Machine learning-based risk assessment for cardiovascular diseases in patients with chronic lung diseases.

The association between chronic lung diseases (CLDs) and the risk of cardiovascular diseases (CVDs) has been extensively recognized. Nevertheless, conventional approaches for CVD risk evaluation cannot fully capture the risk factors (RFs) related to CLDs. This research sought to construct a CLD-specific CVD risk prediction model based on machine learning models and evaluate the prediction performance.

TROP2 overexpression promotes proliferation and invasion of lung adenocarcinoma cells.

Recent studies suggest that the human trophoblast cell-surface antigen TROP2 is highly expressed in a number of tumours and is correlated with poor prognosis. However, its role in non-small cell lung carcinoma (NSCLC) remains largely unknown. Here we examined TROP2 expression by immunohistochemistry in a series of 68 patients with adenocarcinoma (ADC).