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High Glucose Treatment Induces Nuclei Aggregation of Microvascular Endothelial Cells via the - Pathway.

Arterioscler Thromb Vasc Biol

January 2025

Research Center of Clinical Medicine, Affiliated Hospital, Nantong University, China. (X.W., D.L.).

Background: Hyperglycemia is a major contributor to endothelial dysfunction and blood vessel damage, leading to severe diabetic microvascular complications. Despite the growing body of research on the underlying mechanisms of endothelial cell (EC) dysfunction, the available drugs based on current knowledge fall short of effectively alleviating these complications. Therefore, our endeavor to explore novel insights into the cellular and molecular mechanisms of endothelial dysfunction is crucial for the field.

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AimsThe cardioprotective effects of semaglutide 2.4 mg reported in the SELECT cardiovascular (CV) outcomes trial (ClinicalTrials.gov NCT03574597) provide clinical benefit for subjects with overweight or obesity and established CV disease without type 2 diabetes (T2D).

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Growing evidence indicates that type 2 diabetes (T2D) is associated with an increased risk of developing Parkinson's disease (PD) through shared disease mechanisms. Studies show that insulin resistance, which is the driving pathophysiological mechanism of T2D plays a major role in neurodegeneration by impairing neuronal functionality, metabolism and survival. To investigate insulin resistance caused pathological changes in the human midbrain, which could predispose a healthy midbrain to PD development, we exposed iPSC-derived human midbrain organoids from healthy individuals to either high insulin concentration, promoting insulin resistance, or to more physiological insulin concentration restoring insulin signalling function.

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Background: Glecaprevir/pibrentasvir is an effective antiviral therapy for hepatitis C virus infection and is generally regarded safe in patients with renal impairment. However, renal complications are a notable, albeit rare, concern.

Case Presentation: We report a case of acute kidney injury in a man in his 50s with chronic hepatitis C virus, chronic obstructive pulmonary disease, morbid obesity, a history of heroin dependence, and untreated type 2 diabetes mellitus.

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Bayesian deep learning applied to diabetic retinopathy with uncertainty quantification.

Heliyon

January 2025

Information Technology Department, Technical College of Informatics-Akre, Akre University for Applied Sciences, Kurdistan Regain, Iraq.

Deep Learning (DL) has significantly contributed to the field of medical imaging in recent years, leading to advancements in disease diagnosis and treatment. In the case of Diabetic Retinopathy (DR), DL models have shown high efficacy in tasks such as classification, segmentation, detection, and prediction. However, DL model's opacity and complexity lead to errors in decision-making, particularly in complex cases, making it necessary to estimate the model's uncertainty in predictions.

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