Interpretable Machine Learning Model to Predict Bone Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fracture Based on SHapley Additive exPlanations.

Study Design: Retrospective study.

Objectives: Our objective is to create comprehensible machine learning (ML) models that can forecast bone cement leakage in percutaneous vertebral augmentation (PVA) for individuals with osteoporotic vertebral compression fracture (OVCF) while also identifying the associated risk factors.

Methods: We incorporated data from patients (n = 425) which underwent PVA.

Germanicol induces selective growth inhibitory effects in human colon HCT-116 and HT29 cancer cells through induction of apoptosis, cell cycle arrest and inhibition of cell migration.

Purpose: The main aim of this research was to evaluate the anticancer and apoptotic effects of germanicol - a natural triterpene - in HCT-116 and HT29 human colon cancer cells and deciphering its mode of action by studying its effect on the cell cycle and cell migration.

Methods: Cell cytotoxicity was evaluated by MTT assay, while cell death was assessed by LDH assay. Fluorescence microscopy, using DAPI and acridine orange/ethidium bromide (AO-ETBR), was carried out to evaluate the effect of germanicol on cellular morphology and apoptosis induction.

Simultaneous operative treatment of patients with primary liver cancer associated with portal hypertension.

Objective: To explore the operative procedure for patients with primary liver cancer associated with portal hyper tension (PLCPH).

Methods: We analyzed retrospectively the effect of operative procedure for 9 patients with PLCPH complicated by severe esophageal varicosity and hypersplenism.

Results: All patients underwent liver resection and pericardiac devascularization with splenectomy.