AIMC Topic: Disease Models, Animal

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Elucidate senescence-related gene signature and immune infiltration landscape in abdominal aortic aneurysm.

PloS one
BACKGROUND: Abdominal aortic aneurysm (AAA) refers to a lasting enlargement of the abdominal aorta. Senescence, a major risk factor of AAA, demonstrate positive connection with both the formation and rupture of aneurysms. Therefore, investigating the...

Deep Learning-Based Classification of Temporal Stages of AT8-Labeled Tau Pathology After Experimental Traumatic Brain Injury.

Neuroinformatics
Tauopathies are characterised by a progressive accumulation of hyperphosphorylated tau. However, early and intermediate stages remain challenging to quantify due to subtle and heterogeneous morphological characteristics. This study evaluates a deep l...

Multi-omics Mendelian randomization and machine learning identify candidate therapeutic targets for Alzheimer's and Parkinson's diseases.

Mammalian genome : official journal of the International Mammalian Genome Society
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effective therapies. To identify potential drug targets, we integrated large-scale genome-wide association ...

Deep-learning analysis of 3D microarchitectural remodeling in hypertrophic cardiomyopathy.

Science (New York, N.Y.)
Hypertrophic cardiomyopathy (HCM), a genetic heart disease defined by unexplained cardiac wall thickening, is a leading cause of sudden death worldwide. However, the three-dimensional organization of cardiac tissue underlying left ventricular hypertr...

Ultrasound and SWE-based transfer learning for predicting fibrotic NASH.

Scientific reports
The aim of this study was to develop a combined deep-learning model utilizing liver ultrasound, liver elastography images, and clinical features to predict and diagnose fibrotic non-alcoholic steatohepatitis (NASH). A rat model of liver steatosis and...

Deep learning-based detection of murine congenital heart defects from µCT scans.

Communications biology
Micro-computed tomography (μCT) provides 3D images of congenital heart defects (CHD) in mice. However, diagnosing CHD from μCT scans is time-consuming and requires clinical expertise. Here, we present a deep learning approach to automatically segment...

Cortical layer multi-parameter analysis of neurovascular impairments in AD/ADRD rodent model with in vivo optical imaging.

Translational neurodegeneration
BACKGROUND: Neurovascular biomarkers have the potential to enhance early diagnosis of Alzheimer's disease (AD) and AD-related dementias (ADRD), as cerebrovascular alterations often precede neurodegeneration. However, their clinical application remain...

AI-powered SPOT imaging for enhanced myocardial scar detection and quantification.

Nature communications
Cardiovascular disease is the leading global cause of death, underscoring the need for accurate assessment of myocardial injury. The current gold standard, bright-blood late gadolinium enhanced MRI, suffers from poor contrast at the blood-scar interf...

Age-dependent removal of Atg9-containing vesicle accumulations in motoneuron disease models by physical exercise.

Translational neurodegeneration
BACKGROUND: Atg9-containing vesicles are enriched in synapses and undergo cycles of exo- and endocytosis similarly to synaptic vesicles, thereby linking presynaptic autophagy to neuronal activity. Dysfunction of presynaptic autophagy is a pathophysio...

Machine learning-based prediction of drug response in ischemia reperfusion animal model.

Scientific reports
Myocardial ischemia is a major global contributor to mortality. While reperfusion therapy remains the most effective treatment, it paradoxically leads to myocardial ischemia-reperfusion (MI/R) injury, resulting in irreversible cardiac damage for whic...