12 results about "Microbial biomarkers" patented technology

The application discloses a microorganism marker combination for identifying nest susceptibility of chickens and application thereof, and belongs to the technical field of poultry breeding and microbiomics. The microorganism marker combination comprises relative abundance information of at least two bacterial phyla in Bacteroidetes, Firmicutes and Verrucomicrobia in cecal contents. When at least two of the following conditions are met: the abundance of Bacteroidetes is higher than 35%, the abundance of Firmicutes is lower than 35%, and the abundance of Verrucomicrobia is lower than 2%, it is determined that the chicken has nest susceptibility or is in a nest period. Based on the marker combination, the application provides a corresponding identification method, a regulation method and a regulation agent screening strategy.

The present application relates to the technical field of microorganism and the technical field of medicine, and particularly relates to an oral microorganism marker and application thereof in diagnosis of prognosis of gastric cancer. The oral microorganism marker comprises at least one of Aggregatibacter, Filifactor, Moryella and Leptotrichia. The present application firstly discovers that the level of human oral flora changes in different prognosis outcomes of gastric cancer, and by detecting the change of the flora, the prognosis survival period of the patient with gastric cancer can be predicted. The oral microorganism marker has the advantages of high specificity and strong sensitivity in diagnosis. The present application proves the clinical correlation of the oral microorganism flora in the prognosis of gastric cancer, and provides a non-invasive and highly sensitive tool for identifying the patient at risk of poor outcome before treatment.

This invention belongs to the fields of bioinformatics and medical testing technology, specifically relating to a combination of biomarkers related to the postoperative prognosis of colorectal cancer and their application and prediction system. This invention, through 16S rRNA gene sequencing of tumor mucosal samples from colorectal cancer patients, combined with long-term postoperative follow-up data and screening, found that *Peptostreptococcus*, *Fusobacterium*, *Bacteroides*, *Porphyromonas*, and *Prevotella* are closely related to postoperative recurrence of colorectal cancer, with an AUC of 0.81 for assessing postoperative recurrence. Based on this, this invention conducts non-targeted metabolomics analysis, finding that combining alanine glutamate, putrescine, arginine, histidine, and sebacic acid with the above microbial biomarkers can improve the AUC to 0.91, significantly enhancing accuracy, specificity, and precision. This enables prognostic stratification of recurrence-free survival in colorectal cancer patients, demonstrating higher predictive efficacy and stability.

This invention relates to the field of biomedical detection technology, specifically to plasma circulating microbial biomarkers for early screening of gastric cancer and their applications. The plasma circulating microbial biomarkers include: *Ralstonia solanacearum*, *Staphylococcus aureus*, *Alternaria metachromatica*, *Porphyromonas gingivalis*, *Lactobacillus reuteri*, *Rhodococcus erythropolis*, *Akkermansia muciniphila*, *Lactobacillus gasseri*, *Bifidobacterium bifidum*, and *Neisseria gonorrhoeae*. This invention screens and, for the first time, combines 10 specific microbial biomarkers with Low Pass technology. WGS technology can achieve detection results at low depths, significantly reducing screening costs while ensuring detection sensitivity, and providing a brand-new solution for early gastric cancer screening.

The application discloses an adult depression intestinal microorganism marker and application thereof, and belongs to the field of biological medicine. The microorganism marker comprises one or more of the following: Clostridium aldrichii, Coprococcus comes, Klebsiella pneumoniae, Bifidobacterium adolescentis, Bacteroides vulgatus, Eubacterium eligens and Faecalibacterium prausnitzii. The application provides a product (such as a kit) comprising detection reagents for detecting the relative abundance of the microorganism marker. The product provided by the application has good feasibility and accuracy, and can effectively evaluate the risk of whether an adult has depression, thereby providing a new tool for clinical diagnosis.

The application provides a microorganism marker group, a tumor prognosis prediction model establishment method and application thereof, and relates to the technical field of biomedicine. The microorganism marker group is related to a preset total survival time. Based on the microorganism marker group obtained from tumor tissues and paracancer normal tissues, the prognosis prediction accuracy and sensitivity of a digestive tract tumor can be effectively improved.

Provided herein, inter alia, are methods for measuring and assessing intestinal health in poultry. The disclosed microbial biomarkers and associated methods for identifying and quantifying the same are reliable, rapid and, in some embodiments, non-invasive, and can be used to provide information with respect to the gut health of poultry, such as chickens.

This invention belongs to the field of biomedical technology, specifically relating to a set of microbial biomarkers for identifying adenoid hypertrophy and their applications. Based on the relationship between different microbial colonization patterns and the severity of adenoid hypertrophy, this invention utilizes abundance data from combinations of oral microbial biomarkers from different sample types to construct a model that can predict the severity of adenoid hypertrophy in patients. The predictive model constructed in this invention has an AUC value of 0.752, demonstrating good predictive performance. Combining model parameters and microbial characteristic information shows that the invented model is consistent with current clinical understanding, proving the reliability of the model.

The present application belongs to the field of medical artificial intelligence, and specifically relates to a multi-source biological information processing and analysis system and method based on an intestinal mouth axis, which comprises: a data acquisition module that acquires oral microbiome data, host basic clinical data and host metabolome data of a subject; a preprocessing module that performs structured processing on the data; a microbial interaction network construction module that constructs a microbial interaction network based on the oral microbiome data; a graph feature extraction module that performs feature learning on the network using a graph neural network to obtain graph representation features; a risk assessment module that inputs the graph representation features, clinical features and metabolome features into a COX proportional risk model after fusion to generate a risk score; a correlation analysis module that matches and sorts the key microbial markers and the risk score with a preset correlation rule library and outputs suggestions; and a report generation module that generates an individualized analysis report. The present application realizes efficient fusion and structured analysis of multi-source biological information and provides data support for health status evaluation.

The application discloses a health and chronic disease intestinal microorganism marker screening method, comprising the following steps: 1) obtaining sample intestinal microorganism metagenome relative abundance data and clinical information; 2) screening samples covering health and chronic disease phenotypes; 3) normalizing the intestinal microorganism metagenome relative abundance data of each sample; 4) in the training set, using nested cross-validation and sequence feature selection methods, screening phenotype-specific intestinal microorganism markers for health and each type of chronic disease phenotype respectively. The application also discloses a method for constructing a chronic disease early screening model based on the combination of the microorganism markers screened by the above method. The application realizes early precise screening and risk assessment of 11 common chronic diseases by screening intestinal microorganism markers and establishing a chronic disease early screening model, and can be used for distinguishing between healthy people and chronic disease risk people, and accurately identifying high-risk individuals of various chronic diseases.

This invention discloses a gut microbiota-based system for predicting autism in adolescents and a method for building a model, belonging to the field of biomedicine and artificial intelligence. It includes a detection module for acquiring quantitative detection results of preset microbial markers in fecal samples from a donor, said microbial markers including active rumenococci and / or thermophilic streptococci; and a comparison module for comparing the quantitative detection results with preset thresholds to determine whether the adolescent has autism. This invention has good feasibility and accuracy, can effectively assess the risk of autism in adolescents, and provides a new tool for clinical diagnosis.

The application discloses a methane seepage microbial marker mining method based on multi-source data fusion and related equipment, and the embodiment of the application fuses microbial gene data, spatial information and environmental geochemical data, constructs a multi-dimensional feature space, and improves the data dimension and reliability of marker mining; moreover, the embodiment of the application adopts a combination of random forest and regression modeling, realizes quantitative screening of the marker, and reduces manual intervention and subjective bias; specifically, the embodiment of the application grades the marker based on the comprehensive score of the three dimensions of importance, stability and universality, facilitating priority selection in subsequent practical applications; the embodiment of the application is suitable for methane seepage identification in different sea areas and different geological backgrounds, has good generalizability and practicality, and can be widely applied in the technical field of marker analysis.