Computed tomography and guidelines-based human-machine fusion model for predicting resectability of the pancreatic cancer.

Background And Aim: The study aims to develop a hybrid machine learning model for predicting resectability of the pancreatic cancer, which is based on computed tomography (CT) and National Comprehensive Cancer Network (NCCN) guidelines.

Method: We retrospectively studied 349 patients. One hundred seventy-one cases from Center 1 and 92 cases from Center 2 were used as the primary training cohort, and 66 cases from Center 3 and 20 cases from Center 4 were used as the independent test dataset.

A simple and efficient strategy for cell-based and cell-free-based therapies in acute liver failure: hUCMSCs bioartificial liver.

Acute liver failure (ALF) is a life-threatening condition. Cell-based and cell-free-based therapies have proven to be effective in treating ALF; however, their clinical application is limited by cell tumorigenicity and extracellular vesicle (EV) isolation in large doses. Here, we explored the effectiveness and mechanism of umbilical cord mesenchymal stem cells (hUCMSCs)-based bioartificial liver (hUCMSC-BAL), which is a simple and efficient strategy for ALF.