Deep Learning Radiomics Nomogram Based on MRI for Differentiating between Borderline Ovarian Tumors and Stage I Ovarian Cancer: A Multicenter Study.

Rationale And Objectives: To develop and validate a deep learning radiomics nomogram (DLRN) based on T2-weighted MRI to distinguish between borderline ovarian tumors (BOTs) and stage I epithelial ovarian cancer (EOC) preoperatively.

Materials And Methods: This retrospective multicenter study enrolled 279 patients from three centers, divided into a training set (n = 207) and an external test set (n = 72). The intra- and peritumoral radiomics analysis was employed to develop a combined radiomics model.

A Randomized Comparison of Bioheart Sirolimus-Eluting Bioresorbable Scaffold and Everolimus-Eluting Stents: The BIOHEART-II Trial.

Background: First-generation bioresorbable scaffolds (BRS) increased risks of stent thrombosis and adverse events. The Bioheart scaffold is a new poly-L-lactic acid-based BRS.

Objectives: This study sought to evaluate the efficacy and safety of the BRS in patients with coronary artery disease.

Screening, Discovery, and Optimization of the Natural Antitubercular Chlorflavonin from a Marine-Derived Fungal Library.

Tuberculosis (TB), caused by the bacterium (), is still a leading cause of mortality worldwide. Fifty-fungi from a marine-derived fungal library were screened for anti- activity, and an strain with strong anti- activity was found. Three known flavones, chlorflavonin (), dechlorflavonin (), and bromoflavone (), were isolated from this fungus.

Causal relationships between uremic metabolites or toxins and heart failure: Univariate and multivariate Mendelian randomization.

Studies have shown that uremia, renal failure and heart failure (HF) are closely related. However, whether this association reflects a causal effect is still unclear. The aim of this study was to evaluate the causal effect of uremic metabolites or toxins on HF.