The microbiome compositional and functional differences between rectal mucosa and feces.

In recent years, most studies on the gut microbiome have primarily focused on feces samples, leaving the microbial communities in the intestinal mucosa relatively unexplored. To address this gap, our study employed shotgun metagenomics to analyze the microbial compositions in normal rectal mucosa and matched feces from 20 patients with colonic polyps. Our findings revealed a pronounced distinction of the microbial communities between these two sample sets. Compared with feces, the mucosal microbiome contains fewer genera, with Burkholderia being the most discriminating genus between feces and mucosa, highlighting its significant influence on the mucosa. Furthermore, based on the microbial classification and KEGG Orthology (KO) annotation results, we explored the association between rectal mucosal microbiota and factors such as age, gender, BMI, and polyp risk level. Notably, we identified novel biomarkers for these phenotypes, such as Clostridium ramosum and Enterobacter cloacae in age. The mucosal microbiota showed an enrichment of KO pathways related to sugar transport and short chain fatty acid metabolism. Our comprehensive approach not only bridges the knowledge gap regarding the microbial community in the rectal mucosa but also underscores the complexity and specificity of microbial interactions within the human gut, particularly in the Chinese population. IMPORTANCE: This study presents a system-level map of the differences between feces and rectal mucosal microbial communities in samples with colorectal cancer risk. It reveals the unique microecological characteristics of rectal mucosa and its potential influence on health. Additionally, it provides novel insights into the role of the gut microbiome in the pathogenesis of colorectal cancer and paves the way for the development of new prevention and treatment strategies.

Identification of lymph node adulteration in minced pork by comprehensive metabolomics and lipidomics approach based on UPLC/LTQ-Orbitrap MS.

The deliberate pork adulteration with lymph nodes is a common adulteration phenomenon, and it poses a serious threat to public health and food safety. An untargeted metabolomics and lipidomics approach based on ultrahigh performance liquid chromatography coupled with linear ion trap quadrupole-Orbitrap high resolution mass spectrometry (MS) was used to distinguish lymph nodes from minced pork. The principal component analysis and orthogonal projection to latent structures discriminant analysis models were established with the good of fitness and predictivity. The results showed that there were significant differences in metabolites and lipids between lymph nodes and pork. A total of 16 significantly differentiated metabolites were identified, of which 1-palmitoylglycerophosphocholine, 12,13-dihydroxy-9-octadecenoic acid, and prostaglandin E2 (PGE2) were positively correlated with lymph node content and were identified as potential markers of lymph nodes. These three markers were combined to create a binary logistic regression model, and a combined-factor exceeding 0.75 was ultimately identified as a marker for pork adulteration with lymph nodes. The desorption electrospray ionization-MS images showed that PGE2 had a higher relative abundance in the lymph node region than in adjacent non-lymph node regions, indicating that PGE2 was a marker that contributed significantly for identifying lymph nodes adulteration into pork. Our results provide a theoretical basis for identifying lymph node adulteration, which will contribute to combating fraud in the meat industry.

Differential Markers of Subpopulations of Epithelial Cells of the Larynx in Squamous Cell Carcinoma.

In squamous cell carcinoma of the larynx, the population of epithelial cells in the tumor tissue is initially heterogeneous and, in addition to tumor cells invading the organ mucosa, includes normal epithelial cells of protein-mucous glands and cells of the stratified epithelium covering the mucous membrane. A search for differential markers to separate these subpopulations was carried out. The surface marker CD44 and cytokeratins 5 and 17 that are often used to verify carcinoma cells, are common markers for all epithelial cells of the larynx. In highly differentiated carcinoma, subpopulations of normal and tumor epithelial cells can be separated by the level of expression of cytokeratins 10 and 18 and nuclear markers Ki-67 and p63. However, in moderately differentiated carcinoma, tumor cells and normal cells of the basal layer of the stratified epithelium covering the mucous membrane of the larynx have similar phenotypes, which should be taken into account when conducting experimental studies.

Content determination and chemical pattern recognition analysis of Biantong capsules / 中国药房

OBJECTIVE To establish the method for simultaneous determination of 11 components as narirutin in Biantong capsules，to conduct chemical pattern recognition analysis and to screen differential markers affecting their quality . METHODS HPLC method was adopted . The separation was carried out on Venusil XBP C 18 column with mobile phase consisted of acetonitrile - 0.1％ phosphoric acid solution with gradient elution at flow rate of 1.0 mL/min. The sample size was 10 µL，and column temperature was set at 30 ℃. The detection wavelengths were set at 283，330，520，220 nm，respectively. Using verbascoside as an internal standard ，the contents were determined by quantitative analysis of mult -components by single marker （QAMS），and the results were compared with those of external standard method . Cluster analysis ，principle component analysis and orthogonal partial least squares -discriminant analysis were performed with SPSS 26.0 and SIMCA 14.1 software. The differential markers affecting the quality of Biantong capsules were screened using the variable importance in projection （VIP）value greater than 1 as the standard . RESULTS The contents of narirutin ，naringin，neohesperidin，echinacoside，tubuloside A ，isoacteoside，cyanidin-3-O-glucoside， cyanidin-3-O-rutoside，atractylolide Ⅲand atractylolide Ⅰ were 0.739-1.265，1.134-2.158，1.407-2.359，1.368-2.502，0.304-0.522， 0.257-0.521，0.423-0.727，0.375-0.733，0.130-0.283 and 0.062-0.166 mg/g，respectively. The relative average deviation of them from the external standard method was less than 2％. The results of cluster analysis showed that 15 batches of samples could be grouped into three categories ，S1-S7 as a category ，S8-S10 as a category ，and S 11-S15 as a category ，which was consistent with the classification results of principal component analysis . The results of orthogonal partial least squares -discriminant analysis showed that the VIP values of cyanidin -3-O-rutoside，atractylolide Ⅲ， naringin，neohesperidin，echinacoside and verbascoside were all greater than 1. CONCLUSIONS The method for simultaneous determination of 11 components in Biantongcapsules， including narirutin ， is successfully established . Combined with chemical pattern recognition analysis ，it can be used for the quality control of Biantong capsules . Six components such as cyanidin -3-O-rutoside may be the differential markers that affect the quality of Biantong capsules .

Analysis of Chemical Variability on Different Processed Products of Glycyrrhiza uralensis Dry Roots and Rhizomes Based on UPLC-Q-TOF-MSE and Plant Metabolomics / 中国实验方剂学杂志

Objective:To identify the quality differential markers of different processed products of Glycyrrhiza uralensis dry roots and rhizomes. Method:Ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MSE) was used to collect high-precision mass-charge ratio and ion response strength information of the components in G. uralensis dry roots and rhizomes before and after processing by negative ion mode. The data set collected after pretreatment was analyzed with principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) to quickly search the differential components in different processed products of G. uralensis dry roots and rhizomes. Differential components were identified according to the relative molecular weight, fragment ion, mass spectrum database and related literature information, then the migration of components before and after processing was studied. Result:A total of 10 quality differential markers were searched from raw products, roasted products and honey-roasted products of G. uralensis dry roots and rhizomes, mainly derivatives of liquiritin and glycyrrhizic acid. Among them, the contents of 6''-O-acetylliquiritin apioside, 6''-O-acetylliquiritin apioside isomer, 6''-O-acetylliquiritin, formononetin and 11-deoxo-18β-glycyrrhetic acid were the highest in the raw products, the contents of 6''-O-acetylisoliquiritin apioside, 6''-O-acetylisoliquiritin, isoliquiritin and glycyrrhetic acid 3-O-glucuronide were the highest in the roasted products, the content of liquiritin was the lowest in the honey-roasted products. Conclusion:There are some chemical differences among the three products. This study can provide material basis for the quality control and pharmacodynamic research of processed products of G. uralensis dry roots and rhizomes.