Animal Disease Models
Animal Disease Models - Related Videos
26:43
Computer-Generated Animal Model Stimuli
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Cited by 9 •
2007
Computer-generated stimuli using the Jacky dragon as a model.
08:23
Feeding of Ticks on Animals for Transmission and Xenodiagnosis in Lyme Disease Research
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Cited by 27 •
2013
Lyme disease is the most commonly-reported vector-borne disease in North America. The causative agent, Borrelia burgdorferi is a spirochete bacterium transmitted by Ixodid ticks. Transmission and detection of infection in animal models is optimized by the use of tick feeding, which we describe here.
08:27
Establishment of a Valuable Mimic of Alzheimer's Disease in Rat Animal Model by Intracerebroventricular Injection of Composited Amyloid Beta Protein
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Cited by 15 •
2018
This is a protocol to mimic Alzheimer's Disease in rats by evaluation of spatial memory impairment, neuronal pathological changes, neuronal amyloid beta protein (Aβ) burden, and neurofibrillary tangles aggregation, induced by the injection of Aβ25-35 combined with aluminum trichloride and recombinant human transforming growth factor-β1.
09:45
An Isolated Working Heart System for Large Animal Models
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Cited by 22 •
2014
Most studies involving the Langendorff apparatus use small animal models due to the increased complexity of systems for larger mammals. We describe a Langendorff system for large animal models that allows for use across a range of species, including humans, and relatively easy data acquisition.
09:03
The CYP2D6 Animal Model: How to Induce Autoimmune Hepatitis in Mice
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Cited by 31 •
2012
Infection of mice with an Adenovirus expressing the major human autoantigen cytochrome P450 2D6 (hCYP2D6) recognized by sera of patients suffering from type 2 autoimmune hepatitis results in a persistent form of autoimmune-mediated liver disease characterized by extensive hepatitis, fibrosis and generation of a CYP2D6-specific immune response.
FAQs
Selection depends on whether the question concerns disease causes, biological mechanisms, or potential treatments, and on which human disease features can be reproduced. Genetic modification, targeted lesions, toxin exposure, and induced inflammation provide different experimental routes. Comparing complementary species and model types helps reveal which findings are consistent and improves the translational interpretation of neuroscience results.
Researchers introduce defined biological changes through genetic modification, targeted lesions, toxin exposure, or induced inflammation, then examine their neural, molecular, and behavioral effects. This multilevel approach connects cellular pathways with broader nervous-system dysfunction. It also helps distinguish molecular alterations from associated behavioral changes, providing a more integrated picture of how disease-related processes affect the nervous system.
No single model captures every aspect of a human illness, so findings from one organism or model type may represent only part of the disease process. Comparing complementary species and experimental approaches allows investigators to identify converging results, recognize limitations, and strengthen interpretation. This comparison can improve confidence in findings considered for later clinical testing.
Investigators select or create a model using a defined approach, maintain experimental conditions, and measure neural, molecular, and behavioral changes. They then relate these outcomes to disease mechanisms or treatment effects and compare results across complementary models when appropriate. This structured workflow supports controlled investigation while making clear which features of the human condition are represented.
Animal Disease Models can provide evidence at several levels, including changes in neural systems, molecular pathways, and behavior. Together, these measurements help researchers connect cellular mechanisms to nervous-system dysfunction and identify biomarkers associated with disease or treatment response. Using multiple outcome types prevents interpretation from relying on behavior alone and supports more informative preclinical conclusions.
Researchers administer or examine potential drug-based and gene-based interventions under defined biological conditions, then assess resulting neural, molecular, and behavioral changes. The observed effects can indicate whether an intervention influences disease-related pathways or functional outcomes. Such studies also support biomarker identification and help determine which findings warrant consideration before clinical testing.