66 results about "Protein markers" patented technology

The invention provides a method and a system for predicting early gastric cancer prognosis by a circulating marker, and relates to the technical field of auxiliary diagnosis. The method comprises the following steps: performing multi-omics detection on a blood sample based on a preset sampling time sequence to obtain a multi-dimensional time sequence characteristic data set containing three groups of heterogeneous data of circulating tumor DNA, exosomes and protein markers; calculating a change slope and a fluctuation variance of the heterogeneous data in adjacent time sequence intervals, constructing a dynamic variation feature matrix in combination with a standard attenuation weighting factor, and deeply mining spatial cross-correlation and sequence dependence features of the matrix to generate a multi-modal fusion feature fingerprint; and performing regression operation on the feature fingerprints by using an integrated learning stack model to obtain a dynamic prognosis risk score, and further retrieving a risk hierarchical mapping table to generate a prognosis evaluation result containing a survival curve. According to the method, multi-modal heterogeneous data can be effectively fused, the biological dynamic characteristics in the tumor postoperative recovery phase are captured, and the accuracy and timeliness of early gastric cancer prognosis prediction are remarkably improved.

The invention relates to the technical field of western blot analysis, and discloses a full-automatic micro western blot analyzer and an analysis method thereof. The full-automatic micro protein immunoblotting analyzer comprises a full-automatic control system, a horizontal control system, a protein separation system, a temperature control system, a liquid path control system, an ultraviolet curing module, an antibody incubation module and a chip scanning module, the horizontal control system controls the protein separation system to horizontally move and correct; the protein separation system carries out protein separation; the temperature control system is used for carrying out constant-temperature control and temperature adjustment; the liquid path control system is used for filling a constant-temperature reagent into the protein separation system and extracting waste liquid; the ultraviolet light curing module is used for carrying out in-situ immobilization on the separated protein; the antibody incubation module is used for performing antibody incubation on the fixed protein marker; and the chip scanning module is used for chip result reading and data processing. According to the invention, full-automatic control, accurate temperature control and automatic horizontal correction can be realized.

The application discloses an electrochemical sensor for detecting IBD protein markers and a preparation method thereof. The electrochemical sensor is composed of a CNT-embedded semi-cured PDMS flexible substrate, deposited gold nanoparticles and a nucleic acid sensing layer. The nucleic acid sensing layer comprises a tumor necrosis factor-alpha sensor, an interleukin 6 sensor, an interleukin 8 sensor, a transforming growth factor beta 1 sensor, a reference electrode and a counter electrode. The tumor necrosis factor-alpha sensor, the interleukin 6 sensor, the interleukin 8 sensor and the transforming growth factor beta 1 sensor all adopt single-stranded aptamers modified by a signal molecule methylene blue, and the nucleotide sequences corresponding to the single-stranded aptamers are SEQ ID NO. 1-4. The application can improve the modulus matching of the sensor and human tissue and excellent biocompatibility, realize accurate detection of low-concentration biomarkers and stable signal output of the sensor under a strain working condition.

The application belongs to the technical field of biomedicine, and particularly relates to a construction system of a cerebral amyloid angiopathy recognition model, a storage medium and a kit. Based on plasma proteomic data of cerebral amyloid angiopathy patients and normal old controls, six key protein markers closely related to cerebral amyloid angiopathy are screened out. The application also provides a model for recognizing cerebral amyloid angiopathy based on a combination of six plasma protein biomarkers. The model shows excellent performance in multiple independent data sets, can accurately distinguish cerebral amyloid angiopathy patients from normal old controls, and further distinguish cerebral amyloid angiopathy patients with high-risk cerebral hemorrhage risk from those with low-risk cerebral hemorrhage risk. The application provides a new tool for early diagnosis and hemorrhage risk assessment of cerebral amyloid angiopathy.

The present invention provides methods and compositions based on a non-naturally occurring nucleic acid construct encoding a fusion protein for quantifying secretion levels in an individual cell, which may comprise a protein sequence comprising a cytoplasmic domain, a transmembrane domain, and a vesicular domain, wherein the vesicular domain may comprise a sequence of protein marks, wherein upon expression of the fusion protein by a cell, the fusion protein localizes to the membrane of a secretory vesicle such that the protein mark is located in the lumen of the secretory vesicle, and wherein the protein mark binds to a cell-impermeable marker;whereby, after the secretion of the contents of the secretory vesicle, the protein tag is exposed to the cell-impermeable marker, the fusion protein is recycled back into the cell, and the individual cell is tagged with the marker in relation to the amount of secretion.

The invention discloses a plasma protein marker for identifying or assisting in identifying parathyroid cancer and parathyroid adenoma and application of the plasma protein marker. The method comprises the following steps: firstly, collecting plasma specimens of a parathyroid carcinoma patient and a parathyroid adenoma patient before an operation, and screening through an unmarked quantitative proteomics technology to obtain 24 differential expression proteins; on the basis of the other part of plasma specimens of the parathyroid carcinoma patient and the parathyroid adenoma patient collected before the operation, the 24 differential expression proteins are verified through a parallel reaction monitoring technology; finally, three plasma protein markers (myoglobin, coronin-1A and a polyimmunoglobulin receptor) which can be used for identifying the parathyroid carcinoma and the parathyroid adenoma are obtained. Experiments prove that the plasma protein marker or the combination thereof can be used for auxiliary differential diagnosis of parathyroid carcinoma and parathyroid adenoma, and has important significance for improving the accuracy of preoperative diagnosis of parathyroid carcinoma.

The invention provides a multi-omics integrated marker for early screening of colorectal cancer, which comprises an lncRNA marker combination, a protein marker combination, an mRNA marker combination, a metabolism marker combination and a methylation marker combination, and relates to the technical field of gene detection and medical treatment. According to the invention, 11 groups of colorectal cancer tissues and para-carcinoma tissues paired with the colorectal cancer tissues are subjected to transcriptome, proteome and metabolome sequencing, and 61 cases of colorectal cancer tissues and 24 cases of para-carcinoma tissues are subjected to simplified methylation sequencing; by integrating and analyzing the multi-omics data, a multi-level interaction network is obtained, and the network contains lncRNA, protein, mRNA, metabolites and DNA methylation markers which have a close interaction relationship, and has a wide application prospect in diagnosis and treatment of colorectal cancer.

Provided are diagnostic and treatment methods,based on plasma protein markers for neurodegenerative diseases such as mild cognitive impairment (MCI) and Alzheimer's Disease (AD),as well as kits for diagnosing and / or treating these condition.Machine learning systems and methods for assessing the risk for a subject having a neurodegenerative disease based on measured protein marker levels are also provided.

The application discloses a combination of protein markers and clinical indexes related to leukoaraiosis, products and applications thereof. The protein marker combination comprises P05198, P00966, Q8IZP0 and P48061. The clinical indexes comprise MMSE, CTTtrail1 and SDMT. The application also provides applications, kits and computer program products of the combination. The combination can be used for quickly, conveniently and economically identifying leukoaraiosis. The computer program product has good model performance and shows relatively accurate prediction ability, and has clinical use and promotion value.

Provided are diagnostic and treatment methods,based on plasma protein markers for neurodegenerative diseases such as mild cognitive impairment (MCI) and Alzheimer's Disease (AD),as well as kits for diagnosing and / or treating these condition.Machine learning systems and methods for assessing the risk for a subject having a neurodegenerative disease based on measured protein marker levels are also provided.

This invention discloses the application of urinary microvesicle proteins as diagnostic markers for renal cell carcinoma. The protein markers derived from urinary extracellular vesicles associated with clear cell renal carcinoma are characterized by being selected from one or more of the following proteins: CSPG4, AQP1, PLIN2, CA9, and HAVCR1. The invention also describes the application of reagents for detecting these protein markers in the preparation of auxiliary diagnostic reagents for clear cell renal carcinoma. The inventors, using flow cytometry, analyzed 200 patients and found that five proteins derived from urinary extracellular vesicles could effectively distinguish patients with clear cell renal carcinoma from controls (including healthy individuals, patients with benign renal tumors, patients with benign renal cysts, and patients with chronic kidney disease).

The present invention relates to an integrated centrifugal device and method for analyte processing, particularly for the separation, enrichment, labeling, and analysis of nanovesicles such as extracellular vesicles (EVs). The device leverages a compact, rotatable substrate to execute multi-step assay protocols that may include chromatographic separation, centripetal fluid transport, immuno-capture, and protein labeling, all under low-speed centrifugal conditions. The device architecture enables automated, hands-free operation without requiring ultracentrifugation or specialized personnel. Fluidic modules including sedimentation, chromatography, displacement, and multiple assay chambers may be functionally integrated through a series of valves, channels, and immiscible liquid-based displacement mechanisms, facilitating precise sample handling, minimal loss, and multiplexed analysis.

The application discloses a gastric cancer biomarker composition and a screening method and application thereof, and belongs to the technical field of bioinformatics; the screening method of the gastric cancer biomarker composition comprises the following steps: collecting blood samples of gastric cancer patients and healthy controls, performing high-throughput plasma proteomics detection, and screening out differentially expressed proteins; the candidate protein markers are verified by using a prospective cohort in the UK BioSample Bank, 17 kinds of core proteins are finally determined, and the gastric cancer biomarker composition is obtained; and a gastric cancer risk prediction model is constructed by combining clinical risk factors and the protein expression levels of the gastric cancer biomarkers. The gastric cancer risk prediction model constructed by the application can realize precise stratification of gastric cancer risks, and decision curve analysis shows that the net benefit of the gastric cancer risk prediction model is significantly better than that of a traditional screening method, so that the gastric cancer risk prediction model provides an efficient tool for early warning and personalized intervention of gastric cancer.

This invention relates to an immunoRaman multicolor imaging kit for the prediction and assessment of liver cancer. The immunoRaman multicolor imaging reagent contains five Raman probes, which are composed of Raman spheres and antibodies attached to the surface of the Raman spheres. The Raman spheres are polymerized from triple-bonded monomers with (i) acrylic acid or (ii) styrene and acrylic acid, with a particle size of 10–100 nm and a Raman shift of 1800–2800 cm⁻¹. ‑1 The antibodies used for the five Raman probes are selected from one of the following: AFP antibody, HBX antibody, GPC3 antibody, GS antibody, and CD34 antibody. The immunoRaman multicolor imaging reagent and kit provided by this invention can achieve one-step labeling and multiplex color development of five liver cancer-related protein markers in the same liver tissue section. Compared with multiplex fluorescence immunohistochemistry, this invention has significant advantages in both efficiency and accuracy. Experiments show that the detection results of this invention are consistent with clinical diagnostic results, demonstrating great application potential.

The application discloses a protein marker for predicting iodine uptake capacity of a thyroid cancer metastatic focus, a prediction method and a system, and belongs to the technical field of tumor medicine. The application provides 23 protein markers capable of being used for predicting iodine uptake capacity of a thyroid cancer metastatic focus, and the specific prediction method is as follows: the expression level of the protein marker in the metastatic focus tissue is obtained; the protein expression amount or abundance value is subjected to data preprocessing and standardization; the standardized protein expression amount is input into a pre-trained logistic regression model to obtain an iodine uptake positive probability value of the thyroid cancer metastatic focus, and the iodine uptake capacity of the sample is judged based on pre-determined classification threshold comparison. The method can depict iodine uptake related characteristics of the metastatic focus at a molecular level, provides an objective, quantifiable and reproducible iodine uptake capacity prediction scheme, provides an effective auxiliary basis for radioiodine treatment decision and patient risk stratification, and has clear application value and popularization significance.

The invention discloses a digestive tract tumor early screening system based on multi-omics data fusion, and relates to the technical field of tumor screening, the system comprises a double sample collection module, a synchronous detection module, a database support module, a fusion analysis module and a visual output module; according to the method, the accuracy and comprehensiveness of early screening of digestive tract tumors are improved through multi-omics data fusion, multi-dimensional data of fecal microbial genome DNA, metabolites, blood ctDNA and protein markers are integrated, biological information of four levels of florae, metabolism, genes and proteins is covered, and the accuracy and comprehensiveness of early screening of digestive tract tumors are improved through a three-level cross validation mechanism. According to the method, flora-metabolite synergy abnormality and gene-protein synergy abnormality can be recognized, the tumor risk value is calculated and the risk level is set in combination with positive threshold values and clinical weights in a multi-omics feature database, the detection rate of early tumors is increased, and the method has higher sensitivity especially for early digestive tract tumors without obvious symptoms.

The invention provides a urine protein marker related to biliary tract cancer immunotherapy and application of the urine protein marker, and belongs to the technical field of biomedicine. The urine protein marker related to biliary tract cancer immunotherapy comprises a non-receptor tyrosine phosphatase 13 type (PTPN13), an activation RNA polymerase II transcription coactivator p15 (SUB1), an MICAL-like 1 protein (MICALL1) and a valyl-tRNA synthetase 1 (VARS1), and a combination established by the four urine proteins can be used for predicting the curative effect and (or) prognosis of the biliary tract cancer immunotherapy. One or more of the four urine protein markers can be used for prediction and / or prognosis analysis of the immunotherapy curative effect of the biliary tract cancer through mass spectrometric detection or immunodetection.

Provided are a fluorescent probe, a preparation method therefor and a use thereof. The fluorescent probe sensitively and specifically responds to viscosity, and can be used for the specific fluorescence labeling of proteins as well as in the quantification, detection or kinetic study of proteins and the imaging of cells, tissues and living bodies.

The invention belongs to the technical field of plasma protein markers, and discloses a plasma protein marker and a risk prediction system for a heart failure onset risk of a type 2 diabetes mellitus patient, and the protein marker combination is applied to preparation of a kit for predicting the heart failure onset risk of the type 2 diabetes mellitus patient. The protein marker combination comprises a C-C motif chemotactic factor 24, a C-C motif chemotactic factor 7, a carcino-embryonic antigen related cell adhesion molecule 6, a fiber gelling protein 1, a follistatin, a polypeptide N-acetylgalactosamino transferase 5, an ADP ribosylation factor binding protein GGA1, a kallikrein 4, a nerve bundle protein, renin, a plasma protease C1 inhibitor and cardiac troponin I, the brain natriuretic peptide comprises a brain natriuretic peptide precursor, an N-terminal brain natriuretic peptide precursor, apolipoprotein C1, tetramer connexin, a Mepin A beta subunit and multi-ligand proteoglycan-4. The invention further constructs a risk score and prediction model for predicting the attack risk of the heart failure of the type 2 diabetes mellitus patient based on the protein marker.

The application provides a serum protein expression profile-based auxiliary diagnosis and curative effect evaluation system for adolescent depression, and belongs to the technical field of biological detection. The auxiliary diagnosis and curative effect evaluation system selects a combination of MANF, NDUFA13 and HYOU1 protein markers to construct an auxiliary diagnosis system for adolescent depression, has better identification efficiency than single detection index, effectively improves the diagnostic sensitivity and specificity, reduces the misdiagnosis and missed diagnosis, establishes quantitative input characteristics relying on objective protein expression data, discards the subjective judgment mode of a traditional scale, reduces human factor interference, has high stability and accuracy after sample training and blind verification of the diagnosis system, has a standard and normative overall method process, can realize non-invasive, objective and accurate early screening and disease risk prediction for adolescent depression, is convenient for clinical popularization and application, and helps early diagnosis and treatment of adolescent psychological diseases.

The invention discloses an electrochemical sensor for IBD protein marker detection as well as a preparation method and application of the electrochemical sensor. The electrochemical sensor is composed of a semi-cured PDMS flexible substrate in which CNT is embedded, deposited gold nanoparticles and a nucleic acid sensing layer, the nucleic acid sensing layer comprises a tumor necrosis factor-alpha sensor, an interleukin 6 sensor, an interleukin 8 sensor, a transforming growth factor beta1 sensor, a reference electrode and a counter electrode; the tumor necrosis factor-alpha sensor, the interleukin 6 sensor, the interleukin 8 sensor and the transforming growth factor beta1 sensor all adopt aptamer single chains modified by signal molecule methylene blue, and correspondingly adopt nucleotide sequences shown in SEQ ID NO.1-4. Matching and excellent biocompatibility of the sensor and human tissue modulus can be improved, and accurate detection of low-concentration biomarkers and stable signal output of the sensor under the strain working condition are achieved.

The application provides application of a protein marker in preparation of a product for diagnosing Parkinson or predicting Parkinson disease. The protein marker comprises CPA2 and / or DPEP1. The application solves the problem of poor effect of a product for diagnosing or predicting Parkinson disease in the prior art and is suitable for the Parkinson disease diagnosis product application field.

The invention relates to a pair of protein markers for diagnosing type 2 diabetes mellitus and application thereof, and belongs to the technical field of biological medicine. The invention identifies a pair of protein markers for diagnosing type 2 diabetes mellitus (T2DM), wherein the protein markers comprise HtrA serine protease 1 (HTRA1) and renal tubular interstitial nephritis antigen-like 1 (TINAGL1). The expression level of the protein marker has significant difference between type 2 diabetes patients and healthy control people. A random forest prediction model constructed on the basis of HTRA1 and TINAGL1 shows excellent discrimination performance, in an independent verification set, the area under a subject characteristic working curve is 0.992, and under the optimal cutoff value, the diagnosis sensitivity is 0.917, and the specificity is 1.000. The protein marker provided by the invention provides a brand new tool for noninvasive and early diagnosis of T2DM and high-risk population screening, and has important transformation application value.

The invention discloses an application of AHCY protein in pig intramuscular fat content character assisted breeding, and belongs to the technical field of biology. Intramuscular fat contents of longissimus dorsi muscles of ZYH and DLL pigs are detected, a proteomics technology is adopted, longissimus dorsi muscle differential protein is screened, and the characteristic of the longissimus dorsi muscle is obtained. And calculating a correlation coefficient and a P value of the IMF content, the differential protein expression quantity and the intramuscular fat content so as to identify the protein marker significantly related to the intramuscular fat content of the pig. It is found that AHCY protein abundance is positively correlated with pig intramuscular fat content, and a pig sample with high AHCY protein abundance is selected to have higher pig intramuscular fat content. The protein can be used as a marker related to the intramuscular fat content of pigs, and plays a role in assisted breeding.

To provide a method for detecting atopic dermatitis in a low-invasive or non-invasive manner.SOLUTION: The present invention collects protein markers for detecting atopic dermatitis from skin surface lipids collected from subjects. The present invention detects atopic dermatitis using the protein markers.SELECTED DRAWING: None

The invention belongs to the technical field of plasma protein markers and disease risk prediction, discloses a system and method for predicting the risk of diabetic retinopathy needing surgical treatment, and relates to a protein marker combination which simultaneously comprises 13 protein markers positively related to the risk of diabetic retinopathy needing surgical treatment. And 18 protein markers in negative correlation. According to the risk prediction method, the risk of the serious outcome is predicted in advance by systematically introducing plasma proteomics information and combining the plasma proteomics information with traditional clinical risk factors by taking the operative treatment type diabetic retinopathy as a core clinical outcome, and the risk of the serious outcome is predicted in advance. The method can quantify the overall risk level of the subject suffering from the diabetic retinopathy needing surgical treatment on the proteomics level, and effectively solves the problem that a risk prediction model taking the diabetic retinopathy needing surgical treatment as the outcome is lacked at present.

The application discloses a model for predicting changes of detection signals of proteins after perchloric acid precipitation of serum based on physicochemical properties of proteins and a construction method and application thereof, and the method comprises the following steps: obtaining detection signal intensities of the same protein in a perchloric acid precipitation treatment group and an untreated group in serum proteomics data through experiments, and calculating a signal change value log2FC as a target variable; calculating physicochemical property characteristics based on a protein amino acid sequence; dividing samples into a training set and a verification set, screening key features on the training set by using a feature screening algorithm, training a machine learning regression model, evaluating model performance on the verification set, and obtaining a prediction model; inputting an identifier of a protein to be predicted, automatically obtaining an amino acid sequence, calculating physicochemical property characteristics, and outputting a log2FC prediction value and a signal change direction determination result through the prediction model. The application can provide a quantitative tool for design of a serum proteomics sample pretreatment strategy and quantitative pre-evaluation of analysis of protein markers.

The invention discloses a PD-L1 protein high-sensitivity detection method and device based on optical fiber SPR (Surface Plasmon Resonance), and relates to the technical field of biomolecule detection. The method comprises the following steps: preparing a disposable optical fiber sensing probe plated with a gold film; a DNA regular tetrahedron containing a PD-L1 aptamer is fixed through an Au-S bond, and a PD-L1 monoclonal antibody is used for functionalizing gold nanoparticles to amplify a signal; connecting an optical path through a self-adaptive coupler and optimizing a coupling state in real time; collecting dual-channel signals to construct a data set; optimizing a buffer system, detecting labeled serum and establishing a calibration curve; finally, the kit is applied to clinical serum sample detection. According to the present invention, the detection sensitivity and the specificity are significantly improved through the optical fiber SPR technology, and the method has advantages of real time, trace sample consumption, low detection limit, good repeatability and the like, can be widely used for the rapid detection of the clinical tumor immunotherapy related protein marker, and has important practical application value.