Alleviating depressive-like behavior in DSS-induced colitis mice: Exploring naringin and poncirin from Poncirus trifoliata extracts.

Patients with inflammatory bowel diseases (IBDs), including ulcerative colitis (UC) and Crohn's disease (CD), often have concomitant mental disorders such as depression and anxiety. Therefore, a bidirectional approach involving the gut and brain axes is necessary for the prevention and treatment thereof. In this study, we explored the potential of Poncirus trifoliata extract (PT), traditionally known for its neuroprotective effects against gastrointestinal diseases, as a natural treatment agent for IBD in a dextran sulfate sodium (DSS)-induced colitis model.

Potential Phytotherapy of DSS-Induced Colitis: Ameliorating Reactive Oxygen Species-Mediated Necroptosis and Gut Dysbiosis with a New Bunge Variety-Daehong.

Developing new plant varieties plays a crucial role in competitiveness in the agricultural and food industries and enhancing food security. Daehong (DH) is a new variety of Bunge (CP); however, its physiological functions and potential as a nutraceutical ingredient remain unknown. Here, the efficacy of DH on inflammatory bowel disease (IBD) was investigated using dextran sulfate sodium (DSS)-induced colitis mice, and its relative pharmacological effects were analyzed against CP.

Interpretation of SNP combination effects on schizophrenia etiology based on stepwise deep learning with multi-precision data.

Schizophrenia genome-wide association studies (GWAS) have reported many genomic risk loci, but it is unclear how they affect schizophrenia susceptibility through interactions of multiple SNPs. We propose a stepwise deep learning technique with multi-precision data (SLEM) to explore the SNP combination effects on schizophrenia through intermediate molecular and cellular functions. The SLEM technique utilizes two levels of precision data for learning.

Shared co-expression networks in frontal cortex of the normal aged brain and schizophrenia.

Previous studies on the brain of people with schizophrenia have identified structural changes and gene expression changes, suggesting that brain aging maybe accelerated in people with schizophrenia. To better characterize gene expression profiles in schizophrenia and in the aged population we constructed co-expression networks using RNA-Seq data from frontal cortex. The first data set analysed was from 62 subjects with schizophrenia and 51 unaffected controls ranging in age from 19 to 63 years.

Identification of common coexpression modules based on quantitative network comparison.

Background: Finding common molecular interactions from different samples is essential work to understanding diseases and other biological processes. Coexpression networks and their modules directly reflect sample-specific interactions among genes. Therefore, identification of common coexpression network or modules may reveal the molecular mechanism of complex disease or the relationship between biological processes.