Enhanced effect of ferrous sulfate on nitrogen retention and PBAT degradation during co-composting by combing with biochar-loaded FN1 bacterial composites.

The treatment of biodegradable plastics through composting has garnered increasing attention. This study aimed to investigate the effects of Biochar FN1 bacteria and ferrous sulfate on nitrogen retention, greenhouse gas emissions, and degradable plastics during composting and to elucidate their synergistic mechanisms on microbial communities. Compared with the control, applying biochar-loaded FN1 bacteria composites combined with Ferrous sulfate (SGC) markedly accelerated organic matter degradation and reduced cumulative CO and NH emissions.

Suspended sediment (SPS) triggers nitrogen retention by altering microbial network stability and electron transport behavior during the aerobic-anoxic transition.

NO-N transformation, the vital biological process, determines nitrogen removal and retention in aquatic environment. Suspended sediment (SPS) ubiquitous in freshwater ecosystems can accelerate the transitions from aerobic to anoxic states, inevitably impacting NO-N transformation. To elaborate on the microbial mechanism by which SPS content affected NO-N transformation, we explored nitrogen removal and retention, microbial communities, co-occurrence networks, and electron transfer behavior under different SPS content during the aerobic-anoxic transition.

A clinical pilot trial of an artificial intelligence-driven smart phone application of bowel preparation for colonoscopy: a randomized clinical trial.

Background: High-quality bowel preparation is paramount for a successful colonoscopy. This study aimed to explore the effect of artificial intelligence-driven smartphone software on the quality of bowel preparation.

Methods: Firstly, we utilized 3305 valid liquid dung images collected mobile phones as training data.

An internally validated prognostic nomogram model predicts the stone-free rate following endoscopic combined intrarenal surgery for renal stones.

Background: Here, we aim to develop and validate a viable prognostic nomogram model for predicting a stone-free rate of kidney stones patients based on retrospective cohort analysis.

Methods: This is a retrospective study that obtained a continuous cohort from the databases of two hospitals (General Hospital of Southern Theater Command, and Guangdong Second Provincial General Hospital), including 522 patients with kidney stones who underwent Endoscopic Combined Intrarenal Surgery (ECIRS) from January 2015 to December 2022.The characteristics of the primary cohort between the SF (stone-free) and SR (stone residue) groups were identified using single factor and multivariate logistic regression analyses.