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1,274 results for “Disease Model”
Data from: Accuracy in the prediction of disease epidemics when ensembling simple but highly correlated models
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A conceptual disease cycle model to link the size of past and future epidemics
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Parkinson’s disease propagation using MRI biomarkers and partial least squares path modeling
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Modeling management strategies for chronic disease in wildlife: predictions for the control of respiratory disease in bighorn sheep
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Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model
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Cadmium exposure persistently modulates the gut-liver axis in an Alzheimer’s disease mouse model
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A multi-state occupancy modeling framework for robust estimation of disease prevalence in multi-tissue disease systems
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Data: Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model
<p>Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the Metabolic Theory of Ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host – parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time, and final infection prevalence in an experimentally warmed system of <i>Daphnia </i>and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE sub-functions can predict warming-induced disease emergence in data-rich systems – a critical step towards generalizing the approach to other systems.</p>
Data from: Using multi-response models to investigate pathogen coinfections across scales: insights from emerging diseases of amphibians
1.Associations among parasites affect many aspects of host-parasite dynamics, but a lack of analytical tools has limited investigations of parasite correlations in observational data that are often nested across spatial and biological scales. 2.Here we illustrate how hierarchical, multiresponse modeling can characterize parasite associations by allowing for hierarchical structuring, offering estimates of uncertainty, and incorporating correlational model structures. After introducing the general approach, we apply this framework to investigate coinfections among four amphibian parasites (the trematodes Ribeiroia ondatrae and Echinostoma spp., the chytrid fungus Batrachochytrium dendrobatidis, and ranaviruses) and among >2000 individual hosts, 90 study sites, and five amphibian host species. 3.Ninety-two percent of sites and 80% of hosts supported two or more pathogen species. Our results revealed strong correlations between parasite pairs that varied by scale (from among hosts to among sites) and classification (microparasite versus macroparasite), but were broadly consistent across taxonomically diverse host species. At the host-scale, infection by the trematode R. ondatrae correlated positively with the microparasites, B. dendrobatidis and ranavirus, which were themselves positively associated. However, infection by a second trematode (Echinostoma spp.) correlated negatively with B. dendrobatidis and ranavirus, both at the host- and site-level scales, highlighting the importance of differential relationships between micro- and macroparasites. 4.Given the extensive number of coinfecting symbiont combinations inherent to natural systems, particularly across multiple host species, multiresponse modeling of cross-sectional field data offers a valuable tool to identify a tractable number of hypothesized interactions for experimental testing while accounting for uncertainty and potential sources of co-exposure. For amphibians specifically, the high frequency of co-occurrence and coinfection among these pathogens – each of which is known to impair host fitness or survival – highlights the urgency of understanding parasite associations for conservation and disease management.
Data from: Correlations of behavioral deficits with brain pathology assessed through longitudinal MRI and histopathology in the HDHQ150/Q150 mouse model of Huntington's disease
A variety of mouse models have been developed that express mutant huntingtin (mHTT) leading to aggregates and inclusions that model the molecular pathology observed in Huntington's disease. Here we show that although homozygous HdhQ150 knock-in mice developed motor impairments (rotarod, locomotor activity, grip strength) by 36 weeks of age, cognitive dysfunction (swimming T maze, fear conditioning, odor discrimination, social interaction) was not evident by 94 weeks. Concomitant to behavioral assessments, T2-weighted MRI volume measurements indicated a slower striatal growth with a significant difference between wild type (WT) and HdhQ150 mice being present even at 15 weeks. Indeed, MRI indicated significant volumetric changes prior to the emergence of the "clinical horizon" of motor impairments at 36 weeks of age. A striatal decrease of 27% was observed over 94 weeks with cortex (12%) and hippocampus (21%) also indicating significant atrophy. A hypothesis-free analysis using tensor-based morphometry highlighted further regions undergoing atrophy by contrasting brain growth and regional neurodegeneration. Histology revealed the widespread presence of mHTT aggregates and cellular inclusions. However, there was little evidence of correlations between these outcome measures, potentially indicating that other factors are important in the causal cascade linking the molecular pathology to the emergence of behavioral impairments. In conclusion, the HdhQ150 mouse model replicates many aspects of the human condition, including an extended pre-manifest period prior to the emergence of motor impairments.
Data from: The use of functional data analysis to evaluate activity in a spontaneous model of degenerative joint disease associated pain in cats
Accelerometry is used as an objective measure of physical activity in humans and veterinary species. In cats, one important use of accelerometry is in the study of therapeutics designed to treat degenerative joint disease (DJD) associated pain, where it serves as the most widely applied objective outcome measure. These analyses have commonly used summary measures, calculating the mean activity per-minute over days and comparing between treatment periods. While this technique has been effective, information about the pattern of activity in cats is lost. In this study, functional data analysis was applied to activity data from client-owned cats with (n=83) and without (n=15) DJD. Functional data analysis retains information about the pattern of activity over the 24-hour day, providing insight into activity over time. We hypothesized that 1) cats without DJD would have higher activity counts and intensity of activity than cats with DJD; 2) that activity counts and intensity of activity in cats with DJD would be inversely correlated with total radiographic DJD burden and total orthopedic pain score; and 3) that activity counts and intensity would have a different pattern on weekends versus weekdays. Results showed marked inter-cat variability in activity. Cats exhibited a bimodal pattern of activity with a sharp peak in the morning and broader peak in the evening. Results further showed that this pattern was different on weekends than weekdays, with the morning peak being shifted to the right (later). Cats with DJD showed different patterns of activity from cats without DJD, though activity and intensity were not always lower; instead both the peaks and troughs of activity were less extreme than those of the cats without DJD. Functional data analysis provides insight into the pattern of activity in cats, and an alternative method for analyzing accelerometry data that incorporates fluctuations in activity across the day.
Data from: Magnetic resonance imaging and tensor-based morphometry in the MPTP non-human primate model of Parkinson's disease
Parkinson's disease (PD) is the second most common neurodegenerative disorder producing a variety of motor and cognitive deficits with the causes remaining largely unknown. The gradual loss of the nigrostriatal pathway is currently considered the pivotal pathological event. To better understand the progression of PD and improve treatment management, defining the disease on a structural basis and expanding brain analysis to extra-nigral structures is indispensable. The anatomical complexity and the presence of neuromelanin, make the use of non-human primates an essential element in developing putative imaging biomarkers of PD. To this end, ex vivo T2-weighted magnetic resonance images were acquired from control and 1-methyl-4 phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated marmosets. Volume measurements of the caudate, putamen, and substantia nigra indicated significant atrophy and cortical thinning. Tensor-based morphometry provided a more extensive and hypothesis free assessment of widespread changes caused by the toxin insult to the brain, especially highlighting regional cortical atrophy. The results highlight the importance of developing imaging biomarkers of PD in non-human primate models considering their distinct neuroanatomy. It is essential to further develop these biomarkers in vivo to provide non-invasive tools to detect pre-symptomatic PD and to monitor potential disease altering therapeutics.
Data from: Metabolite profile of a mouse model of Charcot-Marie-Tooth type 2D neuropathy: implications for disease mechanisms and interventions
Charcot-Marie-Tooth disease encompasses a genetically heterogeneous class of heritable polyneuropathies that result in axonal degeneration in the peripheral nervous system. Charcot-Marie-Tooth type 2D neuropathy (CMT2D) is caused by dominant mutations in glycyl tRNA synthetase (GARS). Mutations in the mouse Gars gene result in a genetically and phenotypically valid animal model of CMT2D. How mutations in GARS lead to peripheral neuropathy remains controversial. To identify putative disease mechanisms, we compared metabolites isolated from the spinal cord of Gars mutant mice and their littermate controls. A profile of altered metabolites that distinguish the affected and unaffected tissue was determined. Ascorbic acid was decreased fourfold in the spinal cord of CMT2D mice, but was not altered in serum. Carnitine and its derivatives were also significantly reduced in spinal cord tissue of mutant mice, whereas glycine was elevated. Dietary supplementation with acetyl-L-carnitine improved gross motor performance of CMT2D mice, but neither acetyl-L-carnitine nor glycine supplementation altered the parameters directly assessing neuropathy. Other metabolite changes suggestive of liver and kidney dysfunction in the CMT2D mice were validated using clinical blood chemistry. These effects were not secondary to the neuromuscular phenotype, as determined by comparison with another, genetically unrelated mouse strain with similar neuromuscular dysfunction. However, these changes do not seem to be causative or consistent metabolites of CMT2D, because they were not observed in a second mouse Gars allele or in serum samples from CMT2D patients. Therefore, the metabolite 'fingerprint' we have identified for CMT2D improves our understanding of cellular biochemical changes associated with GARS mutations, but identification of efficacious treatment strategies and elucidation of the disease mechanism will require additional studies.
Age-induced midbrain-striatum assembloid models early phenotypes of Parkinson's disease
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Second wave, late-phase neuroinflammation in the brain of aged 5xFAD transgenic Alzheimer's disease model mice iden-tified using macrolaser light sheet microscopy imaging with tissue clearing
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Infectious disease modelling and the dynamics of the active cases - Data
<p>We developed a model that tries to describe the dynamics of the spread of a disease among a population, in particular the progress of infected active cases. The model is then applied to describe Italy CoViD-19 outbreak and subsequently, we tried to predict possible scenarios.</p>
Rodent Model of Non-alcoholic Fatty Liver Disease: A Systematic Review
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Mapping of the dataset of the German National Regsitry for Rare Diseases (NARSE) to Observational Medical Outcomes Partnership Common Data Model (OMOP CDM)
<p>Mapping between the data set of the German National Registry for Rare Diseases ("Nationales Register für Seltene Erkrankungen"; <a href="https://www.narse.de/">NARSE</a>) to Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) using international standards.</p>
Tabular datasets for for Morrone Parfitt, G., Coccia, E., Goldman, C. et al. Disruption of lysosomal proteolysis in astrocytes facilitates midbrain organoid proteostasis failure in an early-onset Parkinson's disease model. Nat Commun 15, 447 (2024). https://doi.org/10.1038/s41467-024-44732-2
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Advanced Iterative Model for Lumpy Skin Disease Prediction Using Fine-grained Feature Fusion and Adaptive Transfer Learning
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.