Biomedical subjects

Bin Ni

Publications and source records attributed to Bin Ni.

3 recordsLinked to original sources

PubMed2026

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds↗

PubMed2025

Characterization of gut microbiota and metabolites in renal transplant recipients during COVID-19 and prediction of one-year allograft function.

BACKGROUND: The gut-lung-kidney axis is pivotal in immune-related kidney diseases, with gut dysbiosis potentially exacerbating the severity of Coronavirus disease 2019 (COVID-19) in recipients of kidney transplant. This study aimed to characterize the gut microbiome and metabolome in renal transplant recipients with COVID-19 pneumonia over a one-year follow-up period. METHODS: A total of 30 renal transplant recipients were enrolled, comprising 17 with COVID-19 pneumonia, six with mild COVID-19, and seven without COVID-19. Fecal samples were collected at the onset of infection for gut microbiome and metabolome analysis. Generalized Estimating Equations (GEE) model and Latent Class Growth Mixed Model (LCGMM) were employed to dissect the relationships among clinical characteristics, laboratory tests, and gut microbiota and metabolites. RESULTS: Four microbial phyla (Deferribacteres, TM7, Fusobacteria, and Gemmatimonadetes) and 13 genera were significantly enriched across three recipients groups, correlating with baseline inflammatory response and allograft function. Additionally, 52 differentially expressed metabolites were identified, with seven significantly correlating with eight altered microbiota genera. LCGMM revealed two distinct classes of recipients, with those suffering from COVID-19 pneumonia exhibiting significantly elevated serum creatinine (Scr) trajectories over the one-year period. GEE further identified 12 genera and 181 metabolites closely associated with these trajectories; a multivariable model incorporating gut metabolites of 1-Caffeoylquinic Acid and PMK was found to effectively predict one-year allograft function. CONCLUSIONS: Our study indicates a possible interaction between the composition of the gut microbiota and metabolites community and COVID-19 in renal transplant recipients, particularly in relation to disease severity and the prediction of one-year allograft function.

Humans↗

PubMed2024

Whole exome sequencing analysis of 167 men with primary infertility.

BACKGROUND: Spermatogenic failure is one of the leading causes of male infertility and its genetic etiology has not yet been fully understood. METHODS: The study screened a cohort of patients (n = 167) with primary male infertility in contrast to 210 normally fertile men using whole exome sequencing (WES). The expression analysis of the candidate genes based on public single cell sequencing data was performed using the R language Seurat package. RESULTS: No pathogenic copy number variations (CNVs) related to male infertility were identified using the the GATK-gCNV tool. Accordingly, variants of 17 known causative (five X-linked and twelve autosomal) genes, including ACTRT1, ADAD2, AR, BCORL1, CFAP47, CFAP54, DNAH17, DNAH6, DNAH7, DNAH8, DNAH9, FSIP2, MSH4, SLC9C1, TDRD9, TTC21A, and WNK3, were identified in 23 patients. Variants of 12 candidate (seven X-linked and five autosomal) genes were identified, among which CHTF18, DDB1, DNAH12, FANCB, GALNT3, OPHN1, SCML2, UPF3A, and ZMYM3 had altered fertility and semen characteristics in previously described knockout mouse models, whereas MAGEC1,RBMXL3, and ZNF185 were recurrently detected in patients with male factor infertility. The human testis single cell-sequencing database reveals that CHTF18, DDB1 and MAGEC1 are preferentially expressed in spermatogonial stem cells. DNAH12 and GALNT3 are found primarily in spermatocytes and early spermatids. UPF3A is present at a high level throughout spermatogenesis except in elongating spermatids. The testicular expression profiles of these candidate genes underlie their potential roles in spermatogenesis and the pathogenesis of male infertility. CONCLUSION: WES is an effective tool in the genetic diagnosis of primary male infertility. Our findings provide useful information on precise treatment, genetic counseling, and birth defect prevention for male factor infertility.

Humans↗