The Molecular Mechanism of Long Non-Coding RNA (LncRNA) Regulation of Notch Signaling in Glucose-Induced Apoptosis of Human Retinal Vascular Endothelial Cell.

Diabetes, a global health concern, affects the health of more than 500 million adults. The absence of Notch protein can cause an imbalance in the retinal vascular environment and cause retinal vascular disease. Long noncoding RNA (lncRNA) is known to be involved in the regulation of many signaling pathways. We hope to understand the specific mechanism of apoptosis in retinal vascular endothelial cells (RVECs) by exploring the regulatory effect of lncRNA on the Notch pathway. In this study, we found that RVECs treated with glucose showed increased levels of Notch transcript and protein expression. The lentiviral interference with Notch RNAi reversed this response. When Notch activity decreased, oxidative stress also decreased, accompanied by increased levels of Caspase-9 and Caspase-3 and an increased rate of apoptosis. Therefore, we believe that Notch is involved in the development of diabetic retinopathy and loss of expression promotes apoptosis of human RVECs. By inhibiting the Notch pathway, lncRNA promotes apoptosis of human RVECs in a high-glucose environment.

Exploring the Risk Factors of Conjunctival Squamous Cell Carcinoma and Establishing a Prognostic Model: Retrospective Study.

Objective: Exploring the risk factors of conjunctival squamous cell carcinoma (CSCC) and establishing a prognostic model. Methods: Information on patients with CSCC was extracted from the SEER database, conducting a retrospective study. 650 patients with CSCC were finally included in the model. Descriptive analysis was performed by Chi-square test and T-test. The risk factors of CSCC were explored by COX multivariate analysis, and the corresponding prognostic model was established as a result. Results: The all-cause mortality rate of CSCC was 38.3%, and the risk factors were age (HR = 1.077), sex (HR = 0.691), grade (HR = 7.857), laterality (HR = 1.403), N (HR = 7.195), M (HR = 0.217), and surgery (HR = 1.618), all P < 0.05. The new model had C index and area under curve ROC (AUC) value greater than 0.7. Calibration curve, Net Reclassification Index (NRI), Integrated Discrimination Improvement (IDI), and Decision Curve Analysis (DCA) indicate the new model has better predictive performance than the American Joint Committee on Cancer (AJCC-TNM). Conclusions: Compared with the clinical guidance of AJCC (TNM) for patients with CSCC, the established model exhibits good performance and can provide guidance for clinical decision-making.