Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

Microbiome-Metabolome Analysis of the Immune Microenvironment of the Cecal Contents, Soft Feces, and Hard Feces of Hyplus Rabbits

The intestinal microbiota and its metabolites play vital roles in host growth, development, and immune regulation. This study analyzed the microbial community distribution and the cytokine and short-chain fatty acid (SCFA) content of cecal contents (Con group), soft feces (SF group), and hard feces (HF group) of 60-day-old Hyplus rabbits and verified the effect of soft feces on the cecal immune microenvironment by coprophagy prevention (CP). The results showed that there were significant differences in the levels of phylum and genus composition, cytokines, and SCFAs among the Con group, SF group, and HF group. The correlation analysis of cytokines and SCFAs with differential microbial communities showed that Muribaculaceae, Ruminococcaceae_UCG-014, Ruminococcaceae_NK4A214_group, and Christensenellaceae_R-7_Group are closely related to cytokines and SCFAs. After CP treatment, the contents of propionic acid, butyric acid, IL-4, and IL-10 in cecum decreased significantly, whereas TNF-α and IL-1β increased significantly. Moreover, the inhibition of coprophagy led to the downregulation of the expression levels of tight junction proteins (Claudin-1, Occludin, and ZO-1) related to intestinal inflammation and intestinal barrier function, and the ring-like structure of ZO-1 was disrupted. In conclusion, coprophagy can not only help rabbits obtain more probiotics and SCFAs but also play an essential role in improving the immune microenvironment of cecum.

Clinical Attributes and Electroencephalogram Analysis of Patients With Varying Alpers' Syndrome Genotypes

Alpers' syndrome is an early inceptive neurodegenerative disorder with a poor prognosis, characterized by developmental regression, intractable epilepsy, and hepatic dysfunction. Candidate genes, such as POLG, PARS2, CARS2, FARS2, NARS2, and GABRB2 are distinguished and registered following research on large cohorts that portray the clinical phenotype in such patients using expanded access to whole-exome sequencing (WES). In this study, we aimed to better understand the electroencephalogram (EEG) characteristics and clinical phenotype of different genotypes of the Alpers' syndrome, which are currently insufficiently studied. We conducted a study on seven patients with Alpers' syndrome who received treatment in Beijing Children's Hospital and had a detailed clinical EEG. Furthermore, a substantial literature search of the Chinese Biomedical Literature Database, PubMed, and Cochrane Central Register of Controlled Trials EMBASE was also conducted, which revealed a total of 22 reported cases between January 2008 to January 2021. We analyzed 29 cases of Alpers' syndrome caused by different gene variants, of which 22 cases were related to POLG gene mutation and 7 cases were related to PARS2, CARS2, FARS2, NARS2, and GABRB2 gene mutation, and found that patients with distinctive pathogenic variants exhibited comparable phenotypes and similar EEG patterns. And we defined EEG characteristics found specifically in Alpers' syndrome. Rhythmic high-amplitude delta with superimposed (poly) spikes (RHADS) is a characteristic EEG finding in the early stages of Alpers' syndrome and is a kind of epileptic phenomenon, which can provide clues for the early diagnosis of the disease.

Basic research in childhood cancer: Progress and future directions in China

Childhood cancer is a leading cause of death in children. Some childhood cancers have a particularly high mortality rate. Following the World Health Organization's emphasis on child health, most governments worldwide have taken measures to facilitate childhood cancer research. Thus, the scientific community is showing increasing interest in this area. Chinese government has prominence in building a system for the diagnosis and treatment of childhood cancer, thereby promoting the development of childhood cancer research. This review summarizes the research progress, challenges, and perspectives in childhood cancer, and the increasing contributions of National Natural Science Foundation of China (NSFC) in the past decade (2008-2018).

DNMIVD: DNA methylation interactive visualization database

Aberrant DNA methylation plays an important role in cancer progression. However, no resource has been available that comprehensively provides DNA methylation-based diagnostic and prognostic models, expression–methylation quantitative trait loci (emQTL), pathway activity-methylation quantitative trait loci (pathway-meQTL), differentially variable and differentially methylated CpGs, and survival analysis, as well as functional epigenetic modules for different cancers. These provide valuable information for researchers to explore DNA methylation profiles from different aspects in cancer. To this end, we constructed a user-friendly database named DNA Methylation Interactive Visualization Database (DNMIVD), which comprehensively provides the following important resources: (i) diagnostic and prognostic models based on DNA methylation for multiple cancer types of The Cancer Genome Atlas (TCGA); (ii) meQTL, emQTL and pathway-meQTL for diverse cancers; (iii) Functional Epigenetic Modules (FEM) constructed from Protein-Protein Interactions (PPI) and Co-Occurrence and Mutual Exclusive (COME) network by integrating DNA methylation and gene expression data of TCGA cancers; (iv) differentially variable and differentially methylated CpGs and differentially methylated genes as well as related enhancer information; (v) correlations between methylation of gene promoter and corresponding gene expression and (vi) patient survival-associated CpGs and genes with different endpoints. DNMIVD is freely available at http://www.unimd.org/dnmivd/. We believe that DNMIVD can facilitate research of diverse cancers.

Sequencing barcode construction and identification methods based on block error-correction codes

Multiplexed sequencing relies on specific sample labels, the barcodes, to tag DNA fragments belonging to different samples and to separate the output of the sequencers. However, the barcodes are often corrupted by insertion, deletion and substitution errors introduced during sequencing, which may lead to sample misassignment. In this paper, we propose a barcode construction method, which combines a block error-correction code with a predetermined pseudorandom sequence to generate a base sequence for labeling different samples. Furthermore, to identify the corrupted barcodes for assigning reads to their respective samples, we present a soft decision identification method that consists of inner decoding and outer decoding. The inner decoder establishes the hidden Markov model (HMM) for base insertion/deletion estimation with the pseudorandom sequence, and adapts the forward-backward (FB) algorithm to output the soft information of each bit in the block code. The outer decoder performs soft decision decoding using the soft information to effectively correct multiple errors in the barcodes. Simulation results show that the proposed methods are highly robust to high error rates of insertions, deletions and substitutions in the barcodes. In addition, compared with the inner decoding algorithm of the barcodes based on watermarks, the proposed inner decoding algorithm can greatly reduce the decoding complexity.