The trade-off between the performances of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) presents a challenge in designing high-performance aqueous rechargeable zinc-air batteries (a-r-ZABs) due to sluggish kinetics and differing reaction requirements. Accurate control of the atomic and electronic structures is crucial for the rational design of efficient bifunctional oxygen electrocatalysts. Herein, we designed a Sn-Co/RuO trimetallic oxide utilizing dual-active sites and tin (Sn) regulation strategy by dispersing Co (for ORR) and auxiliary Sn into the near-surface and surface of RuO (for OER) to enhance both ORR and OER performances.
View Article and Find Full Text PDFA high-throughput sequencing identified 1283 lncRNAs in anthers at different stages in Arabidopsis and their relationship with protein-coding genes and miRNAs during anther and pollen development were analyzed. Long non-coding RNAs (lncRNAs) are important regulatory molecules involved in various biological processes. However, their roles in male reproductive development and interactions with miRNAs remained elusive.
View Article and Find Full Text PDFIschemia-reperfusion injury (IRI) is a major obstacle in liver transplantation, especially with steatotic donor livers. Dysbiosis of the gut microbiota has been implicated in modulating IRI, and plays a pivotal role in regulating host inflammatory and immune responses, but its specific role in liver transplantation IRI remains unclear. This study explores whether can mitigate IRI and its underlying mechanisms.
View Article and Find Full Text PDFDespite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in the complex protein environment, while machine learning (ML) is hampered by the scarcity of experimental data. Here, we report the development of p ML (KaML) models based on decision trees and graph attention networks (GAT), exploiting physicochemical understanding and a new experiment p database (PKAD-3) enriched with highly shifted p's.
View Article and Find Full Text PDFBackground: Anti-signal recognition particle immune-mediated necrotizing myopathy (anti-SRP IMNM) is a rare autoimmune disorder characterized by muscle weakness and necrosis. Identifying clinical subgroups within this patient population could facilitate the management of the disease.
Objectives: To identify distinct clinical subgroups of anti-SRP IMNM patients.