From Monocyclization to Pentacyclization: A Versatile Plant Cyclase Produces Diverse Sesterterpenes with Anti-Liver Fibrosis Potential.

A prolific multi-product sesterterpene synthase CbTPS1 is characterized from the medicinal Brassicaceae plant Capsella bursa-pastoris. Twenty different sesterterpenes including 16 undescribed compounds, possessing 10 different mono-/di-/tri-/tetra-/penta-carbocyclic skeletons, including the unique 15-membered macrocyclic and 24(15→14)-abeo-capbuane scaffolds, are isolated and structurally elucidated from engineered Escherichia coli strains expressing CbTPS1. Site-directed mutagenesis assisted by molecular dynamics simulations resulted in the variant L354M with up to 13.

The Role of Long-Range Interactions Between High-Entropy Single-Atoms in Catalyzing Sulfur Conversion Reactions.

Sulfur conversion reactions are the foundation of lithium-sulfur batteries but usually possess sluggish kinetics during practical battery operation. Herein, a high-entropy single-atom catalyst (HESAC) is synthesized for this process. In contrast to conventional dual-atom catalysts that form metal-metal bonds, the center metal atoms in HESAC are not bonded but exhibit long-range interactions at a sub-nanometer distance (<9 Å).

Spin Canting Promoted Manipulation of Exchange Bias in a Perpendicular Coupled FeGaTe/CrSBr Magnetic van der Waals Heterostructure.

Recently, two-dimensional (2D) van der Waals (vdW) magnetic materials have emerged as a promising platform for studying exchange bias (EB) phenomena due to their atomically flat surfaces and highly versatile stacking configurations. Although complex spin configurations between 2D vdW interfaces introduce challenges in understanding their underlying mechanisms, they can offer more possibilities in realizing effective manipulations. In this study, we present a spin-orthogonal arranged 2D FeGaTe (FGaT)/CrSBr vdW heterostructure, realizing the EB effect with the bias field as large as 1730 Oe at 2 K.

LOGOWheat: deep learning-based prediction of regulatory effects for noncoding variants in wheats.

Identifying the regulatory effects of noncoding variants presents a significant challenge. Recently, the accumulation of epigenomic profiling data in wheat has provided an opportunity to model the functional impacts of these variants. In this study, we introduce Language of Genome for Wheat (LOGOWheat), a deep learning-based tool designed to predict the regulatory effects of noncoding variants in wheat.

Exploring the relationship between MGAT2 and glioblastoma: A Mendelian Randomization and bioinformatics approach.

Background: Mannosyl-glycoprotein beta-1,2-N-acetylglucosaminyltransferase 2 (MGAT2) and tumors' relevant research was in full swing recently. Therefore, we employed Mendelian Randomization (MR) alongside bioinformatics to thoroughly investigate the possible relationship between MGAT2 and glioblastoma (GBM).

Methods: We utilized the summary statistics of genome-wide association studies (GWAS) for MGAT2 (N = 35,559 from deCODE) and glioblastoma (N = 379,155 from FinnGen).