METTL3 Mediates Atheroprone Flow–Induced Glycolysis in Endothelial Cells

Medicine, Cardiovascular System, Life Sciences, Cell Biology, Biochemistry, Immunology,
glycolysis   endothelial cells   atherosclerosis   METTL3   flow   RNA modification   metabolic reprogramming  

1. Research Background Atherosclerosis is the primary pathological basis of cardiovascular diseases, closely associated with endothelial cell (EC) dysfunction. Hemodynamic factors play a critical role in the regional selectivity of atherosclerosis: oscillatory shear stress (OS) (e.g., at vascular bifurcations) promotes plaque formation, while pulsa...

Deep scSTAR: Leveraging Deep Learning for the Extraction and Enhancement of Phenotype-Associated Features from Single-Cell RNA Sequencing and Spatial Transcriptomics Data

Information Science, Artificial Intelligence, Medicine, Life Sciences, Cell Biology, Immunology,
Single-cell RNA sequencing   Spatial transcriptomics   Deep learning   Phenotype-associated features   Tumor microenvironment  

In recent years, cutting-edge technologies such as single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have greatly advanced the development of life sciences and clinical medicine. These technologies have revealed cellular heterogeneity and brought novel insights into major fields such as disease, development, and immunity. Howe...

Ensemble Learning Based on Matrix Completion Improves Microbe-Disease Association Prediction

Information Science, Computer Science, Artificial Intelligence, Medicine, Life Sciences, Microbiology,
microbe-disease association   ensemble learning   matrix completion   prediction algorithm   bioinformatics  

Academic Background and Research Problem Microorganisms, as one of the most widely distributed forms of life on Earth, are closely related to oceans, soil, and the human body. The human body contains approximately 350 trillion microbial cells, which are intricately linked to human health and the onset and progression of diseases. In recent years, w...

Benchmarking Copy Number Aberrations Inference Tools Using Single-Cell Multi-Omics Datasets

Information Science, Artificial Intelligence, Medicine, Oncology, Life Sciences, Cell Biology, Bioengineering, Genetics,
Single-cell RNA sequencing   Copy number aberrations   Tumor heterogeneity   Benchmarking   Multi-omics  

1. Research Background and Significance In the fields of oncology and genomics, chromosomal copy number alterations (CNAs) are a key type of genetic variation driving the occurrence and progression of cancer. CNAs not only determine tumor heterogeneity but also play a crucial role in early tumor detection, subclone evolution analysis, research on d...

Unveiling a Novel Cancer Hallmark by Evaluation of Neural Infiltration in Cancer

Medicine, Oncology, Life Sciences, Cell Biology, Immunology, Genetics,
neural infiltration   cancer hallmark   tumor microenvironment   single-cell RNA sequencing   immunotherapy  

Cancer, as a major global public health challenge, is characterized by complex mechanisms underlying its onset and progression. For a long time, processes within the tumor microenvironment (TME)—such as immunity, inflammation, and angiogenesis—have been extensively studied and considered key determinants of tumor biological behavior. In recent year...

Optimized Phenotyping of Complex Morphological Traits: Enhancing Discovery of Common and Rare Genetic Variants

Medicine, Medical Imaging, Life Sciences, Bioengineering, Genetics,
Genotype–phenotype association   Complex trait   Heritability   Facial phenotyping   3D shape  

1. Academic Background and Research Motivation In recent years, genotype–phenotype (G-P) association analysis has become a core means of revealing the genetic basis of complex traits, especially with rapid development in the study of multidimensional structural traits such as the human face, limbs, and skeleton. Traditionally, G-P analyses rely on ...