Interpretable machine learning model for predicting clinically significant prostate cancer: integrating intratumoral and peritumoral radiomics with clinical and metabolic features.

Background: To develop and validate an interpretable machine learning model based on intratumoral and peritumoral radiomics combined with clinicoradiological features and metabolic information from magnetic resonance spectroscopy (MRS), to predict clinically significant prostate cancer (csPCa, Gleason score ≥ 3 + 4) and avoid unnecessary biopsies.

Methods: This study retrospectively analyzed 350 patients with suspicious prostate lesions from our institution who underwent 3.0 Tesla multiparametric magnetic resonance imaging (mpMRI) prior to biopsy (training set, n = 191, testing set, n = 83, and a temporal validation set, n = 76).

Disulfide bonds-driven assembly and structural complexity of PTX3: High-resolution structures insights into multimeric architecture.

Pentraxin-3 (PTX3) is a multifunctional pattern-recognition molecule that is essential for immune defense, pathogen recognition, and complement activation. PTX3 is stored as a monomer in neutrophil granules, and assembles into higher-order oligomers upon immune activation, thereby enhancing its antimicrobial function. The mechanism underlying this assembly remains elusive.

The optimal labelling method for artificial intelligence-assisted polyp detection in colonoscopy.

Background: The methodology in colon polyp labeling in establishing database for ma-chine learning is not well-described and standardized. We aimed to find out the best annotation method to generate the most accurate model in polyp detection.

Methods: 3542 colonoscopy polyp images were obtained from endoscopy database of a tertiary medical center.

The impact of virtual reality applied in nurse education on students' clinical thinking: A systematic review.

Objective: To summarise and compare the applications and effectiveness of virtual reality in cultivating clinical thinking among nursing students and to further analyse the active ingredients of virtual reality applications.

Design: Systematic review.

Review Methods: A systematic and comprehensive search of PubMed, Web of Science, Cochrane, Scopus, Embase, and CINAHL was conducted from the inception until 5th of February 2024.

Dietary Supplementation with Multi-strain Probiotic Formulation (Bifidobacterium B8101, Lactobacillus L8603, Saccharomyces bayanus S9308, and Enterococcus SF9301), Betaine or their Combination Promotes Growth Performance Via Improving Intestinal Development in Broilers.

This study aimed to investigate the effect of a multi-strain probiotic (Bifidobacterium B8101, Lactobacillus L8603, Saccharomyces bayanus S9308, Enterococcus SF9301), betaine, and their combination on intestinal epithelial development and growth performance in broilers. A total of 2800 one-day-old Ross 308 chickens were randomly divided into four groups: control (Ctrl) fed with a basal diet, multi-strain probiotic (Pb) group fed with basal diet + 100 mg/day/bird probiotic (1-14 d), betaine (Bet) fed with basal diet + 0.1% betaine (1-35 d), and a combination (Pb&Bet) fed with both probiotics and betaine.