66 results about "Adenoma" patented technology

The invention discloses a marker for early colorectal neoplastic lesion diagnosis and application, and belongs to the technical field of biological medicine. Aiming at the problems of low colonoscopy coincidence rate of colorectal cancer patients at present and limited sensitivity and specificity of existing biomarker diagnosis, LncRNA sequencing research is combined with expanded sample verification to obtain high-specificity and high-sensitivity LncRNA which is highly related to colorectal neoplastic lesions (including adenoma and colorectal cancer), the LncRNA is specifically LOC401585, and the LncRNA has the advantages of high specificity, high sensitivity, high specificity and high sensitivity and can be used for detecting colorectal neoplastic lesions (including adenoma and colorectal cancer). The diagnosis efficacy AUC of the LOC401585 on the adenoma and the colorectal cancer is 0.952 and 0.876 respectively. Therefore, the blood LOC401585 marker can be used for auxiliary diagnosis of colorectal neoplastic lesions, and provides data support for finding novel small molecule drugs with potential treatment value.

The invention discloses a colon adenoma identification method and device based on Mueller matrix polarization measurement and regularization, a storage medium and electronic equipment. The method comprises the following steps: acquiring a polarization image corresponding to a fresh medical sample containing colon adenoma and normal tissue through a light polarization system, and preprocessing the polarization image; fourier analysis is carried out on a detection signal in the light polarization system to obtain a Mueller matrix, and a Lu-Chipman polarization decomposition algorithm is used for carrying out polarization decomposition on the Mueller matrix to obtain three polarization decomposition parameters; obtaining polarization data of a plurality of channels based on the Mueller matrix, and constructing a sample set based on the polarization data; constructing a target function based on the projection function and the sample set, solving the target function to obtain an analytic solution of the optimal projection direction, and calculating a characteristic value based on the analytic solution of the optimal projection direction; and classifying the polarization images corresponding to the fresh medical samples of the colon adenoma and the normal tissue based on the feature values to obtain a classification result. The lesion recognition rate can be improved.

The invention relates to the technical field of medicine, in particular to an early evaluation method for endocrine remission of pituitary growth hormone adenoma based on low Knosp grading, which comprises the following steps: acquiring preoperative and postoperative image data and preoperative and postoperative clinical data of a patient with low Knosp grading pituitary growth hormone adenoma; extracting imaging features used for early evaluation of postoperative endocrine remission from the preoperative and postoperative image data; extracting clinical features for early evaluation of postoperative endocrine remission from the preoperative and postoperative clinical data; and performing statistical analysis on the iconography characteristics and the clinical characteristics to obtain an early evaluation result of postoperative endocrine remission. According to the method, risk factors related to whether low-Knosp graded pituitary growth hormone adenoma postoperative endocrine remission can be relieved or not are screened out, then a prediction model is established through a statistical method, and then early prediction of low-Knosp graded pituitary growth hormone adenoma postoperative endocrine remission is achieved.

A group of diagnostic biomarkers usable for diagnosis of colorectal cancer or advanced colorectal adenoma (CRC / ACRA) is provided. The method for detecting CRC / ACRA using the group of diagnostic biomarkers is also provided. For example, the method is a non-invasive approach that may utilize serum samples for detecting colorectal cancer. Moreover, the method for detecting colorectal cancer may detect colorectal cancer of different stages (e.g., pre-cancer stage, early stage, middle stage, late stage). A kit for detecting CRC / ACRA is also provided.

The invention discloses a system and equipment for predicting colorectal cancer and progression thereof. Based on the found expression level difference of AXIN2 and / or EPHB2 in colorectal cancer and the progression thereof, the invention provides a colorectal cancer and progression prediction method, system and equipment, a computer readable storage medium and a computer program product, high-risk groups can be efficiently and accurately screened out from common groups, and colonoscopy is further completed in time. While the economic burden caused by endoscopic screening is relieved, patients suffering from colorectal adenoma and early colorectal cancer are screened out, and the method has great significance in early diagnosis and treatment of colorectal tumor and further remarkable reduction of the morbidity and mortality of colorectal cancer.

In various aspects and embodiments, the Disclosure provides methods for evaluating subjects for the presence or absence of colorectal neoplasms, such as colorectal cancer (CRC), colorectal adenoma (CRA), and progressive colorectal adenoma (CRAA), by metagenomic and multi-omics analysis of feces or other biological samples. In other aspects, the Disclosure provides methods for generating machine learning models or “signatures” based on metagenomic and multi-omics analysis of feces or other biological samples to evaluate subjects for the presence or absence of colorectal diseases, including but not limited to CRC, CRA, and CRAA.

The present invention relates to a method for identifying one or more caudal midbrain (cVM) progenitor cells by measuring the presence and / or amount of adenomatous colonic polyposis down-regulating 1 (APCDD1) expressed by one or more cells. The invention also provides a method for enriching cVM cells, application of the cells in disease treatment, application of APCDD1 as a biomarker and a kit.

The invention relates to the technical field of data prediction, and discloses a colorectal progression stage adenoma data prediction method and system based on machine learning, a terminal and a storage medium, and the method comprises the steps: screening out a corresponding candidate prediction factor according to the colorectal progression stage adenoma data of each target sample; and dividing the candidate prediction factors into a training set and a verification set, constructing a target machine learning model by using the training set, inputting the verification set into a plurality of decision trees of the target machine learning model, outputting an original prediction probability, and converting the original prediction probability into a classification probability to obtain a prediction result. According to the method, an efficient, explainable and visual machine learning early warning model is utilized, a visual decision path is generated, conventional non-invasive indexes can be effectively integrated, and individualized prediction of colorectal progression stage adenoma data is achieved.

The invention discloses a colorectal adenoma screening method based on serum metabolites, and belongs to the field of biomedical detection. The method comprises the steps of serum sample pretreatment, instrument analysis, quantitative analysis and prediction model construction, after 15-25 [mu] L of a serum sample is treated, 41 serum metabolites, age, gender and BMI are combined, and a LightGBM model is used for predicting the disease probability and performing layered suggestion. The kit fills up related gaps, has the advantages of non-invasiveness, high sensitivity and specificity, portability, high efficiency, low cost and the like, and is suitable for large-scale screening.

The present invention relates to novel protein arginine methyltransferase 5 (PRMT5) inhibitor compounds and methods for treating adenomatous polyposis coli (APC) loss-of-function driven adenoma diseases in a human in need thereof.

The present disclosure concerns a computer-implemented method for transforming stool sample data into a diagnostic code, the method including: a) providing a stool sample from a subject; b) determining, as the stool sample data, expression levels of at least two distinct genes from a plurality of mRNA segments in the stool sample; and c) determining, by a computing system executing a machine-learning model and based on the stool sample data, a diagnostic code, wherein the machine-learning model was trained using stool diagnostic training data including a plurality of stool sample data labeled with at least one of two or more corresponding diagnostic codes.

This invention discloses a high-performance computing-based system and method for evaluating colorectal cancer screening strategies, belonging to the field of medical information processing technology. It includes: a dual-pathway disease model module supporting both adenoma-carcinoma pathways and serrated adenoma pathways, modeled using age-dependent normal distribution progression time; an individualized risk scoring module integrating risk factors such as family history, inflammatory bowel disease, obesity, and diabetes; a screening strategy simulation module supporting combined screening strategies using different tools, employing compliance parameters specific to the Chinese urban population; a high-performance computing module using Numba JIT compilation technology for acceleration, multi-process parallel processing for further acceleration, and data structure optimization such as integer age to reduce memory usage; and a health economics evaluation module calculating indicators such as QALY, LYG, and ICER. This invention achieves significant performance improvements while maintaining model accuracy, greatly reducing simulation time for large-scale populations.

The invention discloses an inflammatory bowel disease classification and interpretable diagnosis method and system based on deep learning, an image acquisition module acquires image frames from colonoscope videos, and an image preprocessing module rejects low-quality images with high black pixel proportion and blurred images and executes color space normalization. The qualified image is sent to a double-stage segmentation model to obtain a polyp area mask image, the mask image is used for positioning an ROI image of the polyp area, the ROI image is input into a polyp classification model constructed based on a visual Transform structure, and a hyperplasia type or adenoma type classification result is obtained. According to the method, on the premise that extra cost input is not needed, the efficiency and accuracy of polyp recognition and grading in the colonoscope image are greatly improved, manual subjective errors are reduced, and the intelligent level and clinical practicability of early intestinal cancer screening are improved.

The application relates to a thymoma epithelial cell subpopulation with neuromuscular characteristics and application, and a thymoma epithelial cell subpopulation with neuromuscular characteristics is obtained through single clone dilution culture screening from a thymoma cell line Thy0517 of a patient with myasthenia gravis (MG) in combination, and a thymoma epithelial cell with neuromuscular characteristics in the cell subpopulation is named as Thymus_NMi; the cell subpopulation has synapse-like structures and neuromuscular adhesion characteristics, and efficiently expresses genes participating in neural cell adhesion and synapse connection, highly integrates neuromuscular double characteristics, and simulates key pathological characteristics of abnormal thymus-induced immune tolerance of MG patients in a molecular phenotype and physiological function, so that a cell model closest to a real clinical state is provided for exploring a myasthenia gravis occurrence mechanism.

The present disclosure relates to certain compositions, kits, devices, systems and methods, e.g., certain compositions, kits, devices, systems and methods for assessing methylation status, and / or assessing colorectal cancer and / or advanced adenoma in a subject. In particular aspects, provided herein are compositions, kits, devices, systems and methods for assessing colorectal cancer and / or advanced adenoma in a subject based on assessing methylation status of selected target polynucleotide sequences, e.g., target genomic DNA sequences, from the subject.

The present invention relates to a method for identifying one or more caudal ventral midbrain (cVM) progenitor cells by measuring the presence and / or amount of adenomatosis polyposis coli down-regulated 1 (APCDD1) expressed by one or more cells. The present invention also provides a method for enriching cVM cells, the use of said cells in the treatment of disease, the use of APCDD1 as a biomarker, and a kit.

Disclosed is a drug for preventing and treating diseases related to abnormal intestinal hyperplasia. Specifically disclosed is the following: The accumulation of myeloid-derived inhibitory cells (MDSCs) caused by the reduction of IL-10 is the main cause of abnormal hyperplasia of the intestinal epithelium, and supplementation of IL-10 within myeloid cells at the source helps to restore bone marrow microenvironment homeostasis and reduce the production of pathogenic MDSCs, thereby treating diseases related to abnormal hyperplasia of the intestinal epithelium, such as inflammatory bowel disease and adenomatous polyposis. Disclosed is a recombinant adeno-associated virus vector expressing IL-10. Targeted delivery of IL-10 to myeloid cells is achieved by means of intraosseous injection, avoiding adverse effects caused by systemic administration. This approach offers targeting specificity and safety and provides a new solution for the treatment of diseases related to abnormal intestinal hyperplasia.

The invention discloses an application of a metabolite level detection reagent in preparation of a diagnostic kit for adenoma in a colorectal progression stage. A metabolite is selected from the group consisting of tridecane diacid, methyl 1-(methyl sulfur) propyl disulfide, histidine proline amide, termite dialdehyde, N-acetylglycine, 5-hydroxycaprin, arginyl glutamine, nalmefene and sodium alginate. The compound is selected from at least one of dialaphos and dipifolin. According to the invention, 11 kinds of differential metabolites which change continuously in the colorectal lesion progress process are screened from the serum exosome, and the 11 kinds of metabolites have good identification capability on the stage of colorectal lesion, and have good application prospects in screening and diagnosis of adenoma and colorectal cancer in the colorectal progression stage. And the method has great clinical significance in distinguishing the malignant degree of colorectal adenoma.

Methods of treating colorectal cancer or colorectal adenoma, diagnosing colorectal cancer or colorectal adenoma, monitoring treatment in a patient having colorectal cancer or colorectal adenoma, and monitoring risk for developing colorectal cancer or colorectal adenoma in patients can be accomplished through the use of RNA biomarkers, such as let-7c, miR-100, miR-lOb, miR-1246, miR-1290, miR-135b, miR-150p, miR-184, miR-199b, miR-200a, miR-203a, miR- 205, miR-20a, miR-433. miR-455. miR-543, miR-9, miR-18a, miR-19a, miR-4488, miR-107, miR-1228, miR-1229, miR-1323, miR-141, miR-142, miR-1538, miR-17, miR-195, miR-19b, miR-200b, miR-296, miR-34a, miR-3913, miR-5193, and miR-877.

A method for differential diagnosis of gallbladder adenoma and cholesterol polyps based on the fusion of deep learning and clinical features in ultrasound images includes: performing deep learning on ultrasound images using a deep learning network to output an adenoma / polyp risk score; the deep learning network is selected from one of VGG, ResNet, DenseNet, GoogLeNet, Vision Transformer, and Inception; the adenoma / polyp risk score and clinical features are input into a trained machine learning model for learning to obtain the final probability of identifying the polyp as a gallbladder adenoma rather than a cholesterol polyp; the clinical features include: echo intensity, maximum polyp diameter, and age; the machine learning model is selected from one of Logistic Regression, Gradient Boosting, K-nearest neighbors, Gaussian naïve Bayes, AdaBoost, Random Forest, ExtraTrees, and SVM.

The invention relates to the field of biological medicine, and discloses application of an ENPP1 inhibitor in preparation of a medicine for treating pituitary growth hormone adenoma. The ENPP1 inhibitor is a compound with a structure as shown in a formula I, or an isomer, a derivative, a solvate or a pharmaceutically acceptable salt thereof. It is found for the first time that the ENPP1 inhibitor has a remarkable treatment effect on pituitary growth hormone adenoma, not only inhibits secretion of GH, but also inhibits growth of adenoma. Specifically, the inhibitor efficiently inhibits the activity of growth hormone adenoma cells ENPP1, inhibits adenoma cell proliferation and GH secretion in an in-vitro model, reduces the GH and IGF-1 levels of tumor-bearing mice in an in-vivo model, and is suitable for GH adenoma insensitive to somatostatin analogue drugs (such as octreotide). In addition, when the ENPP1 inhibitor is combined with octreotide for use, a synergistic effect is shown, and the anti-tumor effect is further enhanced.

The invention belongs to the technical field of biological medicine, and particularly relates to application of vitamin B12 in preparation of an auxiliary therapeutic agent for preventing or treating colorectal cancer precancerous lesions. The invention aims to solve the technical problem of providing a novel prevention and intervention means for colorectal cancer (CAC) caused by the cancerization process of colorectal adenoma and inflammatory atypical hyperplasia. The invention further provides a preparation method of the novel prevention and intervention means for the colorectal cancer caused by the cancerization process of the colorectal adenoma and the inflammatory atypical hyperplasia of the colorectal adenoma and the colorectal cancer caused by the inflammatory atypical hyperplasia of the colorectal adenoma. In a colorectal adenoma canceration process, the level of vitamin B12 in a circulatory system is reduced along with the development of diseases. In inflammatory and hereditary colorectal cancer mouse models, MHC-II signals can be enhanced by supplementing medicine vitamin B12, and CD4 effect memory T cell immunity can be reactivated. The invention provides a new thought for further researching the immune recovery strategy in the colorectal cancer precancerous lesion process and the medical application of the vitamin B12.

The application discloses a construction method of a pituitary prolactinoma animal model. The pituitary prolactinoma animal model constructed by subcutaneously injecting 17B-Estradiol preparation can better simulate the pathophysiological process of human prolactinoma, and the construction method is simple, short in time, and an animal model construction method with excellent effect.

The present disclosure provides a prophylactic or therapeutic agent for a benign tumor. Provided is a prophylactic or therapeutic agent for a benign tumor, which comprises a WT1 peptide, an analog thereof, or a nucleic acid molecule encoding the same. In a specific embodiment, the present disclosure provides a prophylactic or therapeutic agent for a benign tumor, which comprises a WT1 peptide, an analog thereof, or a nucleic acid molecule encoding the same. In a preferred embodiment, the prophylactic or therapeutic agent for a benign tumor (e.g., familial adenomatous polyposis) according to the present disclosure comprises a killer-type and / or helper-type WT1 peptide. In a further preferred embodiment, the aforementioned WT1 peptide is a WT1 126 killer peptide and / or WT1 35 helper peptide. In another aspect, provided are WT1 peptide-specific CTLs, a method for inducing WT1-specific helper T cells, and a method for inducing dendritic cells presenting a WT1 peptide.

Familial adenomatous polyposis (FAP) patients harbor mutations in the APC gene and will develop adenoma and early colorectal cancer. Taking biopsies from non-adenomatous (NA) and adenomatous (A) colonic mucosa of FAP patients, we investigated the early events associated with FAP using the intestinal organoid model. In addition to their high proliferative capacity, NA- and A-organoids were characterized by cysts and cysts with buds, respectively, suggesting abnormal maturation. A-organoids were enriched in the stem cell marker LGR5 and dependent on EGF and TGFβ for their growth. Downstream of EGFR, AKT, β-catenin and YAP were found to be activated in A-organoids. While the p110β isoform of PI3K was predominant in A-organoids and essential for their growth, p110α was associated with the immature state of NA-organoids. Accordingly, the present invention relates to a method of treating Familial Adenomatous Polyposis in a subject in need thereof comprising administering to the subject a therapeutically effective amount of a PI3K inhibitor.

Devices for improving adenoma detection during colonoscopy, and more particularly, to devices that are positionable at a distal end of an endoscope and are structured or configured to expand and retract upon longitudinal or rotational displacement of at least a portion of the device about the endoscope.

The application relates to a thymoma epithelial cell subpopulation with neuromuscular characteristics and application, and a thymoma epithelial cell subpopulation with neuromuscular characteristics is obtained through single clone dilution culture screening from a thymoma cell line Thy0517 of a patient with myasthenia gravis (MG) in combination, and a thymoma epithelial cell with neuromuscular characteristics in the cell subpopulation is named as Thymus_NMi. The cell subpopulation has synapse-like structures and neuromuscular adhesion characteristics, and efficiently expresses genes participating in neural cell adhesion and synapse connection, highly integrates neuromuscular double characteristics, and simulates key pathological characteristics of abnormal thymus-induced immune tolerance of MG patients in a molecular phenotype and physiological function, so that a cell model closest to a real clinical state is provided for exploring a myasthenia gravis occurrence mechanism.

The invention provides a diagnostic model for establishing and optimizing colorectal cancer (CRC) and adenoma risks and application, as a non-invasive method, the method comprises the following steps: firstly, collecting a feces sample of a target population, and performing DNA extraction and sequencing to identify a specific genetic marker of a microbiome; then, screening microbiome function markers related to CRC by using the metagenome data set; by comparing genetic markers to functional markers, microbiome functional markers are screened using statistical methods, which are then used to train diagnostic models. According to the model, a machine learning algorithm is adopted, and CRC and adenoma risks are evaluated based on screened markers. The model is verified and optimized through an independent crowd data set to enhance the accuracy, sensitivity and specificity of the model. The model of the present invention can detect changes in microbiome function during colorectal cancer progression, and by identifying these functional changes in the microbiome, dietary / nutritional supplements can be utilized to combat these changes.

The invention relates to the technical field of medical image recognition, in particular to an adenomatous polyp recognition method in colonoscope screening. Acquiring a colonoscope image, and acquiring colonoscope image definition of the colonoscope image; screening the colonoscope image based on the colonoscope image definition to obtain a primarily screened image; a boundary recognizer is adopted to recognize the preliminary screening image, and a boundary recognition result is obtained; based on the boundary recognition result, screening the primary screening image, obtaining a secondary screening image, and recognizing the secondary screening image by adopting a structure recognizer to obtain a structure recognition result; and obtaining an adenomatous polyp recognition result based on the colonoscope image definition, the boundary recognition result and the structure recognition result. By implementing the method, efficient and accurate identification of the adenomatous polyp in the colonoscope image can be realized.

The invention relates to medical technology and can be used in urology for drainage and treatment for the prophylaxis of postoperative complications in the prostate and urethra after surgical treatment of prostate adenoma.Summary of the invention consists in that the device comprises four symmetrical tubes (1, 2, 3, and 13) of different diameters and connected on a line along their longitudinal axis, one end (8) of the device is made blunt, the tubes at the opposite end (9) of the device are separate, each end of which is equipped with a branch pipe. In the tube (1) of a larger diameter are made three channels (4, 5, 6), where one channel (4) communicates with an elastic balloon (7) placed at the blunt end (8) of the device, and two channels (5, 6) pass through the balloon (7) and each ends with an opening (11) on the sides of the blunt end (8). The tube (2) is made of a smaller diameter than the tube (1) and ends with multiple holes (10) on the side of the blunt end (8) under the elastic balloon (7). The tube (3) is made with the smallest diameter and with the blind end under the elastic balloon (7), and along the path of tube (3) in its wall are made 4…5 holes (12) at a distance of 5…6 cm from each other. The tube (13) is made blind, the diameter of which is equal to the diameter of the tube (1), and in this tube (13) is placed an insulated coaxial cable (14) with one end reaching the balloon (7), where the corresponding end of the cable (14) is equipped with a coaxial dipole antenna (15), and the opposite end of the cable (14) is equipped with a connector (16) for connection to a microwave generator, in the tube (13) is also placed an optical fiber (17) with one end reaching the balloon (7), where the corresponding end of the optical fiber (17) is equipped with a transmitter with a diffuser emitter (18) for infrared waves, and the opposite end of the optical fiber (17) is equipped with a connector (19) for connection to an infrared wave generator. The device has a diameter of 28…30 Fr and is made of silicone or natural latex coated with polytetrafluoroethylene.