A5019275058- Diabetes Management and Research
- Hyperglycemia and glycemic control in critically ill and hospitalized patients
- Diet, Metabolism, and Disease
- Liver Disease Diagnosis and Treatment
- Machine Learning in Healthcare
- RNA modifications and cancer
- Appendicitis Diagnosis and Management
- Obesity, Physical Activity, Diet
- Diabetes Treatment and Management
- Topic Modeling
- Ovarian cancer diagnosis and treatment
- Intraperitoneal and Appendiceal Malignancies
- Cancer Mechanisms and Therapy
- Neurological Disorders and Treatments
- Cerebrovascular and Carotid Artery Diseases
- Birth, Development, and Health
- Cardiovascular Function and Risk Factors
- Diet and metabolism studies
- Ferroptosis and cancer prognosis
- Acute Ischemic Stroke Management
- Growth Hormone and Insulin-like Growth Factors
- Alcohol Consumption and Health Effects
- Pituitary Gland Disorders and Treatments
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Teratomas and Epidermoid Cysts
Zhongshan Hospital
2023-2024
Fudan University
2021-2024
Sun Yat-sen University
2023-2024
The First Affiliated Hospital, Sun Yat-sen University
2023-2024
Fudan University Shanghai Cancer Center
2019
Shanghai Medical College of Fudan University
2019
Abstract Background and Aims We previously demonstrated that cancer‐associated fibroblasts (CAFs) promote tumor growth through recruitment of myeloid‐derived suppressor cells (MDSCs). 5‐lipoxygenase (5‐LO) is highly expressed in myeloid critical for synthesizing leukotriene B4 (LTB4), which involved progression by activating its receptor type 2 (BLT2). In this study, we investigated whether how CAFs regulate MDSC function to enhance cancer stemness, the driving force aggressiveness...
Background: Survival rates for Colorectal cancer (CRC) patients who experienced early relapse have usually been relatively low. Our study aims at developing an autophagy signature that could help to detect cases in CRC. Methods: Propensity score matching analysis was carried out between from the group and long-term survival GSE39582. For both groups, respectively, global expression changes were then analyzed identify differentially expressed prognostic related genes by conducting Linear...
Diabetes is a chronic disease that poses significant global health burden, and optimizing diabetes management requires multi-stakeholder collaboration. Large language models (LLMs) have shown promise in various healthcare scenarios, but their effectiveness across diverse range of tasks remains unproven. In this study, we introduced framework to train validate diabetes-specific LLMs. We first developed comprehensive data processing pipeline includes collection, filtering, augmentation...
Abstract Aim The association between sugar‐sweetened beverages and metabolic disorders has been well studied. However, it not determined whether fasting serum fructose is associated with dysfunction‐associated fatty liver disease (MAFLD). Methods Participants were enrolled from 2011 to 2012 in Shanghai. Fasting concentration was measured a validated liquid chromatography–tandem mass spectrometry method. Results A total of 954 participants without diabetes included. They followed for an...
Background & aims The effect of change in non-alcoholic fatty liver disease (NAFLD) status on incident diabetes has not been well studied. We aimed to investigate the association NAFLD development and remission with risk during a median 3.5-year follow-up. Methods A total 2690 participants without were recruited 2011-2012 assessed for 2014. Abdominal ultrasonography was used determine NAFLD. 75 g oral glucose tolerance test (OGTT) performed diabetes. severity using Gholam’s model....
Abstract Aims Large language models (LLMs), exemplified by ChatGPT have recently emerged as potential solutions to challenges of traditional diabetes education. This study aimed explore the feasibility and utility application in Methods We conducted a multi-dataset, multi-reviewer study. In retrospective dataset evaluation, 85 questions covering seven aspects education were collected. Three physicians evaluate responses for reproducibility, relevance, correctness, helpfulness, safety, while...