66 results about "Molecular biomarker" patented technology

The invention discloses a method and system for predicting membranous nephropathy based on machine learning, and relates to the technical field of medical diagnosis and treatment, and the method comprises the steps: collecting multi-source heterogeneous data of a patient; preprocessing the multi-source heterogeneous data, constructing a mapping relation between the traditional Chinese medicine syndrome type and the molecular biomarker, and generating a traditional Chinese and western medicine fusion feature matrix; screening a feature subset related to membranous nephropathy prediction from the traditional Chinese and western medicine fusion feature matrix; constructing a membranous nephropathy multi-level prediction framework according to the feature subset, and training each prediction model in the framework; and applying the trained and optimized membranous nephropathy multi-level prediction framework to the feature subset data of the new patient to generate a membranous nephropathy multi-dimensional prediction result. By establishing the Chinese and western medicine feature mapping relation, deep fusion of traditional Chinese medicine diagnosis and modern medical indexes is realized, and comprehensiveness and accuracy of disease diagnosis are improved.

By a genome-wide gene analysis of expression profiles of over 50,000 known or putative gene sequences in peripheral blood, the present inventors have identified a consensus set of gene expression-based molecular biomarkers associated with chronic allograft nephropathy and / or interstitial fibrosis and tubular atrophy CAN / IFTA and subtypes thereof. These genes sets are useful for diagnosis, prognosis, monitoring and / or subtyping of CAN / IFTA.

Various methods and systems for efficiently providing pharmacogenetic guidelines is disclosed. A drug prescription and a patient genotype can be analyzed to provide a drug therapy recommendation. The analysis can include comparing the patient genotype and the drug name to a drug profile database, a molecular biomarker database, hospital drug reaction records and omics databases, and calculating the patient response to the drug.

The present disclosure provides methods, systems, compositions, and kits for the high-throughput detection of multi-molecule biomarkers in a biological sample. The disclosed methods, systems, compositions, and kits utilize antibody-oligonucleotide tags to detect two or more molecules that are in close proximity.

A method for characterizing disease activity in a systemic lupus erythematosus patient (SLE), comprising obtaining a dataset associated with a blood, serum, plasma or urine sample from the patient, assessing the dataset for a presence or an amount of protein expression of at least one innate serum or plasma mediator, assessing the dataset for a presence or an amount of protein expression of at least one adaptive serum or plasma mediator biomarker, assessing the dataset for a presence or an amount of at least one chemokine / adhesion molecule biomarker, assessing the dataset for a presence or an amount of at least one soluble TNF superfamily biomarker, assessing the dataset for a presence or an amount of at least one inflammatory mediator biomarker, assessing the dataset for a presence or an amount at least one SLE-associated autoantibody specificity biomarker and calculating a Lupus Disease Activity Immune Index (LDAII) score.

The invention discloses a molecular classification prediction method based on molecular biomarkers and images, and relates to the technical field of medical image processing. Comprising the following steps: constructing a molecule and image matching correlation analysis model; training by using the training data set; the channel number of the target preoperative medical image data is increased through the feature extraction convolution block; a space matching relation between an image and a molecular biomarker in the processed target preoperative medical image data is established through an image molecule fine granularity insight module, and a feature map after the space relation is established is obtained through a space molecule mapping map output module; adjusting the feature map into a corresponding molecular channel through a space molecular mapping map output module to obtain a space molecular mapping map; and pooling the spatial molecular mapping map through a global average pooling module, and activating and calculating a molecular category prediction probability through Sigmoid to obtain a molecular classification prediction result. According to the invention, the spatial relation between molecules and images is established.

Compositions, methods, and kits are provided for diagnosing vitreoretinal diseases and age-related pathologies. In particular, aqueous humor biomarkers have been identified that correlate with biological aging and age-related pathologies and morbidity. The use of such biomarkers may allow earlier intervention in treatment of aging-related diseases. In addition, methods of using aqueous humor biomarkers for prognosis, diagnosis, and monitoring treatment of vitreoretinal diseases are also provided.

By a genome-wide gene analysis of expression profiles of over 50,000 known or putative gene sequences in peripheral blood, the present inventors have identified a consensus set of gene expression-based molecular biomarkers associated with chronic allograft nephropathy and / or interstitial fibrosis and tubular atrophy CAN / IFTA and subtypes thereof. These genes sets are useful for diagnosis, prognosis, monitoring and / or subtyping of CAN / IFTA.

Systems and methods for a wearable system that monitors various biomarkers with a 3D-printed wearable electronic skin. Specifically, the wearable system is a 3D-printed epidermal wearable microfluidic electronic skin that may be composed of a combination of multidimensional nanomaterials, polymers, and hydrogels. The epidermal wearable microfluidic electronic skin may be integrated with sensors, electrodes, microfluidics, and a processor to collect and analyze molecular biomarkers of biofluid samples on the user's skin, while simultaneously analyzing the user's physiological biomarkers to conduct a health status assessment or gather health monitoring / surveillance metric.

The invention relates to the in vitro use of various molecular biomarker levels measured in samples from subjects with obesity, said samples being isolated before the bariatric surgery as biomarkers for predicting or prognosing the response to bariatric surgery.

1. The name of the product under this design: Molecular Diagnostic Analyzer. 2. Purpose of this product design: This product design is used in clinical and scientific research fields, and is applied to the detection of molecular biomarkers in samples using molecular biology methods. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: Design 1 Stereoscopic Drawing 1. 5. Designate Design 1 as the base design.

A diagnostic imaging assistance device 1 comprises: a first acquisition unit 10 for acquiring an image of a head through MRI; an image processing unit 11 for extracting a region containing information on a lesion site and the periphery of the lesion site from the acquired image of the head and generating a first image having the extracted region; an extraction unit 12 for extracting a predetermined image feature amount from the first image; a classification unit 14 for determining, on the basis of the image feature amount extracted by the extraction unit 12, the presence or absence of a molecular biomarker associated with the lesion site for classification using a pre-constructed classifier; and a presentation unit 15 for presenting assistance information related to whether or not the lesion site contained in the image of the head has the molecular biomarker, on the basis of the result of the classification by the classification unit 14.

Integrated platforms, systems, and associated processes for measuring lifespan, body size and shape, activity, pathology, pigmentation / color, and multiple in vivo molecular biomarkers using multiple cameras are described. The integrated platform includes a plate and trays supported on the plate. Each tray can hold animals. The integrated platform also includes an imaging module with a first camera and a second camera. The first camera can capture first images associated with movement of the animals and the second camera can capture second images and third images associated with biomarkers of the animals.

Methods for identifying sex bias in an association between an omics variant and a disease state are described. The methods may comprise, for example, receiving omics data and clinical data for a plurality of subjects; processing the omics data and clinical data for the plurality of subjects using a model, wherein the model is configured to identify a sex bias in an association between an omics variant identified in the omics data and a disease state identified in the clinical data and output a prediction of whether the omics variant is likely to be a pathogenic variant associated with the disease state based on subject sex; and outputting a prediction of whether the omics variant is likely to be a pathogenic variant associated with the disease state for a subject of known sex.

The invention discloses a colorectal cancer liver metastasis detection method and system based on multi-omics deep learning, and the method comprises the steps: extracting a characteristic gene group with CRC metastasis-metabolism dual functions, and on the basis of constructing a CRC metastasis risk prediction model, screening molecular markers with CRC metastasis general and CRLM specific characteristics based on the analysis of CRC metastasis risk probability, the biomarker is used as an initial candidate biomarker; meanwhile, a CRLM patient sample and differential expression metabolites corresponding to an LCRC patient sample metabolome are obtained from a metabolome, and a CRLM multilayer core metabolic network is constructed in combination with enrichment pathway analysis of a transcriptome and the metabolome, so that core biomarkers are screened for accurate detection of colorectal cancer liver metastasis; the whole method can effectively screen the biomarker beneficial to detection of colorectal cancer liver metastasis.

The invention relates to application of HLA-DR < + > tumor cells in evaluation of liver cancer prognosis or immunotherapy response, and belongs to the technical field of tumor biomarkers and prognosis evaluation. The technical problem to be solved by the invention is to provide a biomarker for evaluating liver cancer prognosis or immunotherapy response, namely HLA-DR < + > tumor cells. Through scRNA-seq and accurate differential expression analysis, gene expression characteristics of HLA-DR < + > tumor cells in HBV-HCC are disclosed for the first time, and a high-specificity molecular marker is provided for prognosis evaluation or immunotherapy response prediction. A prognosis scoring model is constructed by using the molecular marker, so that the prognosis prediction accuracy of HBV-HCC patients can be improved, and a scientific basis is provided for clinical precision medical treatment. An immune response scoring model is constructed by using the molecular marker, and is used for predicting the treatment response of a patient to a PD-1 / PD-L1 inhibitor and guiding clinical formulation of an individualized treatment scheme. In addition, the invention also helps to deeply reveal an immune escape mechanism of HBV liver cancer, and lays a foundation for subsequent immunotherapy strategy development of targeted HLA-DR + tumor cells.

The invention discloses a method for detecting a protein polypeptide biomarker based on a pH stimulation response material, in the method, a pH stimulation response immunofunctionalized mesoporous material can load more small molecule compounds with strong mass spectrum signals, and the sensitivity of an analysis method is greatly improved; the pH stimuli-responsive immunofunctionalized mesoporous material can achieve the effect of signal conversion, direct analysis of biomacromolecular biomarkers by mass spectrometry is avoided, small molecular compounds with strong mass spectrometry signals are released under specific conditions, and the specificity of the detection method is improved.

The present invention includes a method of characterizing disease activity in a systemic lupus erythematosus patient (SEE), comprising: obtaining a dataset associated with a blood, serum, plasma or urine sample from the patient, wherein the dataset comprises data representing the level of one or more biomarkers in the blood, serum, plasma or urine sample from each of (b) to (g); at least one innate serum or plasma mediator biomarker; at least one adaptive serum or plasma mediator; at least one chemokine / adhesion molecule biomarker; at least one soluble TNF superfamily biomarker; the inflammatory mediator biomarker SCF; at least one SLE-associated autoantibody specificity biomarker; and calculating a Lupus Disease Activity Immune.

The present disclosure relates generally to the field of medical oncology and, in particular, to methods and kits for identifying and treating neuroendocrine carcinomas, such as small cell neuroendocrine (SCN) tumors. Certain aspects of the present disclosure can include methods of diagnosing a patient with a neuroendocrine carcinoma, methods of determining a survival prognosis in a patient diagnosed with a neuroendocrine carcinoma, compositions that effectively inhibits or decreases an expression level of a hepatocyte cell adhesion molecule 2 (HEPACAM2) biomarker in vivo or ex vivo, and methods of treating a patient having, or suspected of having, a neuroendocrine carcinoma.

A microfluidic device (12) for applying a sample of body fluid to a conditioned sensor element for the detection of molecular biomarkers in the body fluid and / or for conditioning the sensor element (14) using a conditioning fluid comprises at least one interaction chamber (40) that is partially closed by a sensor element (14). A pneumatic unit (70) is connected to the at least one first receptacle (46) and is configured to pressurize it and pump the body fluid or the conditioning fluid once and unidirectionally through the at least one interaction chamber (40) along the treated surface (16) and subsequently into the at least one disposal container (52), so that, in the case of body fluid, biomarkers adhere to the surface (16) or, in the case of conditioning fluid, the surface is conditioned.Furthermore, a biomarker detection device (18) and a method for applying a sample of body fluid to a conditioned sensor element (14) for biomarker detection and / or for conditioning a sensor element (14) for biomarker detection are proposed.

The invention discloses an early-stage prostate cancer diagnosis product and a diagnosis model. The invention provides a serum protein marker and urine bacteria which can be used for diagnosing a prostate cancer PSA gray zone patient, and further provides an early-stage prostate cancer diagnosis product, a diagnosis model and a corresponding diagnosis method on the basis of the serum protein marker and the urine bacteria. The diagnostic product and the diagnostic model have very high sensitivity and specificity on the diagnosis of the early prostate cancer, and can be used for screening the early prostate cancer, so that the detection rate of patients with the early prostate cancer is increased, and misdiagnosis and missed diagnosis are reduced. The invention not only enriches molecular markers for early-stage prostate cancer diagnosis, but also provides a non-invasive, simple and high-sensitivity early-stage prostate cancer diagnosis method, and overcomes the defect of low specificity when the existing prostate tumor markers such as PSA are used for early-stage prostate cancer diagnosis. The method has important significance on screening and diagnosis of early-stage prostate cancer.

The present disclosure relates generally to detection on non-coding RNAS molecules in a sample or diagnosis of subject based upon detection or quantification of non-coding nucleic acid sequences in a sample, specifically to identify and use of molecular biomarkers for cancer including breast cancer.

The invention provides an application technology for enabling early screening, early diagnosis and postoperative treatment judgment of gastric cancer by a multi-modal model algorithm, and belongs to the field of molecular biology, medical diagnosis and prevention. The method comprises the following steps: collecting a sample from human body liquid through a modern detection technology, detecting data of a plurality of molecular biomarkers and kit results associated with the gastric cancer or the cancer, and calculating by using a multi-modal model algorithm to find precancerous lesions, early gastric cancer or early cancer so as to reach the best early curing opportunity of a patient; the progression stage, pathological typing, clinical staging, metastatic state and postoperative curative effect inference of gastric cancer or cancer are analyzed and predicted, so that the cure effect of a patient can be improved and precise medical treatment can be realized in combination with a gastroscope pathological biopsy result; the sensitivity and the specificity precision of the kit approved by the country in the future are improved; the problem that early detection of medical early screening is difficult to solve is solved. The non-destructive detection and multi-modal model algorithm technology has wide usability, and has a demonstration effect on gastric cancer and other cancers.

The present invention relates to the field of biomedical technologies, and particularly to a biomarker for diagnosing and predicting the prognosis of triple-negative breast cancer and its applications. Through bioinformatics analysis of the gene expression of triple-negative breast cancer compared with other types of breast cancer, the present invention screens out the gene FAISL that is highly expressed in triple-negative breast cancer and is closely related to the prognosis, which can be used as a new molecular biomarker for triple-negative breast tumors. Its high expression indicates a poor prognosis of the tumor. This gene can also be used as a therapeutic target for tumors. The present invention uses a disulfide bond reduction-responsive nanomaterial to encapsulate siRNA targeting the pro-cancer gene FAISL. Due to the characteristics of the nanocarrier having a long blood circulation time and strong tumor enrichment ability, the nanoparticles loaded with siRNA can significantly inhibit the expression of the pro-cancer gene, inhibit the growth and metastasis of tumor cells, and reduce the damage to normal tissue cells.

Systems and methods for a wearable system that monitors various biomarkers with a 3D-printed wearable electronic skin. Specifically, the wearable system is a 3D-printed epidermal wearable microfluidic electronic skin that may be composed of a combination of multidimensional nanomaterials, polymers, and hydrogels. The epidermal wearable microfluidic electronic skin may be integrated with sensors, electrodes, microfluidics, and a processor to collect and analyze molecular biomarkers of biofluid samples on the user's skin, while simultaneously analyzing the user's physiological biomarkers to conduct a health status assessment or gather health monitoring / surveillance metric.

The invention belongs to the technical field of disease diagnosis and molecular biology, and particularly relates to application of LncRNA 02365 in HBV (Hepatitis B Virus) related HCC (Hepatitis C Chromatography) diagnosis. It is found for the first time that the LncRNA 02365 is abnormally high in expression in HBV-related HCC patients, the verification result of the serum-derived LncRNA 02365 and the verification result of the HBV-related HCC tissue are consistent, the sensitivity of the test result is high, and the specificity is good. Therefore, the LncRNA 02365 can be used as a molecular biomarker for diagnosing the HBV-related HCC, so that the disease risk of HBV-related HCC patients is predicted, high-risk groups are screened, and early and rapid non-invasive diagnosis is performed on the HBV-related HCC patients.

This invention relates to the pharmaceutical applications of MRPS7 as a diagnostic biomarker for non-small cell lung cancer (NSCLC) and its inhibitors, belonging to the field of biomedical technology. For the first time, this invention utilizes immunohistochemical analysis of tumor tissues from NSCLC patients and paired adjacent normal tissues to confirm that MRPS7 protein is significantly overexpressed in NSCLC tissues (p<0.001), and this difference is statistically significant in both lung adenocarcinoma and lung squamous cell carcinoma subtypes. Furthermore, this invention demonstrates through in vitro functional experiments that knocking down MRPS7 gene expression using siRNA targeting MRPS7 significantly inhibits the proliferation, migration, and invasion abilities of NSCLC cells (A549, SK-MES-1) (p<0.001). Therefore, reagents for detecting MRPS7 expression levels can be used to prepare NSCLC diagnostic products, and MRPS7 inhibitors can be used to prepare drugs for treating NSCLC. This invention provides a novel molecular biomarker for the diagnosis of NSCLC and a new strategy for targeted therapy of NSCLC.

The present disclosure relates to systems, methods and computer program products for drug development using in silico techniques. An aspect of the disclosure is directed to an in silico method for determining drug activity of a plurality of drug targets by determining biomarker stratifier effects, calculating a biomarker stratifier score for a chosen disease phenotype; and calculating a pharmacomimetic genetic score using molecular biomarker stratifier data.

The present disclosure relates to systems, methods, and computer program products for drug development using in silico techniques. One aspect of the disclosure relates to an in silico method for determining drug activity for multiple drug targets by determining biomarker stratification factor effects, calculating biomarker stratification factor scores for a selected disease phenotype, and calculating pharmacomimetic gene scores using molecular biomarker stratification factor data.

The present disclosure relates to systems, methods and computer program products for drug development for chronic liver disease (CLD) or non-alcoholic steatohepatitis (NASH) using in silico techniques. An aspect of the disclosure is directed to an in silico method for determining drug activity of a plurality of drug targets by determining biomarker stratifier effects, calculating a biomarker stratifier score for a chosen disease phenotype; and calculating a pharmacomimetic genetic score using molecular biomarker stratifier data.