Multi-step validation of a deep learning-based system with visual explanations for optical diagnosis of polyps with advanced features.

Artificial intelligence (AI) has been found to assist in optical differentiation of hyperplastic and adenomatous colorectal polyps. We investigated whether AI can improve the accuracy of endoscopists' optical diagnosis of polyps with advanced features. We introduced our AI system distinguishing polyps with advanced features with more than 0.

Hypoxia and low-glucose environments co-induced HGDILnc1 promote glycolysis and angiogenesis.

Small bowel vascular malformation disease (SBVM) commonly causes obscure gastrointestinal bleeding (OGIB). However, the pathogenetic mechanism and the role of lncRNAs in SBVM remain largely unknown. Here, we found that hypoxia and low-glucose environments co-augment angiogenesis and existed in SBVM.

Influence of early colorectal cancer component on the positive margins after endoscopic resection: a retrospective study.

Background: Endoscopic treatment methods for early colorectal cancer (ECRC) mainly depend on the size and morphology. It is unclear whether different endoscopic resection methods could achieve curative resection for ECRC confined in the mucosa. The study was designed to compare the rate of positive vertical margin (VM) of ECRC with advanced adenomas (AAs) including adenoma > 1 cm, villous adenoma, high-grade intraepithelial neoplasia/dysplasia stratified by different endoscopic resection methods.

Customized Cellulose Fiber Paper Enabled by an Growth of Ultralong Hydroxyapatite Nanowires.

Cellulose fiber (CF) paper is a low-cost, sustainable, and flexible substrate, which has gained increasing interest recently. Before practical usage, the functionalization of the pristine CF paper is indispensable to meet requirements of specific applications. Different from conventional surface modification or physical mixing methods, we report growth of ultralong hydroxyapatite nanowires (HAPNWs) with lengths larger than 10 μm on the CF paper.

Personalized four-category staging for predicting prognosis in patients with small bowel Adenocarcinoma: an international development and validation study.

Background: Log odds of positive lymph nodes (LODDS) classification showed superiority over 8 edition N staging in predicting survival of small bowel adenocarcinoma (SBA) patients. The aim of this study was to develop and validate the Tumor, LODDS, and Metastasis (TLM) staging of SBA.

Methods: Totally 1789 SBA patients from the Surveillance, Epidemiology, and End Results (SEER) database between 1988-2010, 437 patients from SEER database between 2011-2013 and 166 patients from multicenters were categorized into development, validation and test cohort, respectively.