Discovery of acetohydroxyacid synthase inhibitors as anti-tuberculosis lead compounds from natural products.

Acetohydroxy acid synthase (AHAS) is a key enzyme that catalyzes the synthesis of branched-chain amino acids, which is indispensable for the survival and growth of Mycobacterium tuberculosis (Mtb). Aim to discover new AHAS inhibitors from natural products, here we performed computer assistant target-based screening for Mtb-AHAS inhibitors using Discovery Studio on TCMSP and SELLECK libraries. Mtb-AHAS structure was first simulated and verified for docking, and 80 compounds with top LIBDOCK and CDDOCK scores were obtained.

Identifying prioritization of therapeutic targets for ankylosing spondylitis: a multi-omics Mendelian randomization study.

Background: To investigate the associations of methylation, expression, and protein quantitative trait loci (mQTL, eQTL, and pQTL) with ankylosing spondylitis (AS) and find out genetically supported drug targets for AS.

Methods: The summary-data-based Mendelian randomization (SMR) and Bayesian co-localization analysis were used to assess the potential causality between AS and relevant genes. The GWAS data obtained from the International Genetics of Ankylosing Spondylitis Consortium (IGAS) were set as the discovery stage, and the FinnGen and UK Biobank databases were used to replicate the analysis as an external validation.

Pathway plaques and diffusion-weighted lesion analysis after endovascular treatment of unruptured intracranial aneurysms: a prospective study.

Objectives: To evaluate the prevalence and predictors of ischemic lesions on thin-slice DWI (2 mm) in endovascular treatments for unruptured intracranial aneurysms (UIA), particularly explore the potential relationship with pathway plaques.

Methods: Participants eligible for endovascular treatments with UIA at a national stroke center between March 2023 and August 2023 were prospectively enrolled. All participants performed thin-slice DWI (slice thickness of 2 mm) before and after procedures.

Top-Down Computational Design of Molecule Recognition Peptides (MRPs) for Enzyme-Peptide Self-Assembly and Chemiluminescent Biosensing.

The recognition of small molecules plays a crucial role in disease diagnosis, environmental assessment, and food safety. Currently, their recognition elements predominantly rely on antibodies and aptamers while suffering from a limitation of the complex screening process due to the low immunogenicity of small molecules. Herein, we present a top-down computational design strategy for molecule recognition peptides (MRPs) for enzyme-peptide self-assembly and chemiluminescence biosensing.

Heavy metal contamination of vegetables in China: status, causes, and impacts.

Exposure to heavy metals from vegetable consumption poses a serious health risk to the Chinese population. The lack of knowledge on the overall status of vegetable contamination at the national level hinders the development of national regulations on preventing heavy metal exposure. To address this issue, the study presents an overview of heavy metal contamination in vegetables across China based on 96 peer-reviewed studies published over the past 20 years.