A5002901320- Epigenetics and DNA Methylation
- Diabetes and associated disorders
- Cancer Immunotherapy and Biomarkers
- Blood transfusion and management
- Pancreatic function and diabetes
- Acne and Rosacea Treatments and Effects
- Ocular Infections and Treatments
- Cardiac Arrest and Resuscitation
- Cancer-related molecular mechanisms research
- Immune cells in cancer
- RNA modifications and cancer
- Sphingolipid Metabolism and Signaling
- Immunotherapy and Immune Responses
- Ferroptosis and cancer prognosis
- Acute Kidney Injury Research
- Contact Dermatitis and Allergies
First Affiliated Hospital of Anhui Medical University
2023-2024
Anhui Medical University
2016-2024
Ministry of Education of the People's Republic of China
2023-2024
Third People's Hospital of Hangzhou
2016
Background We explore sphingolipid-related genes (SRGs) in skin melanoma (SKCM) to develop a prognostic indicator for patient outcomes. Dysregulated lipid metabolism is linked aggressive behavior various cancers, including SKCM. However, the exact role and mechanism of sphingolipid remain partially understood. Methods integrated scRNA-seq data from patients sourced GEO database. Through utilization Seurat R package, we successfully identified distinct gene clusters associated with survival...
Object The purpose of this study was to describe the longitudinal dynamic hemoglobin trajectories in patients undergoing cardiac surgery and explore whether they provide a broader perspective predicting AKI compared traditional threshold values. Additionally, interaction red blood cell transfusion also investigated. Methods MIMIC-IV database searched identify with cardiopulmonary bypass. Group-based trajectory modeling (GBTM) used determine first 72 h after ICU admission. correlation between...
Objective: Studies have firmly established the pivotal role of immunogenic cell death (ICD) in development tumors. This study seeks to develop a risk model related ICD predict prognosis patients with endometrial carcinoma (EC). Materials and Methods: RNA-seq data EC retrieved from TCGA database were analyzed using R software. We determined clusters based on ICD-related genes (ICDRGs) expression levels. Cox LASSO analyses further used build prediction model, its accuracy was evaluated train...