of adult bone homeostasis. Multiple kinds of mouse models, mimicking human skeleton diseases caused by missense mutations in FGFs and FGFRs, have been established by knock-in/out and transgenic technologies. These genetically modified mice provide good models for studying the role of FGF/FGFR signaling in skeleton development and homeostasis. In this review, we summarize the mouse models of FGF signaling-related skeleton diseases and recent progresses regarding the molecular mechanisms, underlying the role of FGFs/FGFRs in the regulation of bone development and homeostasis. This review also provides a perspective view on future works to explore the roles of FGF signaling in skeletal development and homeostasis. PMID:26273516

On the intrinsic dynamics of bacteria in waterborne infections.

PubMed

Yang, Chayu; Wang, Jin

2018-02-01

The intrinsic dynamics of bacteria often play an important role in the transmission and spread of waterborne infectious diseases. In this paper, we construct mathematical models for waterborne infections and analyze two types of nontrivial bacterial dynamics: logistic growth, and growth with Allee effects. For the model with logistic growth, we find that regular threshold dynamics take place, and the basic reproduction number can be used to characterize disease extinction and persistence. In contrast, the model with Allee effects exhibits much more complex dynamics, including the existence of multiple endemic equilibria and the presence of backward bifurcation and forward hysteresis. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling Alzheimer's disease cognitive scores using multi-task sparse group lasso.

PubMed

Liu, Xiaoli; Goncalves, André R; Cao, Peng; Zhao, Dazhe; Banerjee, Arindam

2018-06-01

Alzheimer's disease (AD) is a severe neurodegenerative disorder characterized by loss of memory and reduction in cognitive functions due to progressive degeneration of neurons and their connections, eventually leading to death. In this paper, we consider the problem of simultaneously predicting several different cognitive scores associated with categorizing subjects as normal, mild cognitive impairment (MCI), or Alzheimer's disease (AD) in a multi-task learning framework using features extracted from brain images obtained from ADNI (Alzheimer's Disease Neuroimaging Initiative). To solve the problem, we present a multi-task sparse group lasso (MT-SGL) framework, which estimates sparse features coupled across tasks, and can work with loss functions associated with any Generalized Linear Models. Through comparisons with a variety of baseline models using multiple evaluation metrics, we illustrate the promising predictive performance of MT-SGL on ADNI along with its ability to identify brain regions more likely to help the characterization Alzheimer's disease progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gene genealogies for genetic association mapping, with application to Crohn's disease

PubMed Central

Burkett, Kelly M.; Greenwood, Celia M. T.; McNeney, Brad; Graham, Jinko

2013-01-01

A gene genealogy describes relationships among haplotypes sampled from a population. Knowledge of the gene genealogy for a set of haplotypes is useful for estimation of population genetic parameters and it also has potential application in finding disease-predisposing genetic variants. As the true gene genealogy is unknown, Markov chain Monte Carlo (MCMC) approaches have been used to sample genealogies conditional on data at multiple genetic markers. We previously implemented an MCMC algorithm to sample from an approximation to the distribution of the gene genealogy conditional on haplotype data. Our approach samples ancestral trees, recombination and mutation rates at a genomic focal point. In this work, we describe how our sampler can be used to find disease-predisposing genetic variants in samples of cases and controls. We use a tree-based association statistic that quantifies the degree to which case haplotypes are more closely related to each other around the focal point than control haplotypes, without relying on a disease model. As the ancestral tree is a latent variable, so is the tree-based association statistic. We show how the sampler can be used to estimate the posterior distribution of the latent test statistic and corresponding latent p-values, which together comprise a fuzzy p-value. We illustrate the approach on a publicly-available dataset from a study of Crohn's disease that consists of genotypes at multiple SNP markers in a small genomic region. We estimate the posterior distribution of the tree-based association statistic and the recombination rate at multiple focal points in the region. Reassuringly, the posterior mean recombination rates estimated at the different focal points are consistent with previously published estimates. The tree-based association approach finds multiple sub-regions where the case haplotypes are more genetically related than the control haplotypes, and that there may be one or multiple disease-predisposing loci. PMID:24348515

The imbalance between regulatory and IL-17-secreting CD4⁺T cells in multiple-trauma rat.

PubMed

Dai, Heling; Sun, Tiansheng; Liu, Zhi; Zhang, Jianzheng; Zhou, Meng

2013-11-01

It has been well recognised that a deficit of numbers and function of CD4(+)CD25(+)Foxp3(+)cells (Treg) is attributed to the development of auto-immune diseases, inflammatory diseases, tumour and rejection of transplanted tissue; however, there are controversial data regarding the suppressive effect of Treg cells on the T-cell response in auto-immune diseases. Additionally, interleukin-17 (IL-17)-producing cells (Th17) have a pro-inflammatory role. The balance between Th17 and Treg may be essential for maintaining immune homeostasis and has long been thought as one of the important factors in the development/prevention of auto-immune diseases, inflammatory diseases, tumour and rejection of transplanted tissue, but their role in multiple trauma remains unclear. This study aims to investigate whether an imbalance of Treg and Th17 effector cells is characteristic of rats suffering from multiple trauma. Sixty Sprague-Dawley (SD) rats were randomly divided into three groups. The control group (n=20, group I) no received procedures (normal). The sham group (n=20, group II) only received anaesthesia, cannulation and observation. The bilateral femoral shaft fractures with haemorrhagic shock groups (n=20, group III). Rats in groups II and III were killed at the end of 4h after models were established. Peripheral blood samples were collected for assessment of Treg cells, Th17 cells and cytokines (IL-17, IL-6, IL-2, transforming growth factor beta (TGF-β)) and intestine tissue was collected for intestine histological analysis. We observed decreased Treg/Th17 ratios in CD4(+)T cells in rats with multiple trauma and a strong inverse correlation with disease activity (intestinal histological scores). We suggest a role for immune imbalance in the pathogenesis and development of multiple trauma. The alteration of the index of Treg/Th17 cells likely indicates the therapeutic response and progress in the clinic. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

Synergistic induction of apoptosis in multiple myeloma cells by bortezomib and hypoxia-activated prodrug TH-302, in vivo and in vitro.

PubMed

Hu, Jinsong; Van Valckenborgh, Els; Xu, Dehui; Menu, Eline; De Raeve, Hendrik; De Bruyne, Elke; De Bryune, Elke; Xu, Song; Van Camp, Ben; Handisides, Damian; Hart, Charles P; Vanderkerken, Karin

2013-09-01

Recently, we showed that hypoxia is a critical microenvironmental factor in multiple myeloma, and that the hypoxia-activated prodrug TH-302 selectively targets hypoxic multiple myeloma cells and improves multiple disease parameters in vivo. To explore approaches for sensitizing multiple myeloma cells to TH-302, we evaluated in this study the antitumor effect of TH-302 in combination with the clinically used proteasome inhibitor bortezomib. First, we show that TH-302 and bortezomib synergistically induce apoptosis in multiple myeloma cell lines in vitro. Second, we confirm that this synergism is related to the activation of caspase cascades and is mediated by changes of Bcl-2 family proteins. The combination treatment induces enhanced cleavage of caspase-3/8/9 and PARP, and therefore triggers apoptosis and enhances the cleavage of proapoptotic BH3-only protein BAD and BID as well as the antiapoptotic protein Mcl-1. In particular, TH-302 can abrogate the accumulation of antiapoptotic Mcl-1 induced by bortezomib, and decreases the expression of the prosurvival proteins Bcl-2 and Bcl-xL. Furthermore, we found that the induction of the proapoptotic BH3-only proteins PUMA (p53-upregulated modulator of apoptosis) and NOXA is associated with this synergism. In response to the genotoxic and endoplasmic reticulum stresses by TH-302 and bortezomib, the expression of PUMA and NOXA were upregulated in p53-dependent and -independent manners. Finally, in the murine 5T33MMvv model, we showed that the combination of TH-302 and bortezomib can improve multiple disease parameters and significantly prolong the survival of diseased mice. In conclusion, our studies provide a rationale for clinical evaluation of the combination of TH-302 and bortezomib in patients with multiple myeloma.

Simulating the spread of malaria using a generic transmission model for mosquito-borne infectious diseases

NASA Astrophysics Data System (ADS)

Kon, Cynthia Mui Lian; Labadin, Jane

2016-06-01

Malaria is a critical infection caused by parasites which are spread to humans through mosquito bites. Approximately half of the world's population is in peril of getting infected by malaria. Mosquito-borne diseases have a standard behavior where they are transmitted in the same manner, only through vector mosquito. Taking this into account, a generic spatial-temporal model for transmission of multiple mosquito-borne diseases had been formulated. Our interest is to reproduce the actual cases of different mosquito-borne diseases using the generic model and then predict future cases so as to improve control and target measures competently. In this paper, we utilize notified weekly malaria cases in four districts in Sarawak, Malaysia, namely Kapit, Song, Belaga and Marudi. The actual cases for 36 weeks, which is from week 39 in 2012 to week 22 in 2013, are compared with simulations of the generic spatial-temporal transmission mosquito-borne diseases model. We observe that the simulation results display corresponding result to the actual malaria cases in the four districts.

Integrated vector management: a critical strategy for combating vector-borne diseases in South Sudan.

PubMed

Chanda, Emmanuel; Govere, John M; Macdonald, Michael B; Lako, Richard L; Haque, Ubydul; Baba, Samson P; Mnzava, Abraham

2013-10-25

Integrated vector management (IVM) based vector control is encouraged by the World Health Organization (WHO). However, operational experience with the IVM strategy has mostly come from countries with relatively well-established health systems and with malaria control focused programmes. Little is known about deployment of IVM for combating multiple vector-borne diseases in post-emergency settings, where delivery structures are less developed or absent. This manuscript reports on the feasibility of operational IVM for combating vector-borne diseases in South Sudan. A methodical review of published and unpublished documents on vector-borne diseases for South Sudan was conducted via systematic literature search of online electronic databases, Google Scholar, PubMed and WHO, using a combination of search terms. Additional, non-peer reviewed literature was examined for information related to the subject. South Sudan is among the heartlands of vector-borne diseases in the world, characterized by enormous infrastructure, human and financial resource constraints and a weak health system against an increasing number of refugees, returnees and internally displaced people. The presence of a multiplicity of vector-borne diseases in this post-conflict situation presents a unique opportunity to explore the potential of a rational IVM strategy for multiple disease control and optimize limited resource utilization, while maximizing the benefits and providing a model for countries in a similar situation. The potential of integrating vector-borne disease control is enormous in South Sudan. However, strengthened coordination, intersectoral collaboration and institutional and technical capacity for entomological monitoring and evaluation, including enforcement of appropriate legislation are crucial.

Integrated vector management: a critical strategy for combating vector-borne diseases in South Sudan

PubMed Central

2013-01-01

Background Integrated vector management (IVM) based vector control is encouraged by the World Health Organization (WHO). However, operational experience with the IVM strategy has mostly come from countries with relatively well-established health systems and with malaria control focused programmes. Little is known about deployment of IVM for combating multiple vector-borne diseases in post-emergency settings, where delivery structures are less developed or absent. This manuscript reports on the feasibility of operational IVM for combating vector-borne diseases in South Sudan. Case description A methodical review of published and unpublished documents on vector-borne diseases for South Sudan was conducted via systematic literature search of online electronic databases, Google Scholar, PubMed and WHO, using a combination of search terms. Additional, non-peer reviewed literature was examined for information related to the subject. Discussion South Sudan is among the heartlands of vector-borne diseases in the world, characterized by enormous infrastructure, human and financial resource constraints and a weak health system against an increasing number of refugees, returnees and internally displaced people. The presence of a multiplicity of vector-borne diseases in this post-conflict situation presents a unique opportunity to explore the potential of a rational IVM strategy for multiple disease control and optimize limited resource utilization, while maximizing the benefits and providing a model for countries in a similar situation. Conclusion The potential of integrating vector-borne disease control is enormous in South Sudan. However, strengthened coordination, intersectoral collaboration and institutional and technical capacity for entomological monitoring and evaluation, including enforcement of appropriate legislation are crucial. PMID:24156749

Resveratrol and Alzheimer's Disease: Mechanistic Insights.

PubMed

Ahmed, Touqeer; Javed, Sehrish; Javed, Sana; Tariq, Ameema; Šamec, Dunja; Tejada, Silvia; Nabavi, Seyed Fazel; Braidy, Nady; Nabavi, Seyed Mohammad

2017-05-01

Alzheimer's disease (AD) is the leading cause of dementia in the elderly and is characterized by progressive cognitive and memory deficits. The pathological hallmarks of AD include extracellular senile plaques and intracellular neurofibrillary tangles. Although several mechanisms have been used to explain the underlying pathogenesis of AD, current treatment regimens remain inadequate. The neuroprotective effects of the polyphenolic stilbene resveratrol (3,5,4'-trihydroxy-trans-stilbene) have been investigated in several in vitro and in vivo models of AD. The current review discusses the multiple potential mechanisms of action of resveratrol on the pathobiology of AD. Moreover, due to the limited pharmacokinetic parameters of resveratrol, multiple strategies aimed at increasing the bioavailability of resveratrol have also been addressed.

Antecedents of Coping with the Disease in Patients with Multiple Sclerosis: A Qualitative Content Analysis

PubMed Central

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2017-01-01

ABSTRACT Background: Due to many physical and mental disorders that occur in multiple sclerosis patients, identifying the factors affecting coping based on the experiences of patients using qualitative study is essential to improve their quality of life. This study was conducted to explore the antecedents of coping with the disease in patients with multiple sclerosis. Methods: This is a qualitative study conducted on 11 patients with multiple sclerosis in 2015 in Tehran, Iran. These patients were selected based on purposive sampling. Data were collected using semi-structured and in-depth interviews and coded. These data were analyzed using the conventional content analysis. The rigor of qualitative data using the criteria proposed by Guba and Lincoln were assessed. Results: Five main categories were revealed: (1) social support, (2) lenience, (3) reliance on faith, (4) knowledge of multiple sclerosis and modeling, and (5) economic and environmental situation. Each category had several distinct sub-categories. Conclusions: The results of this study showed that coping with multiple sclerosis is a complex, multidimensional and contextual concept that is affected by various factors in relation to the context of Iran. The findings of the study can provide the healthcare professionals with deeper recognition and understanding of these antecedents to improve successful coping in Iranian patients suffering from multiple sclerosis. PMID:28097178

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

PubMed

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

2018-01-01

Protein misfolding refers to a process where proteins become structurally abnormal and lose their specific 3-dimensional spatial configuration. The histopathological presence of misfolded protein (MP) aggregates has been associated as the primary evidence of multiple neurological diseases, including Prion diseases, Alzheimer's disease, Parkinson's disease, and Creutzfeldt-Jacob disease. However, the exact mechanisms of MP aggregation and propagation, as well as their impact in the long-term patient's clinical condition are still not well understood. With this aim, a variety of mathematical models has been proposed for a better insight into the kinetic rate laws that govern the microscopic processes of protein aggregation. Complementary, another class of large-scale models rely on modern molecular imaging techniques for describing the phenomenological effects of MP propagation over the whole brain. Unfortunately, those neuroimaging-based studies do not take full advantage of the tremendous capabilities offered by the chemical kinetics modeling approach. Actually, it has been barely acknowledged that the vast majority of large-scale models have foundations on previous mathematical approaches that describe the chemical kinetics of protein replication and propagation. The purpose of the current manuscript is to present a historical review about the development of mathematical models for describing both microscopic processes that occur during the MP aggregation and large-scale events that characterize the progression of neurodegenerative MP-mediated diseases.

Zebrafish as a disease model for studying human hepatocellular carcinoma.

PubMed

Lu, Jeng-Wei; Ho, Yi-Jung; Yang, Yi-Ju; Liao, Heng-An; Ciou, Shih-Ci; Lin, Liang-In; Ou, Da-Liang

2015-11-14

Liver cancer is one of the world's most common cancers and the second leading cause of cancer deaths. Hepatocellular carcinoma (HCC), a primary hepatic cancer, accounts for 90%-95% of liver cancer cases. The pathogenesis of HCC consists of a stepwise process of liver damage that extends over decades, due to hepatitis, fatty liver, fibrosis, and cirrhosis before developing fully into HCC. Multiple risk factors are highly correlated with HCC, including infection with the hepatitis B or C viruses, alcohol abuse, aflatoxin exposure, and metabolic diseases. Over the last decade, genetic alterations, which include the regulation of multiple oncogenes or tumor suppressor genes and the activation of tumorigenesis-related pathways, have also been identified as important factors in HCC. Recently, zebrafish have become an important living vertebrate model organism, especially for translational medical research. In studies focusing on the biology of cancer, carcinogen induced tumors in zebrafish were found to have many similarities to human tumors. Several zebrafish models have therefore been developed to provide insight into the pathogenesis of liver cancer and the related drug discovery and toxicology, and to enable the evaluation of novel small-molecule inhibitors. This review will focus on illustrative examples involving the application of zebrafish models to the study of human liver disease and HCC, through transgenesis, genome editing technology, xenografts, drug discovery, and drug-induced toxic liver injury.

Zebrafish as a disease model for studying human hepatocellular carcinoma

PubMed Central

Lu, Jeng-Wei; Ho, Yi-Jung; Yang, Yi-Ju; Liao, Heng-An; Ciou, Shih-Ci; Lin, Liang-In; Ou, Da-Liang

2015-01-01

Liver cancer is one of the world’s most common cancers and the second leading cause of cancer deaths. Hepatocellular carcinoma (HCC), a primary hepatic cancer, accounts for 90%-95% of liver cancer cases. The pathogenesis of HCC consists of a stepwise process of liver damage that extends over decades, due to hepatitis, fatty liver, fibrosis, and cirrhosis before developing fully into HCC. Multiple risk factors are highly correlated with HCC, including infection with the hepatitis B or C viruses, alcohol abuse, aflatoxin exposure, and metabolic diseases. Over the last decade, genetic alterations, which include the regulation of multiple oncogenes or tumor suppressor genes and the activation of tumorigenesis-related pathways, have also been identified as important factors in HCC. Recently, zebrafish have become an important living vertebrate model organism, especially for translational medical research. In studies focusing on the biology of cancer, carcinogen induced tumors in zebrafish were found to have many similarities to human tumors. Several zebrafish models have therefore been developed to provide insight into the pathogenesis of liver cancer and the related drug discovery and toxicology, and to enable the evaluation of novel small-molecule inhibitors. This review will focus on illustrative examples involving the application of zebrafish models to the study of human liver disease and HCC, through transgenesis, genome editing technology, xenografts, drug discovery, and drug-induced toxic liver injury. PMID:26576090

Scan-stratified case-control sampling for modeling blood-brain barrier integrity in multiple sclerosis.

PubMed

Pomann, Gina-Maria; Sweeney, Elizabeth M; Reich, Daniel S; Staicu, Ana-Maria; Shinohara, Russell T

2015-09-10

Multiple sclerosis (MS) is an immune-mediated neurological disease that causes morbidity and disability. In patients with MS, the accumulation of lesions in the white matter of the brain is associated with disease progression and worse clinical outcomes. Breakdown of the blood-brain barrier in newer lesions is indicative of more active disease-related processes and is a primary outcome considered in clinical trials of treatments for MS. Such abnormalities in active MS lesions are evaluated in vivo using contrast-enhanced structural MRI, during which patients receive an intravenous infusion of a costly magnetic contrast agent. In some instances, the contrast agents can have toxic effects. Recently, local image regression techniques have been shown to have modest performance for assessing the integrity of the blood-brain barrier based on imaging without contrast agents. These models have centered on the problem of cross-sectional classification in which patients are imaged at a single study visit and pre-contrast images are used to predict post-contrast imaging. In this paper, we extend these methods to incorporate historical imaging information, and we find the proposed model to exhibit improved performance. We further develop scan-stratified case-control sampling techniques that reduce the computational burden of local image regression models, while respecting the low proportion of the brain that exhibits abnormal vascular permeability. Copyright © 2015 John Wiley & Sons, Ltd.

Bluetongue virus spread in Europe is a consequence of climatic, landscape and vertebrate host factors as revealed by phylogeographic inference

PubMed Central

Palmarini, Massimo; Mertens, Peter

2017-01-01

Spatio-temporal patterns of the spread of infectious diseases are commonly driven by environmental and ecological factors. This is particularly true for vector-borne diseases because vector populations can be strongly affected by host distribution as well as by climatic and landscape variables. Here, we aim to identify environmental drivers for bluetongue virus (BTV), the causative agent of a major vector-borne disease of ruminants that has emerged multiple times in Europe in recent decades. In order to determine the importance of climatic, landscape and host-related factors affecting BTV diffusion across Europe, we fitted different phylogeographic models to a dataset of 113 time-stamped and geo-referenced BTV genomes, representing multiple strains and serotypes. Diffusion models using continuous space revealed that terrestrial habitat below 300 m altitude, wind direction and higher livestock densities were associated with faster BTV movement. Results of discrete phylogeographic analysis involving generalized linear models broadly supported these findings, but varied considerably with the level of spatial partitioning. Contrary to common perception, we found no evidence for average temperature having a positive effect on BTV diffusion, though both methodological and biological reasons could be responsible for this result. Our study provides important insights into the drivers of BTV transmission at the landscape scale that could inform predictive models of viral spread and have implications for designing control strategies. PMID:29021180

Pathological synchronization in Parkinson's disease: networks, models and treatments.

PubMed

Hammond, Constance; Bergman, Hagai; Brown, Peter

2007-07-01

Parkinson's disease is a common and disabling disorder of movement owing to dopaminergic denervation of the striatum. However, it is still unclear how this denervation perverts normal functioning to cause slowing of voluntary movements. Recent work using tissue slice preparations, animal models and in humans with Parkinson's disease has demonstrated abnormally synchronized oscillatory activity at multiple levels of the basal ganglia-cortical loop. This excessive synchronization correlates with motor deficit, and its suppression by dopaminergic therapies, ablative surgery or deep-brain stimulation might provide the basic mechanism whereby diverse therapeutic strategies ameliorate motor impairment in patients with Parkinson's disease. This review is part of the INMED/TINS special issue, Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com/).

Stem cell transplantation and mesenchymal cells to treat autoimmune diseases.

PubMed

Tyndall, Alan; van Laar, Jacob M

2016-06-01

Since the start of the international stem cell transplantation project in 1997, over 2000 patients have received a haematopoietic stem cell transplant (HSCT), mostly autologous, as treatment for a severe autoimmune disease, the majority being multiple sclerosis (MS), systemic sclerosis (SSc) and Crohn's disease. There was an overall 85% 5-year survival and 43% progression-free survival. Around 30% of patients in all disease subgroups had a complete response, often durable despite full immune reconstitution. In many cases, e.g. systemic sclerosis, morphological improvement such as reduction of skin collagen and normalization of microvasculature was documented, beyond any predicted known effects of intense immunosuppression alone. It is hoped that the results of the three running large prospective randomized controlled trials will allow modification of the protocols to reduce the high transplant-related mortality which relates to regimen intensity, age of patient, and comorbidity. Mesenchymal stromal cells (MSC), often incorrectly called stem cells, have been the intense focus of in vitro studies and animal models of rheumatic and other diseases over more than a decade. Despite multiple plausible mechanisms of action and a plethora of positive in vivo animal studies, few randomised controlled clinical trials have demonstrated meaningful clinical benefit in any condition so far. This could be due to confusion in cell product terminology, complexity of clinical study design and execution or agreement on meaningful outcome measures. Within the rheumatic diseases, SLE and rheumatoid arthritis (RA) have received most attention. Uncontrolled multiple trial data from over 300 SLE patients have been published from one centre suggesting a positive outcome; one single centre comparative study in 172 RA was positive. In addition, small numbers of patients with Crohn's disease, multiple sclerosis, primary Sjögren's disease, polymyositis/dermatomyositis and type II diabetes mellitus have received MSC therapeutically. The possible reasons for this apparent mismatch between expectation and clinical reality will be discussed. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Multi-criteria decision analysis as an innovative approach to managing zoonoses: results from a study on Lyme disease in Canada

PubMed Central

2013-01-01

Background Zoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria. Methods MCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario. Results In general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model. Conclusions MCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a “One Health” perspective. PMID:24079303

Multi-criteria decision analysis as an innovative approach to managing zoonoses: results from a study on Lyme disease in Canada.

PubMed

Aenishaenslin, Cécile; Hongoh, Valérie; Cissé, Hassane Djibrilla; Hoen, Anne Gatewood; Samoura, Karim; Michel, Pascal; Waaub, Jean-Philippe; Bélanger, Denise

2013-09-30

Zoonoses are a growing international threat interacting at the human-animal-environment interface and call for transdisciplinary and multi-sectoral approaches in order to achieve effective disease management. The recent emergence of Lyme disease in Quebec, Canada is a good example of a complex health issue for which the public health sector must find protective interventions. Traditional preventive and control interventions can have important environmental, social and economic impacts and as a result, decision-making requires a systems approach capable of integrating these multiple aspects of interventions. This paper presents the results from a study of a multi-criteria decision analysis (MCDA) approach for the management of Lyme disease in Quebec, Canada. MCDA methods allow a comparison of interventions or alternatives based on multiple criteria. MCDA models were developed to assess various prevention and control decision criteria pertinent to a comprehensive management of Lyme disease: a first model was developed for surveillance interventions and a second was developed for control interventions. Multi-criteria analyses were conducted under two epidemiological scenarios: a disease emergence scenario and an epidemic scenario. In general, we observed a good level of agreement between stakeholders. For the surveillance model, the three preferred interventions were: active surveillance of vectors by flagging or dragging, active surveillance of vectors by trapping of small rodents and passive surveillance of vectors of human origin. For the control interventions model, basic preventive communications, human vaccination and small scale landscaping were the three preferred interventions. Scenarios were found to only have a small effect on the group ranking of interventions in the control model. MCDA was used to structure key decision criteria and capture the complexity of Lyme disease management. This facilitated the identification of gaps in the scientific literature and enabled a clear identification of complementary interventions that could be used to improve the relevance and acceptability of proposed prevention and control strategy. Overall, MCDA presents itself as an interesting systematic approach for public health planning and zoonoses management with a "One Health" perspective.

Asbestos-related diseases in automobile mechanics.

PubMed

Ameille, Jacques; Rosenberg, Nicole; Matrat, Mireille; Descatha, Alexis; Mompoint, Dominique; Hamzi, Lounis; Atassi, Catherine; Vasile, Manuela; Garnier, Robert; Pairon, Jean-Claude

2012-01-01

Automobile mechanics have been exposed to asbestos in the past, mainly due to the presence of chrysotile asbestos in brakes and clutches. Despite the large number of automobile mechanics, little is known about the non-malignant respiratory diseases observed in this population. The aim of this retrospective multicenter study was to analyse the frequency of pleural and parenchymal abnormalities on high-resolution computed tomography (HRCT) in a population of automobile mechanics. The study population consisted of 103 automobile mechanics with no other source of occupational exposure to asbestos, referred to three occupational health departments in the Paris area for systematic screening of asbestos-related diseases. All subjects were examined by HRCT and all images were reviewed separately by two independent readers; who in the case of disagreement discussed until they reached agreement. Multiple logistic regression models were constructed to investigate factors associated with pleural plaques. Pleural plaques were observed in five cases (4.9%) and interstitial abnormalities consistent with asbestosis were observed in one case. After adjustment for age, smoking status, and a history of non-asbestos-related respiratory diseases, multiple logistic regression models showed a significant association between the duration of exposure to asbestos and pleural plaques. The asbestos exposure experienced by automobile mechanics may lead to pleural plaques. The low prevalence of non-malignant asbestos-related diseases, using a very sensitive diagnostic tool, is in favor of a low cumulative exposure to asbestos in this population of workers.

Neuroimmunology Research. A Report from the Cuban Network of Neuroimmunology.

PubMed

Robinson-Agramonte, María de Los Angeles; Pedre, Lourdes Lorigados; Serrano-Barrera, Orlando Ramón

2018-05-08

Neuroimmunology can be traced back to the XIX century through the descriptions of some of the disease’s models (e.g., multiple sclerosis and Guillain Barret syndrome, amongst others). The diagnostic tools are based in the cerebrospinal fluid (CSF) analysis developed by Quincke or in the development of neuroimmunotherapy with the earlier expression in Pasteur’s vaccine for rabies. Nevertheless, this field, which began to become delineated as an independent research area in the 1940s, has evolved as an innovative and integrative field at the shared edges of neurosciences, immunology, and related clinical and research areas, which are currently becoming a major concern for neuroscience and indeed for all of the scientific community linked to it. The workshop focused on several topics: (1) the molecular mechanisms of immunoregulation in health and neurological diseases, (like multiple sclerosis, autism, ataxias, epilepsy, Alzheimer and Parkinson’s disease); (2) the use of animal models for neurodegenerative diseases (ataxia, fronto-temporal dementia/amyotrophic lateral sclerosis, ataxia-telangiectasia); (3) the results of new interventional technologies in neurology, with a special interest in the implementation of surgical techniques and the management of drug-resistant temporal lobe epilepsy; (4) the use of non-invasive brain stimulation in neurodevelopmental disorders; as well as (5) the efficacy of neuroprotective molecules in neurodegenerative diseases. This paper summarizes the highlights of the symposium.

Co-infections determine patterns of mortality in a population exposed to parasite infection.

PubMed

Woolhouse, Mark E J; Thumbi, Samuel M; Jennings, Amy; Chase-Topping, Margo; Callaby, Rebecca; Kiara, Henry; Oosthuizen, Marinda C; Mbole-Kariuki, Mary N; Conradie, Ilana; Handel, Ian G; Poole, E Jane; Njiiri, Evalyne; Collins, Nicola E; Murray, Gemma; Tapio, Miika; Auguet, Olga Tosas; Weir, Willie; Morrison, W Ivan; Kruuk, Loeske E B; Bronsvoort, B Mark de C; Hanotte, Olivier; Coetzer, Koos; Toye, Philip G

2015-03-01

Many individual hosts are infected with multiple parasite species, and this may increase or decrease the pathogenicity of the infections. This phenomenon is termed heterologous reactivity and is potentially an important determinant of both patterns of morbidity and mortality and of the impact of disease control measures at the population level. Using infections with Theileria parva (a tick-borne protozoan, related to Plasmodium) in indigenous African cattle [where it causes East Coast fever (ECF)] as a model system, we obtain the first quantitative estimate of the effects of heterologous reactivity for any parasitic disease. In individual calves, concurrent co-infection with less pathogenic species of Theileria resulted in an 89% reduction in mortality associated with T. parva infection. Across our study population, this corresponds to a net reduction in mortality due to ECF of greater than 40%. Using a mathematical model, we demonstrate that this degree of heterologous protection provides a unifying explanation for apparently disparate epidemiological patterns: variable disease-induced mortality rates, age-mortality profiles, weak correlations between the incidence of infection and disease (known as endemic stability), and poor efficacy of interventions that reduce exposure to multiple parasite species. These findings can be generalized to many other infectious diseases, including human malaria, and illustrate how co-infections can play a key role in determining population-level patterns of morbidity and mortality due to parasite infections.

Asbestos-related diseases in automobile mechanics

PubMed Central

Ameille, Jacques; Rosenberg, Nicole; Matrat, Mireille; Descatha, Alexis; Mompoint, Dominique; Hamzi, Lounis; Atassi, Catherine; Vasile, Manuela; Garnier, Robert; Pairon, Jean-Claude

2012-01-01

Purpose Automobile mechanics have been exposed to asbestos in the past, mainly due to the presence of chrysotile asbestos in brakes and clutches. Despite the large number of automobile mechanics, little is known about the non-malignant respiratory diseases observed in this population. The aim of this retrospective multicenter study was to analyze the frequency of pleural and parenchymal abnormalities on HRCT in a population of automobile mechanics. Methods The study population consisted of 103 automobile mechanics with no other source of occupational exposure to asbestos, referred to three occupational health departments in the Paris area for systematic screening of asbestos–related diseases. All subjects were examined by HRCT and all images were reviewed separately by two independent readers, with further consensus in the case of disagreement. Multiple logistic regression models were constructed to investigate factors associated with pleural plaques. Results Pleural plaques were observed in 5 cases (4.9%) and interstitial abnormalities consistent with asbestosis were observed in 1 case. After adjustment for age, smoking status, and a history of non-asbestos-related respiratory diseases, multiple logistic regression models showed a significant association between the duration of exposure to asbestos and pleural plaques. Conclusions The asbestos exposure experienced by automobile mechanics may lead to pleural plaques. The low prevalence of non-malignant asbestos-related diseases, using a very sensitive diagnostic tool, is in favor of a low cumulative exposure to asbestos in this population of workers. PMID:21965465

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

Prediction of Drug-Drug Interactions with Crizotinib as the CYP3A Substrate Using a Physiologically Based Pharmacokinetic Model.

PubMed

Yamazaki, Shinji; Johnson, Theodore R; Smith, Bill J

2015-10-01

An orally available multiple tyrosine kinase inhibitor, crizotinib (Xalkori), is a CYP3A substrate, moderate time-dependent inhibitor, and weak inducer. The main objectives of the present study were to: 1) develop and refine a physiologically based pharmacokinetic (PBPK) model of crizotinib on the basis of clinical single- and multiple-dose results, 2) verify the crizotinib PBPK model from crizotinib single-dose drug-drug interaction (DDI) results with multiple-dose coadministration of ketoconazole or rifampin, and 3) apply the crizotinib PBPK model to predict crizotinib multiple-dose DDI outcomes. We also focused on gaining insights into the underlying mechanisms mediating crizotinib DDIs using a dynamic PBPK model, the Simcyp population-based simulator. First, PBPK model-predicted crizotinib exposures adequately matched clinically observed results in the single- and multiple-dose studies. Second, the model-predicted crizotinib exposures sufficiently matched clinically observed results in the crizotinib single-dose DDI studies with ketoconazole or rifampin, resulting in the reasonably predicted fold-increases in crizotinib exposures. Finally, the predicted fold-increases in crizotinib exposures in the multiple-dose DDI studies were roughly comparable to those in the single-dose DDI studies, suggesting that the effects of crizotinib CYP3A time-dependent inhibition (net inhibition) on the multiple-dose DDI outcomes would be negligible. Therefore, crizotinib dose-adjustment in the multiple-dose DDI studies could be made on the basis of currently available single-dose results. Overall, we believe that the crizotinib PBPK model developed, refined, and verified in the present study would adequately predict crizotinib oral exposures in other clinical studies, such as DDIs with weak/moderate CYP3A inhibitors/inducers and drug-disease interactions in patients with hepatic or renal impairment. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Automated Assessment of Disease Progression in Acute Myeloid Leukemia by Probabilistic Analysis of Flow Cytometry Data

PubMed Central

Rajwa, Bartek; Wallace, Paul K.; Griffiths, Elizabeth A.; Dundar, Murat

2017-01-01

Objective Flow cytometry (FC) is a widely acknowledged technology in diagnosis of acute myeloid leukemia (AML) and has been indispensable in determining progression of the disease. Although FC plays a key role as a post-therapy prognosticator and evaluator of therapeutic efficacy, the manual analysis of cytometry data is a barrier to optimization of reproducibility and objectivity. This study investigates the utility of our recently introduced non-parametric Bayesian framework in accurately predicting the direction of change in disease progression in AML patients using FC data. Methods The highly flexible non-parametric Bayesian model based on the infinite mixture of infinite Gaussian mixtures is used for jointly modeling data from multiple FC samples to automatically identify functionally distinct cell populations and their local realizations. Phenotype vectors are obtained by characterizing each sample by the proportions of recovered cell populations, which are in turn used to predict the direction of change in disease progression for each patient. Results We used 200 diseased and non-diseased immunophenotypic panels for training and tested the system with 36 additional AML cases collected at multiple time points. The proposed framework identified the change in direction of disease progression with accuracies of 90% (9 out of 10) for relapsing cases and 100% (26 out of 26) for the remaining cases. Conclusions We believe that these promising results are an important first step towards the development of automated predictive systems for disease monitoring and continuous response evaluation. Significance Automated measurement and monitoring of therapeutic response is critical not only for objective evaluation of disease status prognosis but also for timely assessment of treatment strategies. PMID:27416585

Conjugates of Cell Adhesion Peptides for Therapeutics and Diagnostics Against Cancer and Autoimmune Diseases.

PubMed

Moral, Mario E G; Siahaan, Teruna J

2017-01-01

Overexpressed cell-surface receptors are hallmarks of many disease states and are often used as markers for targeting diseased cells over healthy counterparts. Cell adhesion peptides, which are often derived from interacting regions of these receptor-ligand proteins, mimic surfaces of intact proteins and, thus, have been studied as targeting agents for various payloads to certain cell targets for cancers and autoimmune diseases. Because many cytotoxic agents in the free form are often harmful to healthy cells, the use of cell adhesion peptides in targeting their delivery to diseased cells has been studied to potentially reduce required effective doses and associated harmful side-effects. In this review, multiple cell adhesion peptides from extracellular matrix and ICAM proteins were used to selectively direct drug payloads, signal-inhibitor peptides, and diagnostic molecules, to diseased cells over normal counterparts. RGD constructs have been used to improve the selectivity and efficacy of diagnostic and drug-peptide conjugates against cancer cells. From this precedent, novel conjugates of antigenic and cell adhesion peptides, called Bifunctional Peptide Inhibitors (BPIs), have been designed to selectively regulate immune cells and suppress harmful inflammatory responses in autoimmune diseases. Similar peptide conjugations with imaging agents have delivered promising diagnostic methods in animal models of rheumatoid arthritis. BPIs have also been shown to generate immune tolerance and suppress autoimmune diseases in animal models of type-1 diabetes, rheumatoid arthritis, and multiple sclerosis. Collectively, these studies show the potential of cell adhesion peptides in improving the delivery of drugs and diagnostic agents to diseased cells in clinical settings. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Individual and social determinants of multiple chronic disease behavioral risk factors among youth.

PubMed

Alamian, Arsham; Paradis, Gilles

2012-03-22

Behavioral risk factors are known to co-occur among youth, and to increase risks of chronic diseases morbidity and mortality later in life. However, little is known about determinants of multiple chronic disease behavioral risk factors, particularly among youth. Previous studies have been cross-sectional and carried out without a sound theoretical framework. Using longitudinal data (n = 1135) from Cycle 4 (2000-2001), Cycle 5 (2002-2003) and Cycle 6 (2004-2005) of the National Longitudinal Survey of Children and Youth, a nationally representative sample of Canadian children who are followed biennially, the present study examines the influence of a set of conceptually-related individual/social distal variables (variables situated at an intermediate distance from behaviors), and individual/social ultimate variables (variables situated at an utmost distance from behaviors) on the rate of occurrence of multiple behavioral risk factors (physical inactivity, sedentary behavior, tobacco smoking, alcohol drinking, and high body mass index) in a sample of children aged 10-11 years at baseline. Multiple behavioral risk factors were assessed using a multiple risk factor score. All statistical analyses were performed using SAS, version 9.1, and SUDAAN, version 9.01. Multivariate longitudinal Poisson models showed that social distal variables including parental/peer smoking and peer drinking (Log-likelihood ratio (LLR) = 187.86, degrees of freedom (DF) = 8, p < .001), as well as individual distal variables including low self-esteem (LLR = 76.94, DF = 4, p < .001) increased the rate of occurrence of multiple behavioral risk factors. Individual ultimate variables including age, sex, and anxiety (LLR = 9.34, DF = 3, p < .05), as well as social ultimate variables including family socioeconomic status, and family structure (LLR = 10.93, DF = 5, p = .05) contributed minimally to the rate of co-occurrence of behavioral risk factors. The results suggest targeting individual/social distal variables in prevention programs of multiple chronic disease behavioral risk factors among youth.

CNS infiltration of peripheral immune cells: D-Day for neurodegenerative disease?

PubMed

Rezai-Zadeh, Kavon; Gate, David; Town, Terrence

2009-12-01

While the central nervous system (CNS) was once thought to be excluded from surveillance by immune cells, a concept known as "immune privilege," it is now clear that immune responses do occur in the CNS-giving rise to the field of neuroimmunology. These CNS immune responses can be driven by endogenous (glial) and/or exogenous (peripheral leukocyte) sources and can serve either productive or pathological roles. Recent evidence from mouse models supports the notion that infiltration of peripheral monocytes/macrophages limits progression of Alzheimer's disease pathology and militates against West Nile virus encephalitis. In addition, infiltrating T lymphocytes may help spare neuronal loss in models of amyotrophic lateral sclerosis. On the other hand, CNS leukocyte penetration drives experimental autoimmune encephalomyelitis (a mouse model for the human demyelinating disease multiple sclerosis) and may also be pathological in both Parkinson's disease and human immunodeficiency virus encephalitis. A critical understanding of the cellular and molecular mechanisms responsible for trafficking of immune cells from the periphery into the diseased CNS will be key to target these cells for therapeutic intervention in neurodegenerative diseases, thereby allowing neuroregenerative processes to ensue.

A Review Of Innovative International Financing Mechanisms To Address Noncommunicable Diseases.

PubMed

Meghani, Ankita; Basu, Sanjay

2015-09-01

Noncommunicable diseases have become prevalent in low- and middle-income countries. A key question that remains unresolved is how to support the development of systems to prevent and treat noncommunicable disease through international financing mechanisms. We conducted a review of articles and grey literature published from 2000 through 2014 on innovative financing models proposed or used for other disease control efforts. We found that the greatest available evidence supported pooled funding models, where funding from multiple groups is combined for a specific investment, with such models previously deployed in vaccine and infectious disease funding areas. Robust evidence also supported the viability of international transactions taxes or levies placed on specific transactions to fund investments in drug procurement and supply, and of the front-loading of development aid through bond sales, particularly to stabilize funding and subsidize drug procurement. Far less compelling evidence was available to support diaspora bonds or debt reduction programs as mechanisms to aid low- and middle-income countries' health systems in financing noncommunicable disease prevention and care services. Project HOPE—The People-to-People Health Foundation, Inc.

Ozanimod (RPC1063) is a potent sphingosine-1-phosphate receptor-1 (S1P1 ) and receptor-5 (S1P5 ) agonist with autoimmune disease-modifying activity.

PubMed

Scott, F L; Clemons, B; Brooks, J; Brahmachary, E; Powell, R; Dedman, H; Desale, H G; Timony, G A; Martinborough, E; Rosen, H; Roberts, E; Boehm, M F; Peach, R J

2016-06-01

Sphingosine1-phosphate (S1P) receptors mediate multiple events including lymphocyte trafficking, cardiac function, and endothelial barrier integrity. Stimulation of S1P1 receptors sequesters lymphocyte subsets in peripheral lymphoid organs, preventing their trafficking to inflamed tissue sites, modulating immunity. Targeting S1P receptors for treating autoimmune disease has been established in clinical studies with the non-selective S1P modulator, FTY720 (fingolimod, Gilenya™). The purpose of this study was to assess RPC1063 for its therapeutic utility in autoimmune diseases. The specificity and potency of RPC1063 (ozanimod) was evaluated for all five S1P receptors, and its effect on cell surface S1P1 receptor expression, was characterized in vitro. The oral pharmacokinetic (PK) parameters and pharmacodynamic effects were established in rodents, and its activity in three models of autoimmune disease (experimental autoimmune encephalitis, 2,4,6-trinitrobenzenesulfonic acid colitis and CD4(+) CD45RB(hi) T cell adoptive transfer colitis) was assessed. RPC1063 was specific for S1P1 and S1P5 receptors, induced S1P1 receptor internalization and induced a reversible reduction in circulating B and CCR7(+) T lymphocytes in vivo. RPC1063 showed high oral bioavailability and volume of distribution, and a circulatory half-life that supports once daily dosing. Oral RPC1063 reduced inflammation and disease parameters in all three autoimmune disease models. S1P receptor selectivity, favourable PK properties and efficacy in three distinct disease models supports the clinical development of RPC1063 for the treatment of relapsing multiple sclerosis and inflammatory bowel disease, differentiates RPC1063 from other S1P receptor agonists, and could result in improved safety outcomes in the clinic. © 2016 The British Pharmacological Society.

Time-trend analysis and developing a forecasting model for the prevalence of multiple sclerosis in Kohgiluyeh and Boyer-Ahmad Province, southwest of Iran.

PubMed

Mousavizadeh, A; Dastoorpoor, M; Naimi, E; Dohrabpour, K

2018-01-01

This study was designed and implemented to assess the current situation and to estimate the time trend of multiple sclerosis (MS), as well as to explain potential factors associated with such a trend. This longitudinal study was carried out based on analysis of the data from the monitoring and treatment surveillance system for 421 patients with MS in Kohgiluyeh and Boyer-Ahmad Province, Iran, from 1990 to 2015. To this end, curve estimation approach was used to investigate the changes in prevalence and incidence of the disease, and univariate time series model analysis was applied in order to estimate the disease incidence in the next 10 years. The mean and standard deviation of age were 29.78 and 8.5 years at the time of diagnosis, and the mean and 95% confidence interval of age were 29.18 (28.86-30.77) and 29.68 (28.06-31.30) at the time of diagnosis for women and men, respectively. The sex ratio (males to females) was estimated as 3.3, and the prevalence of the disease was estimated as 60.14 in 100,000 people. The diagram of the 35-year trend of the disease indicated three distinct patterns with a tendency to increase in recent years. The prevalence and incidence trend of the disease in the study population is consistent with regional and global changes. Climatic and environmental factors such as extreme weather changes, dust particles, expansion of the application of new industrial materials, and regional wars with potential use of banned weapons are among the issues that may, in part, be able to justify the global and regional changes of the disease. Predictive models indicate a growing trend of the disease, highlighting the need for more regular monitoring of the disease trend in upcoming years. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Protective and therapeutic role of 2-carba-cyclic phosphatidic acid in demyelinating disease.

PubMed

Yamamoto, Shinji; Yamashina, Kota; Ishikawa, Masaki; Gotoh, Mari; Yagishita, Sosuke; Iwasa, Kensuke; Maruyama, Kei; Murakami-Murofushi, Kimiko; Yoshikawa, Keisuke

2017-07-21

Multiple sclerosis is a neuroinflammatory demyelinating and neurodegenerative disease of the central nervous system characterized by recurrent and progressive demyelination/remyelination cycles, neuroinflammation, oligodendrocyte loss, demyelination, and axonal degeneration. Cyclic phosphatidic acid (cPA) is a natural phospholipid mediator with a unique cyclic phosphate ring structure at the sn-2 and sn-3 positions of the glycerol backbone. We reported earlier that cPA elicits a neurotrophin-like action and protects hippocampal neurons from ischemia-induced delayed neuronal death. We designed, chemically synthesized, and metabolically stabilized derivatives of cPA: 2-carba-cPA (2ccPA), a synthesized compound in which one of the phosphate oxygen molecules is replaced with a methylene group at the sn-2 position. In the present study, we investigated whether 2ccPA exerts protective effects in oligodendrocytes and suppresses pathology in the two most common mouse models of multiple sclerosis. To evaluate whether 2ccPA has potential beneficial effects on the pathology of multiple sclerosis, we investigated the effects of 2ccPA on oligodendrocyte cell death in vitro and administrated 2ccPA to mouse models of experimental autoimmune encephalomyelitis (EAE) and cuprizone-induced demyelination. We demonstrated that 2ccPA suppressed the CoCl 2 -induced increase in the Bax/Bcl-2 protein expression ratio and phosphorylation levels of p38MAPK and JNK protein. 2ccPA treatment reduced cuprizone-induced demyelination, microglial activation, NLRP3 inflammasome, and motor dysfunction. Furthermore, 2ccPA treatment reduced autoreactive T cells and macrophages, spinal cord injury, and pathological scores in EAE, the autoimmune multiple sclerosis mouse model. We demonstrated that 2ccPA protected oligodendrocytes via suppression of the mitochondrial apoptosis pathway. Also, we found beneficial effects of 2ccPA in the multiperiod of cuprizone-induced demyelination and the pathology of EAE. These data indicate that 2ccPA may be a promising compound for the development of new drugs to treat demyelinating disease and ameliorate the symptoms of multiple sclerosis.

A transitional care service for elderly chronic disease patients at risk of readmission.

PubMed

Brand, Caroline A; Jones, Catherine T; Lowe, Adrian J; Nielsen, David A; Roberts, Carol A; King, Bellinda L; Campbell, Donald A

2004-12-13

Multiple hospital admissions, especially those related to chronic disease, represent a particular challenge to the acute health care sector in Australia. To determine whether a nurse-led chronic disease management model of transitional care reduced readmissions to acute care. A quasi-experimental controlled trial. A large tertiary metropolitan teaching hospital. 166 general medical patients aged > or = 65 years with either a history of readmissions to acute care or multiple medical comorbidities. Implementation of a chronic disease management model of transitional care aimed at improving patient management and reducing readmissions to acute care. Readmission rates and emergency department presentation rates at 3-and 6-month follow up. Secondary outcome measures include quality of life, discharge destination, and primary health care service utilisation. There was no difference in readmission rates, emergency department presentation rates, quality of life, discharge destination or primary health care service utilisation. The difficulties inherent in evaluating this type of multifactorial intervention are discussed and consideration is given to patient factors, the difficulty of influencing readmission rates, and local system issues. The outcomes of this study reflect the tension that exists between implementing multifaceted integrated health service programs and attempting to evaluate them within complex and changing environments using robust research methodologies.

Immunologic Endocrine Disorders

PubMed Central

Michels, Aaron W.; Eisenbarth, George S.

2010-01-01

Autoimmunity affects multiple glands in the endocrine system. Animal models and human studies highlight the importance of alleles in HLA (human leukocyte antigen)-like molecules determining tissue specific targeting that with the loss of tolerance leads to organ specific autoimmunity. Disorders such as type 1A diabetes, Grave's disease, Hashimoto's thyroiditis, Addison's disease, and many others result from autoimmune mediated tissue destruction. Each of these disorders can be divided into stages beginning with genetic susceptibility, environmental triggers, active autoimmunity, and finally metabolic derangements with overt symptoms of disease. With an increased understanding of the immunogenetics and immunopathogenesis of endocrine autoimmune disorders, immunotherapies are becoming prevalent, especially in type 1A diabetes. Immunotherapies are being used more in multiple subspecialty fields to halt disease progression. While therapies for autoimmune disorders stop the progress of an immune response, immunomodulatory therapies for cancer and chronic infections can also provoke an unwanted immune response. As a result, there are now iatrogenic autoimmune disorders arising from the treatment of chronic viral infections and malignancies. PMID:20176260

Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease.

PubMed

Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G; Tybjaerg-Hansen, Anne; Sing, Charles F

2009-05-01

This article extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (Genet Epidemiol 31:515-527) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2,258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors.

Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease

PubMed Central

Dyson, Greg; Frikke-Schmidt, Ruth; Nordestgaard, Børge G.; Tybjærg-Hansen, Anne; Sing, Charles F.

2009-01-01

This paper extends the Patient Rule-Induction Method (PRIM) for modeling cumulative incidence of disease developed by Dyson et al. (2007) to include the simultaneous consideration of non-additive combinations of predictor variables, a significance test of each combination, an adjustment for multiple testing and a confidence interval for the estimate of the cumulative incidence of disease in each partition. We employ the partitioning algorithm component of the Combinatorial Partitioning Method (CPM) to construct combinations of predictors, permutation testing to assess the significance of each combination, theoretical arguments for incorporating a multiple testing adjustment and bootstrap resampling to produce the confidence intervals. An illustration of this revised PRIM utilizing a sample of 2258 European male participants from the Copenhagen City Heart Study is presented that assesses the utility of genetic variants in predicting the presence of ischemic heart disease beyond the established risk factors. PMID:19025787

Meningeal mast cells affect early T cell central nervous system infiltration and blood-brain barrier integrity through TNF: a role for neutrophil recruitment?

PubMed

Sayed, Blayne A; Christy, Alison L; Walker, Margaret E; Brown, Melissa A

2010-06-15

Mast cells contribute to the pathogenesis of experimental autoimmune encephalomyelitis, a rodent model of the human demyelinating disease multiple sclerosis. Yet their site and mode of action is unknown. In both diseases, myelin-specific T cells are initially activated in peripheral lymphoid organs. However, for disease to occur, these cells must enter the immunologically privileged CNS through a breach in the relatively impermeable blood-brain barrier. In this study, we demonstrate that a dense population of resident mast cells in the meninges, structures surrounding the brain and spinal cord, regulate basal CNS barrier function, facilitating initial T cell CNS entry. Through the expression of TNF, mast cells recruit an early wave of neutrophils to the CNS. We propose that neutrophils in turn promote the blood-brain barrier breach and together with T cells lead to further inflammatory cell influx and myelin damage. These findings provide specific targets for intervention in multiple sclerosis as well as other immune-mediated CNS diseases.

Epidemiology and population biology of Pseudoperonospora cubensis: a model system for management of downy mildews.

PubMed

Ojiambo, Peter S; Gent, David H; Quesada-Ocampo, Lina M; Hausbeck, Mary K; Holmes, Gerald J

2015-01-01

The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of outbreaks of cucurbit downy mildew. The dispersal potential of Pseudoperonospora cubensis appears to be limited primarily by sporangia production in source fields and availability of susceptible hosts and less by sporangia survival during transport. Uncertainty remains regarding the role of locally produced inoculum in disease outbreaks, but evidence suggests multiple sources of primary inoculum could be important. Understanding pathogen diversity and population differentiation is a critical aspect of disease management and an active research area. Underpinning advances in our understanding of pathogen biology and disease management has been the research capacity and coordination of stakeholders, scientists, and extension personnel. Concepts and approaches developed in this pathosystem can guide future efforts when responding to incursions of new or reemerging downy mildew pathogens.

Diplomatic Assistance: Can Helminth-Modulated Macrophages Act as Treatment for Inflammatory Disease?

PubMed Central

Steinfelder, Svenja; O’Regan, Noëlle Louise; Hartmann, Susanne

2016-01-01

Helminths have evolved numerous pathways to prevent their expulsion or elimination from the host to ensure long-term survival. During infection, they target numerous host cells, including macrophages, to induce an alternatively activated phenotype, which aids elimination of infection, tissue repair, and wound healing. Multiple animal-based studies have demonstrated a significant reduction or complete reversal of disease by helminth infection, treatment with helminth products, or helminth-modulated macrophages in models of allergy, autoimmunity, and sepsis. Experimental studies of macrophage and helminth therapies are being translated into clinical benefits for patients undergoing transplantation and those with multiple sclerosis. Thus, helminths or helminth-modulated macrophages present great possibilities as therapeutic applications for inflammatory diseases in humans. Macrophage-based helminth therapies and the underlying mechanisms of their therapeutic or curative effects represent an under-researched area with the potential to open new avenues of treatment. This review explores the application of helminth-modulated macrophages as a new therapy for inflammatory diseases. PMID:27101372

Disease model curation improvements at Mouse Genome Informatics

PubMed Central

Bello, Susan M.; Richardson, Joel E.; Davis, Allan P.; Wiegers, Thomas C.; Mattingly, Carolyn J.; Dolan, Mary E.; Smith, Cynthia L.; Blake, Judith A.; Eppig, Janan T.

2012-01-01

Optimal curation of human diseases requires an ontology or structured vocabulary that contains terms familiar to end users, is robust enough to support multiple levels of annotation granularity, is limited to disease terms and is stable enough to avoid extensive reannotation following updates. At Mouse Genome Informatics (MGI), we currently use disease terms from Online Mendelian Inheritance in Man (OMIM) to curate mouse models of human disease. While OMIM provides highly detailed disease records that are familiar to many in the medical community, it lacks structure to support multilevel annotation. To improve disease annotation at MGI, we evaluated the merged Medical Subject Headings (MeSH) and OMIM disease vocabulary created by the Comparative Toxicogenomics Database (CTD) project. Overlaying MeSH onto OMIM provides hierarchical access to broad disease terms, a feature missing from the OMIM. We created an extended version of the vocabulary to meet the genetic disease-specific curation needs at MGI. Here we describe our evaluation of the CTD application, the extensions made by MGI and discuss the strengths and weaknesses of this approach. Database URL: http://www.informatics.jax.org/ PMID:22434831

A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

PubMed

Zhang, Xiaotian; Yin, Jian; Zhang, Xu

2018-03-02

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

SUMMIT (Serially Unified Multicenter Multiple Sclerosis Investigation): creating a repository of deeply phenotyped contemporary multiple sclerosis cohorts.

PubMed

Bove, Riley; Chitnis, Tanuja; Cree, Bruce Ac; Tintoré, Mar; Naegelin, Yvonne; Uitdehaag, Bernard Mj; Kappos, Ludwig; Khoury, Samia J; Montalban, Xavier; Hauser, Stephen L; Weiner, Howard L

2017-08-01

There is a pressing need for robust longitudinal cohort studies in the modern treatment era of multiple sclerosis. Build a multiple sclerosis (MS) cohort repository to capture the variability of disability accumulation, as well as provide the depth of characterization (clinical, radiologic, genetic, biospecimens) required to adequately model and ultimately predict a patient's course. Serially Unified Multicenter Multiple Sclerosis Investigation (SUMMIT) is an international multi-center, prospectively enrolled cohort with over a decade of comprehensive follow-up on more than 1000 patients from two large North American academic MS Centers (Brigham and Women's Hospital (Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB; BWH)) and University of California, San Francisco (Expression/genomics, Proteomics, Imaging, and Clinical (EPIC))). It is bringing online more than 2500 patients from additional international MS Centers (Basel (Universitätsspital Basel (UHB)), VU University Medical Center MS Center Amsterdam (MSCA), Multiple Sclerosis Center of Catalonia-Vall d'Hebron Hospital (Barcelona clinically isolated syndrome (CIS) cohort), and American University of Beirut Medical Center (AUBMC-Multiple Sclerosis Interdisciplinary Research (AMIR)). We provide evidence for harmonization of two of the initial cohorts in terms of the characterization of demographics, disease, and treatment-related variables; demonstrate several proof-of-principle analyses examining genetic and radiologic predictors of disease progression; and discuss the steps involved in expanding SUMMIT into a repository accessible to the broader scientific community.

Spontaneous onset and transplant models of the Vk*MYC mouse show immunological sequelae comparable to human multiple myeloma.

PubMed

Cooke, Rachel E; Gherardin, Nicholas A; Harrison, Simon J; Quach, Hang; Godfrey, Dale I; Prince, Miles; Koldej, Rachel; Ritchie, David S

2016-09-06

The Vk*MYC transgenic and transplant mouse models of multiple myeloma (MM) are well established as a research tool for anti-myeloma drug discovery. However, little is known of the immune response in these models. Understanding the immunological relevance of these models is of increasing importance as immunotherapeutic drugs are developed against MM. We set out to examine how cellular immunity is affected in Vk*MYC mouse models and compare that to the immunology of patients with newly diagnosed and relapsed/refractory MM. We found that there were significant immunological responses in mice developing either spontaneous (transgenic) or transplanted MM as a consequence of the degree of tumor burden. Particularly striking were the profound B cell lymphopenia and the expansion of CD8(+) effector memory T cells within the lymphocyte population that progressively developed with advancing disease burden, mirroring changes seen in human MM. High disease burden was also associated with increased inflammatory cytokine production by T lymphocytes, which is more fitting with relapsed/refractory MM in humans. These findings have important implications for the application of this mouse model in the development of MM immunotherapies. Trial registration LitVacc ANZCTR trial ID ACTRN12613000344796; RevLite ANZCTR trial ID NCT00482261.

Concise review: Patient-derived olfactory stem cells: new models for brain diseases.

PubMed

Mackay-Sim, Alan

2012-11-01

Traditional models of brain diseases have had limited success in driving candidate drugs into successful clinical translation. This has resulted in large international pharmaceutical companies moving out of neuroscience research. Cells are not brains, obviously, but new patient-derived stem models have the potential to elucidate cell biological aspects of brain diseases that are not present in worm, fly, or rodent models, the work horses of disease investigations and drug discovery. Neural stem cells are present in the olfactory mucosa, the organ of smell in the nose. Patient-derived olfactory mucosa has demonstrated disease-associated differences in a variety of brain diseases and recently olfactory mucosa stem cells have been generated from patients with schizophrenia, Parkinson's disease, and familial dysautonomia. By comparison with cells from healthy controls, patient-derived olfactory mucosa stem cells show disease-specific alterations in gene expression and cell functions including: a shorter cell cycle and faster proliferation in schizophrenia, oxidative stress in Parkinson's disease, and altered cell migration in familial dysautonomia. Olfactory stem cell cultures thus reveal patient-control differences, even in complex genetic diseases such as schizophrenia and Parkinson's disease, indicating that multiple genes of small effect can converge on shared cell signaling pathways to present as a disease-specific cellular phenotype. Olfactory mucosa stem cells can be maintained in homogeneous cultures that allow robust and repeatable multiwell assays suitable for screening libraries of drug candidate molecules. Copyright © 2012 AlphaMed Press.

Periodontitis in pregnancy: clinical and serum antibody observations from a baboon model of ligature-induced disease.

PubMed

Cappelli, D; Steffen, M J; Holt, S C; Ebersole, J L

2009-07-01

Chronic oral infections that elicit host responses leading to periodontal disease are linked with various sequelae of systemic diseases. This report provides seminal information on the clinical and adaptive immunologic characteristics of a baboon model of ligature-induced periodontitis during pregnancy. Female Papio anubis were evaluated for periodontal health at baseline. Ligatures were tied around selected teeth to initiate oral inflammation and periodontitis. Then the animals were bred. At midpregnancy ( approximately 90 days), a clinical evaluation was performed, and additional ligatures were tied on teeth in the contralateral quadrants to maintain progressing periodontitis throughout pregnancy. A final clinical evaluation was done for all experimental teeth after delivery, and ligatures were removed. Serum was collected at all sampling intervals for the determination of antibody levels to a group of 20 oral bacteria. Unligated animals served as controls. At baseline, 16% of animals exhibited minimal plaque and gingival inflammation without periodontal disease. The remaining baboons demonstrated varying levels of inflammation/bleeding, and approximately 20% of the population had periodontal pocketing (>3 mm). Ligated animals expressed increased levels of inflammation and increased probing depths and clinical attachment loss (AL) and could be stratified into multiple subsets postligation based upon changes in clinical parameters at midpregnancy and at delivery. Baboons were categorized into disease susceptibility groups (periodontal disease susceptibility 1 through 4) that described the extent/severity of induced disease during pregnancy. Control animals showed minimal periodontal changes during gestation. Significant differences in serum antibody to multiple oral bacteria were found in animals presenting with periodontitis at baseline and during the 6 months of ligature-induced disease. A significant correlation to antibody to P. gingivalis, which was sustained throughout ligation and pregnancy, was observed with disease presentation. The clinical presentation at baseline, reflecting the natural history of oral disease in these animals, suggests individual variation that is reflected in the characteristics of the adaptive immune responses to oral bacteria. The variability in the response to ligation with resulting periodontal disease provides a model to document prospectively the relationship between oral and systemic health outcomes.

Optimising experimental research in respiratory diseases: an ERS statement.

PubMed

Bonniaud, Philippe; Fabre, Aurélie; Frossard, Nelly; Guignabert, Christophe; Inman, Mark; Kuebler, Wolfgang M; Maes, Tania; Shi, Wei; Stampfli, Martin; Uhlig, Stefan; White, Eric; Witzenrath, Martin; Bellaye, Pierre-Simon; Crestani, Bruno; Eickelberg, Oliver; Fehrenbach, Heinz; Guenther, Andreas; Jenkins, Gisli; Joos, Guy; Magnan, Antoine; Maitre, Bernard; Maus, Ulrich A; Reinhold, Petra; Vernooy, Juanita H J; Richeldi, Luca; Kolb, Martin

2018-05-01

Experimental models are critical for the understanding of lung health and disease and are indispensable for drug development. However, the pathogenetic and clinical relevance of the models is often unclear. Further, the use of animals in biomedical research is controversial from an ethical perspective.The objective of this task force was to issue a statement with research recommendations about lung disease models by facilitating in-depth discussions between respiratory scientists, and to provide an overview of the literature on the available models. Focus was put on their specific benefits and limitations. This will result in more efficient use of resources and greater reduction in the numbers of animals employed, thereby enhancing the ethical standards and translational capacity of experimental research.The task force statement addresses general issues of experimental research (ethics, species, sex, age, ex vivo and in vitro models, gene editing). The statement also includes research recommendations on modelling asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, lung infections, acute lung injury and pulmonary hypertension.The task force stressed the importance of using multiple models to strengthen validity of results, the need to increase the availability of human tissues and the importance of standard operating procedures and data quality. Copyright ©ERS 2018.

An Integrated Framework For The Prevention And Treatment Of Obesity And Its Related Chronic Diseases.

PubMed

Dietz, William H; Solomon, Loel S; Pronk, Nico; Ziegenhorn, Sarah K; Standish, Marion; Longjohn, Matt M; Fukuzawa, David D; Eneli, Ihuoma U; Loy, Lisel; Muth, Natalie D; Sanchez, Eduardo J; Bogard, Jenny; Bradley, Don W

2015-09-01

Improved patient experience, population health, and reduced cost of care for patients with obesity and other chronic diseases will not be achieved by clinical interventions alone. We offer here a new iteration of the Chronic Care Model that integrates clinical and community systems to address chronic diseases. Obesity contributes substantially to cardiovascular disease, type 2 diabetes mellitus, and cancer. Dietary and physical activity interventions will prevent, mitigate, and treat obesity and its related diseases. Challenges with the implementation of this model include provider training, the need to provide incentives for health systems to move beyond clinical care to link with community systems, and addressing the multiple elements necessary for integration within clinical care and with social systems. The Affordable Care Act, with its emphasis on prevention and new systems for care delivery, provides support for innovative strategies such as those proposed here. Project HOPE—The People-to-People Health Foundation, Inc.

Genetic variants in Alzheimer disease – molecular and brain network approaches

PubMed Central

Gaiteri, Chris; Mostafavi, Sara; Honey, Christopher; De Jager, Philip L.; Bennett, David A.

2016-01-01

Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care for AD. However, due to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extracting actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effect of LOAD-associated genetic variants. We then discuss emerging combinations of omic data types in multiscale models, which provide a more comprehensive representation of the effect of LOAD-associated genetic variants at multiple biophysical scales. Further, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models. PMID:27282653

Cystathionine beta-synthase deficiency alters hepatic phospholipid and choline metabolism: Post-translational repression of phosphatidylethanolamine N-methyltransferase is a consequence rather than a cause of liver injury in homocystinuria.

PubMed

Jacobs, René L; Jiang, Hua; Kennelly, John P; Orlicky, David J; Allen, Robert H; Stabler, Sally P; Maclean, Kenneth N

2017-04-01

Classical homocystinuria (HCU) due to inactivating mutation of cystathionine β-synthase (CBS) is a poorly understood life-threatening inborn error of sulfur metabolism. A previously described cbs-/- mouse model exhibits a semi-lethal phenotype due to neonatal liver failure. The transgenic HO mouse model of HCU exhibits only mild liver injury and recapitulates multiple aspects of the disease as it occurs in humans. Disruption of the methionine cycle in HCU has the potential to impact multiple aspect of phospholipid (PL) metabolism by disruption of both the Kennedy pathway and phosphatidylethanolamine N-methyltransferase (PEMT) mediated synthesis of phosphatidylcholine (PC). Comparative metabolomic analysis of HO mouse liver revealed decreased levels of choline, and choline phosphate indicating disruption of the Kennedy pathway. Alterations in the relative levels of multiple species of PL included significant increases in PL degradation products consistent with enhanced membrane PL turnover. A significant decrease in PC containing 20:4n6 which primarily formed by the methylation of phosphatidylethanolamine to PC was consistent with decreased flux through PEMT. Hepatic expression of PEMT in both the cbs-/- and HO models is post-translationally repressed with decreased levels of PEMT protein and activity that inversely-correlates with the scale of liver injury. Failure to induce further repression of PEMT in HO mice by increased homocysteine, methionine and S-adenosylhomocysteine or depletion of glutathione combined with examination of multiple homocysteine-independent models of liver injury indicated that repression of PEMT in HCU is a consequence rather than a cause of liver injury. Collectively, our data show significant alteration of a broad range of hepatic PL and choline metabolism in HCU with the potential to contribute to multiple aspects of pathogenesis in this disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Prevalence and predictors of dysphagia in Iranian patients with multiple sclerosis

PubMed Central

Tarameshlu, Maryam; Azimi, Amir Reza; Ghelichi, Leila; Ansari, Noureddin Nakhostin

2017-01-01

Background: Dysphagia is frequently observed in patients with multiple sclerosis (MS). Dysphagia and its complications are common causes of morbidity and mortality in final stages of MS disease. This study aimed at determining the prevalence of dysphagia in Iranian patients with MS and identifying predictors associated with dysphagia. Methods: A total of 230 MS patients were enrolled in this cross-sectional study. Dysphagia was evaluated using Mann Assessment of Swallowing Ability (MASA). Demographic characteristics (age and gender), duration of the disease, disease course, and Expanded Disability Status Scale (EDSS) were recorded for all participants. Results: In total, dysphagia was found in 85 participants (37%) with mild to severe dysphagia (mild 50.6%; moderate 29.4%; and severe 20%). The logistic regression model demonstrated that disability status in EDSS (OR= 2.1; 95% CI 0.5-1.2) and disease duration (OR= 2.3; 95% CI 0.4-1.1) predicts a high risk for dysphagia in MS patients. Conclusion: Dysphagia is prevalent in Iranian patients with MS. Disability level and disease duration are significant predictors of dysphagia after MS.

Bayesian Covariate Selection in Mixed-Effects Models For Longitudinal Shape Analysis

PubMed Central

Muralidharan, Prasanna; Fishbaugh, James; Kim, Eun Young; Johnson, Hans J.; Paulsen, Jane S.; Gerig, Guido; Fletcher, P. Thomas

2016-01-01

The goal of longitudinal shape analysis is to understand how anatomical shape changes over time, in response to biological processes, including growth, aging, or disease. In many imaging studies, it is also critical to understand how these shape changes are affected by other factors, such as sex, disease diagnosis, IQ, etc. Current approaches to longitudinal shape analysis have focused on modeling age-related shape changes, but have not included the ability to handle covariates. In this paper, we present a novel Bayesian mixed-effects shape model that incorporates simultaneous relationships between longitudinal shape data and multiple predictors or covariates to the model. Moreover, we place an Automatic Relevance Determination (ARD) prior on the parameters, that lets us automatically select which covariates are most relevant to the model based on observed data. We evaluate our proposed model and inference procedure on a longitudinal study of Huntington's disease from PREDICT-HD. We first show the utility of the ARD prior for model selection in a univariate modeling of striatal volume, and next we apply the full high-dimensional longitudinal shape model to putamen shapes. PMID:28090246

Identifiability and estimation of multiple transmission pathways in cholera and waterborne disease.

PubMed

Eisenberg, Marisa C; Robertson, Suzanne L; Tien, Joseph H

2013-05-07

Cholera and many waterborne diseases exhibit multiple characteristic timescales or pathways of infection, which can be modeled as direct and indirect transmission. A major public health issue for waterborne diseases involves understanding the modes of transmission in order to improve control and prevention strategies. An important epidemiological question is: given data for an outbreak, can we determine the role and relative importance of direct vs. environmental/waterborne routes of transmission? We examine whether parameters for a differential equation model of waterborne disease transmission dynamics can be identified, both in the ideal setting of noise-free data (structural identifiability) and in the more realistic setting in the presence of noise (practical identifiability). We used a differential algebra approach together with several numerical approaches, with a particular emphasis on identifiability of the transmission rates. To examine these issues in a practical public health context, we apply the model to a recent cholera outbreak in Angola (2006). Our results show that the model parameters-including both water and person-to-person transmission routes-are globally structurally identifiable, although they become unidentifiable when the environmental transmission timescale is fast. Even for water dynamics within the identifiable range, when noisy data are considered, only a combination of the water transmission parameters can practically be estimated. This makes the waterborne transmission parameters difficult to estimate, leading to inaccurate estimates of important epidemiological parameters such as the basic reproduction number (R0). However, measurements of pathogen persistence time in environmental water sources or measurements of pathogen concentration in the water can improve model identifiability and allow for more accurate estimation of waterborne transmission pathway parameters as well as R0. Parameter estimates for the Angola outbreak suggest that both transmission pathways are needed to explain the observed cholera dynamics. These results highlight the importance of incorporating environmental data when examining waterborne disease. Copyright © 2013 Elsevier Ltd. All rights reserved.

AgMIP: Next Generation Models and Assessments

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2014-12-01

Next steps in developing next-generation crop models fall into several categories: significant improvements in simulation of important crop processes and responses to stress; extension from simplified crop models to complex cropping systems models; and scaling up from site-based models to landscape, national, continental, and global scales. Crop processes that require major leaps in understanding and simulation in order to narrow uncertainties around how crops will respond to changing atmospheric conditions include genetics; carbon, temperature, water, and nitrogen; ozone; and nutrition. The field of crop modeling has been built on a single crop-by-crop approach. It is now time to create a new paradigm, moving from 'crop' to 'cropping system.' A first step is to set up the simulation technology so that modelers can rapidly incorporate multiple crops within fields, and multiple crops over time. Then the response of these more complex cropping systems can be tested under different sustainable intensification management strategies utilizing the updated simulation environments. Model improvements for diseases, pests, and weeds include developing process-based models for important diseases, frameworks for coupling air-borne diseases to crop models, gathering significantly more data on crop impacts, and enabling the evaluation of pest management strategies. Most smallholder farming in the world involves integrated crop-livestock systems that cannot be represented by crop modeling alone. Thus, next-generation cropping system models need to include key linkages to livestock. Livestock linkages to be incorporated include growth and productivity models for grasslands and rangelands as well as the usual annual crops. There are several approaches for scaling up, including use of gridded models and development of simpler quasi-empirical models for landscape-scale analysis. On the assessment side, AgMIP is leading a community process for coordinated contributions to IPCC AR6 that involves the key modeling groups from around the world including North America, Europe, South America, Sub-Saharan Africa, South Asia, East Asia, and Australia and Oceania. This community process will lead to mutually agreed protocols for coordinated global and regional assessments.

Data-model fusion to better understand emerging pathogens and improve infectious disease forecasting.

PubMed

LaDeau, Shannon L; Glass, Gregory E; Hobbs, N Thompson; Latimer, Andrew; Ostfeld, Richard S

2011-07-01

Ecologists worldwide are challenged to contribute solutions to urgent and pressing environmental problems by forecasting how populations, communities, and ecosystems will respond to global change. Rising to this challenge requires organizing ecological information derived from diverse sources and formally assimilating data with models of ecological processes. The study of infectious disease has depended on strategies for integrating patterns of observed disease incidence with mechanistic process models since John Snow first mapped cholera cases around a London water pump in 1854. Still, zoonotic and vector-borne diseases increasingly affect human populations, and methods used to successfully characterize directly transmitted diseases are often insufficient. We use four case studies to demonstrate that advances in disease forecasting require better understanding of zoonotic host and vector populations, as well of the dynamics that facilitate pathogen amplification and disease spillover into humans. In each case study, this goal is complicated by limited data, spatiotemporal variability in pathogen transmission and impact, and often, insufficient biological understanding. We present a conceptual framework for data-model fusion in infectious disease research that addresses these fundamental challenges using a hierarchical state-space structure to (1) integrate multiple data sources and spatial scales to inform latent parameters, (2) partition uncertainty in process and observation models, and (3) explicitly build upon existing ecological and epidemiological understanding. Given the constraints inherent in the study of infectious disease and the urgent need for progress, fusion of data and expertise via this type of conceptual framework should prove an indispensable tool.

Review: An Australian model of care for co-morbid diabetes and chronic kidney disease.

PubMed

Lo, Clement; Zimbudzi, Edward; Teede, Helena; Cass, Alan; Fulcher, Greg; Gallagher, Martin; Kerr, Peter G; Jan, Stephen; Johnson, Greg; Mathew, Tim; Polkinghorne, Kevan; Russell, Grant; Usherwood, Tim; Walker, Rowan; Zoungas, Sophia

2018-02-05

Diabetes and chronic kidney disease (CKD) are two of the most prevalent co-morbid chronic diseases in Australia. The increasing complexity of multi-morbidity, and current gaps in health-care delivery for people with co-morbid diabetes and CKD, emphasise the need for better models of care for this population. Previously, proposed published models of care for co-morbid diabetes and CKD have not been co-designed with stake-holders or formally evaluated. Particular components of health-care shown to be effective in this population are interventions that: are structured, intensive and multifaceted (treating diabetes and multiple cardiovascular risk factors); involve multiple medical disciplines; improve self-management by the patient; and upskill primary health-care. Here we present an integrated patient-centred model of health-care delivery incorporating these components and co-designed with key stake-holders including specialist health professionals, general practitioners and Diabetes and Kidney Health Australia. The development of the model of care was informed by focus groups of patients and health-professionals; and semi-structured interviews of care-givers and health professionals. Other distinctives of this model of care are routine screening for psychological morbidity; patient-support through a phone advice line; and focused primary health-care support in the management of diabetes and CKD. Additionally, the model of care integrates with the patient-centred health-care home currently being rolled out by the Australian Department of Health. This model of care will be evaluated after implementation across two tertiary health services and their primary care catchment areas. Copyright © 2018 John Wiley & Sons, Ltd. This article is protected by copyright. All rights reserved.

A computational method for computing an Alzheimer’s Disease Progression Score; experiments and validation with the ADNI dataset

PubMed Central

Jedynak, Bruno M.; Liu, Bo; Lang, Andrew; Gel, Yulia; Prince, Jerry L.

2014-01-01

Understanding the time-dependent changes of biomarkers related to Alzheimer’s disease (AD) is a key to assessing disease progression and to measuring the outcomes of disease-modifying therapies. In this paper, we validate an Alzheimer’s disease progression score model which uses multiple biomarkers to quantify the AD progression of subjects following three assumptions: (1) there is a unique disease progression for all subjects, (2) each subject has a different age of onset and rate of progression, and (3) each biomarker is sigmoidal as a function of disease progression. Fitting the parameters of this model is a challenging problem which we approach using an alternating least squares optimization algorithm. In order to validate this optimization scheme under realistic conditions, we use the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. With the help of Monte Carlo simulations, we show that most of the global parameters of the model are tightly estimated, thus enabling an ordering of the biomarkers that fit the model well, ordered as: the Rey auditory verbal learning test with 30 minutes delay, the sum of the two lateral hippocampal volumes divided by the intra-cranial volume, followed by (the clinical dementia rating sum of boxes score and the mini mental state examination score) in no particular order and lastly the Alzheimer’s disease assessment scale-cognitive subscale. PMID:25444605

Deep ensemble learning of sparse regression models for brain disease diagnosis.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2017-04-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer's disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call 'Deep Ensemble Sparse Regression Network.' To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep ensemble learning of sparse regression models for brain disease diagnosis

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2018-01-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer’s disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call ‘ Deep Ensemble Sparse Regression Network.’ To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. PMID:28167394

Incidence and related clinical factors of falls among older Chinese veterans in military communities: a prospective study.

PubMed

Xu, Wei; Chen, Da-Wei; Jin, Yan-Bin; Dong, Zhen-Jun; Zhang, Wei-Jiang; Chen, Jin-Wen; Yang, Shu-Mei; Wang, Jian-Rong

2015-02-01

[Purpose] The aim of this study was to determine fall incidence and explore clinical factors of falls among older Chinese veterans in military communities. [Subjects and Methods] We carried out a 12-month prospective study among 13 military communities in Beijing, China. Fall events were obtained by self-report to military community liaisons and monthly telephone interviews by researchers. [Results] Among the final sample of 447 older veterans, 86 fell once, 25 fell twice or more, and 152 falls occurred altogether. The incidence of falls and fallers were 342/1,000 person-years and 249/1,000 person-years. In Cox regression models, independent clinical factors associated with falls were visual acuity (RR=0.47), stroke (RR=2.43), lumbar diseases (RR=1.73), sedatives (RR=1.80), fall history in the past 6 months (RR=2.77), multiple chronic diseases (RR=1.53), multiple medications (RR=1.34), and five-repetition sit-to-stand test score (RR=1.41). Hearing acuity was close to being statistically significant. [Conclusion] The incidences of falls and fallers among older Chinese veterans were lower than those of Hong Kong and western countries. The clinical risk factors of falls were poor senses, stroke, lumbar diseases, taking sedatives, fall history in the past 6 months, having multiple chronic diseases, taking multiple medications, and poor physical function. The preventive strategies targeting the above risk factors are very significant for reducing falls.

Incidence and related clinical factors of falls among older Chinese veterans in military communities: a prospective study

PubMed Central

Xu, Wei; Chen, Da-Wei; Jin, Yan-Bin; Dong, Zhen-Jun; Zhang, Wei-Jiang; Chen, Jin-Wen; Yang, Shu-Mei; Wang, Jian-Rong

2015-01-01

[Purpose] The aim of this study was to determine fall incidence and explore clinical factors of falls among older Chinese veterans in military communities. [Subjects and Methods] We carried out a 12-month prospective study among 13 military communities in Beijing, China. Fall events were obtained by self-report to military community liaisons and monthly telephone interviews by researchers. [Results] Among the final sample of 447 older veterans, 86 fell once, 25 fell twice or more, and 152 falls occurred altogether. The incidence of falls and fallers were 342/1,000 person-years and 249/1,000 person-years. In Cox regression models, independent clinical factors associated with falls were visual acuity (RR=0.47), stroke (RR=2.43), lumbar diseases (RR=1.73), sedatives (RR=1.80), fall history in the past 6 months (RR=2.77), multiple chronic diseases (RR=1.53), multiple medications (RR=1.34), and five-repetition sit-to-stand test score (RR=1.41). Hearing acuity was close to being statistically significant. [Conclusion] The incidences of falls and fallers among older Chinese veterans were lower than those of Hong Kong and western countries. The clinical risk factors of falls were poor senses, stroke, lumbar diseases, taking sedatives, fall history in the past 6 months, having multiple chronic diseases, taking multiple medications, and poor physical function. The preventive strategies targeting the above risk factors are very significant for reducing falls. PMID:25729162

An architecture model for multiple disease management information systems.

PubMed

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

2013-04-01

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

Therapeutic Approach to the Management of Pediatric Demyelinating Disease: Multiple Sclerosis and Acute Disseminated Encephalomyelitis.

PubMed

Brenton, J Nicholas; Banwell, Brenda L

2016-01-01

Acquired pediatric demyelinating diseases manifest acutely with optic neuritis, transverse myelitis, acute disseminated encephalomyelitis, or with various other acute deficits in focal or polyfocal areas of the central nervous system. Patients may experience a monophasic illness (as in the case of acute disseminated encephalomyelitis) or one that may manifest as a chronic, relapsing disease [e.g., multiple sclerosis (MS)]. The diagnosis of pediatric MS and other demyelinating disorders of childhood has been facilitated by consensus statements regarding diagnostic definitions. Treatment of pediatric MS has been modeled after data obtained from clinical trials in adult-onset MS. There are now an increasing number of new therapeutic agents for MS, and many will be formally studied for use in pediatric patients. There are important efficacy and safety concerns regarding the use of these therapies in children and young adults. This review will discuss acute management as well as chronic immunotherapies in acquired pediatric demyelination.

Imaging plus X: multimodal models of neurodegenerative disease.

PubMed

Oxtoby, Neil P; Alexander, Daniel C

2017-08-01

This article argues that the time is approaching for data-driven disease modelling to take centre stage in the study and management of neurodegenerative disease. The snowstorm of data now available to the clinician defies qualitative evaluation; the heterogeneity of data types complicates integration through traditional statistical methods; and the large datasets becoming available remain far from the big-data sizes necessary for fully data-driven machine-learning approaches. The recent emergence of data-driven disease progression models provides a balance between imposed knowledge of disease features and patterns learned from data. The resulting models are both predictive of disease progression in individual patients and informative in terms of revealing underlying biological patterns. Largely inspired by observational models, data-driven disease progression models have emerged in the last few years as a feasible means for understanding the development of neurodegenerative diseases. These models have revealed insights into frontotemporal dementia, Huntington's disease, multiple sclerosis, Parkinson's disease and other conditions. For example, event-based models have revealed finer graded understanding of progression patterns; self-modelling regression and differential equation models have provided data-driven biomarker trajectories; spatiotemporal models have shown that brain shape changes, for example of the hippocampus, can occur before detectable neurodegeneration; and network models have provided some support for prion-like mechanistic hypotheses of disease propagation. The most mature results are in sporadic Alzheimer's disease, in large part because of the availability of the Alzheimer's disease neuroimaging initiative dataset. Results generally support the prevailing amyloid-led hypothetical model of Alzheimer's disease, while revealing finer detail and insight into disease progression. The emerging field of disease progression modelling provides a natural mechanism to integrate different kinds of information, for example from imaging, serum and cerebrospinal fluid markers and cognitive tests, to obtain new insights into progressive diseases. Such insights include fine-grained longitudinal patterns of neurodegeneration, from early stages, and the heterogeneity of these trajectories over the population. More pragmatically, such models enable finer precision in patient staging and stratification, prediction of progression rates and earlier and better identification of at-risk individuals. We argue that this will make disease progression modelling invaluable for recruitment and end-points in future clinical trials, potentially ameliorating the high failure rate in trials of, e.g., Alzheimer's disease therapies. We review the state of the art in these techniques and discuss the future steps required to translate the ideas to front-line application.

Abnormal pain perception in patients with Multiple System Atrophy.

PubMed

Ory-Magne, F; Pellaprat, J; Harroch, E; Galitzsky, M; Rousseau, V; Pavy-Le Traon, A; Rascol, O; Gerdelat, A; Brefel-Courbon, C

2018-03-01

Patients with Parkinson's disease or Multiple System Atrophy frequently experience painful sensations. The few studies investigating pain mechanisms in Multiple System Atrophy patients have reported contradictory results. In our study, we compared pain thresholds in Multiple System Atrophy and Parkinson's disease patients and healthy controls and evaluated the effect of l-DOPA on pain thresholds. We assessed subjective and objective pain thresholds (using a thermotest and RIII reflex), and pain tolerance in OFF and ON conditions, clinical pain, motor and psychological evaluation. Pain was reported in 78.6% of Multiple System Atrophy patients and in 37.5% of Parkinson's disease patients. In the OFF condition, subjective and objective pain thresholds were significantly lower in Multiple System Atrophy patients than in healthy controls (43.8 °C ± 1.3 vs 45.7 °C ± 0.8; p = 0.0005 and 7.4 mA ± 3.8 vs 13.7 mA ± 2.8; p = 0.002, respectively). They were also significantly reduced in Multiple System Atrophy compared to Parkinson's disease patients. No significant difference was found in pain tolerance for the 3 groups and in the effect of l-DOPA on pain thresholds in Multiple System Atrophy and Parkinson's disease patients. In the ON condition, pain tolerance tended to be reduced in Multiple System Atrophy versus Parkinson's disease patients (p = 0.05). Multiple System Atrophy patients had an increase in pain perception compared to Parkinson's disease patients and healthy controls. The l-DOPA effect was similar for pain thresholds in Multiple System Atrophy and Parkinson's disease patients, but tended to worsen pain tolerance in Multiple System Atrophy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of the Gene for Scleroderma in the Tsk/2 Mouse Strain: Implications for Human Scleroderma Pathogenesis and Subset Distinctions

DTIC Science & Technology

2012-07-01

Philadelphia, PA 19104 1 Jul 2011 - 30 Jun 2012Annual01-07-2012 This project is focused on an animal model of the human disease, systemic sclerosis ...earliest indicator of tight-skin in the tissue Animal model, systemic sclerosis , scleroderma, Tsk2/+, fibrosis, gene, genetics, TGFβ 35 eblanken...the  multiple  clinical parameters of fibrotic disease from birth  onward.   BODY  Milestones were assigned to this proposal, with tasks to be

Concise Review: Stem Cell Trials Using Companion Animal Disease Models.

PubMed

Hoffman, Andrew M; Dow, Steven W

2016-07-01

Studies to evaluate the therapeutic potential of stem cells in humans would benefit from more realistic animal models. In veterinary medicine, companion animals naturally develop many diseases that resemble human conditions, therefore, representing a novel source of preclinical models. To understand how companion animal disease models are being studied for this purpose, we reviewed the literature between 2008 and 2015 for reports on stem cell therapies in dogs and cats, excluding laboratory animals, induced disease models, cancer, and case reports. Disease models included osteoarthritis, intervertebral disc degeneration, dilated cardiomyopathy, inflammatory bowel diseases, Crohn's fistulas, meningoencephalomyelitis (multiple sclerosis-like), keratoconjunctivitis sicca (Sjogren's syndrome-like), atopic dermatitis, and chronic (end-stage) kidney disease. Stem cells evaluated in these studies included mesenchymal stem-stromal cells (MSC, 17/19 trials), olfactory ensheathing cells (OEC, 1 trial), or neural lineage cells derived from bone marrow MSC (1 trial), and 16/19 studies were performed in dogs. The MSC studies (13/17) used adipose tissue-derived MSC from either allogeneic (8/13) or autologous (5/13) sources. The majority of studies were open label, uncontrolled studies. Endpoints and protocols were feasible, and the stem cell therapies were reportedly safe and elicited beneficial patient responses in all but two of the trials. In conclusion, companion animals with naturally occurring diseases analogous to human conditions can be recruited into clinical trials and provide realistic insight into feasibility, safety, and biologic activity of novel stem cell therapies. However, improvements in the rigor of manufacturing, study design, and regulatory compliance will be needed to better utilize these models. Stem Cells 2016;34:1709-1729. © 2016 AlphaMed Press.

Enhancing the Ability of Experimental Autoimmune Encephalomyelitis to Serve as a More Rigorous Model of Multiple Sclerosis through Refinement of the Experimental Design

PubMed Central

Emerson, Mitchell R; Gallagher, Ryan J; Marquis, Janet G; LeVine, Steven M

2009-01-01

Advancing the understanding of the mechanisms involved in the pathogenesis of multiple sclerosis (MS) likely will lead to new and better therapeutics. Although important information about the disease process has been obtained from research on pathologic specimens, peripheral blood lymphocytes and MRI studies, the elucidation of detailed mechanisms has progressed largely through investigations using animal models of MS. In addition, animal models serve as an important tool for the testing of putative interventions. The most commonly studied model of MS is experimental autoimmune encephalomyelitis (EAE). This model can be induced in a variety of species and by various means, but there has been concern that the model may not accurately reflect the disease process, and more importantly, it may give rise to erroneous findings when it is used to test possible therapeutics. Several reasons have been given to explain the shortcomings of this model as a useful testing platform, but one idea provides a framework for improving the value of this model, and thus, it deserves careful consideration. In particular, the idea asserts that EAE studies are inadequately designed to enable appropriate evaluation of putative therapeutics. Here we discuss problem areas within EAE study designs and provide suggestions for their improvement. This paper is principally directed at investigators new to the field of EAE, although experienced investigators may find useful suggestions herein. PMID:19389303

Urine-derived induced pluripotent stem cells as a modeling tool to study rare human diseases

PubMed Central

Shi, Liang; Cui, Yazhou; Luan, Jing; Zhou, Xiaoyan; Han, Jinxiang

2016-01-01

Summary Rare diseases with a low prevalence are a key public health issue because the causes of those diseases are difficult to determine and those diseases lack a clearly established or curative treatment. Thus, investigating the molecular mechanisms that underlie the pathology of rare diseases and facilitating the development of novel therapies using disease models is crucial. Human induced pluripotent stem cells (iPSCs) are well suited to modeling rare diseases since they have the capacity for self-renewal and pluripotency. In addition, iPSC technology provides a valuable tool to generate patient-specific iPSCs. These cells can be differentiated into cell types that have been affected by a disease. These cells would circumvent ethical concerns and avoid immunological rejection, so they could be used in cell replacement therapy or regenerative medicine. To date, human iPSCs could have been generated from multiple donor sources, such as skin, adipose tissue, and peripheral blood. However, these cells are obtained via invasive procedures. In contrast, several groups of researchers have found that urine may be a better source for producing iPSCs from normal individuals or patients. This review discusses urinary iPSC (UiPSC) as a candidate for modeling rare diseases. Cells obtained from urine have overwhelming advantages compared to other donor sources since they are safely, affordably, and frequently obtained and they are readily obtained from patients. The use of iPSC-based models is also discussed. UiPSCs may prove to be a key means of modeling rare diseases and they may facilitate the treatment of those diseases in the future. PMID:27672542

Modelling the Cost Effectiveness of Disease-Modifying Treatments for Multiple Sclerosis

PubMed Central

Thompson, Joel P.; Abdolahi, Amir; Noyes, Katia

2013-01-01

Several cost-effectiveness models of disease-modifying treatments (DMTs) for multiple sclerosis (MS) have been developed for different populations and different countries. Vast differences in the approaches and discrepancies in the results give rise to heated discussions and limit the use of these models. Our main objective is to discuss the methodological challenges in modelling the cost effectiveness of treatments for MS. We conducted a review of published models to describe the approaches taken to date, to identify the key parameters that influence the cost effectiveness of DMTs, and to point out major areas of weakness and uncertainty. Thirty-six published models and analyses were identified. The greatest source of uncertainty is the absence of head-to-head randomized clinical trials. Modellers have used various techniques to compensate, including utilizing extension trials. The use of large observational cohorts in recent studies aids in identifying population-based, ‘real-world’ treatment effects. Major drivers of results include the time horizon modelled and DMT acquisition costs. Model endpoints must target either policy makers (using cost-utility analysis) or clinicians (conducting cost-effectiveness analyses). Lastly, the cost effectiveness of DMTs outside North America and Europe is currently unknown, with the lack of country-specific data as the major limiting factor. We suggest that limited data should not preclude analyses, as models may be built and updated in the future as data become available. Disclosure of modelling methods and assumptions could improve the transferability and applicability of models designed to reflect different healthcare systems. PMID:23640103

The Rho Kinases: Critical Mediators of Multiple Profibrotic Processes and Rational Targets for New Therapies for Pulmonary Fibrosis

PubMed Central

Knipe, Rachel S.; Tager, Andrew M.

2015-01-01

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive lung scarring, short median survival, and limited therapeutic options, creating great need for new pharmacologic therapies. IPF is thought to result from repetitive environmental injury to the lung epithelium, in the context of aberrant host wound healing responses. Tissue responses to injury fundamentally involve reorganization of the actin cytoskeleton of participating cells, including epithelial cells, fibroblasts, endothelial cells, and macrophages. Actin filament assembly and actomyosin contraction are directed by the Rho-associated coiled-coil forming protein kinase (ROCK) family of serine/threonine kinases (ROCK1 and ROCK2). As would therefore be expected, lung ROCK activation has been demonstrated in humans with IPF and in animal models of this disease. ROCK inhibitors can prevent fibrosis in these models, and more importantly, induce the regression of already established fibrosis. Here we review ROCK structure and function, upstream activators and downstream targets of ROCKs in pulmonary fibrosis, contributions of ROCKs to profibrotic cellular responses to lung injury, ROCK inhibitors and their efficacy in animal models of pulmonary fibrosis, and potential toxicities of ROCK inhibitors in humans, as well as involvement of ROCKs in fibrosis in other organs. As we discuss, ROCK activation is required for multiple profibrotic responses, in the lung and multiple other organs, suggesting ROCK participation in fundamental pathways that contribute to the pathogenesis of a broad array of fibrotic diseases. Multiple lines of evidence therefore indicate that ROCK inhibition has great potential to be a powerful therapeutic tool in the treatment of fibrosis, both in the lung and beyond. PMID:25395505

Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

PubMed

Lawson, A B; Carroll, R; Faes, C; Kirby, R S; Aregay, M; Watjou, K

2017-12-01

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.

A Systematic Review and Meta-Analysis of Strength Training in Individuals With Multiple Sclerosis Or Parkinson Disease

PubMed Central

Cruickshank, Travis M.; Reyes, Alvaro R.; Ziman, Melanie R.

2015-01-01

Abstract Strength training has, in recent years, been shown to be beneficial for people with Parkinson disease and multiple sclerosis. Consensus regarding its utility for these disorders nevertheless remains contentious among healthcare professionals. Greater clarity is required, especially in regards to the type and magnitude of effects as well as the response differences to strength training between individuals with Parkinson disease or multiple sclerosis. This study examines the effects, magnitude of those effects, and response differences to strength training between patients with Parkinson disease or multiple sclerosis. A comprehensive search of electronic databases including Physiotherapy Evidence Database scale, PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and CINAHL was conducted from inception to July 2014. English articles investigating the effect of strength training for individuals with neurodegenerative disorders were selected. Strength training trials that met the inclusion criteria were found for individuals with Parkinson disease or multiple sclerosis. Individuals with Parkinson disease or multiple sclerosis were included in the study. Strength training interventions included traditional (free weights/machine exercises) and nontraditional programs (eccentric cycling). Included articles were critically appraised using the Physiotherapy Evidence Database scale. Of the 507 articles retrieved, only 20 articles met the inclusion criteria. Of these, 14 were randomized and 6 were nonrandomized controlled articles in Parkinson disease or multiple sclerosis. Six randomized and 2 nonrandomized controlled articles originated from 3 trials and were subsequently pooled for systematic analysis. Strength training was found to significantly improve muscle strength in people with Parkinson disease (15%–83.2%) and multiple sclerosis (4.5%–36%). Significant improvements in mobility (11.4%) and disease progression were also reported in people with Parkinson disease after strength training. Furthermore, significant improvements in fatigue (8.2%), functional capacity (21.5%), quality of life (8.3%), power (17.6%), and electromyography activity (24.4%) were found in individuals with multiple sclerosis after strength training. The limitations of the study were the heterogeneity of interventions and study outcomes in Parkinson disease and multiple sclerosis trials. Strength training is useful for increasing muscle strength in Parkinson disease and to a lesser extent multiple sclerosis. PMID:25634170

A systematic review and meta-analysis of strength training in individuals with multiple sclerosis or Parkinson disease.

PubMed

Cruickshank, Travis M; Reyes, Alvaro R; Ziman, Melanie R

2015-01-01

Strength training has, in recent years, been shown to be beneficial for people with Parkinson disease and multiple sclerosis. Consensus regarding its utility for these disorders nevertheless remains contentious among healthcare professionals. Greater clarity is required, especially in regards to the type and magnitude of effects as well as the response differences to strength training between individuals with Parkinson disease or multiple sclerosis. This study examines the effects, magnitude of those effects, and response differences to strength training between patients with Parkinson disease or multiple sclerosis. A comprehensive search of electronic databases including Physiotherapy Evidence Database scale, PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and CINAHL was conducted from inception to July 2014. English articles investigating the effect of strength training for individuals with neurodegenerative disorders were selected. Strength training trials that met the inclusion criteria were found for individuals with Parkinson disease or multiple sclerosis. Individuals with Parkinson disease or multiple sclerosis were included in the study. Strength training interventions included traditional (free weights/machine exercises) and nontraditional programs (eccentric cycling). Included articles were critically appraised using the Physiotherapy Evidence Database scale. Of the 507 articles retrieved, only 20 articles met the inclusion criteria. Of these, 14 were randomized and 6 were nonrandomized controlled articles in Parkinson disease or multiple sclerosis. Six randomized and 2 nonrandomized controlled articles originated from 3 trials and were subsequently pooled for systematic analysis. Strength training was found to significantly improve muscle strength in people with Parkinson disease (15%-83.2%) and multiple sclerosis (4.5%-36%). Significant improvements in mobility (11.4%) and disease progression were also reported in people with Parkinson disease after strength training. Furthermore, significant improvements in fatigue (8.2%), functional capacity (21.5%), quality of life (8.3%), power (17.6%), and electromyography activity (24.4%) were found in individuals with multiple sclerosis after strength training. The limitations of the study were the heterogeneity of interventions and study outcomes in Parkinson disease and multiple sclerosis trials. Strength training is useful for increasing muscle strength in Parkinson disease and to a lesser extent multiple sclerosis.

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

PubMed

Zon, Leonard

2016-06-01

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. © 2016. Published by The Company of Biologists Ltd.

Detection of multiple perturbations in multi-omics biological networks.

PubMed

Griffin, Paula J; Zhang, Yuqing; Johnson, William Evan; Kolaczyk, Eric D

2018-05-17

Cellular mechanism-of-action is of fundamental concern in many biological studies. It is of particular interest for identifying the cause of disease and learning the way in which treatments act against disease. However, pinpointing such mechanisms is difficult, due to the fact that small perturbations to the cell can have wide-ranging downstream effects. Given a snapshot of cellular activity, it can be challenging to tell where a disturbance originated. The presence of an ever-greater variety of high-throughput biological data offers an opportunity to examine cellular behavior from multiple angles, but also presents the statistical challenge of how to effectively analyze data from multiple sources. In this setting, we propose a method for mechanism-of-action inference by extending network filtering to multi-attribute data. We first estimate a joint Gaussian graphical model across multiple data types using penalized regression and filter for network effects. We then apply a set of likelihood ratio tests to identify the most likely site of the original perturbation. In addition, we propose a conditional testing procedure to allow for detection of multiple perturbations. We demonstrate this methodology on paired gene expression and methylation data from The Cancer Genome Atlas (TCGA). © 2018, The International Biometric Society.

Blood-brain barrier-on-a-chip: Microphysiological systems that capture the complexity of the blood-central nervous system interface.

PubMed

Phan, Duc Tt; Bender, R Hugh F; Andrejecsk, Jillian W; Sobrino, Agua; Hachey, Stephanie J; George, Steven C; Hughes, Christopher Cw

2017-11-01

The blood-brain barrier is a dynamic and highly organized structure that strictly regulates the molecules allowed to cross the brain vasculature into the central nervous system. The blood-brain barrier pathology has been associated with a number of central nervous system diseases, including vascular malformations, stroke/vascular dementia, Alzheimer's disease, multiple sclerosis, and various neurological tumors including glioblastoma multiforme. There is a compelling need for representative models of this critical interface. Current research relies heavily on animal models (mostly mice) or on two-dimensional (2D) in vitro models, neither of which fully capture the complexities of the human blood-brain barrier. Physiological differences between humans and mice make translation to the clinic problematic, while monolayer cultures cannot capture the inherently three-dimensional (3D) nature of the blood-brain barrier, which includes close association of the abluminal side of the endothelium with astrocyte foot-processes and pericytes. Here we discuss the central nervous system diseases associated with blood-brain barrier pathology, recent advances in the development of novel 3D blood-brain barrier -on-a-chip systems that better mimic the physiological complexity and structure of human blood-brain barrier, and provide an outlook on how these blood-brain barrier-on-a-chip systems can be used for central nervous system disease modeling. Impact statement The field of microphysiological systems is rapidly evolving as new technologies are introduced and our understanding of organ physiology develops. In this review, we focus on Blood-Brain Barrier (BBB) models, with a particular emphasis on how they relate to neurological disorders such as Alzheimer's disease, multiple sclerosis, stroke, cancer, and vascular malformations. We emphasize the importance of capturing the three-dimensional nature of the brain and the unique architecture of the BBB - something that until recently had not been well modeled by in vitro systems. Our hope is that this review will provide a launch pad for new ideas and methodologies that can provide us with truly physiological BBB models capable of yielding new insights into the function of this critical interface.

Influence of genetic, biological and pharmacological factors on levodopa dose in Parkinson's disease.

PubMed

Altmann, Vivian; Schumacher-Schuh, Artur F; Rieck, Mariana; Callegari-Jacques, Sidia M; Rieder, Carlos R M; Hutz, Mara H

2016-04-01

Levodopa is first-line treatment of Parkinson's disease motor symptoms but, dose response is highly variable. Therefore, the aim of this study was to determine how much levodopa dose could be explained by biological, pharmacological and genetic factors. A total of 224 Parkinson's disease patients were genotyped for SV2C and SLC6A3 polymorphisms by allelic discrimination assays. Comedication, demographic and clinical data were also assessed. All variables with p < 0.20 were included in a multiple regression analysis for dose prediction. The final model explained 23% of dose variation (F = 11.54; p < 0.000001). Although a good prediction model was obtained, it still needs to be tested in an independent sample to be validated.

Estimation of Flattened Musk Turtle (Sternotherus depressus) survival, recapture, and recovery rate during and after a disease outbreak

USGS Publications Warehouse

Fonnesbeck, C.J.; Dodd, C.K.

2003-01-01

We estimated survivorship, recapture probabilities and recovery rates in a threatened population of Flattened Musk Turtles (Sternotherus depressus) through a disease outbreak in Alabama in 1985. We evaluated a set of models for the demographic effects of disease by analyzing recaptures and recoveries simultaneously. Multiple-model inference suggested survival was temporally dynamic, whereas recapture probability was sex- and age-specifc. Biweekly survivorship declined from 98-99% before to 82-88% during the outbreak. Live recapture was twice as likely for male turtles relative to juveniles or females, whereas dead recoveries varied only slightly by sex and age. Our results suggest modest reduction in survival over a relatively short time period may severely affect population status.

Stargardt disease: clinical features, molecular genetics, animal models and therapeutic options.

PubMed

Tanna, Preena; Strauss, Rupert W; Fujinami, Kaoru; Michaelides, Michel

2017-01-01

Stargardt disease (STGD1; MIM 248200) is the most prevalent inherited macular dystrophy and is associated with disease-causing sequence variants in the gene ABCA4 Significant advances have been made over the last 10 years in our understanding of both the clinical and molecular features of STGD1, and also the underlying pathophysiology, which has culminated in ongoing and planned human clinical trials of novel therapies. The aims of this review are to describe the detailed phenotypic and genotypic characteristics of the disease, conventional and novel imaging findings, current knowledge of animal models and pathogenesis, and the multiple avenues of intervention being explored. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Quantitative magnetic resonance imaging assessments of autosomal recessive polycystic kidney disease progression and response to therapy in an animal model.

PubMed

Erokwu, Bernadette O; Anderson, Christian E; Flask, Chris A; Dell, Katherine M

2018-05-01

BackgroundAutosomal recessive polycystic kidney disease (ARPKD) is associated with significant mortality and morbidity, and currently, there are no disease-specific treatments available for ARPKD patients. One major limitation in establishing new therapies for ARPKD is a lack of sensitive measures of kidney disease progression. Magnetic resonance imaging (MRI) can provide multiple quantitative assessments of the disease.MethodsWe applied quantitative image analysis of high-resolution (noncontrast) T2-weighted MRI techniques to study cystic kidney disease progression and response to therapy in the PCK rat model of ARPKD.ResultsSerial imaging over a 2-month period demonstrated that renal cystic burden (RCB, %)=[total cyst volume (TCV)/total kidney volume (TKV) × 100], TCV, and, to a lesser extent, TKV detected cystic kidney disease progression, as well as the therapeutic effect of octreotide, a clinically available medication shown previously to slow both kidney and liver disease progression in this model. All three MRI measures correlated significantly with histologic measures of renal cystic area, although the correlation of RCB and TCV was stronger than that of TKV.ConclusionThese preclinical MRI results provide a basis for applying these quantitative MRI techniques in clinical studies, to stage and measure progression in human ARPKD kidney disease.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

PubMed

Wu, Mengmeng; Zeng, Wanwen; Liu, Wenqiang; Lv, Hairong; Chen, Ting; Jiang, Rui

2018-06-03

Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is still a challenging task to extract biological knowledge from the GWAS data, due to such issues as missing heritability and weak interpretability. Indeed, the fact that the majority of discovered loci fall into noncoding regions without clear links to genes has been preventing the characterization of their functions and appealing for a sophisticated approach to bridge genetic and genomic studies. Towards this problem, network-based prioritization of candidate genes, which performs integrated analysis of gene networks with GWAS data, has emerged as a promising direction and attracted much attention. However, most existing methods overlook the sparse and noisy properties of gene networks and thus may lead to suboptimal performance. Motivated by this understanding, we proposed a novel method called REGENT for integrating multiple gene networks with GWAS data to prioritize candidate genes for complex diseases. We leveraged a technique called the network representation learning to embed a gene network into a compact and robust feature space, and then designed a hierarchical statistical model to integrate features of multiple gene networks with GWAS data for the effective inference of genes associated with a disease of interest. We applied our method to six complex diseases and demonstrated the superior performance of REGENT over existing approaches in recovering known disease-associated genes. We further conducted a pathway analysis and showed that the ability of REGENT to discover disease-associated pathways. We expect to see applications of our method to a broad spectrum of diseases for post-GWAS analysis. REGENT is freely available at https://github.com/wmmthu/REGENT. Copyright © 2018 Elsevier Inc. All rights reserved.

Effector stage CC chemokine receptor-1 selective antagonism reduces multiple sclerosis-like rat disease.

PubMed

Eltayeb, Sana; Sunnemark, Dan; Berg, Anna-Lena; Nordvall, Gunnar; Malmberg, Asa; Lassmann, Hans; Wallström, Erik; Olsson, Tomas; Ericsson-Dahlstrand, Anders

2003-09-01

We have studied the role of the chemokine receptor CCR1 during the effector stage of myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis in DA rats. In situ hybridization histochemistry revealed local production of the CCR1 ligands CCL3 (MIP-1 alpha) and CCL5 (RANTES), as well as large numbers of CCR1 and CCR5 expressing cells within inflammatory brain lesions. A low-molecular weight CCR1 selective antagonist potently abrogated both clinical and histopathological disease signs during a 5-day treatment period, without signs of peripheral immune compromise. Thus, we demonstrate therapeutic targeting of CCR1-dependent leukocyte recruitment to the central nervous system in a multiple sclerosis (MS)-like rat model.

The habenula and iron metabolism in cerebral mouse models of multiple sclerosis

PubMed Central

Sands, Scott A.; Tsau, Sheila; LeVine, Steven M.

2015-01-01

Iron accumulates in the CNS of patients with multiple sclerosis, but our understanding of the mechanism accounting for this accumulation is unclear. Mouse models of cerebral experimental autoimmune encephalomyelitis (EAE) in C57BL/6 and SJL mice were used together with a histochemical stain for iron and immunohistochemical stains for transferrin receptor, synaptophysin, iron regulatory protein 1 (IRP1) and/or IRP2 to investigate the role of disease activity on CNS iron metabolism. The expression of transferrin receptor, but not IRP1 or IRP2, increased in the medial habenula, which is adjacent to the third ventricle, in response to both types of cerebral EAE. In the habenula, the elevated expression of transferrin receptor in C57BL/6 mice with cerebral EAE was generally restricted to the medial habenula while the expression in SJL mice with cerebral EAE was more diffusely expressed. Iron levels were increased in all regions of the habenula in C57BL/6 mice with cerebral EAE, and in the medial and medial lateral but not the lateral habenula in SJL mice with cerebral EAE. Synaptophysin, which has been observed previously in endocytic vesicles together with the transferrin receptor, was concentrated at the medial habenula, but its levels did not increase with disease in C57BL/6 mice with cerebral EAE. Our results support the model that the medial habenula responds to disease activity by upregulating transferrin receptor to facilitate the movement of iron into the brain from the third ventricle, raising the possibility that a similar mechanism accounts for iron accumulation in deep gray matter structures in patients with multiple sclerosis. PMID:26362814

Framework for Smart Electronic Health Record- Linked Predictive Models to Optimize Care for Complex Digestive Diseases

DTIC Science & Technology

2015-03-01

data against previous published outcomes in AP and Chronic Pancreatitis (CP). This served as useful validation of our data set before entering the...These patients can develop multiple complications from their disease. In addition, the treatments for CD (both medical and surgical ) can impose...years of diagnosis. The treatment for CD can sometimes involve very expensive medications with potentially serious side effects, as well as surgical

Nrf2: A Novel Biomarker of Disease Severity and Target for Therapeutic Intervention in Multiple Sclerosis

DTIC Science & Technology

2014-10-01

imaging technique used to capture T cell/APC interaction and infiltration in CNS during the disease course of EAE; and finally 3) characterize the...period, we aim to understand the mechanism of APC/T cell interaction by standardizing the available mouse model and imaging techniques in our lab...resulted in the development of new triterpenoids, mouse imaging techniques and biochemistry and chemical library construction. For example, work

Impaired autophagy in macrophages promotes inflammatory eye disease.

PubMed

Santeford, Andrea; Wiley, Luke A; Park, Sunmin; Bamba, Sonya; Nakamura, Rei; Gdoura, Abdelaziz; Ferguson, Thomas A; Rao, P Kumar; Guan, Jun-Lin; Saitoh, Tatsuya; Akira, Shizuo; Xavier, Ramnik; Virgin, Herbert W; Apte, Rajendra S

2016-10-02

Autophagy is critical for maintaining cellular homeostasis. Organs such as the eye and brain are immunologically privileged. Here, we demonstrate that autophagy is essential for maintaining ocular immune privilege. Deletion of multiple autophagy genes in macrophages leads to an inflammation-mediated eye disease called uveitis that can cause blindness. Loss of autophagy activates inflammasome-mediated IL1B secretion that increases disease severity. Inhibition of caspase activity by gene deletion or pharmacological means completely reverses the disease phenotype. Of interest, experimental uveitis was also increased in a model of Crohn disease, a systemic autoimmune disease in which patients often develop uveitis, offering a potential mechanistic link between macrophage autophagy and systemic disease. These findings directly implicate the homeostatic process of autophagy in blinding eye disease and identify novel pathways for therapeutic intervention in uveitis.

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

PubMed Central

Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

2011-01-01

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases. PMID:21909426

Central nervous system remyelination in culture--a tool for multiple sclerosis research.

PubMed

Zhang, Hui; Jarjour, Andrew A; Boyd, Amanda; Williams, Anna

2011-07-01

Multiple sclerosis is a demyelinating disease of the central nervous system which only affects humans. This makes it difficult to study at a molecular level, and to develop and test potential therapies that may change the course of the disease. The development of therapies to promote remyelination in multiple sclerosis is a key research aim, to both aid restoration of electrical impulse conduction in nerves and provide neuroprotection, reducing disability in patients. Testing a remyelination therapy in the many and various in vivo models of multiple sclerosis is expensive in terms of time, animals and money. We report the development and characterisation of an ex vivo slice culture system using mouse brain and spinal cord, allowing investigation of myelination, demyelination and remyelination, which can be used as an initial reliable screen to select the most promising remyelination strategies. We have automated the quantification of myelin to provide a high content and moderately-high-throughput screen for testing therapies for remyelination both by endogenous and exogenous means and as an invaluable way of studying the biology of remyelination. Copyright © 2011 Elsevier Inc. All rights reserved.

Central nervous system remyelination in culture — A tool for multiple sclerosis research

PubMed Central

Zhang, Hui; Jarjour, Andrew A.; Boyd, Amanda; Williams, Anna

2011-01-01

Multiple sclerosis is a demyelinating disease of the central nervous system which only affects humans. This makes it difficult to study at a molecular level, and to develop and test potential therapies that may change the course of the disease. The development of therapies to promote remyelination in multiple sclerosis is a key research aim, to both aid restoration of electrical impulse conduction in nerves and provide neuroprotection, reducing disability in patients. Testing a remyelination therapy in the many and various in vivo models of multiple sclerosis is expensive in terms of time, animals and money. We report the development and characterisation of an ex vivo slice culture system using mouse brain and spinal cord, allowing investigation of myelination, demyelination and remyelination, which can be used as an initial reliable screen to select the most promising remyelination strategies. We have automated the quantification of myelin to provide a high content and moderately-high-throughput screen for testing therapies for remyelination both by endogenous and exogenous means and as an invaluable way of studying the biology of remyelination. PMID:21515259

Stress in multiple sclerosis: review of new developments and future directions.

PubMed

Lovera, Jesus; Reza, Tara

2013-11-01

In the experimental autoimmune encephalitis model of multiple sclerosis, the effects of stress on disease severity depend on multiple factors, including the animal's genetics and the type of stressor. The studies in humans relating stress to the risk of developing multiple sclerosis have found discordant results. The studies looking at the association of stress with relapses show a fairly consistent association, where higher stress is associated with a higher risk of relapse. Higher stress levels also appear to increase the risk of development of gadolinium-enhancing lesions. A recent randomized trial shows that reducing stress using stress management therapy (SMT), a cognitive-behavioral therapy approach, results in a statistically significant reduction in new magnetic resonance imaging lesions. The magnitude of this effect is large and comparable to the effects of existent disease-modifying therapies, but no data exist yet proving that SMT reduces relapses or clinical progression; the effect of SMT appears to be short-lived. Additional work is needed to improve the duration of this effect and make this therapy more widely accessible.

In vivo modification of tRNA with an artificial nucleobase leads to full disease remission in an animal model of multiple sclerosis.

PubMed

Varghese, Sreeja; Cotter, Michelle; Chevot, Franciane; Fergus, Claire; Cunningham, Colm; Mills, Kingston H; Connon, Stephen J; Southern, John M; Kelly, Vincent P

2017-02-28

Queuine is a modified pyrrolopyrimidine nucleobase derived exclusively from bacteria. It post-transcriptionally replaces guanine 34 in transfer RNA isoacceptors for Asp, Asn, His and Tyr, in almost all eukaryotic organisms, through the activity of the ancient tRNA guanine transglycosylase (TGT) enzyme. tRNA hypomodification with queuine is a characteristic of rapidly-proliferating, non-differentiated cells. Autoimmune diseases, including multiple sclerosis, are characterised by the rapid expansion of T cells directed to self-antigens. Here, we demonstrate the potential medicinal relevance of targeting the modification of tRNA in the treatment of a chronic multiple sclerosis model—murine experimental autoimmune encephalomyelitis. Administration of a de novo designed eukaryotic TGT substrate (NPPDAG) led to an unprecedented complete reversal of clinical symptoms and a dramatic reduction of markers associated with immune hyperactivation and neuronal damage after five daily doses. TGT is essential for the therapeutic effect, since animals deficient in TGT activity were refractory to therapy. The data suggest that exploitation of the eukaryotic TGT enzyme is a promising approach for the treatment of multiple sclerosis.

Antibody-enhanced dengue disease generates a marked CNS inflammatory response in the black-tufted marmoset Callithrix penicillata.

PubMed

Vasconcelos, Barbara Cristina Baldez; Vieira, Juliana Almeida; Silva, Geane Oliveira; Fernandes, Taiany Nogueira; Rocha, Luciano Chaves; Viana, André Pereira; Serique, Cássio Diego Sá; Filho, Carlos Santos; Bringel, Raissa Aires Ribeiro; Teixeira, Francisco Fernando Dacier Lobato; Ferreira, Milene Silveira; Casseb, Samir Mansour Moraes; Carvalho, Valéria Lima; de Melo, Karla Fabiane Lopes; de Castro, Paulo Henrique Gomes; Araújo, Sanderson Corrêa; Diniz, José Antonio Picanço; Demachki, Samia; Anaissi, Ana Karyssa Mendes; Sosthenes, Marcia Consentino Kronka; Vasconcelos, Pedro Fernando da Costa; Anthony, Daniel Clive; Diniz, Cristovam Wanderley Picanço; Diniz, Daniel Guerreiro

2016-02-01

Severe dengue disease is often associated with long-term neurological impairments, but it is unclear what mechanisms are associated with neurological sequelae. Previously, we demonstrated antibody-enhanced dengue disease (ADE) dengue in an immunocompetent mouse model with a dengue virus 2 (DENV2) antibody injection followed by DENV3 virus infection. Here we migrated this ADE model to Callithrix penicillata. To mimic human multiple infections of endemic zones where abundant vectors and multiple serotypes co-exist, three animals received weekly subcutaneous injections of DENV3 (genotype III)-infected supernatant of C6/36 cell cultures, followed 24 h later by anti-DENV2 antibody for 12 weeks. There were six control animals, two of which received weekly anti-DENV2 antibodies, and four further animals received no injections. After multiple infections, brain, liver, and spleen samples were collected and tissue was immunolabeled for DENV3 antigens, ionized calcium binding adapter molecule 1, Ki-67, TNFα. There were marked morphological changes in the microglial population of ADE monkeys characterized by more highly ramified microglial processes, higher numbers of trees and larger surface areas. These changes were associated with intense TNFα-positive immunolabeling. It is unclear why ADE should generate such microglial activation given that IgG does not cross the blood-brain barrier, but this study reveals that in ADE dengue therapy targeting the CNS host response is likely to be important. © 2015 Japanese Society of Neuropathology.

Ozanimod (RPC1063) is a potent sphingosine‐1‐phosphate receptor‐1 (S1P1) and receptor‐5 (S1P5) agonist with autoimmune disease‐modifying activity

PubMed Central

Clemons, B; Brooks, J; Brahmachary, E; Powell, R; Dedman, H; Desale, H G; Timony, G A; Martinborough, E; Rosen, H; Roberts, E; Boehm, M F; Peach, R J

2016-01-01

Background and Purpose Sphingosine1‐phosphate (S1P) receptors mediate multiple events including lymphocyte trafficking, cardiac function, and endothelial barrier integrity. Stimulation of S1P1 receptors sequesters lymphocyte subsets in peripheral lymphoid organs, preventing their trafficking to inflamed tissue sites, modulating immunity. Targeting S1P receptors for treating autoimmune disease has been established in clinical studies with the non‐selective S1P modulator, FTY720 (fingolimod, Gilenya™). The purpose of this study was to assess RPC1063 for its therapeutic utility in autoimmune diseases. Experimental Approach The specificity and potency of RPC1063 (ozanimod) was evaluated for all five S1P receptors, and its effect on cell surface S1P1 receptor expression, was characterized in vitro. The oral pharmacokinetic (PK) parameters and pharmacodynamic effects were established in rodents, and its activity in three models of autoimmune disease (experimental autoimmune encephalitis, 2,4,6‐trinitrobenzenesulfonic acid colitis and CD4+CD45RBhi T cell adoptive transfer colitis) was assessed. Key Results RPC1063 was specific for S1P1 and S1P5 receptors, induced S1P1 receptor internalization and induced a reversible reduction in circulating B and CCR7+ T lymphocytes in vivo. RPC1063 showed high oral bioavailability and volume of distribution, and a circulatory half‐life that supports once daily dosing. Oral RPC1063 reduced inflammation and disease parameters in all three autoimmune disease models. Conclusions and Implications S1P receptor selectivity, favourable PK properties and efficacy in three distinct disease models supports the clinical development of RPC1063 for the treatment of relapsing multiple sclerosis and inflammatory bowel disease, differentiates RPC1063 from other S1P receptor agonists, and could result in improved safety outcomes in the clinic. PMID:26990079

Centenarian Rates and Life Expectancy Related to the Death Rates of Multiple Sclerosis, Asthma, and Rheumatoid Arthritis and the Incidence of Type 1 Diabetes in Children.

PubMed

Lens-Pechakova, Lilia S

2016-02-01

The autoimmune diseases are among the 10 leading causes of death for women and the number two cause of chronic illness in America as well as a predisposing factor for cardiovascular diseases and cancer. Patients of some autoimmune diseases have shown a shorter life span and are a model of accelerated immunosenescence. Conversely, centenarians are used as a model of successful aging and have shown several immune parameters that are better preserved and lower levels of autoantibodies. The study reported here focused on clarifying the connection between longevity and some autoimmune and allergic diseases in 29 developed Organisation for Economic Co-operation and Development (OECD) countries, because multidisciplinary analyses of the accelerated or delayed aging data could show a distinct relationship pattern, help to identify common factors, and determine new important factors that contribute to longevity and healthy aging. The relationships between the mortality rates data of multiple sclerosis (MS), rheumatoid arthritis (RA), asthma, the incidence of type 1 diabetes (T1D) from one side and centenarian rates (two sets) as well as life expectancy data from the other side were assessed using regression models and Pearson correlation coefficients. The data obtained correspond to an inverse linear correlation with different degrees of linearity. This is the first observation of a clear tendency of diminishing centenarian rates or life expectancy in countries having higher death rates of asthma, MS, and RA and a higher incidence of T1D in children. The conclusion is that most probably there are common mechanistic pathways and factors affecting the above diseases and at the same time but in the opposite direction the processes of longevity. Further study, comparing genetic data, mechanistic pathways, and other factors connected to autoimmune diseases with those of longevity could clarify the processes involved, so as to promote longevity and limit the expansion of those diseases in the younger and older population.

Disaggregating Tropical Disease Prevalence by Climatic and Vegetative Zones within Tropical West Africa.

PubMed

Beckley, Carl S; Shaban, Salisu; Palmer, Guy H; Hudak, Andrew T; Noh, Susan M; Futse, James E

2016-01-01

Tropical infectious disease prevalence is dependent on many socio-cultural determinants. However, rainfall and temperature frequently underlie overall prevalence, particularly for vector-borne diseases. As a result these diseases have increased prevalence in tropical as compared to temperate regions. Specific to tropical Africa, the tendency to incorrectly infer that tropical diseases are uniformly prevalent has been partially overcome with solid epidemiologic data. This finer resolution data is important in multiple contexts, including understanding risk, predictive value in disease diagnosis, and population immunity. We hypothesized that within the context of a tropical climate, vector-borne pathogen prevalence would significantly differ according to zonal differences in rainfall, temperature, relative humidity and vegetation condition. We then determined if these environmental data were predictive of pathogen prevalence. First we determined the prevalence of three major pathogens of cattle, Anaplasma marginale, Babesia bigemina and Theileria spp, in the three vegetation zones where cattle are predominantly raised in Ghana: Guinea savannah, semi-deciduous forest, and coastal savannah. The prevalence of A. marginale was 63%, 26% for Theileria spp and 2% for B. bigemina. A. marginale and Theileria spp. were significantly more prevalent in the coastal savannah as compared to either the Guinea savanna or the semi-deciduous forest, supporting acceptance of the first hypothesis. To test the predictive power of environmental variables, the data over a three year period were considered in best subsets multiple linear regression models predicting prevalence of each pathogen. Corrected Akaike Information Criteria (AICc) were assigned to the alternative models to compare their utility. Competitive models for each response were averaged using AICc weights. Rainfall was most predictive of pathogen prevalence, and EVI also contributed to A. marginale and B. bigemina prevalence. These findings support the utility of environmental data for understanding vector-borne disease epidemiology on a regional level within a tropical environment.

Disaggregating Tropical Disease Prevalence by Climatic and Vegetative Zones within Tropical West Africa

PubMed Central

Beckley, Carl S.; Shaban, Salisu; Palmer, Guy H.; Hudak, Andrew T.; Noh, Susan M.; Futse, James E.

2016-01-01

Tropical infectious disease prevalence is dependent on many socio-cultural determinants. However, rainfall and temperature frequently underlie overall prevalence, particularly for vector-borne diseases. As a result these diseases have increased prevalence in tropical as compared to temperate regions. Specific to tropical Africa, the tendency to incorrectly infer that tropical diseases are uniformly prevalent has been partially overcome with solid epidemiologic data. This finer resolution data is important in multiple contexts, including understanding risk, predictive value in disease diagnosis, and population immunity. We hypothesized that within the context of a tropical climate, vector-borne pathogen prevalence would significantly differ according to zonal differences in rainfall, temperature, relative humidity and vegetation condition. We then determined if these environmental data were predictive of pathogen prevalence. First we determined the prevalence of three major pathogens of cattle, Anaplasma marginale, Babesia bigemina and Theileria spp, in the three vegetation zones where cattle are predominantly raised in Ghana: Guinea savannah, semi-deciduous forest, and coastal savannah. The prevalence of A. marginale was 63%, 26% for Theileria spp and 2% for B. bigemina. A. marginale and Theileria spp. were significantly more prevalent in the coastal savannah as compared to either the Guinea savanna or the semi-deciduous forest, supporting acceptance of the first hypothesis. To test the predictive power of environmental variables, the data over a three year period were considered in best subsets multiple linear regression models predicting prevalence of each pathogen. Corrected Akaike Information Criteria (AICc) were assigned to the alternative models to compare their utility. Competitive models for each response were averaged using AICc weights. Rainfall was most predictive of pathogen prevalence, and EVI also contributed to A. marginale and B. bigemina prevalence. These findings support the utility of environmental data for understanding vector-borne disease epidemiology on a regional level within a tropical environment. PMID:27022740

Proteomic Profiling of Cranial (Superior) Cervical Ganglia Reveals Beta-Amyloid and Ubiquitin Proteasome System Perturbations in an Equine Multiple System Neuropathy.

PubMed

McGorum, Bruce C; Pirie, R Scott; Eaton, Samantha L; Keen, John A; Cumyn, Elizabeth M; Arnott, Danielle M; Chen, Wenzhang; Lamont, Douglas J; Graham, Laura C; Llavero Hurtado, Maica; Pemberton, Alan; Wishart, Thomas M

2015-11-01

Equine grass sickness (EGS) is an acute, predominantly fatal, multiple system neuropathy of grazing horses with reported incidence rates of ∼2%. An apparently identical disease occurs in multiple species, including but not limited to cats, dogs, and rabbits. Although the precise etiology remains unclear, ultrastructural findings have suggested that the primary lesion lies in the glycoprotein biosynthetic pathway of specific neuronal populations. The goal of this study was therefore to identify the molecular processes underpinning neurodegeneration in EGS. Here, we use a bottom-up approach beginning with the application of modern proteomic tools to the analysis of cranial (superior) cervical ganglion (CCG, a consistently affected tissue) from EGS-affected patients and appropriate control cases postmortem. In what appears to be the proteomic application of modern proteomic tools to equine neuronal tissues and/or to an inherent neurodegenerative disease of large animals (not a model of human disease), we identified 2,311 proteins in CCG extracts, with 320 proteins increased and 186 decreased by greater than 20% relative to controls. Further examination of selected proteomic candidates by quantitative fluorescent Western blotting (QFWB) and subcellular expression profiling by immunohistochemistry highlighted a previously unreported dysregulation in proteins commonly associated with protein misfolding/aggregation responses seen in a myriad of human neurodegenerative conditions, including but not limited to amyloid precursor protein (APP), microtubule associated protein (Tau), and multiple components of the ubiquitin proteasome system (UPS). Differentially expressed proteins eligible for in silico pathway analysis clustered predominantly into the following biofunctions: (1) diseases and disorders, including; neurological disease and skeletal and muscular disorders and (2) molecular and cellular functions, including cellular assembly and organization, cell-to-cell signaling and interaction (including epinephrine, dopamine, and adrenergic signaling and receptor function), and small molecule biochemistry. Interestingly, while the biofunctions identified in this study may represent pathways underpinning EGS-induced neurodegeneration, this is also the first demonstration of potential molecular conservation (including previously unreported dysregulation of the UPS and APP) spanning the degenerative cascades from an apparently unrelated condition of large animals, to small animal models with altered neuronal vulnerability, and human neurological conditions. Importantly, this study highlights the feasibility and benefits of applying modern proteomic techniques to veterinary investigations of neurodegenerative processes in diseases of large animals. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

A Perspective on Multiple Waves of Influenza Pandemics

PubMed Central

Mummert, Anna; Weiss, Howard; Long, Li-Ping; Amigó, José M.; Wan, Xiu-Feng

2013-01-01

Background A striking characteristic of the past four influenza pandemic outbreaks in the United States has been the multiple waves of infections. However, the mechanisms responsible for the multiple waves of influenza or other acute infectious diseases are uncertain. Understanding these mechanisms could provide knowledge for health authorities to develop and implement prevention and control strategies. Materials and Methods We exhibit five distinct mechanisms, each of which can generate two waves of infections for an acute infectious disease. The first two mechanisms capture changes in virus transmissibility and behavioral changes. The third mechanism involves population heterogeneity (e.g., demography, geography), where each wave spreads through one sub-population. The fourth mechanism is virus mutation which causes delayed susceptibility of individuals. The fifth mechanism is waning immunity. Each mechanism is incorporated into separate mathematical models, and outbreaks are then simulated. We use the models to examine the effects of the initial number of infected individuals (e.g., border control at the beginning of the outbreak) and the timing of and amount of available vaccinations. Results Four models, individually or in any combination, reproduce the two waves of the 2009 H1N1 pandemic in the United States, both qualitatively and quantitatively. One model reproduces the two waves only qualitatively. All models indicate that significantly reducing or delaying the initial numbers of infected individuals would have little impact on the attack rate. Instead, this reduction or delay results in a single wave as opposed to two waves. Furthermore, four of these models also indicate that a vaccination program started earlier than October 2009 (when the H1N1 vaccine was initially distributed) could have eliminated the second wave of infection, while more vaccine available starting in October would not have eliminated the second wave. PMID:23637746

A perspective on multiple waves of influenza pandemics.

PubMed

Mummert, Anna; Weiss, Howard; Long, Li-Ping; Amigó, José M; Wan, Xiu-Feng

2013-01-01

A striking characteristic of the past four influenza pandemic outbreaks in the United States has been the multiple waves of infections. However, the mechanisms responsible for the multiple waves of influenza or other acute infectious diseases are uncertain. Understanding these mechanisms could provide knowledge for health authorities to develop and implement prevention and control strategies. We exhibit five distinct mechanisms, each of which can generate two waves of infections for an acute infectious disease. The first two mechanisms capture changes in virus transmissibility and behavioral changes. The third mechanism involves population heterogeneity (e.g., demography, geography), where each wave spreads through one sub-population. The fourth mechanism is virus mutation which causes delayed susceptibility of individuals. The fifth mechanism is waning immunity. Each mechanism is incorporated into separate mathematical models, and outbreaks are then simulated. We use the models to examine the effects of the initial number of infected individuals (e.g., border control at the beginning of the outbreak) and the timing of and amount of available vaccinations. Four models, individually or in any combination, reproduce the two waves of the 2009 H1N1 pandemic in the United States, both qualitatively and quantitatively. One model reproduces the two waves only qualitatively. All models indicate that significantly reducing or delaying the initial numbers of infected individuals would have little impact on the attack rate. Instead, this reduction or delay results in a single wave as opposed to two waves. Furthermore, four of these models also indicate that a vaccination program started earlier than October 2009 (when the H1N1 vaccine was initially distributed) could have eliminated the second wave of infection, while more vaccine available starting in October would not have eliminated the second wave.

Psychosocial Intervention for Young Children With Chronic Tics

ClinicalTrials.gov

2018-06-18

Tourette's Syndrome; Tourette's Disorder; Tourette's Disease; Tourette Disorder; Tourette Disease; Tic Disorder, Combined Vocal and Multiple Motor; Multiple Motor and Vocal Tic Disorder, Combined; Gilles de La Tourette's Disease; Gilles de la Tourette Syndrome; Gilles De La Tourette's Syndrome; Combined Vocal and Multiple Motor Tic Disorder; Combined Multiple Motor and Vocal Tic Disorder; Chronic Motor and Vocal Tic Disorder

Infection prevention behaviour and infectious disease modelling: a review of the literature and recommendations for the future.

PubMed

Weston, Dale; Hauck, Katharina; Amlôt, Richard

2018-03-09

Given the importance of person to person transmission in the spread of infectious diseases, it is critically important to ensure that human behaviour with respect to infection prevention is appropriately represented within infectious disease models. This paper presents a large scale scoping review regarding the incorporation of infection prevention behaviour in infectious disease models. The outcomes of this review are contextualised within the psychological literature concerning health behaviour and behaviour change, resulting in a series of key recommendations for the incorporation of human behaviour in future infectious disease models. The search strategy focused on terms relating to behaviour, infectious disease and mathematical modelling. The selection criteria were developed iteratively to focus on original research articles that present an infectious disease model with human-human spread, in which individuals' self-protective health behaviour varied endogenously within the model. Data extracted included: the behaviour that is modelled; how this behaviour is modelled; any theoretical background for the modelling of behaviour, and; any behavioural data used to parameterise the models. Forty-two papers from an initial total of 2987 were retained for inclusion in the final review. All of these papers were published between 2002 and 2015. Many of the included papers employed a multiple, linked models to incorporate infection prevention behaviour. Both cognitive constructs (e.g., perceived risk) and, to a lesser extent, social constructs (e.g., social norms) were identified in the included papers. However, only five papers made explicit reference to psychological health behaviour change theories. Finally, just under half of the included papers incorporated behavioural data in their modelling. By contextualising the review outcomes within the psychological literature on health behaviour and behaviour change, three key recommendations for future behavioural modelling are made. First, modellers should consult with the psychological literature on health behaviour/ behaviour change when developing new models. Second, modellers interested in exploring the relationship between behaviour and disease spread should draw on social psychological literature to increase the complexity of the social world represented within infectious disease models. Finally, greater use of context-specific behavioural data (e.g., survey data, observational data) is recommended to parameterise models.

A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health.

PubMed

Lee, Duncan; Mukhopadhyay, Sabyasachi; Rushworth, Alastair; Sahu, Sujit K

2017-04-01

In the United Kingdom, air pollution is linked to around 40000 premature deaths each year, but estimating its health effects is challenging in a spatio-temporal study. The challenges include spatial misalignment between the pollution and disease data; uncertainty in the estimated pollution surface; and complex residual spatio-temporal autocorrelation in the disease data. This article develops a two-stage model that addresses these issues. The first stage is a spatio-temporal fusion model linking modeled and measured pollution data, while the second stage links these predictions to the disease data. The methodology is motivated by a new five-year study investigating the effects of multiple pollutants on respiratory hospitalizations in England between 2007 and 2011, using pollution and disease data relating to local and unitary authorities on a monthly time scale. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Yeast Microcapsule-Mediated Targeted Delivery of Diverse Nanoparticles for Imaging and Therapy via the Oral Route.

PubMed

Zhou, Xing; Zhang, Xiangjun; Han, Songling; Dou, Yin; Liu, Mengyu; Zhang, Lin; Guo, Jiawei; Shi, Qing; Gong, Genghao; Wang, Ruibing; Hu, Jiang; Li, Xiaohui; Zhang, Jianxiang

2017-02-08

Targeting of nanoparticles to distant diseased sites after oral delivery remains highly challenging due to the existence of many biological barriers in the gastrointestinal tract. Here we report targeted oral delivery of diverse nanoparticles in multiple disease models, via a "Trojan horse" strategy based on a bioinspired yeast capsule (YC). Diverse charged nanoprobes including quantum dots (QDs), iron oxide nanoparticles (IONPs), and assembled organic fluorescent nanoparticles can be effectively loaded into YC through electrostatic force-driven spontaneous deposition, resulting in different diagnostic YC assemblies. Also, different positive nanotherapies containing an anti-inflammatory drug indomethacin (IND) or an antitumor drug paclitaxel (PTX) are efficiently packaged into YC. YCs containing either nanoprobes or nanotherapies may be rapidly endocytosed by macrophages and maintained in cells for a relatively long period of time. Post oral administration, nanoparticles packaged in YC are first transcytosed by M cells and sequentially endocytosed by macrophages, then transported to neighboring lymphoid tissues, and finally delivered to remote diseased sites of inflammation or tumor in mice or rats, all through the natural route of macrophage activation, recruitment, and deployment. For the examined acute inflammation model, the targeting efficiency of YC-delivered QDs or IONPs is even higher than that of control nanoprobes administered at the same dose via intravenous injection. Assembled IND or PTX nanotherapies orally delivered via YCs exhibit remarkably potentiated efficacies as compared to nanotherapies alone in animal models of inflammation and tumor, which is consistent with the targeting effect and enhanced accumulation of drug molecules at diseased sites. Consequently, through the intricate transportation route, nanoprobes or nanotherapies enveloped in YC can be preferentially delivered to desired targets, affording remarkably improved efficacies for the treatment of multiple diseases associated with inflammation.

Sequence-Based Prioritization of Nonsynonymous Single-Nucleotide Polymorphisms for the Study of Disease Mutations

PubMed Central

Jiang, Rui ; Yang, Hua ; Zhou, Linqi ; Kuo, C.-C. Jay ; Sun, Fengzhu ; Chen, Ting 

2007-01-01

The increasing demand for the identification of genetic variation responsible for common diseases has translated into a need for sophisticated methods for effectively prioritizing mutations occurring in disease-associated genetic regions. In this article, we prioritize candidate nonsynonymous single-nucleotide polymorphisms (nsSNPs) through a bioinformatics approach that takes advantages of a set of improved numeric features derived from protein-sequence information and a new statistical learning model called “multiple selection rule voting” (MSRV). The sequence-based features can maximize the scope of applications of our approach, and the MSRV model can capture subtle characteristics of individual mutations. Systematic validation of the approach demonstrates that this approach is capable of prioritizing causal mutations for both simple monogenic diseases and complex polygenic diseases. Further studies of familial Alzheimer diseases and diabetes show that the approach can enrich mutations underlying these polygenic diseases among the top of candidate mutations. Application of this approach to unclassified mutations suggests that there are 10 suspicious mutations likely to cause diseases, and there is strong support for this in the literature. PMID:17668383

Disease Modeling Using 3D Organoids Derived from Human Induced Pluripotent Stem Cells.

PubMed

Ho, Beatrice Xuan; Pek, Nicole Min Qian; Soh, Boon-Seng

2018-03-21

The rising interest in human induced pluripotent stem cell (hiPSC)-derived organoid culture has stemmed from the manipulation of various combinations of directed multi-lineage differentiation and morphogenetic processes that mimic organogenesis. Organoids are three-dimensional (3D) structures that are comprised of multiple cell types, self-organized to recapitulate embryonic and tissue development in vitro. This model has been shown to be superior to conventional two-dimensional (2D) cell culture methods in mirroring functionality, architecture, and geometric features of tissues seen in vivo. This review serves to highlight recent advances in the 3D organoid technology for use in modeling complex hereditary diseases, cancer, host-microbe interactions, and possible use in translational and personalized medicine where organoid cultures were used to uncover diagnostic biomarkers for early disease detection via high throughput pharmaceutical screening. In addition, this review also aims to discuss the advantages and shortcomings of utilizing organoids in disease modeling. In summary, studying human diseases using hiPSC-derived organoids may better illustrate the processes involved due to similarities in the architecture and microenvironment present in an organoid, which also allows drug responses to be properly recapitulated in vitro.

Effect of a transactional model education program on coping effectiveness in women with multiple sclerosis.

PubMed

Sanaeinasab, Hormoz; Saffari, Mohsen; Hashempour, Mahrokh; Karimi Zarchi, Ali-Akbar; Alghamdi, Waleed A; Koenig, Harold G

2017-10-01

Multiple sclerosis (MS) is a chronic and progressive disease that causes stress due to its unpredictability and lack of definitive treatments. This study examined the effects of an educational program using a transactional model to help women with MS cope with their disease. In a randomized clinical trial, 80 female patients from the MS Society of Iran were randomized to the intervention ( n  = 40) or a control group ( n  = 40). Outcomes were assessed using Cohen's Perceived Stress Scale (PSS) and the Jalowiec Coping Scale (JCS), which were completed by both groups at baseline, 1 month, and 3 months after the intervention. The intervention consisted of six educational sessions administered over 2 months based on a transactional model. The data were analyzed using repeated measures ANOVA. Average PSS scores decreased significantly over time in the intervention group, while increasing in the control group. Between-group differences were significant at both 1-month and 3-month follow-up ( p  < .001). Both problem-focused and emotion-focused coping styles improved over time in use and effectiveness in the intervention group, whereas little or no change occurred in these coping behaviors in the control group. The transactional model-based education program tested here was successful in reducing stress levels and increasing healthy coping styles in women with MS. If these findings are replicated in future studies, widespread adoption of this program may help women with MS cope more successfully with their disease.

Proteomic analysis of lung tissue by DIGE

USDA-ARS?s Scientific Manuscript database

Lungs perform an essential physiological function, mediated by a complex series of events that involve the coordination of multiple cell types to support not only gaseous exchange, but homeostasis and protection from infection. Guinea pigs are an important animal disease model for a number of infect...

MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction.

PubMed

Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

2017-12-12

Recently, as the research of microRNA (miRNA) continues, there are plenty of experimental evidences indicating that miRNA could be associated with various human complex diseases development and progression. Hence, it is necessary and urgent to pay more attentions to the relevant study of predicting diseases associated miRNAs, which may be helpful for effective prevention, diagnosis and treatment of human diseases. Especially, constructing computational methods to predict potential miRNA-disease associations is worthy of more studies because of the feasibility and effectivity. In this work, we developed a novel computational model of multiple kernels learning-based Kronecker regularized least squares for MiRNA-disease association prediction (MKRMDA), which could reveal potential miRNA-disease associations by automatically optimizing the combination of multiple kernels for disease and miRNA. MKRMDA obtained AUCs of 0.9040 and 0.8446 in global and local leave-one-out cross validation, respectively. Meanwhile, MKRMDA achieved average AUCs of 0.8894 ± 0.0015 in fivefold cross validation. Furthermore, we conducted three different kinds of case studies on some important human cancers for further performance evaluation. In the case studies of colonic cancer, esophageal cancer and lymphoma based on known miRNA-disease associations in HMDDv2.0 database, 76, 94 and 88% of the corresponding top 50 predicted miRNAs were confirmed by experimental reports, respectively. In another two kinds of case studies for new diseases without any known associated miRNAs and diseases only with known associations in HMDDv1.0 database, the verified ratios of two different cancers were 88 and 94%, respectively. All the results mentioned above adequately showed the reliable prediction ability of MKRMDA. We anticipated that MKRMDA could serve to facilitate further developments in the field and the follow-up investigations by biomedical researchers.

The intricate mechanisms of neurodegeneration in prion diseases

PubMed Central

Soto, Claudio; Satani, Nikunj

2010-01-01

Prion diseases are a group of infectious neurodegenerative diseases with an entirely novel mechanism of transmission, involving a protein-only infectious agent that propagates the disease by transmitting protein conformational changes. The disease results from extensive and progressive brain degeneration. The molecular mechanisms involved in neurodegeneration are not entirely known but involve multiple processes operating simultaneously and synergistically in the brain, including spongiform degeneration, synaptic alterations, brain inflammation, neuronal death and the accumulation of protein aggregates. Here, we review the pathways implicated in prion-induced brain damage and put the pieces together into a possible model of neurodegeneration in prion disorders. A more comprehensive understanding of the molecular basis of brain degeneration is essential to develop a much needed therapy for these devastating diseases. PMID:20889378

Multi-state modelling of repeated hospitalisation and death in patients with heart failure: The use of large administrative databases in clinical epidemiology.

PubMed

Ieva, Francesca; Jackson, Christopher H; Sharples, Linda D

2017-06-01

In chronic diseases like heart failure (HF), the disease course and associated clinical event histories for the patient population vary widely. To improve understanding of the prognosis of patients and enable health care providers to assess and manage resources, we wish to jointly model disease progression, mortality and their relation with patient characteristics. We show how episodes of hospitalisation for disease-related events, obtained from administrative data, can be used as a surrogate for disease status. We propose flexible multi-state models for serial hospital admissions and death in HF patients, that are able to accommodate important features of disease progression, such as multiple ordered events and competing risks. Fully parametric and semi-parametric semi-Markov models are implemented using freely available software in R. The models were applied to a dataset from the administrative data bank of the Lombardia region in Northern Italy, which included 15,298 patients who had a first hospitalisation ending in 2006 and 4 years of follow-up thereafter. This provided estimates of the associations of age and gender with rates of hospital admission and length of stay in hospital, and estimates of the expected total time spent in hospital over five years. For example, older patients and men were readmitted more frequently, though the total time in hospital was roughly constant with age. We also discuss the relative merits of parametric and semi-parametric multi-state models, and model assessment and comparison.

The role of α9β1 integrin and its ligands in the development of autoimmune diseases.

PubMed

Kon, Shigeyuki; Uede, Toshimitsu

2018-03-01

Adhesion of cells to extracellular matrix proteins through integrins expressed on the cell surface is important for cell adhesion/motility, survival, and differentiation. Recently, α9β1 integrin was reported to be important for the development of autoimmune diseases including rheumatoid arthritis, multiple sclerosis, and their murine models. In addition, ligands for α9β1 integrin, such as osteopontin and tenascin-C, are well established as key regulators of autoimmune diseases. Therefore, this review focused on the role of interactions between α9β1 integrin and its ligands in the development of autoimmune diseases.

A lethal model of disseminated dengue virus type 1 infection in AG129 mice.

PubMed

Milligan, Gregg N; Sarathy, Vanessa V; White, Mellodee M; Greenberg, M Banks; Campbell, Gerald A; Pyles, Richard B; Barrett, Alan D T; Bourne, Nigel

2017-10-01

The mosquito-borne disease dengue is caused by four serologically and genetically related flaviviruses termed DENV-1 to DENV-4. Dengue is a global public health concern, with both the geographical range and burden of disease increasing rapidly. Clinically, dengue ranges from a relatively mild self-limiting illness to a severe life-threatening and sometimes fatal disease. Infection with one DENV serotype produces life-long homotypic immunity, but incomplete and short-term heterotypic protection. The development of small-animal models that recapitulate the characteristics of the disseminated disease seen clinically has been difficult, slowing the development of vaccines and therapeutics. The AG129 mouse (deficient in interferon alpha/beta and gamma receptor signalling) has proven to be valuable for this purpose, with the development of models of disseminated DENV-2,-3 and -4 disease. Recently, a DENV-1 AG129 model was described, but it requires antibody-dependent enhancement (ADE) to produce lethality. Here we describe a new AG129 model utilizing a non-mouse-adapted DENV-1 strain, West Pacific 74, that does not require ADE to induce lethal disease. Following high-titre intraperitoneal challenge, animals experience a virus infection with dissemination to multiple visceral tissues, including the liver, spleen and intestine. The animals also become thrombocytopenic, but vascular leakage is less prominent than in AG129 models with other DENV serotypes. Taken together, our studies demonstrate that this model is an important addition to dengue research, particularly for understanding the pathological basis of the disease between DENV serotypes and allowing the full spectrum of activity to test comparisons for putative vaccines and antivirals.

Dark matter as a cancer hazard

NASA Astrophysics Data System (ADS)

Chashchina, Olga; Silagadze, Zurab

2016-07-01

We comment on the paper ;Dark matter collisions with the human body; by K. Freese and C. Savage (2012) [1] and describe a dark matter model for which the results of the previous paper do not quite apply. Within this mirror dark matter model, potentially hazardous objects, mirror micrometeorites, can exist and may lead to diseases triggered by multiple mutations, such as cancer, though with very low probability.

Natural killer cell lines preferentially kill clonogenic multiple myeloma cells and decrease myeloma engraftment in a bioluminescent xenograft mouse model.

PubMed

Swift, Brenna E; Williams, Brent A; Kosaka, Yoko; Wang, Xing-Hua; Medin, Jeffrey A; Viswanathan, Sowmya; Martinez-Lopez, Joaquin; Keating, Armand

2012-07-01

Novel therapies capable of targeting drug resistant clonogenic MM cells are required for more effective treatment of multiple myeloma. This study investigates the cytotoxicity of natural killer cell lines against bulk and clonogenic multiple myeloma and evaluates the tumor burden after NK cell therapy in a bioluminescent xenograft mouse model. The cytotoxicity of natural killer cell lines was evaluated against bulk multiple myeloma cell lines using chromium release and flow cytometry cytotoxicity assays. Selected activating receptors on natural killer cells were blocked to determine their role in multiple myeloma recognition. Growth inhibition of clonogenic multiple myeloma cells was assessed in a methylcellulose clonogenic assay in combination with secondary replating to evaluate the self-renewal of residual progenitors after natural killer cell treatment. A bioluminescent mouse model was developed using the human U266 cell line transduced to express green fluorescent protein and luciferase (U266eGFPluc) to monitor disease progression in vivo and assess bone marrow engraftment after intravenous NK-92 cell therapy. Three multiple myeloma cell lines were sensitive to NK-92 and KHYG-1 cytotoxicity mediated by NKp30, NKp46, NKG2D and DNAM-1 activating receptors. NK-92 and KHYG-1 demonstrated 2- to 3-fold greater inhibition of clonogenic multiple myeloma growth, compared with killing of the bulk tumor population. In addition, the residual colonies after treatment formed significantly fewer colonies compared to the control in a secondary replating for a cumulative clonogenic inhibition of 89-99% at the 20:1 effector to target ratio. Multiple myeloma tumor burden was reduced by NK-92 in a xenograft mouse model as measured by bioluminescence imaging and reduction in bone marrow engraftment of U266eGFPluc cells by flow cytometry. This study demonstrates that NK-92 and KHYG-1 are capable of killing clonogenic and bulk multiple myeloma cells. In addition, multiple myeloma tumor burden in a xenograft mouse model was reduced by intravenous NK-92 cell therapy. Since multiple myeloma colony frequency correlates with survival, our observations have important clinical implications and suggest that clinical studies of NK cell lines to treat MM are warranted.

Fingolimod modulates multiple neuroinflammatory markers in a mouse model of Alzheimer’s disease

PubMed Central

Aytan, Nurgul; Choi, Ji-Kyung; Carreras, Isabel; Brinkmann, Volker; Kowall, Neil W.; Jenkins, Bruce G.; Dedeoglu, Alpaslan

2016-01-01

Sphingosine 1-phosphate (SP1) receptors may be attractive targets for modulation of inflammatory processes in neurodegenerative diseases. Recently fingolimod, a functional S1P1 receptor antagonist, was introduced for treatment of multiple sclerosis. We postulated that anti-inflammatory mechanisms of fingolimod might also be protective in Alzheimer’s disease (AD). Therefore, we treated a mouse model of AD, the 5xFAD model, with two doses of fingolimod (1 and 5 mg/kg/day) and measured the response of numerous markers of Aβ pathology as well as inflammatory markers and neurochemistry using biochemical, immunohistochemistry and high resolution magic angle spinning magnetic resonance spectroscopy (MRS). In mice at 3 months of age, we found that fingolimod decreased plaque density as well as soluble plus insoluble Aβ measured by ELISA. Fingolimod also decreased GFAP staining and the number of activated microglia. Taurine has been demonstrated to play a role as an endogenous anti-inflammatory molecule. Taurine levels, measured using MRS, showed a very strong inverse correlation with GFAP levels and ELISA measurements of Aβ, but not with plaque density or activated microglia levels. MRS also showed an effect of fingolimod on glutamate levels. Fingolimod at 1 mg/kg/day provided better neuroprotection than 5 mg/kg/day. Together, these data suggest a potential therapeutic role for fingolimod in AD. PMID:27117087

Fingolimod modulates multiple neuroinflammatory markers in a mouse model of Alzheimer's disease.

PubMed

Aytan, Nurgul; Choi, Ji-Kyung; Carreras, Isabel; Brinkmann, Volker; Kowall, Neil W; Jenkins, Bruce G; Dedeoglu, Alpaslan

2016-04-27

Sphingosine 1-phosphate (SP1) receptors may be attractive targets for modulation of inflammatory processes in neurodegenerative diseases. Recently fingolimod, a functional S1P1 receptor antagonist, was introduced for treatment of multiple sclerosis. We postulated that anti-inflammatory mechanisms of fingolimod might also be protective in Alzheimer's disease (AD). Therefore, we treated a mouse model of AD, the 5xFAD model, with two doses of fingolimod (1 and 5 mg/kg/day) and measured the response of numerous markers of Aβ pathology as well as inflammatory markers and neurochemistry using biochemical, immunohistochemistry and high resolution magic angle spinning magnetic resonance spectroscopy (MRS). In mice at 3 months of age, we found that fingolimod decreased plaque density as well as soluble plus insoluble Aβ measured by ELISA. Fingolimod also decreased GFAP staining and the number of activated microglia. Taurine has been demonstrated to play a role as an endogenous anti-inflammatory molecule. Taurine levels, measured using MRS, showed a very strong inverse correlation with GFAP levels and ELISA measurements of Aβ, but not with plaque density or activated microglia levels. MRS also showed an effect of fingolimod on glutamate levels. Fingolimod at 1 mg/kg/day provided better neuroprotection than 5 mg/kg/day. Together, these data suggest a potential therapeutic role for fingolimod in AD.

Conduction block in the peripheral nervous system in experimental allergic encephalomyelitis

NASA Astrophysics Data System (ADS)

Pender, M. P.; Sears, T. A.

1982-04-01

Experimental allergic encephalomyelitis (EAE) has been widely studied as a model of multiple sclerosis, a central nervous system (CNS) disease of unknown aetiology. The clinical features of both EAE and multiple sclerosis provide the only guide to the progress and severity of these diseases, and are used to assess the response to treatment. In such comparisons the clinical features of EAE are assumed to be due to lesions in the CNS, but in this disease there is also histological evidence of damage to the peripheral nervous system1-8. However, the functional consequences of such peripheral lesions have been entirely ignored. To examine this we have studied nerve conduction in rabbits with EAE. We report here that most of the large diameter afferent fibres are blocked in the region of the dorsal root ganglion and at the dorsal root entry zone, thus accounting for the loss of tendon jerks and also, through the severe loss of proprioceptive information, the ataxia of these animals. We conclude that whenever clinical comparisons are made between EAE and multiple sclerosis, the pathophysiology associated with the histological damage of the peripheral nervous system must be taken into account.

Towards a 21st-century roadmap for biomedical research and drug discovery: consensus report and recommendations.

PubMed

Langley, Gillian R; Adcock, Ian M; Busquet, François; Crofton, Kevin M; Csernok, Elena; Giese, Christoph; Heinonen, Tuula; Herrmann, Kathrin; Hofmann-Apitius, Martin; Landesmann, Brigitte; Marshall, Lindsay J; McIvor, Emily; Muotri, Alysson R; Noor, Fozia; Schutte, Katrin; Seidle, Troy; van de Stolpe, Anja; Van Esch, Hilde; Willett, Catherine; Woszczek, Grzegorz

2017-02-01

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and non-governmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathways-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fluctuations in epidemic modeling - disease extinction and control

NASA Astrophysics Data System (ADS)

Schwartz, Ira

2009-03-01

The analysis of infectious disease fluctuations has recently seen an increasing rise in the use of new tools and models from stochastic dynamics and statistical physics. Examples arise in modeling fluctuations of multi-strain diseases, in modeling adaptive social behavior and its impact on disease fluctuations, and in the analysis of disease extinction in finite population models. Proper stochastic model reduction [1] allows one to predict unobserved fluctuations from observed data in multi-strain models [2]. Degree alteration and power law behavior is predicted in adaptive network epidemic models [3,4]. And extinction rates derived from large fluctuation theory exhibit scaling with respect to distance to the bifurcation point of disease onset with an unusual exponent [5]. In addition to outbreak prediction, another main goal of epidemic modeling is one of eliminating the disease to extinction through various control mechanisms, such as vaccine implementation or quarantine. In this talk, a description will be presented of the fluctuational behavior of several epidemic models and their extinction rates. A general framework and analysis of the effect of non-Gaussian control actuations which enhance the rate to disease extinction will be described. In particular, in it is shown that even in the presence of a small Poisson distributed vaccination program, there is an exponentially enhanced rate to disease extinction. These ideas may lead to improved methods of controlling disease where random vaccinations are prevalent. [4pt] Recent papers:[0pt] [1] E. Forgoston and I. B. Schwartz, ``Escape Rates in a Stochastic Environment with Multiple Scales,'' arXiv:0809.1345 2008.[0pt] [2] L. B. Shaw, L. Billings, I. B. Schwartz, ``Using dimension reduction to improve outbreak predictability of multi-strain diseases,'' J. Math. Bio. 55, 1 2007.[0pt] [3] L. B. Shaw and I. B. Schwartz, ``Fluctuating epidemics on adaptive networks,'' Physical Review E 77, 066101 2008.[0pt] [4] L. B. Shaw and I. B. Schwartz, ``Noise induced dynamics in adaptivenetworks with applications to epidemiology,'' arXiv:0807.3455 2008.[0pt] [5] M. I. Dykman, I. B. Schwartz, A. S. Landsman, ``Disease Extinction in the Presence of Random Vaccination,'' Phys. Rev. Letts. 101, 078101 2008.

A regenerative approach to the treatment of multiple sclerosis.

PubMed

Deshmukh, Vishal A; Tardif, Virginie; Lyssiotis, Costas A; Green, Chelsea C; Kerman, Bilal; Kim, Hyung Joon; Padmanabhan, Krishnan; Swoboda, Jonathan G; Ahmad, Insha; Kondo, Toru; Gage, Fred H; Theofilopoulos, Argyrios N; Lawson, Brian R; Schultz, Peter G; Lairson, Luke L

2013-10-17

Progressive phases of multiple sclerosis are associated with inhibited differentiation of the progenitor cell population that generates the mature oligodendrocytes required for remyelination and disease remission. To identify selective inducers of oligodendrocyte differentiation, we performed an image-based screen for myelin basic protein (MBP) expression using primary rat optic-nerve-derived progenitor cells. Here we show that among the most effective compounds identifed was benztropine, which significantly decreases clinical severity in the experimental autoimmune encephalomyelitis (EAE) model of relapsing-remitting multiple sclerosis when administered alone or in combination with approved immunosuppressive treatments for multiple sclerosis. Evidence from a cuprizone-induced model of demyelination, in vitro and in vivo T-cell assays and EAE adoptive transfer experiments indicated that the observed efficacy of this drug results directly from an enhancement of remyelination rather than immune suppression. Pharmacological studies indicate that benztropine functions by a mechanism that involves direct antagonism of M1 and/or M3 muscarinic receptors. These studies should facilitate the development of effective new therapies for the treatment of multiple sclerosis that complement established immunosuppressive approaches.

Myeloma Cell Dynamics in Response to Treatment Supports a Model of Hierarchical Differentiation and Clonal Evolution.

PubMed

Tang, Min; Zhao, Rui; van de Velde, Helgi; Tross, Jennifer G; Mitsiades, Constantine; Viselli, Suzanne; Neuwirth, Rachel; Esseltine, Dixie-Lee; Anderson, Kenneth; Ghobrial, Irene M; San Miguel, Jesús F; Richardson, Paul G; Tomasson, Michael H; Michor, Franziska

2016-08-15

Since the pioneering work of Salmon and Durie, quantitative measures of tumor burden in multiple myeloma have been used to make clinical predictions and model tumor growth. However, such quantitative analyses have not yet been performed on large datasets from trials using modern chemotherapy regimens. We analyzed a large set of tumor response data from three randomized controlled trials of bortezomib-based chemotherapy regimens (total sample size n = 1,469 patients) to establish and validate a novel mathematical model of multiple myeloma cell dynamics. Treatment dynamics in newly diagnosed patients were most consistent with a model postulating two tumor cell subpopulations, "progenitor cells" and "differentiated cells." Differential treatment responses were observed with significant tumoricidal effects on differentiated cells and less clear effects on progenitor cells. We validated this model using a second trial of newly diagnosed patients and a third trial of refractory patients. When applying our model to data of relapsed patients, we found that a hybrid model incorporating both a differentiation hierarchy and clonal evolution best explains the response patterns. The clinical data, together with mathematical modeling, suggest that bortezomib-based therapy exerts a selection pressure on myeloma cells that can shape the disease phenotype, thereby generating further inter-patient variability. This model may be a useful tool for improving our understanding of disease biology and the response to chemotherapy regimens. Clin Cancer Res; 22(16); 4206-14. ©2016 AACR. ©2016 American Association for Cancer Research.

Risk factors for low bone mineral density in children and adolescents with inflammatory bowel disease.

PubMed

Lopes, Letícia Helena Caldas; Sdepanian, Vera Lucia; Szejnfeld, Vera Lúcia; de Morais, Mauro Batista; Fagundes-Neto, Ulysses

2008-10-01

To evaluate bone mineral density of the lumbar spine in children and adolescents with inflammatory bowel disease, and to identify the clinical risk factors associated with low bone mineral density. Bone mineral density of the lumbar spine was evaluated using dual-energy X-ray absorptiometry (DXA) in 40 patients with inflammatory bowel disease. Patients were 11.8 (SD = 4.1) years old and most of them were male (52.5%). Multiple linear regression analysis was performed to identify potential associations between bone mineral density Z-score and age, height-for-age Z-score, BMI Z-score, cumulative corticosteroid dose in milligrams and in milligrams per kilogram, disease duration, number of relapses, and calcium intake according to the dietary reference intake. Low bone mineral density (Z-score bellow -2) was observed in 25% of patients. Patients with Crohn's disease and ulcerative colitis had equivalent prevalence of low bone mineral density. Multiple linear regression models demonstrated that height-for-age Z-score, BMI Z-score, and cumulative corticosteroid dose in mg had independent effects on BMD, respectively, beta = 0.492 (P = 0.000), beta = 0.460 (P = 0.001), beta = - 0.014 (P = 0.000), and these effects remained significant after adjustments for disease duration, respectively, beta = 0.489 (P = 0.013), beta = 0.467 (P = 0.001), and beta = - 0.005 (P = 0.015). The model accounted for 54.6% of the variability of the BMD Z-score (adjusted R2 = 0.546). The prevalence of low bone mineral density in children and adolescents with inflammatory bowel disease is considerably high and independent risk factors associated with bone mineral density are corticosteroid cumulative dose in milligrams, height-for-age Z-score, and BMI Z-score.

Patients with Alzheimer disease with multiple microbleeds: relation with cerebrospinal fluid biomarkers and cognition.

PubMed

Goos, Jeroen D C; Kester, M I; Barkhof, Frederik; Klein, Martin; Blankenstein, Marinus A; Scheltens, Philip; van der Flier, Wiesje M

2009-11-01

Microbleeds (MBs) are commonly observed in Alzheimer disease. A minority of patients has multiple MBs. We aimed to investigate associations of multiple MBs in Alzheimer disease with clinical and MRI characteristics and cerebrospinal fluid biomarkers. Patients with Alzheimer disease with multiple (>or=8) MBs on T2*-weighted MRI were matched for age, sex, and field strength with patients with Alzheimer disease without MBs on a 1:2 basis. We included 21 patients with multiple MBs (73+/-7 years, 33% female) and 42 patients without MBs (72+/-7 years, 38% female). Mini-Mental State Examination was used to assess dementia severity. Cognitive functions were assessed using neuropsychological tests. Medial temporal lobe atrophy (0 to 4), global cortical atrophy (0 to 3), and white matter hyperintensities (0 to 30) were assessed using visual rating scales. In a subset, apolipoprotein E genotype and cerebrospinal fluid amyloid beta 1-42, total tau and tau phosphorylated at threonine 181 were determined. Patients with multiple MBs performed worse on Mini-Mental State Examination (multiple MB: 17+/-7; no MB: 22+/-4, P<0.05) despite similar disease duration. Atrophy was not related to presence of MBs, but patients with multiple MBs had more white matter hyperintensities (multiple MB: 8.8+/-4.8; no MB: 3.2+/-3.6, P<0.05). Adjusted for age, sex, white matter hyperintensities, and medial temporal lobe atrophy, the multiple MB group additionally performed worse on Visual Association Test object naming and animal fluency. Patients with multiple MBs had lower cerebrospinal fluid amyloid beta 1-42 levels (307+/-61) than patients without MBs (505+/-201, P<0.05). Adjusted for the same covariates, total tau, and tau phosphorylated at threonine 181 were higher in the multiple MB group. Microbleeds are associated with the clinical manifestation and biochemical hallmarks of Alzheimer disease, suggesting possible involvement of MBs in the pathogenesis of Alzheimer disease.

[Application of multiple seasonal autoregressive integrated moving average model in predicting the mumps incidence].

PubMed

Hui, Shisheng; Chen, Lizhang; Liu, Fuqiang; Ouyang, Yanhao

2015-12-01

To establish multiple seasonal autoregressive integrated moving average model(ARIMA) according to mumps disease incidence in Hunan province, and to predict the mumps incidence from May 2015 to April 2016 in Hunan province by the model. The data were downloaded from "Disease Surveillance Information Reporting Management System" in China Information System for Disease Control and Prevention. The monthly incidence of mumps in Hunan province was collected from January 2004 to April 2015 according to the onset date, including clinical diagnosis and laboratory confirmed cases. The predictive analysis method was the ARIMA model in SPSS 18.0 software, the ARIMA model was established on the monthly incidence of mumps from January 2004 to April 2014, and the date from May 2014 to April 2015 was used as the testing sample, Box-Ljung Q test was used to test the residual of the selected model. Finally, the monthly incidence of mumps from May 2015 to April 2016 was predicted by the model. The peak months of the mumps incidence were May to July every year, and the secondary peak months were November to January of the following year, during January 2004 to April 2014 in Hunan province. After the data sequence was handled by smooth sequence, model identification, establishment and diagnosis, the ARIMA(2,1,1) × (0,1,1)(12) was established, Box-Ljung Q test found, Q=8.40, P=0.868, the residual sequence was white noise, the established model to the data information extraction was complete, the model was reasonable. The R(2) value of the model fitting degree was 0.871, and the value of BIC was -1.646, while the average absolute error of the predicted value and the actual value was 0.025/100 000, the average relative error was 13.004%. The relative error of the model for the prediction of the mumps incidence in Hunan province was small, and the predicting results were reliable. Using the ARIMA(2,1,1) ×(0,1,1)(12) model to predict the mumps incidence from April 2016 to May 2015 in Hunan province, the peak months of the mumps incidence were May to July, and the secondary peak months were November to January of the following year, the incidence of the peak month was close to the same period. The ARIMA(2,1,1)×(0,1,1)(12) model is well fitted the trend of the mumps disease incidence in Hunan province, it has some practical value for the prevention and control of the disease.

‘Multi-Epitope-Targeted’ Immune-Specific Therapy for a Multiple Sclerosis-Like Disease via Engineered Multi-Epitope Protein Is Superior to Peptides

PubMed Central

Zilkha-Falb, Rina; Yosef-Hemo, Reut; Cohen, Lydia; Ben-Nun, Avraham

2011-01-01

Antigen-induced peripheral tolerance is potentially one of the most efficient and specific therapeutic approaches for autoimmune diseases. Although highly effective in animal models, antigen-based strategies have not yet been translated into practicable human therapy, and several clinical trials using a single antigen or peptidic-epitope in multiple sclerosis (MS) yielded disappointing results. In these clinical trials, however, the apparent complexity and dynamics of the pathogenic autoimmunity associated with MS, which result from the multiplicity of potential target antigens and “epitope spread”, have not been sufficiently considered. Thus, targeting pathogenic T-cells reactive against a single antigen/epitope is unlikely to be sufficient; to be effective, immunospecific therapy to MS should logically neutralize concomitantly T-cells reactive against as many major target antigens/epitopes as possible. We investigated such “multi-epitope-targeting” approach in murine experimental autoimmune encephalomyelitis (EAE) associated with a single (“classical”) or multiple (“complex”) anti-myelin autoreactivities, using cocktail of different encephalitogenic peptides vis-a-vis artificial multi-epitope-protein (designated Y-MSPc) encompassing rationally selected MS-relevant epitopes of five major myelin antigens, as “multi-epitope-targeting” agents. Y-MSPc was superior to peptide(s) in concomitantly downregulating pathogenic T-cells reactive against multiple myelin antigens/epitopes, via inducing more effective, longer lasting peripheral regulatory mechanisms (cytokine shift, anergy, and Foxp3+ CTLA4+ regulatory T-cells). Y-MSPc was also consistently more effective than the disease-inducing single peptide or peptide cocktail, not only in suppressing the development of “classical” or “complex EAE” or ameliorating ongoing disease, but most importantly, in reversing chronic EAE. Overall, our data emphasize that a “multi-epitope-targeting” strategy is required for effective immune-specific therapy of organ-specific autoimmune diseases associated with complex and dynamic pathogenic autoimmunity, such as MS; our data further demonstrate that the “multi-epitope-targeting” approach to therapy is optimized through specifically designed multi-epitope-proteins, rather than myelin peptide cocktails, as “multi-epitope-targeting” agents. Such artificial multi-epitope proteins can be tailored to other organ-specific autoimmune diseases. PMID:22140475

[Feasibility of device closure for multiple atrial septal defects using 3D printing and ultrasound-guided intervention technique].

PubMed

Qiu, X; Lü, B; Xu, N; Yan, C W; Ouyang, W B; Liu, Y; Zhang, F W; Yue, Z Q; Pang, K J; Pan, X B

2017-04-25

Objective: To investigate the feasibility of trans-catheter closure of multiple atrial septal defects (ASD) monitored by trans-thoracic echocardiography (TTE) under the guidance of 3D printing heart model. Methods: Between April and August 2016, a total of 21 patients (8 male and 13 female) with multiple ASD in Fuwai Hospital of Chinese Academy of Medical Sciences underwent CT scan and 3-dimensional echocardiography for heart disease model produced by 3D printing technique. The best occlusion program was determined through the simulation test on the model. Percutaneous device closure of multiple ASD was performed follow the predetermined program guided by TTE. Clinical follow-up including electrocardiogram and TTE was arranged at 1 month after the procedure. Results: The trans-catheter procedure was successful in all 21 patients using a single atrial septal occluder. Mild residual shunt was found in 5 patient in the immediate postoperative period, 3 of them were disappeared during postoperative follow-up. There was no death, vascular damage, arrhythmia, device migration, thromboembolism, valvular dysfunction during the follow-up period. Conclusion: The use of 3D printing heart model provides a useful reference for transcatheter device closure of multiple ASD achieving through ultrasound-guided intervention technique, which appears to be safe and feasible with good outcomes of short-term follow-up.

From animal models to human disease: a genetic approach for personalized medicine in ALS.

PubMed

Picher-Martel, Vincent; Valdmanis, Paul N; Gould, Peter V; Julien, Jean-Pierre; Dupré, Nicolas

2016-07-11

Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disease in adults. Classical ALS is characterized by the death of upper and lower motor neurons leading to progressive paralysis. Approximately 10 % of ALS patients have familial form of the disease. Numerous different gene mutations have been found in familial cases of ALS, such as mutations in superoxide dismutase 1 (SOD1), TAR DNA-binding protein 43 (TDP-43), fused in sarcoma (FUS), C9ORF72, ubiquilin-2 (UBQLN2), optineurin (OPTN) and others. Multiple animal models were generated to mimic the disease and to test future treatments. However, no animal model fully replicates the spectrum of phenotypes in the human disease and it is difficult to assess how a therapeutic effect in disease models can predict efficacy in humans. Importantly, the genetic and phenotypic heterogeneity of ALS leads to a variety of responses to similar treatment regimens. From this has emerged the concept of personalized medicine (PM), which is a medical scheme that combines study of genetic, environmental and clinical diagnostic testing, including biomarkers, to individualized patient care. In this perspective, we used subgroups of specific ALS-linked gene mutations to go through existing animal models and to provide a comprehensive profile of the differences and similarities between animal models of disease and human disease. Finally, we reviewed application of biomarkers and gene therapies relevant in personalized medicine approach. For instance, this includes viral delivering of antisense oligonucleotide and small interfering RNA in SOD1, TDP-43 and C9orf72 mice models. Promising gene therapies raised possibilities for treating differently the major mutations in familial ALS cases.

Excess Circulating Alternatively Activated Myeloid (M2) Cells Accelerate ALS Progression While Inhibiting Experimental Autoimmune Encephalomyelitis

PubMed Central

Miller, Omer; Butovsky, Oleg; Bukshpan, Shay; Beers, David R.; Henkel, Jenny S.; Yoles, Eti; Appel, Stanley H.; Schwartz, Michal

2011-01-01

Background Circulating immune cells including autoreactive T cells and monocytes have been documented as key players in maintaining, protecting and repairing the central nervous system (CNS) in health and disease. Here, we hypothesized that neurodegenerative diseases might be associated, similarly to tumors, with increased levels of circulating peripheral myeloid derived suppressor cells (MDSCs), representing a subset of suppressor cells that often expand under pathological conditions and inhibit possible recruitment of helper T cells needed for fighting off the disease. Methods and Findings We tested this working hypothesis in amyotrophic lateral sclerosis (ALS) and its mouse model, which are characterized by a rapid progression once clinical symptoms are evident. Adaptive transfer of alternatively activated myeloid (M2) cells, which homed to the spleen and exhibited immune suppressive activity in G93A mutant superoxide dismutase-1 (mSOD1) mice at a stage before emergence of disease symptoms, resulted in earlier appearance of disease symptoms and shorter life expectancy. The same protocol mitigated the inflammation-induced disease model of multiple sclerosis, experimental autoimmune encephalomyelitis (EAE), which requires circulating T cells for disease induction. Analysis of whole peripheral blood samples obtained from 28 patients suffering from sporadic ALS (sALS), revealed a two-fold increase in the percentage of circulating MDSCs (LIN−/LowHLA-DR−CD33+) compared to controls. Conclusions Taken together, these results emphasize the distinct requirements for fighting the inflammatory neurodegenerative disease, multiple sclerosis, and the neurodegenerative disease, ALS, though both share a local inflammatory component. Moreover, the increased levels of circulating MDSCs in ALS patients indicates the operation of systemic mechanisms that might lead to an impairment of T cell reactivity needed to overcome the disease conditions within the CNS. This high level of suppressive immune cells might represent a risk factor and a novel target for therapeutic intervention in ALS at least at the early stage. PMID:22073221

Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes, and Cytokine Signaling Genes in Crohn's Disease

PubMed Central

Carbonetto, Peter; Stephens, Matthew

2013-01-01

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn's disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and “Measles” pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14, and FYN) constitute novel putative T1D loci for further study. PMID:24098138

Neuroimmunology Research. A Report from the Cuban Network of Neuroimmunology

PubMed Central

Robinson-Agramonte, María de los Angeles

2018-01-01

Neuroimmunology can be traced back to the XIX century through the descriptions of some of the disease’s models (e.g., multiple sclerosis and Guillain Barret syndrome, amongst others). The diagnostic tools are based in the cerebrospinal fluid (CSF) analysis developed by Quincke or in the development of neuroimmunotherapy with the earlier expression in Pasteur’s vaccine for rabies. Nevertheless, this field, which began to become delineated as an independent research area in the 1940s, has evolved as an innovative and integrative field at the shared edges of neurosciences, immunology, and related clinical and research areas, which are currently becoming a major concern for neuroscience and indeed for all of the scientific community linked to it. The workshop focused on several topics: (1) the molecular mechanisms of immunoregulation in health and neurological diseases, (like multiple sclerosis, autism, ataxias, epilepsy, Alzheimer and Parkinson’s disease); (2) the use of animal models for neurodegenerative diseases (ataxia, fronto-temporal dementia/amyotrophic lateral sclerosis, ataxia-telangiectasia); (3) the results of new interventional technologies in neurology, with a special interest in the implementation of surgical techniques and the management of drug-resistant temporal lobe epilepsy; (4) the use of non-invasive brain stimulation in neurodevelopmental disorders; as well as (5) the efficacy of neuroprotective molecules in neurodegenerative diseases. This paper summarizes the highlights of the symposium. PMID:29738432

Solving Immunology?

PubMed

Vodovotz, Yoram; Xia, Ashley; Read, Elizabeth L; Bassaganya-Riera, Josep; Hafler, David A; Sontag, Eduardo; Wang, Jin; Tsang, John S; Day, Judy D; Kleinstein, Steven H; Butte, Atul J; Altman, Matthew C; Hammond, Ross; Sealfon, Stuart C

2017-02-01

Emergent responses of the immune system result from the integration of molecular and cellular networks over time and across multiple organs. High-content and high-throughput analysis technologies, concomitantly with data-driven and mechanistic modeling, hold promise for the systematic interrogation of these complex pathways. However, connecting genetic variation and molecular mechanisms to individual phenotypes and health outcomes has proven elusive. Gaps remain in data, and disagreements persist about the value of mechanistic modeling for immunology. Here, we present the perspectives that emerged from the National Institute of Allergy and Infectious Disease (NIAID) workshop 'Complex Systems Science, Modeling and Immunity' and subsequent discussions regarding the potential synergy of high-throughput data acquisition, data-driven modeling, and mechanistic modeling to define new mechanisms of immunological disease and to accelerate the translation of these insights into therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Drug-disease association and drug-repositioning predictions in complex diseases using causal inference-probabilistic matrix factorization.

PubMed

Yang, Jihong; Li, Zheng; Fan, Xiaohui; Cheng, Yiyu

2014-09-22

The high incidence of complex diseases has become a worldwide threat to human health. Multiple targets and pathways are perturbed during the pathological process of complex diseases. Systematic investigation of complex relationship between drugs and diseases is necessary for new association discovery and drug repurposing. For this purpose, three causal networks were constructed herein for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. A causal inference-probabilistic matrix factorization (CI-PMF) approach was proposed to predict and classify drug-disease associations, and further used for drug-repositioning predictions. First, multilevel systematic relations between drugs and diseases were integrated from heterogeneous databases to construct causal networks connecting drug-target-pathway-gene-disease. Then, the association scores between drugs and diseases were assessed by evaluating a drug's effects on multiple targets and pathways. Furthermore, PMF models were learned based on known interactions, and associations were then classified into three types by trained models. Finally, therapeutic associations were predicted based upon the ranking of association scores and predicted association types. In terms of drug-disease association prediction, modified causal inference included in CI-PMF outperformed existing causal inference with a higher AUC (area under receiver operating characteristic curve) score and greater precision. Moreover, CI-PMF performed better than single modified causal inference in predicting therapeutic drug-disease associations. In the top 30% of predicted associations, 58.6% (136/232), 50.8% (31/61), and 39.8% (140/352) hit known therapeutic associations, while precisions obtained by the latter were only 10.2% (231/2264), 8.8% (36/411), and 9.7% (189/1948). Clinical verifications were further conducted for the top 100 newly predicted therapeutic associations. As a result, 21, 12, and 32 associations have been studied and many treatment effects of drugs on diseases were investigated for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. Related chains in causal networks were extracted for these 65 clinical-verified associations, and we further illustrated the therapeutic role of etodolac in breast cancer by inferred chains. Overall, CI-PMF is a useful approach for associating drugs with complex diseases and provides potential values for drug repositioning.

Vaccine Effects on Heterogeneity in Susceptibility and Implications for Population Health Management.

PubMed

Langwig, Kate E; Wargo, Andrew R; Jones, Darbi R; Viss, Jessie R; Rutan, Barbara J; Egan, Nicholas A; Sá-Guimarães, Pedro; Kim, Min Sun; Kurath, Gael; Gomes, M Gabriela M; Lipsitch, Marc

2017-11-21

Heterogeneity in host susceptibility is a key determinant of infectious disease dynamics but is rarely accounted for in assessment of disease control measures. Understanding how susceptibility is distributed in populations, and how control measures change this distribution, is integral to predicting the course of epidemics with and without interventions. Using multiple experimental and modeling approaches, we show that rainbow trout have relatively homogeneous susceptibility to infection with infectious hematopoietic necrosis virus and that vaccination increases heterogeneity in susceptibility in a nearly all-or-nothing fashion. In a simple transmission model with an R 0 of 2, the highly heterogeneous vaccine protection would cause a 35 percentage-point reduction in outbreak size over an intervention inducing homogenous protection at the same mean level. More broadly, these findings provide validation of methodology that can help to reduce biases in predictions of vaccine impact in natural settings and provide insight into how vaccination shapes population susceptibility. IMPORTANCE Differences among individuals influence transmission and spread of infectious diseases as well as the effectiveness of control measures. Control measures, such as vaccines, may provide leaky protection, protecting all hosts to an identical degree, or all-or-nothing protection, protecting some hosts completely while leaving others completely unprotected. This distinction can have a dramatic influence on disease dynamics, yet this distribution of protection is frequently unaccounted for in epidemiological models and estimates of vaccine efficacy. Here, we apply new methodology to experimentally examine host heterogeneity in susceptibility and mode of vaccine action as distinct components influencing disease outcome. Through multiple experiments and new modeling approaches, we show that the distribution of vaccine effects can be robustly estimated. These results offer new experimental and inferential methodology that can improve predictions of vaccine effectiveness and have broad applicability to human, wildlife, and ecosystem health. Copyright © 2017 Langwig et al.

Preconditioning Provides Neuroprotection in Models of CNS Disease: Paradigms and Clinical Significance

PubMed Central

Stetler, R. Anne; Leak, Rehana K.; Gan, Yu; Li, Peiying; Hu, Xiaoming; Jing, Zheng; Chen, Jun; Zigmond, Michael J.; Gao, Yanqin

2014-01-01

Preconditioning is a phenomenon in which brief episodes of a sublethal insult induce robust protection against subsequent lethal injuries. Preconditioning has been observed in multiple organisms and can occur in the brain as well as other tissues. Extensive animal studies suggest that the brain can be preconditioned to resist acute injuries, such as ischemic stroke, neonatal hypoxia/ischemia, trauma, and agents that are used in models of neurodegenerative diseases, such as Parkinson’s disease and Alzheimer’s disease. Effective preconditioning stimuli are numerous and diverse, ranging from transient ischemia, hypoxia, hyperbaric oxygen, hypothermia and hyperthermia, to exposure to neurotoxins and pharmacological agents. The phenomenon of “cross-tolerance,” in which a sublethal stress protects against a different type of injury, suggests that different preconditioning stimuli may confer protection against a wide range of injuries. Research conducted over the past few decades indicates that brain preconditioning is complex, involving multiple effectors such as metabolic inhibition, activation of extra- and intracellular defense mechanisms, a shift in the neuronal excitatory/inhibitory balance, and reduction in inflammatory sequelae. An improved understanding of brain preconditioning should help us identify innovative therapeutic strategies that prevent or at least reduce neuronal damage in susceptible patients. In this review, we focus on the experimental evidence of preconditioning in the brain and systematically survey the models used to develop paradigms for neuroprotection, and then discuss the clinical potential of brain preconditioning. In a subsequent components of this two-part series, we will discuss the cellular and molecular events that are likely to underlie these phenomena. PMID:24389580

Combinations of chromosome transfer and genome editing for the development of cell/animal models of human disease and humanized animal models.

PubMed

Uno, Narumi; Abe, Satoshi; Oshimura, Mitsuo; Kazuki, Yasuhiro

2018-02-01

Chromosome transfer technology, including chromosome modification, enables the introduction of Mb-sized or multiple genes to desired cells or animals. This technology has allowed innovative developments to be made for models of human disease and humanized animals, including Down syndrome model mice and humanized transchromosomic (Tc) immunoglobulin mice. Genome editing techniques are developing rapidly, and permit modifications such as gene knockout and knockin to be performed in various cell lines and animals. This review summarizes chromosome transfer-related technologies and the combined technologies of chromosome transfer and genome editing mainly for the production of cell/animal models of human disease and humanized animal models. Specifically, these include: (1) chromosome modification with genome editing in Chinese hamster ovary cells and mouse A9 cells for efficient transfer to desired cell types; (2) single-nucleotide polymorphism modification in humanized Tc mice with genome editing; and (3) generation of a disease model of Down syndrome-associated hematopoiesis abnormalities by the transfer of human chromosome 21 to normal human embryonic stem cells and the induction of mutation(s) in the endogenous gene(s) with genome editing. These combinations of chromosome transfer and genome editing open up new avenues for drug development and therapy as well as for basic research.

Bridging paradigms: hybrid mechanistic-discriminative predictive models.

PubMed

Doyle, Orla M; Tsaneva-Atansaova, Krasimira; Harte, James; Tiffin, Paul A; Tino, Peter; Díaz-Zuccarini, Vanessa

2013-03-01

Many disease processes are extremely complex and characterized by multiple stochastic processes interacting simultaneously. Current analytical approaches have included mechanistic models and machine learning (ML), which are often treated as orthogonal viewpoints. However, to facilitate truly personalized medicine, new perspectives may be required. This paper reviews the use of both mechanistic models and ML in healthcare as well as emerging hybrid methods, which are an exciting and promising approach for biologically based, yet data-driven advanced intelligent systems.

The social and political lives of zoonotic disease models: narratives, science and policy.

PubMed

Leach, Melissa; Scoones, Ian

2013-07-01

Zoonotic diseases currently pose both major health threats and complex scientific and policy challenges, to which modelling is increasingly called to respond. In this article we argue that the challenges are best met by combining multiple models and modelling approaches that elucidate the various epidemiological, ecological and social processes at work. These models should not be understood as neutral science informing policy in a linear manner, but as having social and political lives: social, cultural and political norms and values that shape their development and which they carry and project. We develop and illustrate this argument in relation to the cases of H5N1 avian influenza and Ebola, exploring for each the range of modelling approaches deployed and the ways they have been co-constructed with a particular politics of policy. Addressing the complex, uncertain dynamics of zoonotic disease requires such social and political lives to be made explicit in approaches that aim at triangulation rather than integration, and plural and conditional rather than singular forms of policy advice. Copyright © 2013 Elsevier Ltd. All rights reserved.

Insights into Parkinson's disease from computational models of the basal ganglia.

PubMed

Humphries, Mark D; Obeso, Jose Angel; Dreyer, Jakob Kisbye

2018-04-17

Movement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their amelioration of symptoms are incompletely understood. Using Parkinson's disease as a case study, we review here how computational models are a crucial tool for taming this complexity, across causative mechanisms, consequent neural dynamics and treatments. For mechanisms, we review models that capture the effects of losing dopamine on basal ganglia function; for dynamics, we discuss models that have transformed our understanding of how beta-band (15-30 Hz) oscillations arise in the parkinsonian basal ganglia. For treatments, we touch on the breadth of computational modelling work trying to understand the therapeutic actions of deep brain stimulation. Collectively, models from across all levels of description are providing a compelling account of the causes, symptoms and treatments for Parkinson's disease. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Broadening perspectives on pediatric oral health care provision: social determinants of health and behavioral management.

PubMed

Fisher-Owens, Susan

2014-01-01

Dental caries is not just the most common chronic childhood disease, with not insignificant burden of disease during childhood, but also lifelong impact. Traditional models that focus on the "mouth in the chair" have been helpful but insufficient to identify structural root causes for its high incidence, thus having a limited ability to prevent the disease. The addition of social and behavioral determinants to strictly biologic models provides the full context of care, enabling providers to better tailor their guidance and improve health outcomes. In-office behavioral management involves understanding these determinants and applying appropriate techniques; these not only can help reset family and patient expectations but can actually increase compliance. Lastly, children with multiple medical issues require additional focus, as they can carry greater burden of disease, making it even more critical during office visits to offer multifactorial compliance strategies for these patients and their parents.

[Nurse-Led Care Models in the Context of Community Elders With Chronic Disease Management: A Systematic Review].

PubMed

Hsieh, Pei-Lun; Chen, Ching-Min

2016-08-01

Longer average life expectancies have caused the rapid growth of the elderly as a percentage of Taiwan's population and, as a result of the number of elders with chronic diseases and disability. Providing continuing-care services in community settings for elderly with multiple chronic conditions has become an urgent need. To review the nurse-led care models that are currently practiced among elders with chronic disease in the community and to further examine the effectiveness and essential components of these models using a systematic review method. Twelve original articles on chronic disease-care planning for the elderly or on nurse-led care management interventions that were published between 2000 and 2015 in any of five electronic databases: MEDLINE, PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature) Plus with Full Text, Cochrane Library, and CEPS (Chinese Electronic Periodicals Service）were selected and analyzed systematically. Four types of nurse-led community care models, including primary healthcare, secondary prevention care, cross-boundary models, and case management, were identified. Chronic disease-care planning, case management, and disease self-management were found to be the essential components of the services that were provided. The care models used systematic processes to conduct assessment, planning, implementation, coordination, and follow-up activities as well as to deliver services and to evaluate disease status. The results revealed that providing continuing-care services through the nurse-led community chronic disease-care model and cross-boundary model enhanced the ability of the elderly to self-manage their chronic diseases, improved healthcare referrals, provided holistic care, and maximized resource utilization efficacy. The present study cross-referenced all reviewed articles in terms of target clients, content, intervention, measurements, and outcome indicators. Study results may be referenced in future implementations of nurse-led community care models as well as in future research.

The use of fish models to study human neurological disorders.

PubMed

Matsui, Hideaki

2017-07-01

Small teleost fish including zebrafish and medaka have been used as animal models in basic science research due to the relative ease of handling and transparency during embryogenesis. Current advances in genetic engineering and progress in disease genetics allowed utilization of these fish to study neurological diseases and psychiatric disorders. This review summarizes the advantages and disadvantages of using fish for neuropsychiatric research using primarily our own studies as examples. We discuss how fish belong to a class of vertebrates, are feasible for imaging, and include diverse species with multiple research possibilities yet to be discovered. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

Therapeutic role of rifampicin in Alzheimer's disease.

PubMed

Yulug, Burak; Hanoglu, Lütfü; Ozansoy, Mehmet; Isık, Dogan; Kilic, Ulkan; Kilic, Ertugrul; Schabitz, Wolf Rüdiger

2018-03-01

Rifampicin exerts significant brain protective functions in multiple experimental models. Here we summarize the underlying mechanisms of the neuroprotective and pro-cognitive effects of rifampicin that are mediated by its anti-inflammatory, anti-tau, anti-amyloid, and cholinergic effects. Beyond suggesting that rifampicin shows strong brain protective effects in preclinical models of Alzheimer's disease, we also provide substantial clinical evidence for the neuroprotective and pro-cognitive effects of rifampicin. Future neuroimaging studies combined with clinical assessment scores are the following steps to be taken in this field of research. © 2018 The Authors. Psychiatry and Clinical Neurosciences © 2018 Japanese Society of Psychiatry and Neurology.

The expanding syndrome of amyotrophic lateral sclerosis: a clinical and molecular odyssey

PubMed Central

Turner, Martin R; Swash, Michael

2015-01-01

Recent advances in understanding amyotrophic lateral sclerosis (ALS) have delivered new questions. Disappointingly, the initial enthusiasm for transgenic mouse models of the disease has not been followed by rapid advances in therapy or prevention. Monogenic models may have inadvertently masked the true complexity of the human disease. ALS has evolved into a multisystem disorder, involving a final common pathway accessible via multiple upstream aetiological tributaries. Nonetheless, there is a common clinical core to ALS, as clear today as it was to Charcot and others. We stress the continuing relevance of clinical observations amid the increasing molecular complexity of ALS. PMID:25644224

Noninvasive optical monitoring multiple physiological parameters response to cytokine storm

NASA Astrophysics Data System (ADS)

Li, Zebin; Li, Ting

2018-02-01

Cancer and other disease originated by immune or genetic problems have become a main cause of death. Gene/cell therapy is a highlighted potential method for the treatment of these diseases. However, during the treatment, it always causes cytokine storm, which probably trigger acute respiratory distress syndrome and multiple organ failure. Here we developed a point-of-care device for noninvasive monitoring cytokine storm induced multiple physiological parameters simultaneously. Oxy-hemoglobin, deoxy-hemoglobin, water concentration and deep-tissue/tumor temperature variations were simultaneously measured by extended near infrared spectroscopy. Detection algorithms of symptoms such as shock, edema, deep-tissue fever and tissue fibrosis were developed and included. Based on these measurements, modeling of patient tolerance and cytokine storm intensity were carried out. This custom device was tested on patients experiencing cytokine storm in intensive care unit. The preliminary data indicated the potential of our device in popular and milestone gene/cell therapy, especially, chimeric antigen receptor T-cell immunotherapy (CAR-T).

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

PubMed

Ross, Elsie Gyang; Shah, Nigam H; Dalman, Ronald L; Nead, Kevin T; Cooke, John P; Leeper, Nicholas J

2016-11-01

A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aims of this study were to develop machine learning algorithms for the identification of disease and the prognostication of mortality risk and to determine whether such models perform better than classical statistical analyses. Focusing on peripheral artery disease (PAD), patient data were derived from a prospective, observational study of 1755 patients who presented for elective coronary angiography. We employed multiple supervised machine learning algorithms and used diverse clinical, demographic, imaging, and genomic information in a hypothesis-free manner to build models that could identify patients with PAD and predict future mortality. Comparison was made to standard stepwise linear regression models. Our machine-learned models outperformed stepwise logistic regression models both for the identification of patients with PAD (area under the curve, 0.87 vs 0.76, respectively; P = .03) and for the prediction of future mortality (area under the curve, 0.76 vs 0.65, respectively; P = .10). Both machine-learned models were markedly better calibrated than the stepwise logistic regression models, thus providing more accurate disease and mortality risk estimates. Machine learning approaches can produce more accurate disease classification and prediction models. These tools may prove clinically useful for the automated identification of patients with highly morbid diseases for which aggressive risk factor management can improve outcomes. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health.

PubMed

Conlon, Kathryn C; Kintziger, Kristina W; Jagger, Meredith; Stefanova, Lydia; Uejio, Christopher K; Konrad, Charles

2016-08-09

There is interest among agencies and public health practitioners in the United States (USA) to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE) program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida.

Mechanism-based approaches to treating fragile X.

PubMed

Dölen, Gül; Carpenter, Randall L; Ocain, Timothy D; Bear, Mark F

2010-07-01

Fragile X is the leading inherited cause of mental retardation and autism. Recent advances in our mechanistic understanding of the disease have led to the identification of the metabotropic glutamate receptor (mGluR) as a therapeutic target for the disease. These studies have revealed that core defects in multiple animal models can be corrected by down regulation of mGluR5 signaling. Although it remains to be seen if mGluR5 antagonists or related approaches will succeed in humans with fragile X, the progress in fragile X stands as a strong testament to the power of applying knowledge of basic neurobiology to understand pathophysiology in a genetically validated model of human psychiatric disease. These breakthroughs and several of the resulting drug development efforts are reviewed. (c) 2010 Elsevier Inc. All rights reserved.

Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health

PubMed Central

Conlon, Kathryn C.; Kintziger, Kristina W.; Jagger, Meredith; Stefanova, Lydia; Uejio, Christopher K.; Konrad, Charles

2016-01-01

There is interest among agencies and public health practitioners in the United States (USA) to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE) program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida. PMID:27517942

Negligible impact of differential item functioning between Black and White dialysis patients on the Kidney Disease Quality of Life 36-item short form survey (KDQOLTM-36).

PubMed

Peipert, John D; Bentler, Peter; Klicko, Kristi; Hays, Ron D

2018-05-14

Black dialysis patients report better health-related quality of life (HRQOL) than White patients, which may be explained if Black and White patients respond systematically differently to HRQOL survey items. We examined differential item functioning (DIF) of the Kidney Disease Quality of Life 36-item (KDQOL TM -36) Burden of Kidney Disease, Symptoms and Problems with Kidney Disease, and Effects of Kidney Disease scales between Black (n = 18,404) and White (n = 21,439) dialysis patients. We fit multiple group confirmatory factor analysis models with increasing invariance: a Configural model (invariant factor structure), a Metric model (invariant factor loadings), and a Scalar model (invariant intercepts). Criteria for invariance included non-significant χ 2 tests, > 0.002 difference in the models' CFI, and > 0.015 difference in RMSEA and SRMR. Next, starting with a fully invariant model, we freed loadings and intercepts item-by-item to determine if DIF impacted estimated KDQOL TM -36 scale means. ΔCFI was 0.006 between the metric and scalar models but was reduced to 0.001 when we freed intercepts for the burdens and symptoms and problems of kidney disease scales. In comparison to standardized means of 0 in the White group, those for the Black group on the Burdens, Symptoms and Problems, and Effects of Kidney Disease scales were 0.218, 0.061, and 0.161, respectively. When loadings and thresholds were released sequentially, differences in means between models ranged between 0.001 and 0.048. Despite some DIF, impacts on KDQOL TM -36 responses appear to be minimal. We conclude that the KDQOL TM -36 is appropriate to make substantive comparisons of HRQOL between Black and White dialysis patients.

Impact of the Alzheimer's Disease Neuroimaging Initiative, 2004 to 2014.

PubMed

Weiner, Michael W; Veitch, Dallas P; Aisen, Paul S; Beckett, Laurel A; Cairns, Nigel J; Cedarbaum, Jesse; Donohue, Michael C; Green, Robert C; Harvey, Danielle; Jack, Clifford R; Jagust, William; Morris, John C; Petersen, Ronald C; Saykin, Andrew J; Shaw, Leslie; Thompson, Paul M; Toga, Arthur W; Trojanowski, John Q

2015-07-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer's disease (AD) by validating biomarkers for AD clinical trials. We searched for ADNI publications using established methods. ADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson's disease and multiple sclerosis. ADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials. Copyright © 2015 The Alzheimer's Association. All rights reserved.

Impact of the Alzheimer’s Disease Neuroimaging Initiative, 2004 to 2014

PubMed Central

Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Cedarbaum, Jesse; Donohue, Michael C.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie; Thompson, Paul M.; Toga, Arthur W.; Trojanowski, John Q.

2015-01-01

Introduction The Alzheimer’s Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer’s disease (AD) by validating biomarkers for AD clinical trials. Methods We searched for ADNI publications using established methods. Results ADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson’s disease and multiple sclerosis. Discussion ADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials. PMID:26194320

Fibrinogen signal transduction as a mediator and therapeutic target in inflammation: lessons from multiple sclerosis.

PubMed

Adams, R A; Schachtrup, C; Davalos, D; Tsigelny, I; Akassoglou, K

2007-01-01

The blood protein fibrinogen as a ligand for integrin and non-integrin receptors functions as the molecular nexus of coagulation, inflammation and immunity. Studies in animal models and in human disease have demonstrated that extravascular fibrinogen that is deposited in tissues upon vascular rupture is not merely a marker, but a mediator of diseases with an inflammatory component, such as rheumatoid arthritis, multiple sclerosis, sepsis, myocardial infarction and bacterial infection. The present article focuses on the recent discoveries of specific cellular targets and receptors for fibrinogen within tissues that have extended the role of fibrinogen from a coagulation factor to a regulator of inflammation and immunity. Fibrinogen has the potential for selective drug targeting that would target its proinflammatory properties without affecting its beneficial effects in hemostasis, since it interacts with different receptors to mediate blood coagulation and inflammation. Strategies to target receptors for fibrinogen and fibrin within the tissue microenvironment could reveal selective and disease-specific agents for therapeutic intervention in a variety of human diseases associated with fibrin deposition.

Manipulation of host factors optimizes the pathogenesis of western equine encephalitis virus infections in mice for antiviral drug development.

PubMed

Blakely, Pennelope K; Delekta, Phillip C; Miller, David J; Irani, David N

2015-02-01

While alphaviruses spread naturally via mosquito vectors, some can also be transmitted as aerosols making them potential bioterrorism agents. One such pathogen, western equine encephalitis virus (WEEV), causes fatal human encephalitis via multiple routes of infection and thus presumably via multiple mechanisms. Although WEEV also produces acute encephalitis in non-human primates, a small animal model that recapitulates features of human disease would be useful for both pathogenesis studies and to evaluate candidate antiviral therapies. We have optimized conditions to infect mice with a low passage isolate of WEEV, thereby allowing detailed investigation of virus tropism, replication, neuroinvasion, and neurovirulence. We find that host factors strongly influence disease outcome, and in particular, that age, gender, and genetic background all have significant effects on disease susceptibility independent of virus tropism or replication within the central nervous system. Our data show that experimental variables can be adjusted in mice to recapitulate disease features known to occur in both non-human primates and humans, thus aiding further study of WEEV pathogenesis and providing a realistic therapeutic window for antiviral drug delivery.

Manipulation of host factors optimizes the pathogenesis of western equine encephalitis virus infections in mice for antiviral drug development

PubMed Central

Blakely, Pennelope K.; Delekta, Phillip C.; Miller, David J.; Irani, David N.

2014-01-01

While alphaviruses spread naturally via mosquito vectors, some can also be transmitted as aerosols making them potential bioterrorism agents. One such pathogen, western equine encephalitis virus (WEEV), causes fatal human encephalitis via multiple routes of infection and thus presumably via multiple mechanisms. Although WEEV also produces acute encephalitis in non-human primates, a small animal model that recapitulates features of human disease would be useful for both pathogenesis studies and to evaluate candidate antiviral therapies. We have optimized conditions to infect mice with a low passage isolate of WEEV, thereby allowing detailed investigation of virus tropism, replication, neuroinvasion, and neurovirulence. We find that host factors strongly influence disease outcome, and in particular that age, gender and genetic background all have significant effects on disease susceptibility independent of virus tropism or replication within the central nervous system. Our data show that experimental variables can be adjusted in mice to recapitulate disease features known to occur in both non-human primates and humans, thus aiding further study of WEEV pathogenesis and providing a realistic therapeutic window for antiviral drug delivery. PMID:25361697

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer

PubMed Central

González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Taruscio, Domenica; Lochmüller, Hanns

2017-01-01

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries. PMID:29214177

Framing Progress In Global Tobacco Control To Inform Action On Noncommunicable Diseases.

PubMed

Wipfli, Heather L; Samet, Jonathan

2015-09-01

Much has been learned about the tobacco epidemic, including its consequences, effective measures to control it, and the actors involved. This article identifies lessons learned that are applicable to the other principal external causes of noncommunicable diseases: alcohol abuse, poor nutrition, and physical inactivity. Among these lessons are the development of evidence-based strategies such as proven cessation methods, tax increases, and smoke-free policies; the role of multinational corporations in maintaining markets and undermining control measures; and the need for strategies that reach across the life course and that begin with individuals and extend to higher levels of societal organization. Differences are also clear. Tobacco products are relatively homogeneous and have no direct benefit to consumers, whereas food and alcohol consumed in moderation are not inherently dangerous. Some tobacco-related diseases have the singular predominant cause of smoking, while many noncommunicable diseases have multiple interlocking causes such as poor diet, excess alcohol consumption, insufficient physical activity, and smoking, along with genetics. Thus, the tobacco control model of comprehensive multilevel strategies is applicable to the control of noncommunicable diseases, but the focus must be on multiple risk factors. Project HOPE—The People-to-People Health Foundation, Inc.

Treatment and disease management of multiple sclerosis patients: A review for nurse practitioners.

PubMed

Roman, Cortnee; Menning, Kara

2017-10-01

This review discusses the role of the nurse practitioner (NP) in evaluating the clinical effects, potential side effects, and monitoring requirements for treatment options in multiple sclerosis (MS) and provides guidance on how to help patients understand these issues. A literature search was conducted on PubMed to identify publications on monitoring and disease management of MS patients. Additional resources included drug information web sites and package inserts. NPs play an active role in the management of MS patients via effective monitoring and communication throughout the patient's treatment regimen and disease course. In the shared decision-making model of MS treatment, NPs ensure that patients understand the implications of their disease-modifying therapies (DMTs). As patients move through treatments during the course of their disease, the importance of this role increases, and it is critical that NPs follow the guidelines in each medication's product label and take into account any potential lingering effects of prior medications. It is critical for NPs to promote patient adherence, to ensure that patients understand treatment side effects and monitoring requirements, and to take sequencing and reversibility implications of DMTs into account when making clinical decisions. ©2017 American Association of Nurse Practitioners.

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.

PubMed

Sernadela, Pedro; González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Posada, Manuel; Taruscio, Domenica; Lochmüller, Hanns; Robinson, Peter; Roos, Marco; Oliveira, José Luís

2017-01-01

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.

[Microbiota and autoimmunity].

PubMed

Miyake, Sachiko

2014-01-01

The microbiota plays a fundamental role in the development and the maintenance of the host immune system. Since microbiota is important in the induction and the expansion of Th17 cells and regulatory T cells, growing evidence supports that microbiome affect the induction and the disease course of autoimmune disorders. In this review, we describe the recent studies on the involvement of microbes in animal models of autoimmune diseases such as rheumatoid arthritis (RA) and multiple sclerosis (MS) using germ-free conditions, antibiotics treatment and gnotobiotic mice. Furthermore, we introduce the studies on analysis of microbiota in human autoimmune diseases including RA and MS.

Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

PubMed

Iturria-Medina, Yasser; Carbonell, Félix M; Sotero, Roberto C; Chouinard-Decorte, Francois; Evans, Alan C

2017-05-15

Generative models focused on multifactorial causal mechanisms in brain disorders are scarce and generally based on limited data. Despite the biological importance of the multiple interacting processes, their effects remain poorly characterized from an integrative analytic perspective. Here, we propose a spatiotemporal multifactorial causal model (MCM) of brain (dis)organization and therapeutic intervention that accounts for local causal interactions, effects propagation via physical brain networks, cognitive alterations, and identification of optimum therapeutic interventions. In this article, we focus on describing the model and applying it at the population-based level for studying late onset Alzheimer's disease (LOAD). By interrelating six different neuroimaging modalities and cognitive measurements, this model accurately predicts spatiotemporal alterations in brain amyloid-β (Aβ) burden, glucose metabolism, vascular flow, resting state functional activity, structural properties, and cognitive integrity. The results suggest that a vascular dysregulation may be the most-likely initial pathologic event leading to LOAD. Nevertheless, they also suggest that LOAD it is not caused by a unique dominant biological factor (e.g. vascular or Aβ) but by the complex interplay among multiple relevant direct interactions. Furthermore, using theoretical control analysis of the identified population-based multifactorial causal network, we show the crucial advantage of using combinatorial over single-target treatments, explain why one-target Aβ based therapies might fail to improve clinical outcomes, and propose an efficiency ranking of possible LOAD interventions. Although still requiring further validation at the individual level, this work presents the first analytic framework for dynamic multifactorial brain (dis)organization that may explain both the pathologic evolution of progressive neurological disorders and operationalize the influence of multiple interventional strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

Using a multidimensional unfolding approach to assess multiple sclerosis patient preferences for disease-modifying therapy: a pilot study

PubMed Central

Sempere, Angel Perez; Vera-Lopez, Vanesa; Gimenez-Martinez, Juana; Ruiz-Beato, Elena; Cuervo, Jesús; Maurino, Jorge

2017-01-01

Purpose Multidimensional unfolding is a multivariate method to assess preferences using a small sample size, a geometric model locating individuals and alternatives as points in a joint space. The objective was to evaluate relapsing–remitting multiple sclerosis (RRMS) patient preferences toward key disease-modifying therapy (DMT) attributes using multidimensional unfolding. Patients and methods A cross-sectional pilot study in RRMS patients was conducted. Drug attributes included relapse prevention, disease progression prevention, side-effect risk and route and schedule of administration. Assessment of preferences was performed through a five-card game. Patients were asked to value attributes from 1 (most preferred) to 5 (least preferred). Results A total of 37 patients were included; the mean age was 38.6 years, and 78.4% were female. Disease progression prevention was the most important factor (51.4%), followed by relapse prevention (40.5%). The frequency of administration had the lowest preference rating for 56.8% of patients. Finally, 19.6% valued the side-effect risk attribute as having low/very low importance. Conclusion Patients’ perspective for DMT attributes may provide valuable information to facilitate shared decision-making. Efficacy attributes were the most important drug characteristics for RRMS patients. Multidimensional unfolding seems to be a feasible approach to assess preferences in multiple sclerosis patients. Further elicitation studies using multidimensional unfolding with other stated choice methods are necessary to confirm these findings. PMID:28615928

Analysis of the immune system of multiple myeloma patients achieving long-term disease control by multidimensional flow cytometry

PubMed Central

Pessoa de Magalhães, Roberto J.; Vidriales, María-Belén; Paiva, Bruno; Fernandez-Gimenez, Carlos; García-Sanz, Ramón; Mateos, Maria-Victoria; Gutierrez, Norma C.; Lecrevisse, Quentin; Blanco, Juan F; Hernández, Jose; de las Heras, Natalia; Martinez-Lopez, Joaquin; Roig, Monica; Costa, Elaine Sobral; Ocio, Enrique M.; Perez-Andres, Martin; Maiolino, Angelo; Nucci, Marcio; De La Rubia, Javier; Lahuerta, Juan-Jose; San-Miguel, Jesús F.; Orfao, Alberto

2013-01-01

Multiple myeloma remains largely incurable. However, a few patients experience more than 10 years of relapse-free survival and can be considered as operationally cured. Interestingly, long-term disease control in multiple myeloma is not restricted to patients with a complete response, since some patients revert to having a profile of monoclonal gammopathy of undetermined significance. We compared the distribution of multiple compartments of lymphocytes and dendritic cells in the bone marrow and peripheral blood of multiple myeloma patients with long-term disease control (n=28), patients with newly diagnosed monoclonal gammopathy of undetermined significance (n=23), patients with symptomatic multiple myeloma (n=23), and age-matched healthy adults (n=10). Similarly to the patients with monoclonal gammopathy of undetermined significance and symptomatic multiple myeloma, patients with long-term disease control showed an expansion of cytotoxic CD8+ T cells and natural killer cells. However, the numbers of bone marrow T-regulatory cells were lower in patients with long-term disease control than in those with symptomatic multiple myeloma. It is noteworthy that B cells were depleted in patients with monoclonal gammopathy of undetermined significance and in those with symptomatic multiple myeloma, but recovered in both the bone marrow and peripheral blood of patients with long-term disease control, due to an increase in normal bone marrow B-cell precursors and plasma cells, as well as pre-germinal center peripheral blood B cells. The number of bone marrow dendritic cells and tissue macrophages differed significantly between patients with long-term disease control and those with symptomatic multiple myeloma, with a trend to cell count recovering in the former group of patients towards levels similar to those found in healthy adults. In summary, our results indicate that multiple myeloma patients with long-term disease control have a constellation of unique immune changes favoring both immune cytotoxicity and recovery of B-cell production and homing, suggesting improved immune surveillance. PMID:22773604

A randomized controlled trial of a community health worker intervention in a population of patients with multiple chronic diseases: Study design and protocol

PubMed Central

Kangovi, Shreya; Mitra, Nandita; Turr, Lindsey; Huo, Hairong; Grande, David; Long, Judith A.

2017-01-01

Upstream interventions – e.g. housing programs and community health worker interventions-address socioeconomic and behavioral factors that influence health outcomes across diseases. Studying these types of interventions in clinical trials raises a methodological challenge: how should researchers measure the effect of an upstream intervention in a sample of patients with different diseases? This paper addresses this question using an illustrative protocol of a randomized controlled trial of collaborative-goal setting versus goal-setting plus community health worker support among patients multiple chronic diseases: diabetes, obesity, hypertension and tobacco dependence. At study enrollment, patients met with their primary care providers to select one of their chronic diseases to focus on during the study, and to collaboratively set a goal for that disease. Patients randomly assigned to a community health worker also received six months of support to address socioeconomic and behavioral barriers to chronic disease control. The primary hypothesis was that there would be differences in patients’ selected chronic disease control as measured by HbA1c, body mass index, systolic blood pressure and cigarettes per day, between the goal-setting alone and community health worker support arms. To test this hypothesis, we will conduct a stratum specific multivariate analysis of variance which allows all patients (regardless of their selected chronic disease) to be included in a single model for the primary outcome. Population health researchers can use this approach to measure clinical outcomes across diseases. PMID:27965180

Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts

PubMed Central

Genders, Tessa S S; Steyerberg, Ewout W; Nieman, Koen; Galema, Tjebbe W; Mollet, Nico R; de Feyter, Pim J; Krestin, Gabriel P; Alkadhi, Hatem; Leschka, Sebastian; Desbiolles, Lotus; Meijs, Matthijs F L; Cramer, Maarten J; Knuuti, Juhani; Kajander, Sami; Bogaert, Jan; Goetschalckx, Kaatje; Cademartiri, Filippo; Maffei, Erica; Martini, Chiara; Seitun, Sara; Aldrovandi, Annachiara; Wildermuth, Simon; Stinn, Björn; Fornaro, Jürgen; Feuchtner, Gudrun; De Zordo, Tobias; Auer, Thomas; Plank, Fabian; Friedrich, Guy; Pugliese, Francesca; Petersen, Steffen E; Davies, L Ceri; Schoepf, U Joseph; Rowe, Garrett W; van Mieghem, Carlos A G; van Driessche, Luc; Sinitsyn, Valentin; Gopalan, Deepa; Nikolaou, Konstantin; Bamberg, Fabian; Cury, Ricardo C; Battle, Juan; Maurovich-Horvat, Pál; Bartykowszki, Andrea; Merkely, Bela; Becker, Dávid; Hadamitzky, Martin; Hausleiter, Jörg; Dewey, Marc; Zimmermann, Elke; Laule, Michael

2012-01-01

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations. Design Retrospective pooled analysis of individual patient data. Setting 18 hospitals in Europe and the United States. Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. Results We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory. Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates. PMID:22692650

Reversal of CD8 T-Cell–Mediated Mucocutaneous Graft-Versus-Host-Like Disease by the JAK Inhibitor Tofacitinib

PubMed Central

Okiyama, Naoko; Furumoto, Yasuko; Villarroel, Vadim A; Linton, Jay T; Tsai, Wanxia L; Gutermuth, Jan; Ghoreschi, Kamran; Gadina, Massimo; O'Shea, John J; Katz, Stephen I

2014-01-01

The utility of allogeneic hematopoietic stem cell transplantation is limited by graft-versus-host disease (GVHD), a significant cause of morbidity and mortality. Patients with GVHD exhibit cutaneous manifestations with histological features of interface dermatitis followed by scleroderma-like changes. JAK inhibitors represent a class of immunomodulatory drugs that inhibit signaling by multiple cytokines. Herein we report the effects of tofacitinib in a murine model of GVHD. Oral administration of tofacitinib prevented GVHD-like disease manifested by weight loss and mucocutaneous lesions. More importantly, tofacitinib was also effective in reversing established disease. Tofacitinib diminished the expansion and activation of murine CD8 T cells in this model, and had similar effects on IL-2-stimulated human CD8 T cells. Tofacitinib also inhibited the expression of IFN-γ-inducible chemoattractants by keratinocytes, and IFN-γ-inducible cell death of keratinocytes. Tofacitinib may be an effective drug for treatment against CD8 T-cell–mediated mucocutaneous diseases in patients with GVHD. PMID:24213371

The draft genome sequence of the ferret (Mustela putorius furo) facilitates study of human respiratory disease.

PubMed

Peng, Xinxia; Alföldi, Jessica; Gori, Kevin; Eisfeld, Amie J; Tyler, Scott R; Tisoncik-Go, Jennifer; Brawand, David; Law, G Lynn; Skunca, Nives; Hatta, Masato; Gasper, David J; Kelly, Sara M; Chang, Jean; Thomas, Matthew J; Johnson, Jeremy; Berlin, Aaron M; Lara, Marcia; Russell, Pamela; Swofford, Ross; Turner-Maier, Jason; Young, Sarah; Hourlier, Thibaut; Aken, Bronwen; Searle, Steve; Sun, Xingshen; Yi, Yaling; Suresh, M; Tumpey, Terrence M; Siepel, Adam; Wisely, Samantha M; Dessimoz, Christophe; Kawaoka, Yoshihiro; Birren, Bruce W; Lindblad-Toh, Kerstin; Di Palma, Federica; Engelhardt, John F; Palermo, Robert E; Katze, Michael G

2014-12-01

The domestic ferret (Mustela putorius furo) is an important animal model for multiple human respiratory diseases. It is considered the 'gold standard' for modeling human influenza virus infection and transmission. Here we describe the 2.41 Gb draft genome assembly of the domestic ferret, constituting 2.28 Gb of sequence plus gaps. We annotated 19,910 protein-coding genes on this assembly using RNA-seq data from 21 ferret tissues. We characterized the ferret host response to two influenza virus infections by RNA-seq analysis of 42 ferret samples from influenza time-course data and showed distinct signatures in ferret trachea and lung tissues specific to 1918 or 2009 human pandemic influenza virus infections. Using microarray data from 16 ferret samples reflecting cystic fibrosis disease progression, we showed that transcriptional changes in the CFTR-knockout ferret lung reflect pathways of early disease that cannot be readily studied in human infants with cystic fibrosis disease.

The draft genome sequence of the ferret (Mustela putorius furo) facilitates study of human respiratory disease

PubMed Central

Peng, Xinxia; Alföldi, Jessica; Gori, Kevin; Eisfeld, Amie J.; Tyler, Scott R.; Tisoncik-Go, Jennifer; Brawand, David; Law, G. Lynn; Skunca, Nives; Hatta, Masato; Gasper, David J.; Kelly, Sara M.; Chang, Jean; Thomas, Matthew J.; Johnson, Jeremy; Berlin, Aaron M.; Lara, Marcia; Russell, Pamela; Swofford, Ross; Turner-Maier, Jason; Young, Sarah; Hourlier, Thibaut; Aken, Bronwen; Searle, Steve; Sun, Xingshen; Yi, Yaling; Suresh, M.; Tumpey, Terrence M.; Siepel, Adam; Wisely, Samantha M.; Dessimoz, Christophe; Kawaoka, Yoshihiro; Birren, Bruce W.; Lindblad-Toh, Kerstin; Di Palma, Federica; Engelhardt, John F.; Palermo, Robert E.; Katze, Michael G.

2014-01-01

The domestic ferret (Mustela putorius furo) is an important animal model for multiple human respiratory diseases. It is considered the ‘gold standard’ for modeling human influenza virus infection and transmission1–4. Here we describe the 2.41 Gb draft genome assembly of the domestic ferret, constituting 2.28 Gb of sequence plus gaps. We annotate 19,910 protein-coding genes on this assembly using RNA-seq data from 21 ferret tissues. We characterize the ferret host response to two influenza virus infections by RNA-seq analysis of 42 ferret samples from influenza time courses, and show distinct signatures in ferret trachea and lung tissues specific to 1918 or 2009 human pandemic influenza virus infections. Using microarray data from 16 ferret samples reflecting cystic fibrosis (CF) disease progression, we show that transcriptional changes in the CFTR-knockout ferret lung reflect pathways of early disease that cannot be readily studied in human infants with CF disease. PMID:25402615

Disease phenotype of a ferret CFTR-knockout model of cystic fibrosis

PubMed Central

Sun, Xingshen; Sui, Hongshu; Fisher, John T.; Yan, Ziying; Liu, Xiaoming; Cho, Hyung-Ju; Joo, Nam Soo; Zhang, Yulong; Zhou, Weihong; Yi, Yaling; Kinyon, Joann M.; Lei-Butters, Diana C.; Griffin, Michelle A.; Naumann, Paul; Luo, Meihui; Ascher, Jill; Wang, Kai; Frana, Timothy; Wine, Jeffrey J.; Meyerholz, David K.; Engelhardt, John F.

2010-01-01

Cystic fibrosis (CF) is a recessive disease that affects multiple organs. It is caused by mutations in CFTR. Animal modeling of this disease has been challenging, with species- and strain-specific differences in organ biology and CFTR function influencing the emergence of disease pathology. Here, we report the phenotype of a CFTR-knockout ferret model of CF. Neonatal CFTR-knockout ferrets demonstrated many of the characteristics of human CF disease, including defective airway chloride transport and submucosal gland fluid secretion; variably penetrant meconium ileus (MI); pancreatic, liver, and vas deferens disease; and a predisposition to lung infection in the early postnatal period. Severe malabsorption by the gastrointestinal (GI) tract was the primary cause of death in CFTR-knockout kits that escaped MI. Elevated liver function tests in CFTR-knockout kits were corrected by oral administration of ursodeoxycholic acid, and the addition of an oral proton-pump inhibitor improved weight gain and survival. To overcome the limitations imposed by the severe intestinal phenotype, we cloned 4 gut-corrected transgenic CFTR-knockout kits that expressed ferret CFTR specifically in the intestine. One clone passed feces normally and demonstrated no detectable ferret CFTR expression in the lung or liver. The animals described in this study are likely to be useful tools for dissecting CF disease pathogenesis and developing treatments. PMID:20739752

Disease phenotype of a ferret CFTR-knockout model of cystic fibrosis.

PubMed

Sun, Xingshen; Sui, Hongshu; Fisher, John T; Yan, Ziying; Liu, Xiaoming; Cho, Hyung-Ju; Joo, Nam Soo; Zhang, Yulong; Zhou, Weihong; Yi, Yaling; Kinyon, Joann M; Lei-Butters, Diana C; Griffin, Michelle A; Naumann, Paul; Luo, Meihui; Ascher, Jill; Wang, Kai; Frana, Timothy; Wine, Jeffrey J; Meyerholz, David K; Engelhardt, John F

2010-09-01

Cystic fibrosis (CF) is a recessive disease that affects multiple organs. It is caused by mutations in CFTR. Animal modeling of this disease has been challenging, with species- and strain-specific differences in organ biology and CFTR function influencing the emergence of disease pathology. Here, we report the phenotype of a CFTR-knockout ferret model of CF. Neonatal CFTR-knockout ferrets demonstrated many of the characteristics of human CF disease, including defective airway chloride transport and submucosal gland fluid secretion; variably penetrant meconium ileus (MI); pancreatic, liver, and vas deferens disease; and a predisposition to lung infection in the early postnatal period. Severe malabsorption by the gastrointestinal (GI) tract was the primary cause of death in CFTR-knockout kits that escaped MI. Elevated liver function tests in CFTR-knockout kits were corrected by oral administration of ursodeoxycholic acid, and the addition of an oral proton-pump inhibitor improved weight gain and survival. To overcome the limitations imposed by the severe intestinal phenotype, we cloned 4 gut-corrected transgenic CFTR-knockout kits that expressed ferret CFTR specifically in the intestine. One clone passed feces normally and demonstrated no detectable ferret CFTR expression in the lung or liver. The animals described in this study are likely to be useful tools for dissecting CF disease pathogenesis and developing treatments.

Plasma Endothelial Microparticles in Multiple Sclerosis: A Novel Metric Assay of Disease Activity and Response to Treatment

DTIC Science & Technology

2011-09-01

direct link to a source of increased tissue iron deposition which is characteristic for multiple sclerosis . The results of these data and their... Multiple Sclerosis : A Novel Metric Assay of Disease Activity and Response to Treatment PRINCIPAL INVESTIGATOR: Jonathan Steven...SUBTITLE 5a. CONTRACT NUMBER Plasma Endothelial Microparticles in Multiple Sclerosis : A Novel Metric Assay of Disease Activity and Response to

Using a Programmable Calculator to Teach Teophylline Pharmacokinetics.

ERIC Educational Resources Information Center

Closson, Richard Grant

1981-01-01

A calculator program for a Texas Instruments Model 59 to predict serum theophylline concentrations is described. The program accommodates the input of multiple dose times at irregular intervals, clearance changes due to concurrent patient diseases and age less than 17 years. The calculations for five hypothetical patients are given. (Author/MLW)

Helminth Infections Decrease Host Susceptibility to Immune-Mediated Diseases

PubMed Central

Weinstock, Joel V; Elliott, David E.

2014-01-01

Helminthic infection has become rare in highly industrialized nations. Concurrent with the decline in helminthic infection is an increase in prevalence of inflammatory disease. Removal of helminths from our environment and their powerful effects on host immunity may have contributed to this increase. Several different helminth species can abrogate disease in murine models of inflammatory bowel disease, type 1 diabetes, multiple sclerosis and other conditions. Helminths evoke immune regulatory pathways often involving dendritic cells, Tregs and macrophages that help control disease. Cytokines such as IL4, IL10 and TGFβ have a role. Notable is helminthic modulatory effect on innate immunity, which impedes development of aberrant adaptive immunity. Investigators are identifying key helminth-derived immune modulatory molecules that may have therapeutic utility in the control of inflammatory disease. PMID:25240019

Untargeted Plasma Metabolomics Identifies Endogenous Metabolite with Drug-like Properties in Chronic Animal Model of Multiple Sclerosis*

PubMed Central

Poisson, Laila M.; Suhail, Hamid; Singh, Jaspreet; Datta, Indrani; Denic, Aleksandar; Labuzek, Krzysztof; Hoda, Md Nasrul; Shankar, Ashray; Kumar, Ashok; Cerghet, Mirela; Elias, Stanton; Mohney, Robert P.; Rodriguez, Moses; Rattan, Ramandeep; Mangalam, Ashutosh K.; Giri, Shailendra

2015-01-01

We performed untargeted metabolomics in plasma of B6 mice with experimental autoimmune encephalitis (EAE) at the chronic phase of the disease in search of an altered metabolic pathway(s). Of 324 metabolites measured, 100 metabolites that mapped to various pathways (mainly lipids) linked to mitochondrial function, inflammation, and membrane stability were observed to be significantly altered between EAE and control (p < 0.05, false discovery rate <0.10). Bioinformatics analysis revealed six metabolic pathways being impacted and altered in EAE, including α-linolenic acid and linoleic acid metabolism (PUFA). The metabolites of PUFAs, including ω-3 and ω-6 fatty acids, are commonly decreased in mouse models of multiple sclerosis (MS) and in patients with MS. Daily oral administration of resolvin D1, a downstream metabolite of ω-3, decreased disease progression by suppressing autoreactive T cells and inducing an M2 phenotype of monocytes/macrophages and resident brain microglial cells. This study provides a proof of principle for the application of metabolomics to identify an endogenous metabolite(s) possessing drug-like properties, which is assessed for therapy in preclinical mouse models of MS. PMID:26546682

Profile of Circulatory Metabolites in a Relapsing-remitting Animal Model of Multiple Sclerosis using Global Metabolomics

PubMed Central

Mangalam, AK; Poisson, LM; Nemutlu, E; Datta, I; Denic, A; Dzeja, P; Rodriguez, M; Rattan, R; Giri, S

2013-01-01

Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease of the CNS. Although, MS is well characterized in terms of the role played by immune cells, cytokines and CNS pathology, nothing is known about the metabolic alterations that occur during the disease process in circulation. Recently, metabolic aberrations have been defined in various disease processes either as contributing to the disease, as potential biomarkers, or as therapeutic targets. Thus in an attempt to define the metabolic alterations that may be associated with MS disease progression, we profiled the plasma metabolites at the chronic phase of disease utilizing relapsing remitting-experimental autoimmune encephalomyelitis (RR-EAE) model in SJL mice. At the chronic phase of the disease (day 45), untargeted global metabolomic profiling of plasma collected from EAE diseased SJL and healthy mice was performed, using a combination of high-throughput liquid-and-gas chromatography with mass spectrometry. A total of 282 metabolites were identified, with significant changes observed in 44 metabolites (32 up-regulated and 12 down-regulated), that mapped to lipid, amino acid, nucleotide and xenobiotic metabolism and distinguished EAE from healthy group (p<0.05, false discovery rate (FDR)<0.23). Mapping the differential metabolite signature to their respective biochemical pathways using the Kyoto Encyclopedia of Genes and Genomics (KEGG) database, we found six major pathways that were significantly altered (containing concerted alterations) or impacted (containing alteration in key junctions). These included bile acid biosynthesis, taurine metabolism, tryptophan and histidine metabolism, linoleic acid and D-arginine metabolism pathways. Overall, this study identified a 44 metabolite signature drawn from various metabolic pathways which correlated well with severity of the EAE disease, suggesting that these metabolic changes could be exploited as (1) biomarkers for EAE/MS progression and (2) to design new treatment paradigms where metabolic interventions could be combined with present and experimental therapeutics to achieve better treatment of MS. PMID:24273690

Serum neurofilament as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis.

PubMed

Barro, Christian; Benkert, Pascal; Disanto, Giulio; Tsagkas, Charidimos; Amann, Michael; Naegelin, Yvonne; Leppert, David; Gobbi, Claudio; Granziera, Cristina; Yaldizli, Özgür; Michalak, Zuzanna; Wuerfel, Jens; Kappos, Ludwig; Parmar, Katrin; Kuhle, Jens

2018-05-30

Neuro-axonal injury is a key factor in the development of permanent disability in multiple sclerosis. Neurofilament light chain in peripheral blood has recently emerged as a biofluid marker reflecting neuro-axonal damage in this disease. We aimed at comparing serum neurofilament light chain levels in multiple sclerosis and healthy controls, to determine their association with measures of disease activity and their ability to predict future clinical worsening as well as brain and spinal cord volume loss. Neurofilament light chain was measured by single molecule array assay in 2183 serum samples collected as part of an ongoing cohort study from 259 patients with multiple sclerosis (189 relapsing and 70 progressive) and 259 healthy control subjects. Clinical assessment, serum sampling and MRI were done annually; median follow-up time was 6.5 years. Brain volumes were quantified by structural image evaluation using normalization of atrophy, and structural image evaluation using normalization of atrophy, cross-sectional, cervical spinal cord volumes using spinal cord image analyser (cordial). Results were analysed using ordinary linear regression models and generalized estimating equation modelling. Serum neurofilament light chain was higher in patients with a clinically isolated syndrome or relapsing remitting multiple sclerosis as well as in patients with secondary or primary progressive multiple sclerosis than in healthy controls (age adjusted P < 0.001 for both). Serum neurofilament light chain above the 90th percentile of healthy controls values was an independent predictor of Expanded Disability Status Scale worsening in the subsequent year (P < 0.001). The probability of Expanded Disability Status Scale worsening gradually increased by higher serum neurofilament light chain percentile category. Contrast enhancing and new/enlarging lesions were independently associated with increased serum neurofilament light chain (17.8% and 4.9% increase per lesion respectively; P < 0.001). The higher the serum neurofilament light chain percentile level, the more pronounced was future brain and cervical spinal volume loss: serum neurofilament light chain above the 97.5th percentile was associated with an additional average loss in brain volume of 1.5% (P < 0.001) and spinal cord volume of 2.5% over 5 years (P = 0.009). Serum neurofilament light chain correlated with concurrent and future clinical and MRI measures of disease activity and severity. High serum neurofilament light chain levels were associated with both brain and spinal cord volume loss. Neurofilament light chain levels are a real-time, easy to measure marker of neuro-axonal injury that is conceptually more comprehensive than brain MRI.

Cost-effectiveness of natalizumab vs fingolimod for the treatment of relapsing-remitting multiple sclerosis: analyses in Sweden.

PubMed

O'Day, Ken; Meyer, Kellie; Stafkey-Mailey, Dana; Watson, Crystal

2015-04-01

To assess the cost-effectiveness of natalizumab vs fingolimod over 2 years in relapsing-remitting multiple sclerosis (RRMS) patients and patients with rapidly evolving severe disease in Sweden. A decision analytic model was developed to estimate the incremental cost per relapse avoided of natalizumab and fingolimod from the perspective of the Swedish healthcare system. Modeled 2-year costs in Swedish kronor of treating RRMS patients included drug acquisition costs, administration and monitoring costs, and costs of treating MS relapses. Effectiveness was measured in terms of MS relapses avoided using data from the AFFIRM and FREEDOMS trials for all patients with RRMS and from post-hoc sub-group analyses for patients with rapidly evolving severe disease. Probabilistic sensitivity analyses were conducted to assess uncertainty. The analysis showed that, in all patients with MS, treatment with fingolimod costs less (440,463 Kr vs 444,324 Kr), but treatment with natalizumab results in more relapses avoided (0.74 vs 0.59), resulting in an incremental cost-effectiveness ratio (ICER) of 25,448 Kr per relapse avoided. In patients with rapidly evolving severe disease, natalizumab dominated fingolimod. Results of the sensitivity analysis demonstrate the robustness of the model results. At a willingness-to-pay (WTP) threshold of 500,000 Kr per relapse avoided, natalizumab is cost-effective in >80% of simulations in both patient populations. Limitations include absence of data from direct head-to-head studies comparing natalizumab and fingolimod, use of relapse rate reduction rather than sustained disability progression as the primary model outcome, assumption of 100% adherence to MS treatment, and exclusion of adverse event costs in the model. Natalizumab remains a cost-effective treatment option for patients with MS in Sweden. In the RRMS patient population, the incremental cost per relapse avoided is well below a 500,000 Kr WTP threshold per relapse avoided. In the rapidly evolving severe disease patient population, natalizumab dominates fingolimod.

A gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging

PubMed Central

Louapre, Céline; Govindarajan, Sindhuja T.; Giannì, Costanza; Nielsen, A. Scott; Cohen-Adad, Julien; Sloane, Jacob; Kinkel, Revere P.

2015-01-01

We used a surface-based analysis of T2* relaxation rates at 7 T magnetic resonance imaging, which allows sampling quantitative T2* throughout the cortical width, to map in vivo the spatial distribution of intracortical pathology in multiple sclerosis. Ultra-high resolution quantitative T2* maps were obtained in 10 subjects with clinically isolated syndrome/early multiple sclerosis (≤3 years disease duration), 18 subjects with relapsing-remitting multiple sclerosis (≥4 years disease duration), 13 subjects with secondary progressive multiple sclerosis, and in 17 age-matched healthy controls. Quantitative T2* maps were registered to anatomical cortical surfaces for sampling T2* at 25%, 50% and 75% depth from the pial surface. Differences in laminar quantitative T2* between each patient group and controls were assessed using general linear model (P < 0.05 corrected for multiple comparisons). In all 41 multiple sclerosis cases, we tested for associations between laminar quantitative T2*, neurological disability, Multiple Sclerosis Severity Score, cortical thickness, and white matter lesions. In patients, we measured, T2* in intracortical lesions and in the intracortical portion of leukocortical lesions visually detected on 7 T scans. Cortical lesional T2* was compared with patients’ normal-appearing cortical grey matter T2* (paired t-test) and with mean cortical T2* in controls (linear regression using age as nuisance factor). Subjects with multiple sclerosis exhibited relative to controls, independent from cortical thickness, significantly increased T2*, consistent with cortical myelin and iron loss. In early disease, T2* changes were focal and mainly confined at 25% depth, and in cortical sulci. In later disease stages T2* changes involved deeper cortical laminae, multiple cortical areas and gyri. In patients, T2* in intracortical and leukocortical lesions was increased compared with normal-appearing cortical grey matter (P < 10−10 and P < 10−7), and mean cortical T2* in controls (P < 10−5 and P < 10−6). In secondary progressive multiple sclerosis, T2* in normal-appearing cortical grey matter was significantly increased relative to controls (P < 0.001). Laminar T2* changes may, thus, result from cortical pathology within and outside focal cortical lesions. Neurological disability and Multiple Sclerosis Severity Score correlated each with the degree of laminar quantitative T2* changes, independently from white matter lesions, the greatest association being at 25% depth, while they did not correlate with cortical thickness and volume. These findings demonstrate a gradient in the expression of cortical pathology throughout stages of multiple sclerosis, which was associated with worse disability and provides in vivo evidence for the existence of a cortical pathological process driven from the pial surface. PMID:25681411

Endocannabinoids in Multiple Sclerosis and Amyotrophic Lateral Sclerosis.

PubMed

Pryce, Gareth; Baker, David

2015-01-01

There are numerous reports that people with multiple sclerosis (MS) have for many years been self-medicating with illegal street cannabis or more recently medicinal cannabis to alleviate the symptoms associated with MS and also amyotrophic lateral sclerosis (ALS). These anecdotal reports have been confirmed by data from animal models and more recently clinical trials on the ability of cannabinoids to alleviate limb spasticity, a common feature of progressive MS (and also ALS) and neurodegeneration. Experimental studies into the biology of the endocannabinoid system have revealed that cannabinoids have efficacy, not only in symptom relief but also as neuroprotective agents which may slow disease progression and thus delay the onset of symptoms. This review discusses what we now know about the endocannabinoid system as it relates to MS and ALS and also the therapeutic potential of cannabinoid therapeutics as disease-modifying or symptom control agents, as well as future therapeutic strategies including the potential for slowing disease progression in MS and ALS.

Frontiers in the pathogenesis of Alzheimer’s disease

PubMed Central

Sambamurti, Kumar; Jagannatha Rao, K. S.; Pappolla, Miguel A.

2009-01-01

Alzheimer’s disease (AD) is characterized by progressive dementia and brain deposits of the amyloid β protein (Aβ) as senile plaques and the microtubule-associated protein, Tau, as neurofibrillary tangles (NFT). The current treatment of AD is limited to drugs that attempt to correct deficits in the cholinergic pathway or glutamate toxicity. These drugs show some improvement over a short period of time but the disease ultimately requires treatment to prevent and stop the neurodegeneration that affects multiple pathways. The currently favored hypothesis is that Aβ aggregates to toxic forms that induce neurodegeneration. Drugs that reduce Aβ successfully treat transgenic mouse models of AD, but the most promising anti-Aβ vaccination approach did not successfully treat AD in a clinical trial. These studies suggest that AD pathogenesis is a complex phenomenon and requires a more broad-based approach to identify mechanisms of neurodegeneration. Multiple hypotheses have been proposed and the field is ready for a new generation of ideas to develop early diagnostic approaches and develop successful treatment plans. PMID:21416019

The severity of Minamata disease declined in 25 years: temporal profile of the neurological findings analyzed by multiple logistic regression model.

PubMed

Uchino, Makoto; Hirano, Teruyuki; Satoh, Hiroshi; Arimura, Kimiyoshi; Nakagawa, Masanori; Wakamiya, Jyunji

2005-01-01

Minamata disease (MD) was caused by ingestion of seafood from the methylmercury-contaminated areas. Although 50 years have passed since the discovery of MD, there have been only a few studies on the temporal profile of neurological findings in certified MD patients. Thus, we evaluated changes in neurological symptoms and signs of MD using discriminants by multiple logistic regression analysis. The severity of predictive index declined in 25 years in most of the patients. Only a few patients showed aggravation of neurological findings, which was due to complications such as spino-cerebellar degeneration. Patients with chronic MD aged over 45 years had several concomitant diseases so that their clinical pictures were complicated. It was difficult to differentiate chronic MD using statistically established discriminants based on sensory disturbance alone. In conclusion, the severity of MD declined in 25 years along with the modification by age-related concomitant disorders.

G protein-coupled receptors as therapeutic targets for multiple sclerosis

PubMed Central

Du, Changsheng; Xie, Xin

2012-01-01

G protein-coupled receptors (GPCRs) mediate most of our physiological responses to hormones, neurotransmitters and environmental stimulants. They are considered as the most successful therapeutic targets for a broad spectrum of diseases. Multiple sclerosis (MS) is an inflammatory disease that is characterized by immune-mediated demyelination and degeneration of the central nervous system (CNS). It is the leading cause of non-traumatic disability in young adults. Great progress has been made over the past few decades in understanding the pathogenesis of MS. Numerous data from animal and clinical studies indicate that many GPCRs are critically involved in various aspects of MS pathogenesis, including antigen presentation, cytokine production, T-cell differentiation, T-cell proliferation, T-cell invasion, etc. In this review, we summarize the recent findings regarding the expression or functional changes of GPCRs in MS patients or animal models, and the influences of GPCRs on disease severity upon genetic or pharmacological manipulations. Hopefully some of these findings will lead to the development of novel therapies for MS in the near future. PMID:22664908

Lymphatics in Neurological Disorders: A neuro-lympho-vascular Component of Multiple Sclerosis and Alzheimer’s Disease

PubMed Central

Louveau, Antoine; Mesquita, Sandro Da; Kipnis, Jonathan

2016-01-01

Summary Lymphatic vasculature drains interstitial fluids, which contain the tissue’s waste products and ensures immune surveillance of the tissues, allowing immune-cell recirculation. Until recently the central nervous system (CNS) was considered to be devoid of a conventional lymphatic vasculature. The recent discovery in the meninges of a lymphatic network that drains the CNS calls into question classic models for the drainage of macromolecules and immune cells from the CNS. In the context of neurological disorders, the presence of a lymphatic system draining the CNS potentially offers a new player and a new avenue for therapy. In this review, we will attempt to integrate the known primary functions of the tissue lymphatic vasculature that exists in peripheral organs with the proposed function of meningeal lymphatic vessels in neurological disorders, specifically multiple sclerosis and Alzheimer’s disease. We propose that these (and potentially other) neurological afflictions can be viewed as diseases with neuro-lympho-vascular component and should be therapeutically targeted as such. PMID:27608759

[Application progress of proteomic in pharmacological study of Chinese medicinal formulae].

PubMed

Liu, Yu-Qian; Zhan, Shu-Yu; Ruan, Yu-Er; Zuo, Zhi-Yan; Ji, Xiao-Ming; Wang, Shuai-Jie; Ding, Bao-Yue

2017-10-01

Chinese medicinal formulae are the important means of clinical treatment in traditional Chinese medicine. It is urgent to use modern advanced scientific and technological means to reveal the complicated mechanism of Chinese medicinal formulae because they have the function characteristics of multiple components, multiple targets and integrated regulation. The systematic and comprehensive research model of proteomic is in line with the function characteristics of Chinese medicinal formulae, and proteomic has been widely used in the study of pharmacological mechanism of Chinese medicinal formulae. The recent applications of proteomic in pharmacological study of Chinese medicinal formulae in anti-cardiovascular and cerebrovascular diseases, anti-liver disease, antidiabetic, anticancer, anti-rheumatoid arthritis and other diseases were reviewed in this paper, and then the future development direction of proteomic in pharmacological study of Chinese medicinal formulae was put forward. This review is to provide the ideas and method for proteomic research on function mechanism of Chinese medicinal formulae. Copyright© by the Chinese Pharmaceutical Association.

CREATION OF A MODEL TO PREDICT SURVIVAL IN PATIENTS WITH REFRACTORY COELIAC DISEASE USING A MULTINATIONAL REGISTRY

PubMed Central

Rubio-Tapia, Alberto; Malamut, Georgia; Verbeek, Wieke H.M.; van Wanrooij, Roy L.J.; Leffler, Daniel A.; Niveloni, Sonia I.; Arguelles-Grande, Carolina; Lahr, Brian D.; Zinsmeister, Alan R.; Murray, Joseph A.; Kelly, Ciaran P.; Bai, Julio C.; Green, Peter H.; Daum, Severin; Mulder, Chris J.J.; Cellier, Christophe

2016-01-01

Background Refractory coeliac disease is a severe complication of coeliac disease with heterogeneous outcome. Aim To create a prognostic model to estimate survival of patients with refractory coeliac disease. Methods We evaluated predictors of 5-year mortality using Cox proportional hazards regression on subjects from a multinational registry. Bootstrap re-sampling was used to internally validate the individual factors and overall model performance. The mean of the estimated regression coefficients from 400 bootstrap models was used to derive a risk score for 5-year mortality. Results The multinational cohort was composed of 232 patients diagnosed with refractory coeliac disease across 7 centers (range of 11–63 cases per center). The median age was 53 years and 150 (64%) were women. A total of 51 subjects died during 5-year follow-up (cumulative 5-year all-cause mortality = 30%). From a multiple variable Cox proportional hazards model, the following variables were significantly associated with 5-year mortality: age at refractory coeliac disease diagnosis (per 20 year increase, hazard ratio = 2.21; 95% confidence interval: 1.38, 3.55), abnormal intraepithelial lymphocytes (hazard ratio = 2.85; 95% confidence interval: 1.22, 6.62), and albumin (per 0.5 unit increase, hazard ratio = 0.72; 95% confidence interval: 0.61, 0.85). A simple weighted 3-factor risk score was created to estimate 5-year survival. Conclusions Using data from a multinational registry and previously-reported risk factors, we create a prognostic model to predict 5-year mortality among patients with refractory coeliac disease. This new model may help clinicians to guide treatment and follow-up. PMID:27485029

Creation of a model to predict survival in patients with refractory coeliac disease using a multinational registry.

PubMed

Rubio-Tapia, A; Malamut, G; Verbeek, W H M; van Wanrooij, R L J; Leffler, D A; Niveloni, S I; Arguelles-Grande, C; Lahr, B D; Zinsmeister, A R; Murray, J A; Kelly, C P; Bai, J C; Green, P H; Daum, S; Mulder, C J J; Cellier, C

2016-10-01

Refractory coeliac disease is a severe complication of coeliac disease with heterogeneous outcome. To create a prognostic model to estimate survival of patients with refractory coeliac disease. We evaluated predictors of 5-year mortality using Cox proportional hazards regression on subjects from a multinational registry. Bootstrap resampling was used to internally validate the individual factors and overall model performance. The mean of the estimated regression coefficients from 400 bootstrap models was used to derive a risk score for 5-year mortality. The multinational cohort was composed of 232 patients diagnosed with refractory coeliac disease across seven centres (range of 11-63 cases per centre). The median age was 53 years and 150 (64%) were women. A total of 51 subjects died during a 5-year follow-up (cumulative 5-year all-cause mortality = 30%). From a multiple variable Cox proportional hazards model, the following variables were significantly associated with 5-year mortality: age at refractory coeliac disease diagnosis (per 20 year increase, hazard ratio = 2.21; 95% confidence interval, CI: 1.38-3.55), abnormal intraepithelial lymphocytes (hazard ratio = 2.85; 95% CI: 1.22-6.62), and albumin (per 0.5 unit increase, hazard ratio = 0.72; 95% CI: 0.61-0.85). A simple weighted three-factor risk score was created to estimate 5-year survival. Using data from a multinational registry and previously reported risk factors, we create a prognostic model to predict 5-year mortality among patients with refractory coeliac disease. This new model may help clinicians to guide treatment and follow-up. © 2016 John Wiley & Sons Ltd.

A three-dimensional point process model for the spatial distribution of disease occurrence in relation to an exposure source.

PubMed

Grell, Kathrine; Diggle, Peter J; Frederiksen, Kirsten; Schüz, Joachim; Cardis, Elisabeth; Andersen, Per K

2015-10-15

We study methods for how to include the spatial distribution of tumours when investigating the relation between brain tumours and the exposure from radio frequency electromagnetic fields caused by mobile phone use. Our suggested point process model is adapted from studies investigating spatial aggregation of a disease around a source of potential hazard in environmental epidemiology, where now the source is the preferred ear of each phone user. In this context, the spatial distribution is a distribution over a sample of patients rather than over multiple disease cases within one geographical area. We show how the distance relation between tumour and phone can be modelled nonparametrically and, with various parametric functions, how covariates can be included in the model and how to test for the effect of distance. To illustrate the models, we apply them to a subset of the data from the Interphone Study, a large multinational case-control study on the association between brain tumours and mobile phone use. Copyright © 2015 John Wiley & Sons, Ltd.

Combined Diffusion Tensor Imaging and Apparent Transverse Relaxation Rate Differentiate Parkinson Disease and Atypical Parkinsonism.

PubMed

Du, G; Lewis, M M; Kanekar, S; Sterling, N W; He, L; Kong, L; Li, R; Huang, X

2017-05-01

Both diffusion tensor imaging and the apparent transverse relaxation rate have shown promise in differentiating Parkinson disease from atypical parkinsonism (particularly multiple system atrophy and progressive supranuclear palsy). The objective of the study was to assess the ability of DTI, the apparent transverse relaxation rate, and their combination for differentiating Parkinson disease, multiple system atrophy, progressive supranuclear palsy, and controls. A total of 106 subjects (36 controls, 35 patients with Parkinson disease, 16 with multiple system atrophy, and 19 with progressive supranuclear palsy) were included. DTI and the apparent transverse relaxation rate measures from the striatal, midbrain, limbic, and cerebellar regions were obtained and compared among groups. The discrimination performance of DTI and the apparent transverse relaxation rate among groups was assessed by using Elastic-Net machine learning and receiver operating characteristic curve analysis. Compared with controls, patients with Parkinson disease showed significant apparent transverse relaxation rate differences in the red nucleus. Compared to those with Parkinson disease, patients with both multiple system atrophy and progressive supranuclear palsy showed more widespread changes, extending from the midbrain to striatal and cerebellar structures. The pattern of changes, however, was different between the 2 groups. For instance, patients with multiple system atrophy showed decreased fractional anisotropy and an increased apparent transverse relaxation rate in the subthalamic nucleus, whereas patients with progressive supranuclear palsy showed an increased mean diffusivity in the hippocampus. Combined, DTI and the apparent transverse relaxation rate were significantly better than DTI or the apparent transverse relaxation rate alone in separating controls from those with Parkinson disease/multiple system atrophy/progressive supranuclear palsy; controls from those with Parkinson disease; those with Parkinson disease from those with multiple system atrophy/progressive supranuclear palsy; and those with Parkinson disease from those with multiple system atrophy; but not those with Parkinson disease from those with progressive supranuclear palsy, or those with multiple system atrophy from those with progressive supranuclear palsy. DTI and the apparent transverse relaxation rate provide different but complementary information for different parkinsonisms. Combined DTI and apparent transverse relaxation rate may be a superior marker for the differential diagnosis of parkinsonisms. © 2017 by American Journal of Neuroradiology.

Modeling Human Cancers in Drosophila.

PubMed

Sonoshita, M; Cagan, R L

2017-01-01

Cancer is a complex disease that affects multiple organs. Whole-body animal models provide important insights into oncology that can lead to clinical impact. Here, we review novel concepts that Drosophila studies have established for cancer biology, drug discovery, and patient therapy. Genetic studies using Drosophila have explored the roles of oncogenes and tumor-suppressor genes that when dysregulated promote cancer formation, making Drosophila a useful model to study multiple aspects of transformation. Not limited to mechanism analyses, Drosophila has recently been showing its value in facilitating drug development. Flies offer rapid, efficient platforms by which novel classes of drugs can be identified as candidate anticancer leads. Further, we discuss the use of Drosophila as a platform to develop therapies for individual patients by modeling the tumor's genetic complexity. Drosophila provides both a classical and a novel tool to identify new therapeutics, complementing other more traditional cancer tools. © 2017 Elsevier Inc. All rights reserved.

The effect of alcohol and red wine consumption on clinical and MRI outcomes in multiple sclerosis.

PubMed

Diaz-Cruz, Camilo; Chua, Alicia S; Malik, Muhammad Taimur; Kaplan, Tamara; Glanz, Bonnie I; Egorova, Svetlana; Guttmann, Charles R G; Bakshi, Rohit; Weiner, Howard L; Healy, Brian C; Chitnis, Tanuja

2017-10-01

Alcohol and in particular red wine have both immunomodulatory and neuroprotective properties, and may exert an effect on the disease course of multiple sclerosis (MS). To assess the association between alcohol and red wine consumption and MS course. MS patients enrolled in the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB) who completed a self-administered questionnaire about their past year drinking habits at a single time point were included in the study. Alcohol and red wine consumption were measured as servings/week. The primary outcome was the Expanded Disability Status Scale (EDSS) at the time of the questionnaire. Secondary clinical outcomes were the Multiple Sclerosis Severity Score (MSSS) and number of relapses in the year before the questionnaire. Secondary MRI outcomes included brain parenchymal fraction and T2 hyperintense lesion volume (T2LV). Appropriate regression models were used to test the association of alcohol and red wine intake on clinical and MRI outcomes. All analyses were controlled for sex, age, body mass index, disease phenotype (relapsing vs. progressive), the proportion of time on disease modifying therapy during the previous year, smoking exposure, and disease duration. In the models for the MRI outcomes, analyses were also adjusted for acquisition protocol. 923 patients (74% females, mean age 47 ± 11 years, mean disease duration 14 ± 9 years) were included in the analysis. Compared to abstainers, patients drinking more than 4 drinks per week had a higher likelihood of a lower EDSS score (OR, 0.41; p = 0.0001) and lower MSSS (mean difference, - 1.753; p = 0.002) at the time of the questionnaire. Similarly, patients drinking more than 3 glasses of red wine per week had greater odds of a lower EDSS (OR, 0.49; p = 0.0005) and lower MSSS (mean difference, - 0.705; p = 0.0007) compared to nondrinkers. However, a faster increase in T2LV was observed in patients consuming 1-3 glasses of red wine per week compared to nondrinkers. Higher total alcohol and red wine intake were associated with a lower cross-sectional level of neurologic disability in MS patients but increased T2LV accumulation. Further studies should explore a potential cause-effect neuroprotective relationship, as well as the underlying biological mechanisms. Copyright © 2017 Elsevier B.V. All rights reserved.

Therapeutic action of ghrelin in a mouse model of colitis.

PubMed

Gonzalez-Rey, Elena; Chorny, Alejo; Delgado, Mario

2006-05-01

Ghrelin is a novel growth hormone-releasing peptide with potential endogenous anti-inflammatory activities ameliorating some pathologic inflammatory conditions. Crohn's disease is a chronic debilitating disease characterized by severe T helper cell (Th)1-driven inflammation of the colon. The aim of this study was to investigate the therapeutic effect of ghrelin in a murine model of colitis. We examined the anti-inflammatory action of ghrelin in the colitis induced by intracolonic administration of trinitrobenzene sulfonic acid. Diverse clinical signs of the disease were evaluated, including weight loss, diarrhea, colitis, and histopathology. We also investigated the mechanisms involved in the potential therapeutic effect of ghrelin, such as inflammatory cytokines and chemokines, Th1-type response, and regulatory factors. Ghrelin ameliorated significantly the clinical and histopathologic severity of the trinitrobenzene sulfonic acid-induced colitis; abrogating body weight loss, diarrhea, and inflammation; and increasing survival. The therapeutic effect was associated with down-regulation of both inflammatory and Th1-driven autoimmune response through the regulation of a wide spectrum of inflammatory mediators. In addition, a partial involvement of interluekin-10/transforming growth factor-beta1-secreting regulatory T cells in this therapeutic effect was demonstrated. Importantly, the ghrelin treatment was therapeutically effective in established colitis and avoided the recurrence of the disease. Our data demonstrate novel anti-inflammatory actions for ghrelin in the gastrointestinal tract, ie, the capacity to deactivate the intestinal inflammatory response and to restore mucosal immune tolerance at multiple levels. Consequently, ghrelin administration represents a novel possible therapeutic approach for the treatment of Crohn's disease and other Th1-mediated inflammatory diseases, such as rheumatoid arthritis and multiple sclerosis.

Development of simulated and ovine models of extracorporeal life support to improve understanding of circuit-host interactions.

PubMed

Shekar, Kiran; Fung, Yoke L; Diab, Sara; Mullany, Daniel V; McDonald, Charles I; Dunster, Kimble R; Fisquet, Stephanie; Platts, David G; Stewart, David; Wallis, Steven C; Smith, Maree T; Roberts, Jason A; Fraser, John F

2012-06-01

Extracorporeal life support (ECLS) is a lifesaving technology that is being increasingly used in patients with severe cardiorespiratory failure. However, ECLS is not without risks. The biosynthetic interface between the patient and the circuit can significantly alter inflammation, coagulation, pharmacokinetics and disposition of trace elements. The relative contributions of the pump, disease and patient in propagating these alterations are difficult to quantify in critically ill patients with multiple organ failure. To design a model where the relevance of individual components could be assessed, in isolation and in combination. Four ECLS models were developed and tested - an in-vitro simulated ECLS circuit; and ECLS in healthy sheep, sheep with acute lung injury (ALI), and sheep with ALI together with transfusion of old or new blood. Successful design of in-vitro and in-vivo models. We successfully conducted multiple experiments in the simulated circuits and ECLS runs in healthy and ALI sheep. We obtained preliminary data on inflammation, coagulation, histology, pharmacokinetics and trace element disposition during ECLS. The establishment of in-vitro and in-vivo models provides a powerful means for enhancing knowledge of the pathophysiology associated with ECLS and identification of key factors likely to influence patient outcomes. A clearer description of the contribution of disease and therapeutic interventions may allow improved design of equipment, membranes, medicines and physiological goals for improved patient care.

Many diseases, one model of care?

PubMed Central

Albreht, Tit; Dyakova, Mariana; Schellevis, François G.

2016-01-01

Patients with multiple chronic conditions (multimorbidity) have complex and extensive health and social care needs that are not well served by current silo-based models of care. A lack of integration between care providers often leads to fragmented, incomplete, and ineffective care, leaving many patients overwhelmed and unable to navigate their way towards better health outcomes. In planning for the future, healthcare policies and models of care are required that cater for the complex needs of patients with multimorbidity and that deliver coordinated care that is patient-centred and focused on disease prevention, multidisciplinary teamwork and shared decision-making, and on empowering patients to self-manage. Salient lessons can be learnt from the work undertaken at a European and national level to develop care models in cancer and diabetes – two complex and often co-occurring conditions requiring coordinated long-term care. Innovative work is also underway in many European countries aimed at improving the integration of care for people with multimorbidity, resulting in more efficient and cost-effective health outcomes. This article reviews some of the most innovative programmes that have been initiated across and within Europe with the aim of improving the way care is delivered to people with complex and multiple long-term conditions. This work provides a foundation upon which to build better, more effective models of care for people with multimorbidity. PMID:29090167

Concise Review: Heteroplasmic Mitochondrial DNA Mutations and Mitochondrial Diseases: Toward iPSC-Based Disease Modeling, Drug Discovery, and Regenerative Therapeutics.

PubMed

Hatakeyama, Hideyuki; Goto, Yu-Ichi

2016-04-01

Mitochondria contain multiple copies of their own genome (mitochondrial DNA; mtDNA). Once mitochondria are damaged by mutant mtDNA, mitochondrial dysfunction is strongly induced, followed by symptomatic appearance of mitochondrial diseases. Major genetic causes of mitochondrial diseases are defects in mtDNA, and the others are defects of mitochondria-associating genes that are encoded in nuclear DNA (nDNA). Numerous pathogenic mutations responsible for various types of mitochondrial diseases have been identified in mtDNA; however, it remains uncertain why mitochondrial diseases present a wide variety of clinical spectrum even among patients carrying the same mtDNA mutations (e.g., variations in age of onset, in affected tissues and organs, or in disease progression and phenotypic severity). Disease-relevant induced pluripotent stem cells (iPSCs) derived from mitochondrial disease patients have therefore opened new avenues for understanding the definitive genotype-phenotype relationship of affected tissues and organs in various types of mitochondrial diseases triggered by mtDNA mutations. In this concise review, we briefly summarize several recent approaches using patient-derived iPSCs and their derivatives carrying various mtDNA mutations for applications in human mitochondrial disease modeling, drug discovery, and future regenerative therapeutics. © 2016 AlphaMed Press.

Decisional role preferences, risk knowledge and information interests in patients with multiple sclerosis.

PubMed

Heesen, Christoph; Kasper, Jürgen; Segal, Julia; Köpke, Sascha; Mühlhauser, Ingrid

2004-12-01

Shared decision making is increasingly recognized as the ideal model of patient-physician communication especially in chronic diseases with partially effective treatments as multiple sclerosis (MS). To evaluate prerequisite factors for this kind of decision making we studied patients' decisional role preferences in medical decision making, knowledge on risks, information interests and the relations between these factors in MS. After conducting focus groups to generate hypotheses, 219 randomly selected patients from the MS Outpatient Clinic register (n = 1374) of the University Hospital Hamburg received mailed questionnaires on their knowledge of risks in MS, their perception of their own level of knowledge, information interests and role preferences. Most patients (79%) indicated that they preferred an active role in treatment decisions giving the shared decision and the informed choice model the highest priority. MS risk knowledge was low but questionnaire results depended on disease course, disease duration and ongoing immune therapy. Measured knowledge as well as perceived knowledge was only weakly correlated with preferences of active roles. Major information interests were related to symptom alleviation, diagnostic procedures and prognosis. Patients with MS claimed autonomous roles in their health care decisions. The weak correlation between knowledge and preferences for active roles implicates that other factors largely influence role preferences.

Lack of magnetic resonance imaging lesion activity as a treatment target in multiple sclerosis: An evaluation using electronically collected outcomes.

PubMed

Conway, Devon S; Thompson, Nicolas R; Cohen, Jeffrey A

2016-09-01

The appropriate treatment target in multiple sclerosis (MS) is unclear. Lack of magnetic resonance imaging (MRI) lesion activity, a component of the no evidence of disease activity concept, has been proposed as a treatment target in MS. We used our MS database to investigate whether aggressively pursuing MRI stability by changing disease modifying therapy (DMT) when MRI activity is observed leads to better clinical and imaging outcomes. The Knowledge Program (KP) is a database linked to our electronic medical record allowing capture of patient and clinician reported outcomes. Through KP query and chart review, we identified all relapsing-remitting MS patients visiting between 1 January 2008 and 31 December 2014 with active MRIs despite DMT. Propensity modeling based on demographic and disease characteristics was used to match DMT switchers to non-switchers. KP and MRI outcomes were compared 18 months after the active MRI using mixed-effects linear regression models. We identified 417 patients who met criteria for our analysis. After propensity matching, 78 switchers and 91 non-switchers were analyzed. There was no difference in clinical or radiologic outcomes between these groups at 18 months. We did not find a short-term benefit of changing DMT to pursue MRI stability. Copyright © 2016 Elsevier B.V. All rights reserved.

Caspase-1 inhibition prevents glial inflammasome activation and pyroptosis in models of multiple sclerosis.

PubMed

McKenzie, Brienne A; Mamik, Manmeet K; Saito, Leina B; Boghozian, Roobina; Monaco, Maria Chiara; Major, Eugene O; Lu, Jian-Qiang; Branton, William G; Power, Christopher

2018-06-12

Multiple sclerosis (MS) is a progressive inflammatory demyelinating disease of the CNS of unknown cause that remains incurable. Inflammasome-associated caspases mediate the maturation and release of the proinflammatory cytokines IL-1β and IL-18 and activate the pore-forming protein gasdermin D (GSDMD). Inflammatory programmed cell death, pyroptosis, was recently shown to be mediated by GSDMD. Here, we report molecular evidence for GSDMD-mediated inflammasome activation and pyroptosis in both myeloid cells (macrophages/microglia) and, unexpectedly, in myelin-forming oligodendrocytes (ODCs) in the CNS of patients with MS and in the MS animal model, experimental autoimmune encephalomyelitis (EAE). We observed inflammasome activation and pyroptosis in human microglia and ODCs in vitro after exposure to inflammatory stimuli and demonstrate caspase-1 inhibition by the small-molecule inhibitor VX-765 in both cell types. GSDMD inhibition by siRNA transduction suppressed pyroptosis in human microglia. VX-765 treatment of EAE animals reduced the expression of inflammasome- and pyroptosis-associated proteins in the CNS, prevented axonal injury, and improved neurobehavioral performance. Thus, GSDMD-mediated pyroptosis in select glia cells is a previously unrecognized mechanism of inflammatory demyelination and represents a unique therapeutic opportunity for mitigating the disease process in MS and other CNS inflammatory diseases.

Renal redox stress and remodeling in metabolic syndrome, type 2 diabetes mellitus, and diabetic nephropathy: paying homage to the podocyte.

PubMed

Hayden, Melvin R; Whaley-Connell, Adam; Sowers, James R

2005-01-01

Type 2 diabetes mellitus has reached epidemic proportions and diabetic nephropathy is the leading cause of end-stage renal disease. The metabolic syndrome constitutes a milieu conducive to tissue redox stress. This loss of redox homeostasis contributes to renal remodeling and parallels the concurrent increased vascular redox stress associated with the cardiometabolic syndrome. The multiple metabolic toxicities, redox stress and endothelial dysfunction combine to weave the complicated mosaic fabric of diabetic glomerulosclerosis and diabetic nephropathy. A better understanding may provide both the clinician and researcher tools to unravel this complicated disease process. Cellular remodeling of podocyte foot processes in the Ren-2 transgenic rat model of tissue angiotensin II overexpression (TG(mREN-2)27) and the Zucker diabetic fatty model of type 2 diabetes mellitus have been observed in preliminary studies. Importantly, angiotensin II receptor blockers have been shown to abrogate these ultrastructural changes in the foot processes of the podocyte in preliminary studies. An integrated, global risk reduction, approach in therapy addressing the multiple metabolic abnormalities combined with attempts to reach therapeutic goals at an earlier stage could have a profound effect on the development and progressive nature to end-stage renal disease and ultimately renal replacement therapy.

An in vivo model of functional and vascularized human brain organoids.

PubMed

Mansour, Abed AlFatah; Gonçalves, J Tiago; Bloyd, Cooper W; Li, Hao; Fernandes, Sarah; Quang, Daphne; Johnston, Stephen; Parylak, Sarah L; Jin, Xin; Gage, Fred H

2018-06-01

Differentiation of human pluripotent stem cells to small brain-like structures known as brain organoids offers an unprecedented opportunity to model human brain development and disease. To provide a vascularized and functional in vivo model of brain organoids, we established a method for transplanting human brain organoids into the adult mouse brain. Organoid grafts showed progressive neuronal differentiation and maturation, gliogenesis, integration of microglia, and growth of axons to multiple regions of the host brain. In vivo two-photon imaging demonstrated functional neuronal networks and blood vessels in the grafts. Finally, in vivo extracellular recording combined with optogenetics revealed intragraft neuronal activity and suggested graft-to-host functional synaptic connectivity. This combination of human neural organoids and an in vivo physiological environment in the animal brain may facilitate disease modeling under physiological conditions.

Are Astrocytes the Predominant Cell Type for Activation of Nrf2 in Aging and Neurodegeneration?

PubMed Central

2017-01-01

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a transcription factor that regulates hundreds of antioxidant genes, and is activated in response to oxidative stress. Given that many neurodegenerative diseases including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease and multiple sclerosis are characterised by oxidative stress, Nrf2 is commonly activated in these diseases. Evidence demonstrates that Nrf2 activity is repressed in neurons in vitro, and only cultured astrocytes respond strongly to Nrf2 inducers, leading to the interpretation that Nrf2 signalling is largely restricted to astrocytes. However, Nrf2 activity can be observed in neurons in post-mortem brain tissue and animal models of disease. Thus this interpretation may be false, and a detailed analysis of the cell type expression of Nrf2 in neurodegenerative diseases is required. This review describes the evidence for Nrf2 activation in each cell type in prominent neurodegenerative diseases and normal aging in human brain and animal models of neurodegeneration, the response to pharmacological and genetic modulation of Nrf2, and clinical trials involving Nrf2-modifying drugs. PMID:28820437

Cost-effectiveness of disease-modifying therapy for multiple sclerosis

PubMed Central

Bajorska, A.; Chappel, A.; Schwid, S.R.; Mehta, L.R.; Weinstock-Guttman, B.; Holloway, R.G.; Dick, A.W.

2011-01-01

Objective: To evaluate the cost-effectiveness of disease-modifying therapies (DMTs) in the United States compared to basic supportive therapy without DMT for patients with relapsing multiple sclerosis (MS). Methods: Using data from a longitudinal MS survey, we generated 10-year disease progression paths for an MS cohort. We used first-order annual Markov models to estimate transitional probabilities. Costs associated with losses of employment were obtained from the Bureau of Labor Statistics. Medical costs were estimated using the Centers for Medicare and Medicaid Services reimbursement rates and other sources. Outcomes were measured as gains in quality-adjusted life-years (QALY) and relapse-free years. Monte Carlo simulations, resampling methods, and sensitivity analyses were conducted to evaluate model uncertainty. Results: Using DMT for 10 years resulted in modest health gains for all DMTs compared to treatment without DMT (0.082 QALY or <1 quality-adjusted month gain for glatiramer acetate, and 0.126–0.192 QALY gain for interferons). The cost-effectiveness of all DMTs far exceeded $800,000/QALY. Reducing the cost of DMTs had by far the greatest impact on the cost-effectiveness of these treatments (e.g., cost reduction by 67% would improve the probability of Avonex being cost-effective at $164,000/QALY to 50%). Compared to treating patients with all levels of disease, starting DMT earlier was associated with a lower (more favorable) incremental cost-effectiveness ratio compared to initiating treatment at any disease state. Conclusion: Use of DMT in MS results in health gains that come at a very high cost. PMID:21775734

Genome-wide association mapping identifies multiple loci for a canine SLE-related disease complex.

PubMed

Wilbe, Maria; Jokinen, Päivi; Truvé, Katarina; Seppala, Eija H; Karlsson, Elinor K; Biagi, Tara; Hughes, Angela; Bannasch, Danika; Andersson, Göran; Hansson-Hamlin, Helene; Lohi, Hannes; Lindblad-Toh, Kerstin

2010-03-01

The unique canine breed structure makes dogs an excellent model for studying genetic diseases. Within a dog breed, linkage disequilibrium is extensive, enabling genome-wide association (GWA) with only around 15,000 SNPs and fewer individuals than in human studies. Incidences of specific diseases are elevated in different breeds, indicating that a few genetic risk factors might have accumulated through drift or selective breeding. In this study, a GWA study with 81 affected dogs (cases) and 57 controls from the Nova Scotia duck tolling retriever breed identified five loci associated with a canine systemic lupus erythematosus (SLE)-related disease complex that includes both antinuclear antibody (ANA)-positive immune-mediated rheumatic disease (IMRD) and steroid-responsive meningitis-arteritis (SRMA). Fine mapping with twice as many dogs validated these loci. Our results indicate that the homogeneity of strong genetic risk factors within dog breeds allows multigenic disorders to be mapped with fewer than 100 cases and 100 controls, making dogs an excellent model in which to identify pathways involved in human complex diseases.

Helminth–host immunological interactions: prevention and control of immune-mediated diseases

PubMed Central

Elliott, David E.; Weinstock, Joel V.

2013-01-01

Exposure to commensal and pathogenic organisms strongly influences our immune system. Exposure to helminths was frequent before humans constructed their current highly hygienic environment. Today, in highly industrialized countries, contact between humans and helminths is rare. Congruent with the decline in helminth infections is an increase in the prevalence of autoimmune and inflammatory disease. It is possible that exclusion of helminths from the environment has permitted the emergence of immune-mediated disease. We review the protective effects of helminths on expression of inflammatory bowel disease, multiple sclerosis, and animal models of these and other inflammatory diseases. We also review the immune pathways altered by helminths that may afford protection from these illnesses. Helminth exposure tends to inhibit IFN-γ and IL-17 production, promote IL-4, IL-10, and TGF-β release, induce CD4+ T cell Foxp3 expression, and generate regulatory macrophages, dendritic cells, and B cells. Helminths enable protective pathways that may vary by specific species and disease model. Helminths or their products likely have therapeutic potential to control or prevent immune-mediated illness. PMID:22239614

Dysautonomia, a heuristic approach to a revised model for etiology of disease.

PubMed

Lonsdale, Derrick

2009-03-01

Dysautonomia refers to a disease where the autonomic nervous system is dysfunctional. This may be a central control mechanism, as in genetically determined familial dysautonomia (Riley-Day Syndrome), or peripherally in the distribution of the sympathetic and parasympathetic systems. There are multiple reports of a number of different diseases associated with dysautonomia. The etiology of this association has never been explained. There are also multiple publications on dysautonomia associated with specific non-caloric nutritional deficiencies. Beriberi is the prototype of autonomic dysfunction. It is the best known nutritional deficiency disease caused by an imbalance between ingested calories and the vitamins required for their oxidation, particularly thiamin. Long thought to be abolished in modern medical thinking, there are occasional isolated reports of the full-blown disease in developed Western cultures. Apart from genetically and epigenetically determined disease, evidence is presented that marginal high calorie malnutrition, particularly with reference to simple carbohydrates, is responsible for widespread dysautonomia. The brain and heart are the organs that have a fast rate of oxidative metabolism and are affected early by any mechanism that reduces oxidative efficiency. It is hypothesized that this results in a chaotic state of the hypothalamic/autonomic/endocrine axis. Due to the lack of adequate automatic controls, this may be responsible in some cases for breakdown of organ systems through long-standing energy deficiency, thus leading eventually to organic disease.

Coexistence of multiple sclerosis and ankylosing spondylitis: Report of four cases from Russia and review of the literature.

PubMed

Fominykh, Vera; Shevtsova, Tatyana; Arzumanian, Narine; Brylev, Lev

2017-10-01

Multiple sclerosis is a chronic demyelinating disorder of the central nervous system. There are many cases of multiple sclerosis - like syndrome and demyelinating disorders in systemic lupus erythematosus, Sjogren disease, Behcet disease and other autoimmune conditions. Coexistence of ankylosing spondylitis and multiple sclerosis usually is rare but in this article we report 4 Russian patients with concomitant multiple sclerosis and ankylosing spondylitis diseases. None of these patients received anti-tumor necrosis factor alpha therapy prior to diagnosis of multiple sclerosis. Pathogenesis, diagnostic and treatment challenges are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiple-trait estimates of genetic parameters for metabolic disease traits, fertility disorders, and their predictors in Canadian Holsteins.

PubMed

Jamrozik, J; Koeck, A; Kistemaker, G J; Miglior, F

2016-03-01

Producer-recorded health data for metabolic disease traits and fertility disorders on 35,575 Canadian Holstein cows were jointly analyzed with selected indicator traits. Metabolic diseases included clinical ketosis (KET) and displaced abomasum (DA); fertility disorders were metritis (MET) and retained placenta (RP); and disease indicators were fat-to-protein ratio, milk β-hydroxybutyrate, and body condition score (BCS) in the first lactation. Traits in first and later (up to fifth) lactations were treated as correlated in the multiple-trait (13 traits in total) animal linear model. Bayesian methods with Gibbs sampling were implemented for the analysis. Estimates of heritability for disease incidence were low, up to 0.06 for DA in first lactation. Among disease traits, the environmental herd-year variance constituted 4% of the total variance for KET and less for other traits. First- and later-lactation disease traits were genetically correlated (from 0.66 to 0.72) across all traits, indicating different genetic backgrounds for first and later lactations. Genetic correlations between KET and DA were relatively strong and positive (up to 0.79) in both first- and later-lactation cows. Genetic correlations between fertility disorders were slightly lower. Metritis was strongly genetically correlated with both metabolic disease traits in the first lactation only. All other genetic correlations between metabolic and fertility diseases were statistically nonsignificant. First-lactation KET and MET were strongly positively correlated with later-lactation performance for these traits due to the environmental herd-year effect. Indicator traits were moderately genetically correlated (from 0.30 to 0.63 in absolute values) with both metabolic disease traits in the first lactation. Smaller and mostly nonsignificant genetic correlations were among indicators and metabolic diseases in later lactations. The only significant genetic correlations between indicators and fertility disorders were those between BCS and MET in both first and later lactations. Results indicated a limited value of a joint genetic evaluation model for metabolic disease traits and fertility disorders in Canadian Holsteins. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Differential factors associated with challenge-proven food allergy phenotypes in a population cohort of infants: a latent class analysis.

PubMed

Peters, R L; Allen, K J; Dharmage, S C; Lodge, C J; Koplin, J J; Ponsonby, A-L; Wake, M; Lowe, A J; Tang, M L K; Matheson, M C; Gurrin, L C

2015-05-01

Food allergy, eczema and wheeze are early manifestations of allergic disease and commonly co-occur in infancy although their interrelationship is not well understood. Data from population studies are essential to determine whether there are differential drivers of multi-allergy phenotypes. We aimed to define phenotypes and risk factors of allergic disease using latent class analysis (LCA). The HealthNuts study is a prospective, population-based cohort of 5276 12-month-old infants in Melbourne, Australia. LCA was performed using the following baseline data collected at age 12 months: food sensitization (skin prick test ≥ 2 mm) and allergy (oral food challenge) to egg, peanut and sesame; early (< 4 months) and late-onset eczema; and wheeze in the first year of life. Risk factors were modelled using multinomial logistic regression. Five distinct phenotypes were identified: no allergic disease (70%), non-food-sensitized eczema (16%), single egg allergy (9%), multiple food allergies (predominantly peanut) (3%) and multiple food allergies (predominantly egg) (2%). Compared to the baseline group of no allergic disease, shared risk factors for all allergic phenotypes were parents born overseas (particularly Asia), delayed introduction of egg, male gender (except for single egg allergy) and family history of allergic disease, whilst exposure to pet dogs was protective for all phenotypes. Other factors including filaggrin mutations, vitamin D and the presence of older siblings differed by phenotype. Multiple outcomes in infancy can be used to determine five distinct allergy phenotypes at the population level, which have both shared and separate risk factors suggesting differential mechanisms of disease. © 2014 John Wiley & Sons Ltd.

Acute Traumatic Brain Injury Does Not Exacerbate Amyotrophic Lateral Sclerosis in the SOD1G93A Rat Model1,2,3

PubMed Central

Thomsen, Gretchen M.

2015-01-01

Abstract Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease in which upper and lower motor neurons degenerate, leading to muscle atrophy, paralysis, and death within 3 to 5 years of onset. While a small percentage of ALS cases are genetically linked, the majority are sporadic with unknown origin. Currently, etiological links are associated with disease onset without mechanistic understanding. Of all the putative risk factors, however, head trauma has emerged as a consistent candidate for initiating the molecular cascades of ALS. Here, we test the hypothesis that traumatic brain injury (TBI) in the SOD1 G93A transgenic rat model of ALS leads to early disease onset and shortened lifespan. We demonstrate, however, that a one-time acute focal injury caused by controlled cortical impact does not affect disease onset or survival. Establishing the negligible involvement of a single acute focal brain injury in an ALS rat model increases the current understanding of the disease. Critically, untangling a single focal TBI from multiple mild injuries provides a rationale for scientists and physicians to increase focus on repeat injuries to hopefully pinpoint a contributing cause of ALS. PMID:26464984

Atmospheric Spread of Foot-and-mouth Disease During The Early Phase of The Uk Epidemic 2001

NASA Astrophysics Data System (ADS)

Sørensen, J. H.; Mikkelsen, T.; Astrup, P.; Alexandersen, S.; Donaldson, A. I.

Foot-and-mouth disease (FMD) is a highly contagious viral disease in cloven-hoofed domesticated and wild animals. The highly contagious nature of FMD is a reflection of the wide range of species which are susceptible, the enormous quantities of virus liberated by infected animals, the range of excretions and secretions which can be infectious, the stability of the virus in the environment, the multiplicity of routes of infection and the very small doses of virus that can initiate infection in susceptible hosts. One of the routes for the spread of the disease is the atmospheric dispersion of virus exhaled by infected animals. Such spread can be rapid and extensive, and it is known in certain circumstances to have occurred over a distance of several hundred kilometres. For the FMD epidemic in UK in 2001, atmospheric dispersion models were applied in real time in order to describe the atmospheric dispersion of virus for the larger outbreaks of the disease. The operational value of such modelling is first of all to identify risk zones, which is helpful to the emergency management. The paper addresses the modelling techniques and presents results related with the epidemic in UK in 2001.

Axonal loss in the multiple sclerosis spinal cord revisited.

PubMed

Petrova, Natalia; Carassiti, Daniele; Altmann, Daniel R; Baker, David; Schmierer, Klaus

2018-05-01

Preventing chronic disease deterioration is an unmet need in people with multiple sclerosis, where axonal loss is considered a key substrate of disability. Clinically, chronic multiple sclerosis often presents as progressive myelopathy. Spinal cord cross-sectional area (CSA) assessed using MRI predicts increasing disability and has, by inference, been proposed as an indirect index of axonal degeneration. However, the association between CSA and axonal loss, and their correlation with demyelination, have never been systematically investigated using human post mortem tissue. We extensively sampled spinal cords of seven women and six men with multiple sclerosis (mean disease duration= 29 years) and five healthy controls to quantify axonal density and its association with demyelination and CSA. 396 tissue blocks were embedded in paraffin and immuno-stained for myelin basic protein and phosphorylated neurofilaments. Measurements included total CSA, areas of (i) lateral cortico-spinal tracts, (ii) gray matter, (iii) white matter, (iv) demyelination, and the number of axons within the lateral cortico-spinal tracts. Linear mixed models were used to analyze relationships. In multiple sclerosis CSA reduction at cervical, thoracic and lumbar levels ranged between 19 and 24% with white (19-24%) and gray (17-21%) matter atrophy contributing equally across levels. Axonal density in multiple sclerosis was lower by 57-62% across all levels and affected all fibers regardless of diameter. Demyelination affected 24-48% of the gray matter, most extensively at the thoracic level, and 11-13% of the white matter, with no significant differences across levels. Disease duration was associated with reduced axonal density, however not with any area index. Significant association was detected between focal demyelination and decreased axonal density. In conclusion, over nearly 30 years multiple sclerosis reduces axonal density by 60% throughout the spinal cord. Spinal cord cross sectional area, reduced by about 20%, appears to be a poor predictor of axonal density. © 2017 The Authors. Brain Pathology published by John Wiley & Sons Ltd on behalf of International Society of Neuropathology.

Optimization methods for decision making in disease prevention and epidemic control.

PubMed

Deng, Yan; Shen, Siqian; Vorobeychik, Yevgeniy

2013-11-01

This paper investigates problems of disease prevention and epidemic control (DPEC), in which we optimize two sets of decisions: (i) vaccinating individuals and (ii) closing locations, given respective budgets with the goal of minimizing the expected number of infected individuals after intervention. The spread of diseases is inherently stochastic due to the uncertainty about disease transmission and human interaction. We use a bipartite graph to represent individuals' propensities of visiting a set of location, and formulate two integer nonlinear programming models to optimize choices of individuals to vaccinate and locations to close. Our first model assumes that if a location is closed, its visitors stay in a safe location and will not visit other locations. Our second model incorporates compensatory behavior by assuming multiple behavioral groups, always visiting the most preferred locations that remain open. The paper develops algorithms based on a greedy strategy, dynamic programming, and integer programming, and compares the computational efficacy and solution quality. We test problem instances derived from daily behavior patterns of 100 randomly chosen individuals (corresponding to 195 locations) in Portland, Oregon, and provide policy insights regarding the use of the two DPEC models. Copyright © 2013 Elsevier Inc. All rights reserved.

Use of ferrets for electrophysiologic monitoring of ion transport

PubMed Central

Kaza, Niroop; Raju, S. Vamsee; Cadillac, Joan M.; Trombley, John A.; Rasmussen, Lawrence; Tang, Liping; Dohm, Erik; Harrod, Kevin S.

2017-01-01

Limited success achieved in translating basic science discoveries into clinical applications for chronic airway diseases is attributed to differences in respiratory anatomy and physiology, poor approximation of pathologic processes, and lack of correlative clinical endpoints between humans and laboratory animal models. Here, we discuss advantages of using ferrets (Mustela putorus furo) as a model for improved understanding of human airway physiology and demonstrate assays for quantifying airway epithelial ion transport in vivo and ex vivo, and establish air-liquid interface cultures of ferret airway epithelial cells as a complementary in vitro model for mechanistic studies. We present data here that establishes the feasibility of measuring these human disease endpoints in ferrets. Briefly, potential difference across the nasal and the lower airway epithelium in ferrets could be consistently assessed, were highly reproducible, and responsive to experimental interventions. Additionally, ferret airway epithelial cells were amenable to primary cell culture methods for in vitro experiments as was the use of ferret tracheal explants as an ex vivo system for assessing ion transport. The feasibility of conducting multiple assessments of disease outcomes supports the adoption of ferrets as a highly relevant model for research in obstructive airway diseases. PMID:29077751

Use of ferrets for electrophysiologic monitoring of ion transport.

PubMed

Kaza, Niroop; Raju, S Vamsee; Cadillac, Joan M; Trombley, John A; Rasmussen, Lawrence; Tang, Liping; Dohm, Erik; Harrod, Kevin S; Rowe, Steven M

2017-01-01

Limited success achieved in translating basic science discoveries into clinical applications for chronic airway diseases is attributed to differences in respiratory anatomy and physiology, poor approximation of pathologic processes, and lack of correlative clinical endpoints between humans and laboratory animal models. Here, we discuss advantages of using ferrets (Mustela putorus furo) as a model for improved understanding of human airway physiology and demonstrate assays for quantifying airway epithelial ion transport in vivo and ex vivo, and establish air-liquid interface cultures of ferret airway epithelial cells as a complementary in vitro model for mechanistic studies. We present data here that establishes the feasibility of measuring these human disease endpoints in ferrets. Briefly, potential difference across the nasal and the lower airway epithelium in ferrets could be consistently assessed, were highly reproducible, and responsive to experimental interventions. Additionally, ferret airway epithelial cells were amenable to primary cell culture methods for in vitro experiments as was the use of ferret tracheal explants as an ex vivo system for assessing ion transport. The feasibility of conducting multiple assessments of disease outcomes supports the adoption of ferrets as a highly relevant model for research in obstructive airway diseases.

Endothelial cell culture in microfluidic devices for investigating microvascular processes.

PubMed

Mannino, Robert G; Qiu, Yongzhi; Lam, Wilbur A

2018-07-01

Numerous conditions and disease states such as sickle cell disease, malaria, thrombotic microangiopathy, and stroke significantly impact the microvasculature function and its role in disease progression. Understanding the role of cellular interactions and microvascular hemodynamic forces in the context of disease is crucial to understanding disease pathophysiology. In vivo models of microvascular disease using animal models often coupled with intravital microscopy have long been utilized to investigate microvascular phenomena. However, these methods suffer from some major drawbacks, including the inability to tightly and quantitatively control experimental conditions, the difficulty of imaging multiple microvascular beds within a living organism, and the inability to isolate specific microvascular geometries such as bifurcations. Thus, there exists a need for in vitro microvascular models that can mitigate the drawbacks associated with in vivo systems. To that end, microfluidics has been widely used to develop such models, as it allows for tight control of system inputs, facile imaging, and the ability to develop robust and repeatable systems with well-defined geometries. Incorporating endothelial cells to branching microfluidic models allows for the development of "endothelialized" systems that accurately recapitulate physiological microvessels. In this review, we summarize the field of endothelialized microfluidics, specifically focusing on fabrication methods, limitations, and applications of these systems. We then speculate on future directions and applications of these cutting edge technologies. We believe that this review of the field is of importance to vascular biologists and bioengineers who aim to utilize microfluidic technologies to solve vascular problems.

Vicious circles in inflammatory bowel disease.

PubMed

Sonnenberg, Amnon; Collins, Judith F

2006-10-01

Inflammatory bowel disease can present with a bewildering array of disease manifestations whose overall impact on patient health is difficult to disentangle. The multitude of disease complications and therapeutic side effects result in conflicting ideas on how to best manage a patient. The aim of the study is to test the usefulness of influence diagrams in resolving conflicts centered on managing complex disease processes. The influences of a disease process and the ensuing medical interventions on the health of a patient with inflammatory bowel disease are modeled by an influence diagram. Patient health is the focal point of multiple influences affecting its overall strength. Any downstream influence represents the focal point of other preceding upstream influences. The mathematics underlying the influence diagram is similar to that of a decision tree. Its formalism allows one to consider additive and inhibitory influences and include in the same analysis qualitatively different types of parameters, such as diagnoses, complications, side effects, and therapeutic outcomes. Three exemplary cases are presented to illustrate the potential use of influence diagrams. In all three case scenarios, Crohn's disease resulted in disease manifestations that seemingly interfered with its own therapy. The presence of negative feedback loops rendered the management of each case particularly challenging. The analyses by influence diagrams revealed subtle interactions among the multiple influences and their joint contributions to the patient's overall health that would have been difficult to appreciate by verbal reasoning alone. Influence diagrams represent a decision tool that is particularly suited to improve decision-making in inflammatory bowel disease. They highlight key factors of a complex disease process and help to assess their quantitative interactions.

Early Life Stress, Air Pollution, Inflammation, and Disease: An Integrative Review and Immunologic Model of Social-Environmental Adversity and Lifespan Health.

PubMed

Olvera Alvarez, Hector A; Kubzansky, Laura D; Campen, Matthew J; Slavich, George M

2018-06-03

Socially disadvantaged individuals are at greater risk for simultaneously being exposed to adverse social and environmental conditions. Although the mechanisms underlying joint effects remain unclear, one hypothesis is that toxic social and environmental exposures have synergistic effects on inflammatory processes that underlie the development of chronic diseases, including cardiovascular disease, diabetes, depression, and certain types of cancer. In the present review, we examine how exposure to two risk factors that commonly occur with social disadvantage-early life stress and air pollution-affect health. Specifically, we identify neuroimmunologic pathways that could link early life stress, inflammation, air pollution, and poor health, and use this information to propose an integrated, multi-level model that describes how these factors may interact and cause health disparity across individuals based on social disadvantage. This model highlights the importance of interdisciplinary research considering multiple exposures across domains and the potential for synergistic, cross-domain effects on health, and may help identify factors that could potentially be targeted to reduce disease risk and improve lifespan health. Copyright © 2018. Published by Elsevier Ltd.

Multi-stage Vector-Borne Zoonoses Models: A Global Analysis.

PubMed

Bichara, Derdei; Iggidr, Abderrahman; Smith, Laura

2018-04-25

A class of models that describes the interactions between multiple host species and an arthropod vector is formulated and its dynamics investigated. A host-vector disease model where the host's infection is structured into n stages is formulated and a complete global dynamics analysis is provided. The basic reproduction number acts as a sharp threshold, that is, the disease-free equilibrium is globally asymptotically stable (GAS) whenever [Formula: see text] and that a unique interior endemic equilibrium exists and is GAS if [Formula: see text]. We proceed to extend this model with m host species, capturing a class of zoonoses where the cross-species bridge is an arthropod vector. The basic reproduction number of the multi-host-vector, [Formula: see text], is derived and shown to be the sum of basic reproduction numbers of the model when each host is isolated with an arthropod vector. It is shown that the disease will persist in all hosts as long as it persists in one host. Moreover, the overall basic reproduction number increases with respect to the host and that bringing the basic reproduction number of each isolated host below unity in each host is not sufficient to eradicate the disease in all hosts. This is a type of "amplification effect," that is, for the considered vector-borne zoonoses, the increase in host diversity increases the basic reproduction number and therefore the disease burden.

Computational modeling of the obstructive lung diseases asthma and COPD

PubMed Central

2014-01-01

Asthma and chronic obstructive pulmonary disease (COPD) are characterized by airway obstruction and airflow limitation and pose a huge burden to society. These obstructive lung diseases impact the lung physiology across multiple biological scales. Environmental stimuli are introduced via inhalation at the organ scale, and consequently impact upon the tissue, cellular and sub-cellular scale by triggering signaling pathways. These changes are propagated upwards to the organ level again and vice versa. In order to understand the pathophysiology behind these diseases we need to integrate and understand changes occurring across these scales and this is the driving force for multiscale computational modeling. There is an urgent need for improved diagnosis and assessment of obstructive lung diseases. Standard clinical measures are based on global function tests which ignore the highly heterogeneous regional changes that are characteristic of obstructive lung disease pathophysiology. Advances in scanning technology such as hyperpolarized gas MRI has led to new regional measurements of ventilation, perfusion and gas diffusion in the lungs, while new image processing techniques allow these measures to be combined with information from structural imaging such as Computed Tomography (CT). However, it is not yet known how to derive clinical measures for obstructive diseases from this wealth of new data. Computational modeling offers a powerful approach for investigating this relationship between imaging measurements and disease severity, and understanding the effects of different disease subtypes, which is key to developing improved diagnostic methods. Gaining an understanding of a system as complex as the respiratory system is difficult if not impossible via experimental methods alone. Computational models offer a complementary method to unravel the structure-function relationships occurring within a multiscale, multiphysics system such as this. Here we review the current state-of-the-art in techniques developed for pulmonary image analysis, development of structural models of the respiratory system and predictions of function within these models. We discuss application of modeling techniques to obstructive lung diseases, namely asthma and emphysema and the use of models to predict response to therapy. Finally we introduce a large European project, AirPROM that is developing multiscale models to investigate structure-function relationships in asthma and COPD. PMID:25471125

Epigenetics: relevance and implications for public health.

PubMed

Rozek, Laura S; Dolinoy, Dana C; Sartor, Maureen A; Omenn, Gilbert S

2014-01-01

Improved understanding of the multilayer regulation of the human genome has led to a greater appreciation of environmental, nutritional, and epigenetic risk factors for human disease. Chromatin remodeling, histone tail modifications, and DNA methylation are dynamic epigenetic changes responsive to external stimuli. Careful interpretation can provide insights for actionable public health through collaboration between population and basic scientists and through integration of multiple data sources. We review key findings in environmental epigenetics both in human population studies and in animal models, and discuss the implications of these results for risk assessment and public health protection. To ultimately succeed in identifying epigenetic mechanisms leading to complex phenotypes and disease, researchers must integrate the various animal models, human clinical approaches, and human population approaches while paying attention to life-stage sensitivity, to generate effective prescriptions for human health evaluation and disease prevention.

Using classification models for the generation of disease-specific medications from biomedical literature and clinical data repository.

PubMed

Wang, Liqin; Haug, Peter J; Del Fiol, Guilherme

2017-05-01

Mining disease-specific associations from existing knowledge resources can be useful for building disease-specific ontologies and supporting knowledge-based applications. Many association mining techniques have been exploited. However, the challenge remains when those extracted associations contained much noise. It is unreliable to determine the relevance of the association by simply setting up arbitrary cut-off points on multiple scores of relevance; and it would be expensive to ask human experts to manually review a large number of associations. We propose that machine-learning-based classification can be used to separate the signal from the noise, and to provide a feasible approach to create and maintain disease-specific vocabularies. We initially focused on disease-medication associations for the purpose of simplicity. For a disease of interest, we extracted potentially treatment-related drug concepts from biomedical literature citations and from a local clinical data repository. Each concept was associated with multiple measures of relevance (i.e., features) such as frequency of occurrence. For the machine purpose of learning, we formed nine datasets for three diseases with each disease having two single-source datasets and one from the combination of previous two datasets. All the datasets were labeled using existing reference standards. Thereafter, we conducted two experiments: (1) to test if adding features from the clinical data repository would improve the performance of classification achieved using features from the biomedical literature only, and (2) to determine if classifier(s) trained with known medication-disease data sets would be generalizable to new disease(s). Simple logistic regression and LogitBoost were two classifiers identified as the preferred models separately for the biomedical-literature datasets and combined datasets. The performance of the classification using combined features provided significant improvement beyond that using biomedical-literature features alone (p-value<0.001). The performance of the classifier built from known diseases to predict associated concepts for new diseases showed no significant difference from the performance of the classifier built and tested using the new disease's dataset. It is feasible to use classification approaches to automatically predict the relevance of a concept to a disease of interest. It is useful to combine features from disparate sources for the task of classification. Classifiers built from known diseases were generalizable to new diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of aquatic exercises in a rat model of brainstem demyelination with ethidium bromide on the beam walking test.

PubMed

Nassar, Cíntia Cristina Souza; Bondan, Eduardo Fernandes; Alouche, Sandra Regina

2009-09-01

Multiple sclerosis is a demyelinating disease of the central nervous system associated with varied levels of disability. The impact of early physiotherapeutic interventions in the disease progression is unknown. We used an experimental model of demyelination with the gliotoxic agent ethidium bromide and early aquatic exercises to evaluate the motor performance of the animals. We quantified the number of footsteps and errors during the beam walking test. The demyelinated animals walked fewer steps with a greater number of errors than the control group. The demyelinated animals that performed aquatic exercises presented a better motor performance than those that did not exercise. Therefore aquatic exercising was beneficial to the motor performance of rats in this experimental model of demyelination.

Global stability of a multiple delayed viral infection model with general incidence rate and an application to HIV infection.

PubMed

Ji, Yu

2015-06-01

In this paper, the dynamical behavior of a viral infection model with general incidence rate and two time delays is studied. By using the Lyapunov functional and LaSalle invariance principle, the global stabilities of the infection-free equilibrium and the endemic equilibrium are obtained. We obtain a threshold of the global stability for the uninfected equilibrium, which means the disease will be under control eventually. These results can be applied to a variety of viral infections of disease that would make it possible to devise optimal treatment strategies. Numerical simulations with application to HIV infection are given to verify the analytical results.

Primary hyperoxaluria type I: a model for multiple mutations in a monogenic disease within a distinct ethnic group.

PubMed

Rinat, C; Wanders, R J; Drukker, A; Halle, D; Frishberg, Y

1999-11-01

Primary hyperoxaluria type 1 is an autosomal recessive inherited metabolic disease in which excessive oxalates are formed by the liver and excreted by the kidneys, causing a wide spectrum of phenotypes ranging from renal failure in infancy to mere renal stones in late adulthood. Mutations in the AGXT gene, encoding the liver-specific enzyme alanine:glyoxylate aminotransferase, are responsible for the disease. Seven mutations were detected in eight families in Israel. Four of these mutations are novel and three occur in children living in single-clan villages. The mutations are scattered along various exons (1, 4, 5, 7, 9, 10), and on different alleles comprising at least five different haplotypes. All but one of the mutations are in a homozygous pattern, reflecting the high rate of consanguinity in our patient population. Two affected brothers are homozygous for two different mutations expressed on the same allele. The patients comprise a distinct ethnic group (Israeli Arabs) residing in a confined geographic area. These results, which are supported by previous data, suggest for the first time that the phenomenon of multiple mutations in a relatively closed isolate is common and almost exclusive to the Israeli-Arab population. Potential mechanisms including selective advantage to heterozygotes, digenic inheritance, and the recent emergence of multiple mutations are discussed.

Elastic-net regularization approaches for genome-wide association studies of rheumatoid arthritis.

PubMed

Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung

2009-12-15

The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.

Burden of Disease Measured by Disability-Adjusted Life Years and a Disease Forecasting Time Series Model of Scrub Typhus in Laiwu, China

PubMed Central

Yang, Li-Ping; Liang, Si-Yuan; Wang, Xian-Jun; Li, Xiu-Jun; Wu, Yan-Ling; Ma, Wei

2015-01-01

Background Laiwu District is recognized as a hyper-endemic region for scrub typhus in Shandong Province, but the seriousness of this problem has been neglected in public health circles. Methodology/Principal Findings A disability-adjusted life years (DALYs) approach was adopted to measure the burden of scrub typhus in Laiwu, China during the period 2006 to 2012. A multiple seasonal autoregressive integrated moving average model (SARIMA) was used to identify the most suitable forecasting model for scrub typhus in Laiwu. Results showed that the disease burden of scrub typhus is increasing yearly in Laiwu, and which is higher in females than males. For both females and males, DALY rates were highest for the 60–69 age group. Of all the SARIMA models tested, the SARIMA(2,1,0)(0,1,0)12 model was the best fit for scrub typhus cases in Laiwu. Human infections occurred mainly in autumn with peaks in October. Conclusions/Significance Females, especially those of 60 to 69 years of age, were at highest risk of developing scrub typhus in Laiwu, China. The SARIMA (2,1,0)(0,1,0)12 model was the best fit forecasting model for scrub typhus in Laiwu, China. These data are useful for developing public health education and intervention programs to reduce disease. PMID:25569248

Heat Shock Protein 70: Roles in Multiple Sclerosis

PubMed Central

Mansilla, María José; Montalban, Xavier; Espejo, Carmen

2012-01-01

Heat shock proteins (HSP) have long been considered intracellular chaperones that possess housekeeping and cytoprotective functions. Consequently, HSP overexpression was proposed as a potential therapy for neurodegenerative diseases characterized by the accumulation or aggregation of abnormal proteins. Recently, the discovery that cells release HSP with the capacity to trigger proinflammatory as well as immunoregulatory responses has focused attention on investigating the role of HSP in chronic inflammatory autoimmune diseases such as multiple sclerosis (MS). To date, the most relevant HSP is the inducible Hsp70, which exhibits both cytoprotectant and immunoregulatory functions. Several studies have presented contradictory evidence concerning the involvement of Hsp70 in MS or experimental autoimmune encephalomyelitis (EAE), the MS animal model. In this review, we dissect the functions of Hsp70 and discuss the controversial data concerning the role of Hsp70 in MS and EAE. PMID:22669475

A spatial scan statistic for compound Poisson data.

PubMed

Rosychuk, Rhonda J; Chang, Hsing-Ming

2013-12-20

The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits. Copyright © 2013 John Wiley & Sons, Ltd.

Detection of severe respiratory disease epidemic outbreaks by CUSUM-based overcrowd-severe-respiratory-disease-index model.

PubMed

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

2013-01-01

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

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

Imaging of Small Animal Peripheral Artery Disease Models: Recent Advancements and Translational Potential

PubMed Central

Lin, Jenny B.; Phillips, Evan H.; Riggins, Ti’Air E.; Sangha, Gurneet S.; Chakraborty, Sreyashi; Lee, Janice Y.; Lycke, Roy J.; Hernandez, Clarissa L.; Soepriatna, Arvin H.; Thorne, Bradford R. H.; Yrineo, Alexa A.; Goergen, Craig J.

2015-01-01

Peripheral artery disease (PAD) is a broad disorder encompassing multiple forms of arterial disease outside of the heart. As such, PAD development is a multifactorial process with a variety of manifestations. For example, aneurysms are pathological expansions of an artery that can lead to rupture, while ischemic atherosclerosis reduces blood flow, increasing the risk of claudication, poor wound healing, limb amputation, and stroke. Current PAD treatment is often ineffective or associated with serious risks, largely because these disorders are commonly undiagnosed or misdiagnosed. Active areas of research are focused on detecting and characterizing deleterious arterial changes at early stages using non-invasive imaging strategies, such as ultrasound, as well as emerging technologies like photoacoustic imaging. Earlier disease detection and characterization could improve interventional strategies, leading to better prognosis in PAD patients. While rodents are being used to investigate PAD pathophysiology, imaging of these animal models has been underutilized. This review focuses on structural and molecular information and disease progression revealed by recent imaging efforts of aortic, cerebral, and peripheral vascular disease models in mice, rats, and rabbits. Effective translation to humans involves better understanding of underlying PAD pathophysiology to develop novel therapeutics and apply non-invasive imaging techniques in the clinic. PMID:25993289

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

PubMed Central

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

2013-01-01

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

Restorative Integral Support (RIS) for Older Adults Experiencing Co-Occurring Disorders

ERIC Educational Resources Information Center

Larkin, Heather; MacFarland, Nicole S.

2012-01-01

The Restorative Integral Support (RIS) model is a whole person response that assists people to overcome adversity. The Adverse Childhood Experiences (ACE) Study conducted by Kaiser Permanente and the Centers for Disease Control and Prevention shows the association between stressors in childhood and multiple later-life health and social problems.…

A Meta-Analysis of Trials Evaluating Patient Education and Counseling for Three Groups of Preventive Health Behaviors.

ERIC Educational Resources Information Center

Mullen, Patricia Dolan; Simons-Morton, Denise G.; Ramirez, Gilbert; Frankowski, Ralph F.; Green, Lawrence W.; Mains, Douglas A.

1997-01-01

The overall effectiveness of patient education and counseling on preventive health behaviors was examined across published clinical trials, 1971-1994. The effectiveness of various approaches for modifying specific types of behaviors among patients without diagnosed disease was assessed. Multiple regression models indicated differences among…

A Multiple Logistic Regression Model for Predicting the Development of Phytophthora ramorum symptoms in Tanoak (Lithocarpus densiflorus)

Treesearch

Mark Spencer; Kevin O' Hara

2007-01-01

Phytophthora ramorum attacks tanoak (Lithocarpus densiflorus) in California and Oregon. We present a stand-level study examining the presence of disease symptoms in individual stems. Working with data from four plots in redwood (Sequoia sempervirens)/tanoak forests in Marin County, and three plots in Mendocino...

Self-Reported Weight Perceptions, Dieting Behavior, and Breakfast Eating among High School Adolescents

ERIC Educational Resources Information Center

Zullig, Keith; Ubbes, Valerie A.; Pyle, Jennifer; Valois, Robert F.

2006-01-01

This study explored the relationships among weight perceptions, dieting behavior, and breakfast eating in 4597 public high school adolescents using the Centers for Disease Control and Prevention Youth Risk Behavior Survey. Adjusted multiple logistic regression models were constructed separately for race and gender groups via SUDAAN (Survey Data…

Natural killer cell lines preferentially kill clonogenic multiple myeloma cells and decrease myeloma engraftment in a bioluminescent xenograft mouse model

PubMed Central

Swift, Brenna E.; Williams, Brent A.; Kosaka, Yoko; Wang, Xing-Hua; Medin, Jeffrey A.; Viswanathan, Sowmya; Martinez-Lopez, Joaquin; Keating, Armand

2012-01-01

Background Novel therapies capable of targeting drug resistant clonogenic MM cells are required for more effective treatment of multiple myeloma. This study investigates the cytotoxicity of natural killer cell lines against bulk and clonogenic multiple myeloma and evaluates the tumor burden after NK cell therapy in a bioluminescent xenograft mouse model. Design and Methods The cytotoxicity of natural killer cell lines was evaluated against bulk multiple myeloma cell lines using chromium release and flow cytometry cytotoxicity assays. Selected activating receptors on natural killer cells were blocked to determine their role in multiple myeloma recognition. Growth inhibition of clonogenic multiple myeloma cells was assessed in a methylcellulose clonogenic assay in combination with secondary replating to evaluate the self-renewal of residual progenitors after natural killer cell treatment. A bioluminescent mouse model was developed using the human U266 cell line transduced to express green fluorescent protein and luciferase (U266eGFPluc) to monitor disease progression in vivo and assess bone marrow engraftment after intravenous NK-92 cell therapy. Results Three multiple myeloma cell lines were sensitive to NK-92 and KHYG-1 cytotoxicity mediated by NKp30, NKp46, NKG2D and DNAM-1 activating receptors. NK-92 and KHYG-1 demonstrated 2- to 3-fold greater inhibition of clonogenic multiple myeloma growth, compared with killing of the bulk tumor population. In addition, the residual colonies after treatment formed significantly fewer colonies compared to the control in a secondary replating for a cumulative clonogenic inhibition of 89–99% at the 20:1 effector to target ratio. Multiple myeloma tumor burden was reduced by NK-92 in a xenograft mouse model as measured by bioluminescence imaging and reduction in bone marrow engraftment of U266eGFPluc cells by flow cytometry. Conclusions This study demonstrates that NK-92 and KHYG-1 are capable of killing clonogenic and bulk multiple myeloma cells. In addition, multiple myeloma tumor burden in a xenograft mouse model was reduced by intravenous NK-92 cell therapy. Since multiple myeloma colony frequency correlates with survival, our observations have important clinical implications and suggest that clinical studies of NK cell lines to treat MM are warranted. PMID:22271890

Paternal epigenetic programming: evolving metabolic disease risk.

PubMed

Hur, Suzy S J; Cropley, Jennifer E; Suter, Catherine M

2017-04-01

Parental health or exposures can affect the lifetime health outcomes of offspring, independently of inherited genotypes. Such 'epigenetic' effects occur over a broad range of environmental stressors, including defects in parental metabolism. Although maternal metabolic effects are well documented, it has only recently been established that that there is also an independent paternal contribution to long-term metabolic health. Both paternal undernutrition and overnutrition can induce metabolic phenotypes in immediate offspring, and in some cases, the induced phenotype can affect multiple generations, implying inheritance of an acquired trait. The male lineage transmission of metabolic disease risk in these cases implicates a heritable factor carried by sperm. Sperm-based transmission provides a tractable system to interrogate heritable epigenetic factors influencing metabolism, and as detailed here, animal models of paternal programming have already provided some significant insights. Here, we review the evidence for paternal programming of metabolism in humans and animal models, and the available evidence on potential underlying mechanisms. Programming by paternal metabolism can be observed in multiple species across animal phyla, suggesting that this phenomenon may have a unique evolutionary significance. © 2017 Society for Endocrinology.

Smoking cessation treatment and outcomes patterns simulation: a new framework for evaluating the potential health and economic impact of smoking cessation interventions.

PubMed

Getsios, Denis; Marton, Jenő P; Revankar, Nikhil; Ward, Alexandra J; Willke, Richard J; Rublee, Dale; Ishak, K Jack; Xenakis, James G

2013-09-01

Most existing models of smoking cessation treatments have considered a single quit attempt when modelling long-term outcomes. To develop a model to simulate smokers over their lifetimes accounting for multiple quit attempts and relapses which will allow for prediction of the long-term health and economic impact of smoking cessation strategies. A discrete event simulation (DES) that models individuals' life course of smoking behaviours, attempts to quit, and the cumulative impact on health and economic outcomes was developed. Each individual is assigned one of the available strategies used to support each quit attempt; the outcome of each attempt, time to relapses if abstinence is achieved, and time between quit attempts is tracked. Based on each individual's smoking or abstinence patterns, the risk of developing diseases associated with smoking (chronic obstructive pulmonary disease, lung cancer, myocardial infarction and stroke) is determined and the corresponding costs, changes to mortality, and quality of life assigned. Direct costs are assessed from the perspective of a comprehensive US healthcare payer ($US, 2012 values). Quit attempt strategies that can be evaluated in the current simulation include unassisted quit attempts, brief counselling, behavioural modification therapy, nicotine replacement therapy, bupropion, and varenicline, with the selection of strategies and time between quit attempts based on equations derived from survey data. Equations predicting the success of quit attempts as well as the short-term probability of relapse were derived from five varenicline clinical trials. Concordance between the five trials and predictions from the simulation on abstinence at 12 months was high, indicating that the equations predicting success and relapse in the first year following a quit attempt were reliable. Predictions allowing for only a single quit attempt versus unrestricted attempts demonstrate important differences, with the single quit attempt simulation predicting 19 % more smoking-related diseases and 10 % higher costs associated with smoking-related diseases. Differences are most prominent in predictions of the time that individuals abstain from smoking: 13.2 years on average over a lifetime allowing for multiple quit attempts, versus only 1.2 years with single quit attempts. Differences in abstinence time estimates become substantial only 5 years into the simulation. In the multiple quit attempt simulations, younger individuals survived longer, yet had lower lifetime smoking-related disease and total costs, while the opposite was true for those with high levels of nicotine dependence. By allowing for multiple quit attempts over the course of individuals' lives, the simulation can provide more reliable estimates on the health and economic impact of interventions designed to increase abstinence from smoking. Furthermore, the individual nature of the simulation allows for evaluation of outcomes in populations with different baseline profiles. DES provides a framework for comprehensive and appropriate predictions when applied to smoking cessation over smoker lifetimes.

Drug and alcohol treatment providers' views about the disease model of addiction and its impact on clinical practice: A systematic review.

PubMed

Barnett, Anthony I; Hall, Wayne; Fry, Craig L; Dilkes-Frayne, Ella; Carter, Adrian

2017-12-14

Addiction treatment providers' views about the disease model of addiction (DMA), and their contemporary views about the brain disease model of addiction (BDMA), remain an understudied area. We systematically reviewed treatment providers' attitudes about the DMA/BDMA, examined factors associated with positive or negative attitudes and assessed their views on the potential clinical impact of both models. Pubmed, EMBASE, PsycINFO, CINAHL Plus and Sociological Abstracts were systematically searched. Original papers on treatment providers' views about the DMA/BDMA and its clinical impact were included. Studies focussing on tobacco, behavioural addictions or non-Western populations were excluded. The 34 included studies were predominantly quantitative and conducted in the USA. Among mixed findings of treatment providers' support for the DMA, strong validity studies indicated treatment providers supported the disease concept and moral, free-will or social models simultaneously. Support for the DMA was positively associated with treatment providers' age, year of qualification, certification status, religious beliefs, being in recovery and Alcoholics Anonymous attendance. Greater education was negatively associated with DMA support. Treatment providers identified potential positive (e.g. reduced stigma) and negative (e.g. increased sense of helplessness) impacts of the DMA on client behaviour. The review suggests treatment providers may endorse disease and other models while strategically deploying the DMA for presumed therapeutic benefits. Varying DMA support across workforces indicated service users may experience multiple and potentially contradictory explanations of addiction. Future policy development will benefit by considering how treatment providers adopt disease concepts in practice. © 2017 Australasian Professional Society on Alcohol and other Drugs.

Estrogen receptor β ligand therapy activates PI3K/Akt/mTOR signaling in oligodendrocytes and promotes remyelination in a mouse model of multiple sclerosis

PubMed Central

Kumar, Shalini; Patel, Rhusheet; Moore, Spencer; Crawford, Daniel K.; Suwanna, Nirut; Mangiardi, Mario; Tiwari-Woodruff, Seema K.

2013-01-01

The identification of a drug that stimulates endogenous myelination and spares axon degeneration during multiple sclerosis (MS) could potentially reduce the rate of disease progression. Using experimental autoimmune encephalomyelitis (EAE), a mouse model of MS, we have previously shown that prophylactic administration of the estrogen receptor (ER) β ligand 2,3-bis(4-hydroxyphenyl)-propionitrile (DPN) decreases clinical disease, is neuroprotective, stimulates endogenous myelination, and improves axon conduction without altering peripheral cytokine production or reducing central nervous system (CNS) inflammation. Here, we assessed the effects of therapeutic DPN treatment during peak EAE disease, which represents a more clinically relevant treatment paradigm. In addition, we investigated the mechanism of action of DPN treatment-induced recovery during EAE. Given that prophylactic and therapeutic treatment with DPN during EAE improved remyelination-induced axon conduction, and that ER (α and β) and membrane (m)ERs are present on oligodendrocyte lineage cells, a direct effect of treatment on oligodendrocytes is likely. DPN treatment of EAE animals resulted in phosphorylated ERβ and activated the phosphatidylinositol 3-kinase (PI3K)/ serine–threonine-specific protein kinase (Akt)/ mammalian target of rapamycin (mTOR) signaling pathway, a pathway required for oligodendrocyte survival and axon myelination. These results, along with our previous studies of prophylactic DPN treatment, make DPN and similar ERβ ligands immediate and favorable therapeutic candidates for demyelinating disease. PMID:23603111

Tissue material properties and computational modelling of the human tibiofemoral joint: a critical review

PubMed Central

Akhtar, Riaz; Comerford, Eithne J.; Bates, Karl T.

2018-01-01

Understanding how structural and functional alterations of individual tissues impact on whole-joint function is challenging, particularly in humans where direct invasive experimentation is difficult. Finite element (FE) computational models produce quantitative predictions of the mechanical and physiological behaviour of multiple tissues simultaneously, thereby providing a means to study changes that occur through healthy ageing and disease such as osteoarthritis (OA). As a result, significant research investment has been placed in developing such models of the human knee. Previous work has highlighted that model predictions are highly sensitive to the various inputs used to build them, particularly the mathematical definition of material properties of biological tissues. The goal of this systematic review is two-fold. First, we provide a comprehensive summation and evaluation of existing linear elastic material property data for human tibiofemoral joint tissues, tabulating numerical values as a reference resource for future studies. Second, we review efforts to model tibiofemoral joint mechanical behaviour through FE modelling with particular focus on how studies have sourced tissue material properties. The last decade has seen a renaissance in material testing fuelled by development of a variety of new engineering techniques that allow the mechanical behaviour of both soft and hard tissues to be characterised at a spectrum of scales from nano- to bulk tissue level. As a result, there now exists an extremely broad range of published values for human tibiofemoral joint tissues. However, our systematic review highlights gaps and ambiguities that mean quantitative understanding of how tissue material properties alter with age and OA is limited. It is therefore currently challenging to construct FE models of the knee that are truly representative of a specific age or disease-state. Consequently, recent tibiofemoral joint FE models have been highly generic in terms of material properties even relying on non-human data from multiple species. We highlight this by critically evaluating current ability to quantitatively compare and model (1) young and old and (2) healthy and OA human tibiofemoral joints. We suggest that future research into both healthy and diseased knee function will benefit greatly from a subject- or cohort-specific approach in which FE models are constructed using material properties, medical imagery and loading data from cohorts with consistent demographics and/or disease states. PMID:29379690

Tissue material properties and computational modelling of the human tibiofemoral joint: a critical review.

PubMed

Peters, Abby E; Akhtar, Riaz; Comerford, Eithne J; Bates, Karl T

2018-01-01

Understanding how structural and functional alterations of individual tissues impact on whole-joint function is challenging, particularly in humans where direct invasive experimentation is difficult. Finite element (FE) computational models produce quantitative predictions of the mechanical and physiological behaviour of multiple tissues simultaneously, thereby providing a means to study changes that occur through healthy ageing and disease such as osteoarthritis (OA). As a result, significant research investment has been placed in developing such models of the human knee. Previous work has highlighted that model predictions are highly sensitive to the various inputs used to build them, particularly the mathematical definition of material properties of biological tissues. The goal of this systematic review is two-fold. First, we provide a comprehensive summation and evaluation of existing linear elastic material property data for human tibiofemoral joint tissues, tabulating numerical values as a reference resource for future studies. Second, we review efforts to model tibiofemoral joint mechanical behaviour through FE modelling with particular focus on how studies have sourced tissue material properties. The last decade has seen a renaissance in material testing fuelled by development of a variety of new engineering techniques that allow the mechanical behaviour of both soft and hard tissues to be characterised at a spectrum of scales from nano- to bulk tissue level. As a result, there now exists an extremely broad range of published values for human tibiofemoral joint tissues. However, our systematic review highlights gaps and ambiguities that mean quantitative understanding of how tissue material properties alter with age and OA is limited. It is therefore currently challenging to construct FE models of the knee that are truly representative of a specific age or disease-state. Consequently, recent tibiofemoral joint FE models have been highly generic in terms of material properties even relying on non-human data from multiple species. We highlight this by critically evaluating current ability to quantitatively compare and model (1) young and old and (2) healthy and OA human tibiofemoral joints. We suggest that future research into both healthy and diseased knee function will benefit greatly from a subject- or cohort-specific approach in which FE models are constructed using material properties, medical imagery and loading data from cohorts with consistent demographics and/or disease states.

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

PubMed

Pushpanathan, Maria E; Loftus, Andrea M; Gasson, Natalie; Thomas, Meghan G; Timms, Caitlin F; Olaithe, Michelle; Bucks, Romola S

2018-01-01

Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD). The Parkinson's Disease Sleep Scale (PDSS) and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

A Meta-Analysis of Probiotic Efficacy for Gastrointestinal Diseases

PubMed Central

Ritchie, Marina L.; Romanuk, Tamara N.

2012-01-01

Background Meta-analyses on the effects of probiotics on specific gastrointestinal diseases have generally shown positive effects on disease prevention and treatment; however, the relative efficacy of probiotic use for treatment and prevention across different gastrointestinal diseases, with differing etiology and mechanisms of action, has not been addressed. Methods/Principal Findings We included randomized controlled trials in humans that used a specified probiotic in the treatment or prevention of Pouchitis, Infectious diarrhea, Irritable Bowel Syndrome, Helicobacter pylori, Clostridium difficile Disease, Antibiotic Associated Diarrhea, Traveler's Diarrhea, or Necrotizing Enterocolitis. Random effects models were used to evaluate efficacy as pooled relative risks across the eight diseases as well as across probiotic species, single vs. multiple species, patient ages, dosages, and length of treatment. Probiotics had a positive significant effect across all eight gastrointestinal diseases with a relative risk of 0.58 (95% (CI) 0.51–0.65). Six of the eight diseases: Pouchitis, Infectious diarrhea, Irritable Bowel Syndrome, Helicobacter pylori, Clostridium difficile Disease, and Antibiotic Associated Diarrhea, showed positive significant effects. Traveler's Diarrhea and Necrotizing Enterocolitis did not show significant effects of probiotcs. Of the 11 species and species mixtures, all showed positive significant effects except for Lactobacillus acidophilus, Lactobacillus plantarum, and Bifidobacterium infantis. Across all diseases and probiotic species, positive significant effects of probiotics were observed for all age groups, single vs. multiple species, and treatment lengths. Conclusions/Significance Probiotics are generally beneficial in treatment and prevention of gastrointestinal diseases. Efficacy was not observed for Traveler's Diarrhea or Necrotizing Enterocolitis or for the probiotic species L. acidophilus, L. plantarum, and B. infantis. When choosing to use probiotics in the treatment or prevention of gastrointestinal disease, the type of disease and probiotic species (strain) are the most important factors to take into consideration. PMID:22529959

Antibody-dependent enhancement of severe dengue disease in humans*

PubMed Central

Katzelnick, Leah C.; Gresh, Lionel; Halloran, M. Elizabeth; Mercado, Juan Carlos; Kuan, Guillermina; Gordon, Aubree; Balmaseda, Angel; Harris, Eva

2018-01-01

For dengue viruses (DENV1-4), a specific range of antibody titer has been shown to enhance viral replication in vitro and severe disease in animal models. Although suspected, such antibody-dependent enhancement (ADE) of severe disease has not been shown to occur in humans. Using multiple statistical approaches to study a long-term pediatric cohort in Nicaragua, we show that risk of severe dengue disease is highest within a narrow range of pre-existing anti-DENV antibody titers. By contrast, we observe protection from all symptomatic dengue disease at high antibody titers. Thus, immune correlates of severe dengue must be evaluated separately from correlates of protection against symptomatic disease. These results have implications for studies of dengue pathogenesis and for vaccine development, because enhancement, not just lack of protection, is of concern. PMID:29097492

Innate lymphoid cells in autoimmunity and chronic inflammatory diseases.

PubMed

Xiong, Tingting; Turner, Jan-Eric

2018-03-22

Abnormal activation of the innate immune system is a common feature of autoimmune and chronic inflammatory diseases. Since their identification as a separate family of leukocytes, innate lymphoid cells (ILCs) have emerged as important effector cells of the innate immune system. Alterations in ILC function and subtype distribution have been observed in a variety of immune-mediated diseases in humans and evidence from experimental models suggests a subtype specific role of ILCs in the pathophysiology of autoimmune inflammation. In this review, we discuss recent advances in the understanding of ILC biology in autoimmune and chronic inflammatory disorders, including multiple sclerosis, inflammatory bowel diseases, psoriasis, and rheumatic diseases, with a special focus on the potential of ILCs as therapeutic targets for the development of novel treatment strategies in humans.

Curcumin and autoimmune disease.

PubMed

Bright, John J

2007-01-01

The immune system has evolved to protect the host from microbial infection; nevertheless, a breakdown in the immune system often results in infection, cancer, and autoimmune diseases. Multiple sclerosis, rheumatoid arthritis, type 1 diabetes, inflammatory bowel disease, myocarditis, thyroiditis, uveitis, systemic lupus erythromatosis, and myasthenia gravis are organ-specific autoimmune diseases that afflict more than 5% of the population worldwide. Although the etiology is not known and a cure is still wanting, the use of herbal and dietary supplements is on the rise in patients with autoimmune diseases, mainly because they are effective, inexpensive, and relatively safe. Curcumin is a polyphenolic compound isolated from the rhizome of the plant Curcuma longa that has traditionally been used for pain and wound-healing. Recent studies have shown that curcumin ameliorates multiple sclerosis, rheumatoid arthritis, psoriasis, and inflammatory bowel disease in human or animal models. Curcumin inhibits these autoimmune diseases by regulating inflammatory cytokines such as IL-1beta, IL-6, IL-12, TNF-alpha and IFN-gamma and associated JAK-STAT, AP-1, and NF-kappaB signaling pathways in immune cells. Although the beneficial effects of nutraceuticals are traditionally achieved through dietary consumption at low levels for long periods of time, the use of purified active compounds such as curcumin at higher doses for therapeutic purposes needs extreme caution. A precise understanding of effective dose, safe regiment, and mechanism of action is required for the use of curcumin in the treatment of human autoimmune diseases.

DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates

PubMed Central

Peng, Hao; Yang, Yifan; Zhe, Shandian; Wang, Jian; Gribskov, Michael; Qi, Yuan

2017-01-01

Abstract Motivation High-throughput mRNA sequencing (RNA-Seq) is a powerful tool for quantifying gene expression. Identification of transcript isoforms that are differentially expressed in different conditions, such as in patients and healthy subjects, can provide insights into the molecular basis of diseases. Current transcript quantification approaches, however, do not take advantage of the shared information in the biological replicates, potentially decreasing sensitivity and accuracy. Results We present a novel hierarchical Bayesian model called Differentially Expressed Isoform detection from Multiple biological replicates (DEIsoM) for identifying differentially expressed (DE) isoforms from multiple biological replicates representing two conditions, e.g. multiple samples from healthy and diseased subjects. DEIsoM first estimates isoform expression within each condition by (1) capturing common patterns from sample replicates while allowing individual differences, and (2) modeling the uncertainty introduced by ambiguous read mapping in each replicate. Specifically, we introduce a Dirichlet prior distribution to capture the common expression pattern of replicates from the same condition, and treat the isoform expression of individual replicates as samples from this distribution. Ambiguous read mapping is modeled as a multinomial distribution, and ambiguous reads are assigned to the most probable isoform in each replicate. Additionally, DEIsoM couples an efficient variational inference and a post-analysis method to improve the accuracy and speed of identification of DE isoforms over alternative methods. Application of DEIsoM to an hepatocellular carcinoma (HCC) dataset identifies biologically relevant DE isoforms. The relevance of these genes/isoforms to HCC are supported by principal component analysis (PCA), read coverage visualization, and the biological literature. Availability and implementation The software is available at https://github.com/hao-peng/DEIsoM Contact pengh@alumni.purdue.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:28595376

Development of the Digital Arthritis Index, a Novel Metric to Measure Disease Parameters in a Rat Model of Rheumatoid Arthritis.

PubMed

Lim, Maria A; Louie, Brenton; Ford, Daniel; Heath, Kyle; Cha, Paulyn; Betts-Lacroix, Joe; Lum, Pek Yee; Robertson, Timothy L; Schaevitz, Laura

2017-01-01

Despite a broad spectrum of anti-arthritic drugs currently on the market, there is a constant demand to develop improved therapeutic agents. Efficient compound screening and rapid evaluation of treatment efficacy in animal models of rheumatoid arthritis (RA) can accelerate the development of clinical candidates. Compound screening by evaluation of disease phenotypes in animal models facilitates preclinical research by enhancing understanding of human pathophysiology; however, there is still a continuous need to improve methods for evaluating disease. Current clinical assessment methods are challenged by the subjective nature of scoring-based methods, time-consuming longitudinal experiments, and the requirement for better functional readouts with relevance to human disease. To address these needs, we developed a low-touch, digital platform for phenotyping preclinical rodent models of disease. As a proof-of-concept, we utilized the rat collagen-induced arthritis (CIA) model of RA and developed the Digital Arthritis Index (DAI), an objective and automated behavioral metric that does not require human-animal interaction during the measurement and calculation of disease parameters. The DAI detected the development of arthritis similar to standard in vivo methods, including ankle joint measurements and arthritis scores, as well as demonstrated a positive correlation to ankle joint histopathology. The DAI also determined responses to multiple standard-of-care (SOC) treatments and nine repurposed compounds predicted by the SMarTR TM Engine to have varying degrees of impact on RA. The disease profiles generated by the DAI complemented those generated by standard methods. The DAI is a highly reproducible and automated approach that can be used in-conjunction with standard methods for detecting RA disease progression and conducting phenotypic drug screens.

Tesevatinib ameliorates progression of polycystic kidney disease in rodent models of autosomal recessive polycystic kidney disease

PubMed Central

Sweeney, William E; Frost, Philip; Avner, Ellis D

2017-01-01

AIM To investigate the therapeutic potential of tesevatinib (TSV), a unique multi-kinase inhibitor currently in Phase II clinical trials for autosomal dominant polycystic kidney disease (ADPKD), in well-defined rodent models of autosomal recessive polycystic kidney disease (ARPKD). METHODS We administered TSV in daily doses of 7.5 and 15 mg/kg per day by I.P. to the well characterized bpk model of polycystic kidney disease starting at postnatal day (PN) 4 through PN21 to assess efficacy and toxicity in neonatal mice during postnatal development and still undergoing renal maturation. We administered TSV by oral gavage in the same doses to the orthologous PCK model (from PN30 to PN90) to assess efficacy and toxicity in animals where developmental processes are complete. The following parameters were assessed: Body weight, total kidney weight; kidney weight to body weight ratios; and morphometric determination of a cystic index and a measure of hepatic disease. Renal function was assessed by: Serum BUN; creatinine; and a 12 h urinary concentrating ability. Validation of reported targets including the level of angiogenesis and inhibition of angiogenesis (active VEGFR2/KDR) was assessed by Western analysis. RESULTS This study demonstrates that: (1) in vivo pharmacological inhibition of multiple kinase cascades with TSV reduced phosphorylation of key mediators of cystogenesis: EGFR, ErbB2, c-Src and KDR; and (2) this reduction of kinase activity resulted in significant reduction of renal and biliary disease in both bpk and PCK models of ARPKD. The amelioration of disease by TSV was not associated with any apparent toxicity. CONCLUSION The data supports the hypothesis that this multi-kinase inhibitor TSV may provide an effective clinical therapy for human ARPKD. PMID:28729967

Animal Models of Fibrotic Lung Disease

PubMed Central

Lawson, William E.; Oury, Tim D.; Sisson, Thomas H.; Raghavendran, Krishnan; Hogaboam, Cory M.

2013-01-01

Interstitial lung fibrosis can develop as a consequence of occupational or medical exposure, as a result of genetic defects, and after trauma or acute lung injury leading to fibroproliferative acute respiratory distress syndrome, or it can develop in an idiopathic manner. The pathogenesis of each form of lung fibrosis remains poorly understood. They each result in a progressive loss of lung function with increasing dyspnea, and most forms ultimately result in mortality. To better understand the pathogenesis of lung fibrotic disorders, multiple animal models have been developed. This review summarizes the common and emerging models of lung fibrosis to highlight their usefulness in understanding the cell–cell and soluble mediator interactions that drive fibrotic responses. Recent advances have allowed for the development of models to study targeted injuries of Type II alveolar epithelial cells, fibroblastic autonomous effects, and targeted genetic defects. Repetitive dosing in some models has more closely mimicked the pathology of human fibrotic lung disease. We also have a much better understanding of the fact that the aged lung has increased susceptibility to fibrosis. Each of the models reviewed in this report offers a powerful tool for studying some aspect of fibrotic lung disease. PMID:23526222

What multiple sclerosis could bring to cognitive neuroscience?

PubMed

Naccache, L

2009-01-01

The relevance of multiple sclerosis for cognitive neuroscience has evolved significantly during the last decades. After a relative and enduring disinterest, the 1980's has been marked by a first wave of studies aiming at characterizing the cognitive dysfunctions associated with this disease. Once identified, and grouped under the relatively vague and nonspecific concept of "subcorticofrontal syndrome", these cognitive symptoms had to wait until the end of the 1990's to give rise to a new and vigorous resurgence of attention. Interestingly, this genuine contemporary revival of interest originates in the promotion of the very same arguments that served until there to explain the weak investment of multiple sclerosis by neuropsychology and cognitive neuroscience. The early disseminated nature of brain lesions, their dynamic and unstable nature, the prevalence of white-matter lesions, and the alteration of non-modular aspects of cognition: all these arguments have discouraged neuropsychologists for a long time. Today, these very same specific properties of multiple sclerosis offer an extremely relevant model to explore cognitive dimensions of brain plasticity, to revivify the concept of disconnection in neuropsychology, and to evaluate some neuroscientific models of consciousness.

The role of appraisal and coping style in relation with societal participation in fatigued patients with multiple sclerosis: a cross-sectional multiple mediator analysis.

PubMed

van den Akker, Lizanne Eva; Beckerman, Heleen; Collette, Emma Hubertine; Bleijenberg, Gijs; Dekker, Joost; Knoop, Hans; de Groot, Vincent

2016-10-01

To determine the relationship between appraisal and societal participation in fatigued patients with Multiple Sclerosis (MS), and whether this relation is mediated by coping styles. 265 severely-fatigued MS patients. Appraisal, a latent construct, was created from the General Self-Efficacy Scale and the helplessness and acceptance subscales of the Illness Cognition Questionnaire. Coping styles were assessed using the Coping Inventory Stressful Situations (CISS21) and societal participation was assessed using the Impact on Participation and Autonomy. A multiple mediator model was developed and tested by structural equation modeling on cross-sectional data. We corrected for confounding by disease-related factors. Mediation was determined using a product-of-coefficients approach. A significant relationship existed between appraisal and participation (β = 0.21, 95 % CI 0.04-0.39). The pathways via coping styles were not significant. In patients with severe MS-related fatigue, appraisal and societal participation show a positive relationship that is not mediated by coping styles.

NF-κB Activation Protects Oligodendrocytes against Inflammation

PubMed Central

Stone, Sarrabeth; Jamison, Stephanie; Yue, Yuan; Durose, Wilaiwan

2017-01-01

NF-κB is a key player in inflammatory diseases, including multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE). However, the effects of NF-κB activation on oligodendrocytes in MS and EAE remain unknown. We generated a mouse model that expresses IκBαΔN, a super-suppressor of NF-κB, specifically in oligodendrocytes and demonstrated that IκBαΔN expression had no effect on oligodendrocytes under normal conditions (both sexes). Interestingly, we showed that oligodendrocyte-specific expression of IκBαΔN blocked NF-κB activation in oligodendrocytes and resulted in exacerbated oligodendrocyte death and hypomyelination in young, developing mice that express IFN-γ ectopically in the CNS (both sexes). We also showed that NF-κB inactivation in oligodendrocytes aggravated IFN-γ-induced remyelinating oligodendrocyte death and remyelination failure in the cuprizone model (male mice). Moreover, we found that NF-κB inactivation in oligodendrocytes increased the susceptibility of mice to EAE (female mice). These findings imply the cytoprotective effects of NF-κB activation on oligodendrocytes in MS and EAE. SIGNIFICANCE STATEMENT Multiple sclerosis (MS) is an inflammatory demyelinating disease of the CNS. NF-κB is a major player in inflammatory diseases that acts by regulating inflammation and cell viability. Data indicate that NF-κB activation in inflammatory cells facilitates the development of MS. However, to date, attempts to understand the role of NF-κB activation in oligodendrocytes in MS have been unsuccessful. Herein, we generated a mouse model that allows for inactivation of NF-κB specifically in oligodendrocytes and then used this model to determine the precise role of NF-κB activation in oligodendrocytes in models of MS. The results presented in this study represent the first demonstration that NF-κB activation acts cell autonomously to protect oligodendrocytes against inflammation in animal models of MS. PMID:28842413

Pathophysiology and Mechanisms of Nonalcoholic Fatty Liver Disease.

PubMed

Haas, Joel T; Francque, Sven; Staels, Bart

2016-01-01

Nonalcoholic fatty liver disease (NAFLD) encompasses a spectrum of liver disorders characterized by abnormal hepatic fat accumulation, inflammation, and hepatocyte dysfunction. Importantly, it is also closely linked to obesity and the metabolic syndrome. NAFLD predisposes susceptible individuals to cirrhosis, hepatocellular carcinoma, and cardiovascular disease. Although the precise signals remain poorly understood, NAFLD pathogenesis likely involves actions of the different hepatic cell types and multiple extrahepatic signals. The complexity of this disease has been a major impediment to the development of appropriate metrics of its progression and effective therapies. Recent clinical data place increasing importance on identifying fibrosis, as it is a strong indicator of hepatic disease-related mortality. Preclinical modeling of the fibrotic process remains challenging, particularly in the contexts of obesity and the metabolic syndrome. Future studies are needed to define the molecular pathways determining the natural progression of NAFLD, including key determinants of fibrosis and disease-related outcomes. This review covers the evolving concepts of NAFLD from both human and animal studies. We discuss recent clinical and diagnostic methods assessing NAFLD diagnosis, progression, and outcomes; compare the features of genetic and dietary animal models of NAFLD; and highlight pharmacological approaches for disease treatment.

Impact of biodiversity and seasonality on Lyme-pathogen transmission.

PubMed

Lou, Yijun; Wu, Jianhong; Wu, Xiaotian

2014-11-28

Lyme disease imposes increasing global public health challenges. To better understand the joint effects of seasonal temperature variation and host community composition on the pathogen transmission, a stage-structured periodic model is proposed by integrating seasonal tick development and activity, multiple host species and complex pathogen transmission routes between ticks and reservoirs. Two thresholds, one for tick population dynamics and the other for Lyme-pathogen transmission dynamics, are identified and shown to fully classify the long-term outcomes of the tick invasion and disease persistence. Seeding with the realistic parameters, the tick reproduction threshold and Lyme disease spread threshold are estimated to illustrate the joint effects of the climate change and host community diversity on the pattern of Lyme disease risk. It is shown that climate warming can amplify the disease risk and slightly change the seasonality of disease risk. Both the "dilution effect" and "amplification effect" are observed by feeding the model with different possible alternative hosts. Therefore, the relationship between the host community biodiversity and disease risk varies, calling for more accurate measurements on the local environment, both biotic and abiotic such as the temperature and the host community composition.

Simian hemorrhagic fever virus infection of rhesus macaques as a model of viral hemorrhagic fever: Clinical characterization and risk factors for severe disease

PubMed Central

Johnson, Reed F.; Dodd, Lori; Yellayi, Srikanth; Gu, Wenjuan; Cann, Jennifer A.; Jett, Catherine; Bernbaum, John G.; Ragland, Dan R.; Claire, Marisa St.; Byrum, Russell; Paragas, Jason; Blaney, Joseph E.; Jahrling, Peter B.

2011-01-01

Simian Hemorrhagic Fever Virus (SHFV) has caused sporadic outbreaks of hemorrhagic fevers in macaques at primate research facilities. SHFV is a BSL-2 pathogen that has not been linked to human disease; as such, investigation of SHFV pathogenesis in non-human primates (NHPs) could serve as a model for hemorrhagic fever viruses such as Ebola, Marburg, and Lassa viruses. Here we describe the pathogenesis of SHFV in rhesus macaques inoculated with doses ranging from 50 PFU to 500,000 PFU. Disease severity was independent of dose with an overall mortality rate of 64% with signs of hemorrhagic fever and multiple organ system involvement. Analyses comparing survivors and non-survivors were performed to identify factors associated with survival revealing differences in the kinetics of viremia, immunosuppression, and regulation of hemostasis. Notable similarities between the pathogenesis of SHFV in NHPs and hemorrhagic fever viruses in humans suggest that SHFV may serve as a suitable model of BSL-4 pathogens. PMID:22014505

The zebrafish eye—a paradigm for investigating human ocular genetics

PubMed Central

Richardson, R; Tracey-White, D; Webster, A; Moosajee, M

2017-01-01

Although human epidemiological and genetic studies are essential to elucidate the aetiology of normal and aberrant ocular development, animal models have provided us with an understanding of the pathogenesis of multiple developmental ocular malformations. Zebrafish eye development displays in depth molecular complexity and stringent spatiotemporal regulation that incorporates developmental contributions of the surface ectoderm, neuroectoderm and head mesenchyme, similar to that seen in humans. For this reason, and due to its genetic tractability, external fertilisation, and early optical clarity, the zebrafish has become an invaluable vertebrate system to investigate human ocular development and disease. Recently, zebrafish have been at the leading edge of preclinical therapy development, with their amenability to genetic manipulation facilitating the generation of robust ocular disease models required for large-scale genetic and drug screening programmes. This review presents an overview of human and zebrafish ocular development, genetic methodologies employed for zebrafish mutagenesis, relevant models of ocular disease, and finally therapeutic approaches, which may have translational leads in the future. PMID:27612182

Early axonal damage and progressive myelin pathology define the kinetics of CNS histopathology in a mouse model of multiple sclerosis.

PubMed

Recks, Mascha S; Stormanns, Eva R; Bader, Jonas; Arnhold, Stefan; Addicks, Klaus; Kuerten, Stefanie

2013-10-01

Studies of MS histopathology are largely dependent on suitable animal models. While light microscopic analysis gives an overview of tissue pathology, it falls short in evaluating detailed changes in nerve fiber morphology. The ultrastructural data presented here and obtained from studies of myelin oligodendrocyte glycoprotein (MOG):35-55-induced experimental autoimmune encephalomyelitis (EAE) in C57BL/6 mice delineate that axonal damage and myelin pathology follow different kinetics in the disease course. While myelin pathology accumulated with disease progression, axonal damage coincided with the initial clinical disease symptoms and remained stable over time. This pattern applied both to irreversible axolysis and early axonal pathology. Notably, these histopathological patterns were reflected by the normal-appearing white matter (NAWM), suggesting that the NAWM is also in an active neurodegenerative state. The data underline the need for neuroprotection in MS and suggest the MOG model as a highly valuable tool for the assessment of different therapeutic strategies. Copyright © 2013 Elsevier Inc. All rights reserved.

Analysis of cohort studies with multivariate and partially observed disease classification data.

PubMed

Chatterjee, Nilanjan; Sinha, Samiran; Diver, W Ryan; Feigelson, Heather Spencer

2010-09-01

Complex diseases like cancers can often be classified into subtypes using various pathological and molecular traits of the disease. In this article, we develop methods for analysis of disease incidence in cohort studies incorporating data on multiple disease traits using a two-stage semiparametric Cox proportional hazards regression model that allows one to examine the heterogeneity in the effect of the covariates by the levels of the different disease traits. For inference in the presence of missing disease traits, we propose a generalization of an estimating equation approach for handling missing cause of failure in competing-risk data. We prove asymptotic unbiasedness of the estimating equation method under a general missing-at-random assumption and propose a novel influence-function-based sandwich variance estimator. The methods are illustrated using simulation studies and a real data application involving the Cancer Prevention Study II nutrition cohort.

Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions

NASA Astrophysics Data System (ADS)

Galimzianova, Alfiia; Lesjak, Žiga; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga

2015-03-01

Neuroimaging biomarkers are an important paraclinical tool used to characterize a number of neurological diseases, however, their extraction requires accurate and reliable segmentation of normal and pathological brain structures. For MR images of healthy brains the intensity models of normal-appearing brain tissue (NABT) in combination with Markov random field (MRF) models are known to give reliable and smooth NABT segmentation. However, the presence of pathology, MR intensity bias and natural tissue-dependent intensity variability altogether represent difficult challenges for a reliable estimation of NABT intensity model based on MR images. In this paper, we propose a novel method for segmentation of normal and pathological structures in brain MR images of multiple sclerosis (MS) patients that is based on locally-adaptive NABT model, a robust method for the estimation of model parameters and a MRF-based segmentation framework. Experiments on multi-sequence brain MR images of 27 MS patients show that, compared to whole-brain model and compared to the widely used Expectation-Maximization Segmentation (EMS) method, the locally-adaptive NABT model increases the accuracy of MS lesion segmentation.