Identification of N-phenyl-N-(quinolin-4-yl) amino carboxylic acids as URAT1 inhibitors with hypouricemic effects.

Urate transporter 1 (URAT1) is a therapeutic target for the treatment of hyperuricemia and gout. However, the application of currently marketed URAT1 inhibitors is hampered by insufficient efficacy and poor safety profiles. A series of N-phenyl-N-(quinolin-4-yl) amino carboxylic acids were designed by adopting strategies of molecular hybridization, scaffold hopping, and functional variation.

Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications.

Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing.

A System for Discovering Novel Uricosurics Targeting Urate Transporter 1 Based on In Vitro and In Vivo Modeling.

Hyperuricemia has become a global burden with the increasing prevalence and risk of associated metabolic disorders and cardiovascular diseases. Uricosurics act as a vital urate-lowering therapy by promoting uric acid excretion via the kidneys. However, potent and safe uricosurics are still in urgent demand for use in the clinic.

Prediction of genome-wide imipenem resistance features in using machine learning.

The resistance rate of () to imipenem is increasing year by year, and the imipenem resistance mechanism of is complex. Therefore, it is urgent to develop new strategies to explore the resistance mechanism of imipenem for its effective and accurate use in clinical practice. Machine learning could identify resistance features and biological process that influence microbial resistance from whole-genome sequencing (WGS) data.

Pdif-mediated antibiotic resistance genes transfer in bacteria identified by pdifFinder.

Modules consisting of antibiotic resistance genes (ARGs) flanked by inverted repeat Xer-specific recombination sites were thought to be mobile genetic elements that promote horizontal transmission. Less frequently, the presence of mobile modules in plasmids, which facilitate a pdif-mediated ARGs transfer, has been reported. Here, numerous ARGs and toxin-antitoxin genes have been found in pdif site pairs.

Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.

, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of is increasing year by year, posing a severe threat to public health worldwide. has been listed as one of the pathogens causing the global crisis of antimicrobial resistance in nosocomial infections.