AIMC Topic: Apolipoproteins E

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Exercise mitigates high-fat diet-induced cardiac dysfunction via APOE genotype- and immune-dependent mechanisms: A photon-counting CT study in adult mice.

PloS one
BACKGROUND: Cardiovascular dysfunction frequently accompanies aging and is often worsened by adverse lifestyle factors and genetic susceptibility. The apolipoprotein E (APOE) gene modulates susceptibility to cardiovascular disease, but how exercise a...

Identification and validation of palmitoylation-related signature genes based on machine learning for prostate cancer.

PloS one
Prostate cancer (PCa) remains a leading cause of cancer-related mortality in men, with challenges in diagnosis and treatment due to tumor heterogeneity. This study identifies palmitoylation-related signature genes as potential diagnostic and therapeu...

Microglial pruning of glycinergic synapses disinhibits spinal PKCγ interneurons to drive pain hypersensitivity in mice.

Science translational medicine
Microglial activation is linked to neuroinflammation in neuropathic pain. Recently, microglia-mediated synaptic pruning has received mounting attention. However, the exact role of spinal microglia in modulating neuropathic pain-associated neural circ...

Assessing the cardioprotective effects of exercise in APOE mouse models using deep learning and photon-counting micro-CT.

PloS one
BACKGROUND: The allelic variations of the apolipoprotein E (APOE) gene play a critical role in regulating lipid metabolism and significantly impact cardiovascular disease risk (CVD). This study aimed to evaluate the impact of exercise on cardiac stru...

Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia.

Translational psychiatry
Existing dementia prediction models using non-neuroimaging clinical measures have been limited in their ability to identify disease. This study used machine learning to re-examine the diagnostic potential of clinical measures for dementia. Data was s...

Assessing polyomic risk to predict Alzheimer's disease using a machine learning model.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Alzheimer's disease (AD) is the most common form of dementia in the elderly. Given that AD neuropathology begins decades before symptoms, there is a dire need for effective screening tools for early detection of AD to facilitate early i...

Tackling APOE's structural challenges via in silico modeling in the era of neural networks: Can AlphaFold II help circumvent the problem of lacking full-length protein structure?

Archives of biochemistry and biophysics
The APOE gene, encoding apolipoprotein E, is a predictor of longevity and age-related diseases. Despite numerous genetic studies, the data on molecular mechanisms by which apolipoprotein E affects the human phenotype remain incomplete due to the stru...

Predicting conversion to Alzheimer's disease in individuals with Mild Cognitive Impairment using clinically transferable features.

Scientific reports
Patients with Mild Cognitive Impairment (MCI) have an increased risk of Alzheimer's disease (AD). Early identification of underlying neurodegenerative processes is essential to provide treatment before the disease is well established in the brain. He...