Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [F]PSMA-1007 PET/CT and multiparametric MRI.

Purpose: Accurate prediction of adverse pathology (AP) in prostate cancer (PCa) patients is crucial for formulating effective treatment strategies. This study aims to develop and evaluate a multimodal deep learning model based on [F]PSMA-1007 PET/CT and multiparametric MRI (mpMRI) to predict the presence of AP, and investigate whether the model that integrates [F]PSMA-1007 PET/CT and mpMRI outperforms the individual PET/CT or mpMRI models in predicting AP.

Methods: 341 PCa patients who underwent radical prostatectomy (RP) with mpMRI and PET/CT scans were retrospectively analyzed.

Probiotics and reshape the intestinal microbiota of Pengze crucian carp ( var. Pengze) fed with high plant protein diets.

The intestinal dysfunction induced by high plant protein diets is frequently observed in farmed fish, and probiotics of genus were documented to benefit the intestinal health through the modulation of intestinal microbiota without clearness in its underlying mechanism yet. Fusobacteria, Proteobacteria, and Firmicutes were observed to be the dominate phyla, but their proportion differentiated in the intestinal bacterial community of Pengze crucian carp ( var. Pengze) fed different diets in this study.