Unveiling the role of microRNAs in nonhost resistance to Sclerotinia sclerotiorum: Rice-specific microRNAs attack the pathogen via cross-kingdom RNAi.

The development of rapeseed with high resistance against the pathogen Sclerotinia sclerotiorum is impeded by the lack of effective resistance resources within host species. Unraveling the molecular basis of nonhost resistance (NHR) holds substantial value for resistance improvement in crops. In the present study, small RNA sequencing and transcriptome sequencing were carried out between rice (a nonhost species of S.

Near-Infrared Fluorescent Probe for Simultaneously Imaging Ferrous Ions and Viscosity in a Mouse Model of Hepatocellular Carcinoma.

Abnormal ferrous ion (Fe) levels lead to an increase in reactive oxygen species (ROS) in cells, disrupting intracellular viscosity and the occurrence of hepatocellular carcinoma (HCC). Simultaneously visualizing Fe and intracellular viscosity is essential for understanding the detailed pathophysiological processes of HCC. Herein, we report the first dual-responsive probe, , capable of simultaneously monitoring Fe and viscosity.

Structural and functional alterations in the brain gray matter among Tourette syndrome patients: a multimodal meta-analysis of fMRI and VBM studies.

Background: Tourette syndrome (TS) is a prevalent neurodevelopmental disorder with an uncertain etiology. Numerous neuroimaging studies have investigated patients with TS, but their conclusions remain inconsistent. The current study attempted to provide an unbiased statistical meta-analysis of published neuroimaging studies of TS.

Clair3-RNA: A deep learning-based small variant caller for long-read RNA sequencing data.

Variant calling using long-read RNA sequencing (lrRNA-seq) can be applied to diverse tasks, such as capturing full-length isoforms and gene expression profiling. It poses challenges, however, due to higher error rates than DNA data, the complexities of transcript diversity, RNA editing events, etc. In this paper, we propose Clair3-RNA, the first deep learning-based variant caller tailored for lrRNA-seq data.