Results 141 to 150 of about 2,069,350 (347)
The study reveals that glutaminolysis in macrophages is inhibited under type 2 diabetes mellitus (T2DM) conditions, which impedes fracture healing by reducing bone morphogenetic protein 2 (BMP2) production through increased cytosine methylation on the promoter.
Jing Wang+12 more
wiley +1 more source
This study investigates the role of macrophage pyruvate carboxylase (PC) in atherosclerosis (AS) demonstrating that PC upregulation in macrophages promotes metabolism reprogramming to enhance inflammatory responses via the HIF‐1 signaling pathway.
Ling‐Na Zhao+17 more
wiley +1 more source
Polymorphic gene conferring susceptibility to insulin-dependent diabetes mellitus typed by ps-resolved FRET on nonamplified genomic DNA [PDF]
This work concerns the identification of the allelic sequences of the DQB1 gene of the human leukocyte antigen system conferring susceptibility to the development of insulin-dependent diabetes mellitus (IDDM) in DNA samples with no need of PCR amplification. Our method is based on the time-resolved analysis of a F\"orster energy-transfer mechanism that
arxiv
Lingwen Ying,1,* Yong Zhang,2,* Jun Yin,1,* Yufei Wang,1 Wei Lu,1 Wei Zhu,1 Yuqian Bao,1 Jian Zhou1 1Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital; Shanghai Clinical Center for ...
Ying L+7 more
doaj
The research indicates that dual energy CT scanning can accurately predict the stroke source and clinical outcomes by analyzing thrombus heterogeneity. Based on histopathological analysis of thrombus components, these scans are better able to display thrombus details than standard CT scans, which is helpful for the development of visual navigation ...
Jingxuan Jiang+15 more
wiley +1 more source
Explainable Deep Multilevel Attention Learning for Predicting Protein Carbonylation Sites
Selective carbonylation sites (SCANS) are conceptualized, designed, evaluated, and released. SCANS captures segment‐level, protein‐level, and residue embeddings features. It utilizes elaborate loss function to penalize cross‐predictions at the residue level.
Jian Zhang+6 more
wiley +1 more source
Exploring Biomarker Relationships in Both Type 1 and Type 2 Diabetes Mellitus Through a Bayesian Network Analysis Approach [PDF]
Understanding the complex relationships of biomarkers in diabetes is pivotal for advancing treatment strategies, a pressing need in diabetes research. This study applies Bayesian network structure learning to analyze the Shanghai Type 1 and Type 2 diabetes mellitus datasets, revealing complex relationships among key diabetes-related biomarkers.
arxiv
This study develops a human engineered heart tissue‐derived model of diabetic cardiomyopathy that accurately replicates the dynamic changes in the structural, contractile, and electrophysiological properties of the myocardium. Furthermore, this model is used to confirm the direct protective effects of empagliflozin on the heart through an SGLT2 off ...
Lin Cai+9 more
wiley +1 more source
Tumor‐associated TP53 inactivation correlates with lipid droplet (LD) accumulation. High‐fat diets drive Cyb5r3‐Myh9‐mediated p53 enrichment on LD surfaces, accelerating its degradation while upregulating LD‐promoting factor CD36 expression to establish a feed‐forward loop. LD suppression or dietary intervention restores p53 and inhibits tumorigenesis,
Haiyang Liu+20 more
wiley +1 more source
Integrating Bayesian Approaches and Expert Knowledge for Forecasting Continuous Glucose Monitoring Values in Type 2 Diabetes Mellitus [PDF]
Precise and timely forecasting of blood glucose levels is essential for effective diabetes management. While extensive research has been conducted on Type 1 diabetes mellitus, Type 2 diabetes mellitus (T2DM) presents unique challenges due to its heterogeneity, underscoring the need for specialized blood glucose forecasting systems.
arxiv