Background: Stroke is a major cause of mortality and long-term disability worldwide. Whether the associations between brain imaging-derived phenotypes (IDPs) and stroke are causal is uncertain. Methods: We performed two-sample bidirectional Mendelian randomization (MR) analyses to explore the causal associations between IDPs and stroke. Summary data of 587 brain IDPs (up to 33,224 individuals) from the UK Biobank and five stroke types (sample size range from 301,663 to 446,696, case number range from 5,386 to 40,585) from the MEGASTROKE consortium were used. Results: Forward MR indicated 14 IDPs belong to projection fibers or association fibers were associated with stroke. For example, higher genetically determined mean diffusivity (MD) in the right external capsule was causally associated with an increased risk of small vessel stroke (IVW OR = 2.76, 95% CI 2.07 to 3.68, P = 5.87 × 10⁻¹²). Reverse MR indicated that genetically determined higher risk of any ischemic stroke was associated with increased isotropic or free water volume fraction (ISOVF) in body of corpus callosum (IVW β = 0.23, 95% CI 0.14 to 0.33, P = 3.22 × 10⁻⁷). This IDP is a commissural fiber and it is not included in the IDPs identified by forward MR. Conclusions: We identified 14 IDPs with statistically significant evidence of causal effects on stroke or stroke subtypes. We also identified potential causal effects of stroke on one IDP of commissural fiber. These findings might guide further work toward identifying preventative strategies at the brain imaging levels.

Background: Clustering the metagenomic contigs into potential genomes is a key step to investigate the functional roles of microbial populations. Existing algorithms have achieved considerable success with simulated or real sequencing datasets. However, accurately classifying contigs from complex metagenomes is still a challenge. Results: We introduced a novel clustering algorithm, MetaDecoder, which can classify metagenomic contigs based on the frequencies of k-mers and coverages. MetaDecoder was built as a two-layer model with the first layer being a GPU-based modified Dirichlet process Gaussian mixture model (DPGMM), which controls the weight of each DPGMM cluster to avoid over-segmentation by dynamically dissolving contigs in small clusters and reassigning them to the remaining clusters. The second layer comprises a semi-supervised k-mer frequency probabilistic model and a modified Gaussian mixture model for modeling the coverage based on single copy marker genes. Benchmarks on simulated and real-world datasets demonstrated that MetaDecoder can be served as a promising approach for effectively clustering metagenomic contigs. Conclusions: In conclusion, we developed the GPU-based MetaDecoder for effectively clustering metagenomic contigs and reconstructing microbial communities from microbial data. Applying MetaDecoder on both simulated and real-world datasets demonstrated that it could generate more complete clusters with lower contamination. Using MetaDecoder, we identified novel high-quality genomes and expanded the existing catalog of bacterial genomes.

Sirtuin 2 (SIRT2) is an NAD+ dependent deacetylase that is the most abundant sirtuin protein in the brain. Accumulating evidence revealed the role of SIRT2 in a wide range of biological processes and age‐related diseases. However, the pivotal mechanism of SIRT2 played in Alzheimer's disease (AD) remains unknown. Here, we report that pharmacological inactivation of SIRT2 has a beneficial effect in AD. The deacetylase inhibitor of SIRT2 rescued the cognitive impairment in amyloid precursor protein/presenilin 1 transgenic mouse (APP/PS1 mouse), and the BACE1 cleavage was weakened to reduce the β‐amyloid (Aβ) production in the hippocampus. Moreover, we firstly identified that Reticulon 4B (RTN4B) played a crucial role between SIRT2/BACE1 regulation in AD. RTN4B, as a deacetylation substrate for SIRT2, the deacetylation by SIRT2 drived the ubiquitination and degradation of RTN4B and then the disturbed RTN4B interacted with and influenced the expression of BACE1. When we overexpressed RTN4B in neurons of the hippocampus in the AD mouse model, the abnormal Aβ accumulation and cognitive impairment were ameliorated, consistent with the results of SIRT2 inhibition in vivo. Moreover, we showed that the regulatory effect of SIRT2 on BACE1 is dependent on RTN4B. When RTN4B was knocked down, the effects of SIRT2 inhibition on the BACE1 level, Aβ pathology, and AD‐liked behaviors were also blocked. Collectively, we provide evidence that SIRT2 may be a potential target for AD; the new found SIRT2/RTN4B/BACE1 pathological pathway is one of the critical mechanisms for the improvement of SIRT2 on AD.

Background: MEIS2 has been identified as one of the key transcription factors in the gene regulatory network in the development and pathogenesis of human cancers. Our study aims to identify the regulatory mechanisms of MEIS2 in hepatocellular carcinoma (HCC), which could be targeted to develop new therapeutic strategies. Methods: The variation of MEIS2 levels were assayed in a cohort of HCC patients. The proliferation, clone-formation, migration, and invasion abilities of HCC cells were measured to analyze the effects of MEIS2C and MEIS2D (MEIS2C/D) knockdown with small hairpin RNAs in vitro and in vivo. Chromatin immunoprecipitation (ChIP) was performed to identify MEIS2 binding site. Immunoprecipitation and immunofluorescence assays were employed to detect proteins regulated by MEIS2. Results: The expression of MEIS2C/D was increased in the HCC specimens when compared with the adjacent noncancerous liver (ANL) tissues. Moreover, MEIS2C/D expression negatively correlated with the prognosis of HCC patients. On the other hand, knockdown of MEIS2C/D could inhibit proliferation and diminish migration and invasion of hepatoma cells in vitro and in vivo. Mechanistically, MESI2C activated Wnt/β-catenin pathway in cooperation with Parafibromin (CDC73), while MEIS2D suppressed Hippo pathway by promoting YAP nuclear translocation via miR-1307-3p/LATS1 axis. Notably, CDC73 could directly either interact with MEIS2C/β-catenin or MEIS2D/YAP complex, depending on its tyrosine-phosphorylation status. Conclusions: Our studies indicate that MEISC/D promote HCC development via Wnt/β-catenin and Hippo/YAP signaling pathways, highlighting the complex molecular network of MEIS2C/D in HCC pathogenesis. These results suggest that MEISC/D may serve as a potential novel therapeutic target for HCC.