269 results about "Tumor marker" patented technology

The invention relates to the technical field of medical information processing, in particular to a method for constructing a model for predicting the onset risk of hyperglycemia-related ovarian cancer, which comprises the following steps of: performing isolated analysis on the blood glucose level of a patient during each physical examination, and calculating the blood glucose abnormality of the patient during each physical examination in combination with the local trend characteristics of the blood glucose level, so as to determine the onset risk of hyperglycemia-related ovarian cancer; analyzing the difference between the blood glucose value of the patient and the overall trend information, and evaluating the abnormal blood glucose condition in combination with the abnormal blood glucose degree of the patient; the prediction credibility of the blood glucose value of the patient during each physical examination is calculated by utilizing the incidence relation between the blood glucose value and the tumor marker concentration in different periods and combining the evaluation result of the abnormal blood glucose condition of the patient during each physical examination; therefore, the blood sugar value data is subjected to data cleaning so as to further predict the onset risk of the hyperglycemia-related ovarian cancer of the patient. According to the method, the prediction accuracy of the onset risk of the hyperglycemia-related ovarian cancer is effectively improved.

The invention discloses a novel tsRNA high-sensitivity detection kit based on CRISPR (clustered regularly interspaced short palindromic repeats) / Cas13a-Cas14a, and belongs to the field of tumor marker detection. The tsRNA (tRNA-derived small RNA) is a diagnostic marker which is found recently and has great potential. In order to realize the clinical transformation of tsRNA as soon as possible, the tsRNA detection kit is developed on the basis of nuclease P1 combined with CRISPR / Cas13a-Cas14a linkage dual systems, and comprehensive, ultra-sensitive, high-specificity, low-cost and rapid tsRNA detection is realized through multiple signal amplification. Compared with the traditional technology, the sensitivity of the method is improved by 105-107 times, 1% of tsRNA in the mixture can be detected, and the method has more advantages in clinical application. Therefore, a new scheme is provided for application of the tsRNA in clinical diagnosis of diseases, and meanwhile, a reliable technology is provided for mechanism research of the tsRNA in occurrence and development of the diseases.

The invention relates to the technical field of medical treatment, in particular to an intelligent general surgery preoperative risk assessment system which comprises a data acquisition module, a data fusion and processing module, a feature extraction module, a risk assessment module, a prediction and optimization module and a visual display module. The data fusion and processing module adopts a multi-modal data fusion algorithm to generate a patient comprehensive information model, the feature extraction module extracts cardiovascular health status, renal function and tumor marker key features, and the risk assessment module constructs a preoperative risk assessment model to generate a preoperative risk score; the prediction and optimization module predicts the risk of postoperative complications, and the visual display module displays an evaluation result and a prediction result in real time through a graphical interface; according to the method, the accuracy and scientificity of preoperative risk assessment and postoperative complication prediction are remarkably improved, and reliable support is provided for postoperative management of patients.

The invention belongs to the technical field of in-vitro diagnosis, and particularly relates to a detection kit and a detection method for a pretumor marker. The kit comprises an elisa plate coated with a captured antibody, an HRP labeled antibody, an antigen standard substance, a washing solution, a developing solution and a stop solution, the capture antibody and the HRP labeled antibody are both prepared from a monoclonal antibody of the anti-SLC31A1 protein. According to the detection method of the kit for detecting the pretumor marker, the SLC31A1 protein content in human serum is detected through the kit, the specificity is high, a large batch of samples can be rapidly detected in a high-throughput mode, the cancer risk of a to-be-detected crowd can be effectively judged, and therefore relevant patients can find and treat the pretumor marker in advance, treatment prognosis is improved, and the death rate is reduced.

The invention relates to the technical field of spectral analysis and biomedical detection, and discloses an SERS (Surface Enhanced Raman Scattering) spectrum quantitative detection method and system based on interpretable stacked ensemble learning. The method comprises the following steps: acquiring SERS spectral data of serum tumor marker standard substances with different concentration gradients; performing baseline correction and normalization preprocessing on the data, performing sparse feature selection by using an LASSO algorithm, and screening out key spectral features to construct a sample data set; constructing an interpretable stacking integration model, wherein the model adopts a base learner layer and a meta learner layer; training the model by using the training set, optimizing model hyper-parameters by using a cross validation strategy, and establishing a mapping relationship between spectral features and tumor marker concentrations; and collecting SERS spectral data of a to-be-detected serum sample, extracting key spectral features, inputting the key spectral features into the trained interpretable stacked integrated model, and outputting a concentration predicted value of the tumor marker in the to-be-detected serum sample. The method has the advantages of high precision, universality and molecular level interpretability.

Disclosed herein are methods, compositions, and devices for use in early detection of cancer. The methods include sequencing a panel of regions in cell-free nucleic acid molecules and detecting one or more tumor markers that are indicative of a cancer.

The invention relates to the technical field of tumor markers, in particular to a pancreatic cancer early screening marker combination based on blood protein and application of the pancreatic cancer early screening marker combination. Through proteomics analysis and bioinformatics screening, 12 kinds of proteins such as NME3, HPGDS, CEACAM5, TNFSF12, SCG3, VTCN1, GFRA1, KRT19, TMPRSS12, NELL2, KAZALD and MMP12 are determined to serve as the potential early screening markers of the pancreatic cancer. Researches show that the combination of the proteins can effectively distinguish pancreatic cancer patients from non-pancreatic cancer patients, and has good sensitivity and specificity. A screening model constructed based on the protein combination can be applied to auxiliary diagnosis, risk assessment and population screening of pancreatic cancer, and has important clinical transformation value.

To provide a novel squaraine dye-peptide complex that enables selective detection of esterase, being one of tumor markers.SOLUTION: A squaraine dye-peptide complex is prepared by incorporating an oligopeptide between two squaraine dyes represented by formula (1), where R1B and R2B each independently represent a C1 to C30 monovalent aliphatic hydrocarbon group, with at least one having a carboxyl group at a terminal, and R3B and R4B each independently represent H or a carboxyl group, with at least one being a carboxyl group.SELECTED DRAWING: Figure 3

Methods for detecting a tumor using a sample in which tumor DNA fragments are present only in a very low concentration, beyond the statistical limit of detection, where methods include: obtaining sequence data for tumor nucleic acid from a tumor from a subject and analyzing the sequence data to identify a plurality of tumor-specific variants that are in the tumor nucleic acid and that are not in non-tumor nucleic acid of the subject; selecting a marker variant that appears duplicated in tumor nucleic acid (compared to non-tumor nucleic acid) a greater number of times than other ones of the tumor variants; performing an assay to detect the marker variant in a sample from the subject; and reporting the presence of the tumor in the subject when the assay is positive for the marker variant in the sample.

The invention belongs to the technical field of biomedical detection, and discloses a Raman spectrum analysis device for quantitative detection of hematologic tumor markers, which comprises a blood collection centrifugal unit with a self-adaptive load regulation mechanism for monitoring blood density and components in real time, centrifugal force and time parameters are automatically adjusted according to the blood density and components; the optical fiber Raman spectrometer is provided with an automatic wavelength calibration system, and an ultrafast laser pulse transmitter and a high-sensitivity photon counting detector are integrated on the optical fiber Raman spectrometer. Raman scattering signals are enhanced by adopting a quantum entanglement light source and a nonlinear optical crystal; according to the invention, the detection capability on low-concentration tumor markers can be obviously improved. Due to the improvement, the device can accurately detect the existence of the tumor marker at the early stage of cancer, and powerful support is provided for early treatment of a patient.

The invention discloses an immune quantitative detection device for tumor markers, relates to the technical field of medical detection, and aims to solve the problems of complicated operation, long detection period and poor portability in immune quantitative detection of tumor markers in the prior art. Comprising a shell, a disposable detection card, a multi-channel micro-fluidic chip, a high-sensitivity sensing system, a micro magnetic control incubation module, an AI auxiliary image recognition system and a wireless transmission module, the disposable detection card is used for accommodating the multi-channel micro-fluidic chip and a reaction reagent, and the multi-channel micro-fluidic chip is respectively aligned with the high-sensitivity sensing system and the micro magnetic control incubation module; the high-sensitivity sensing system is composed of a surface plasma resonance sensor and a quantum dot fluorescence labeling module, and the surface of a sensing chip of the surface plasma resonance sensor is modified with a tumor marker specific capture antibody. The method has the advantages of convenient detection and high efficiency and precision.

The invention provides a serum tumor marker detection array optimization method and system.The method is applied to a control module of an array device.The method comprises the steps that when a multi-needle detection platform conducts serum tumor marker detection on a preset sample, preliminary expression information sent by the multi-needle detection platform is obtained; acquiring patient medical history information, iconography information and pathology information corresponding to the preset sample; inputting the preliminary expression information, the patient medical history information, the iconography information and the pathology information into a pre-constructed Bayesian analysis model, and outputting a prediction weight, a prediction disease progress direction and a correlation marker corresponding to each tumor marker to generate target information; wherein the target spot information comprises a plurality of target markers; and controlling the multi-needle detection platform to perform serum tumor marker detection on the preset sample again according to the target spot information to complete array optimization of serum tumor marker detection. Therefore, an efficient and innovative solution is provided for early diagnosis and monitoring.

The invention discloses a big data-based digestive system department prediction analysis system. The system comprises a data acquisition module, a knowledge graph fusion module, a disease course evolution prediction module and an intelligent diagnosis and treatment decision module. The invention relates to the technical field of medical health information, in particular to a big-data-based predictive analysis system for the department of gastroenterology. According to the scheme, a physiological signal is reconstructed by using a multi-scale mask auto-encoder, and the signal and a text are aligned; mapping knowledge graph regularization is introduced, the joint code is mapped to a digestive system knowledge graph space, and medical semantic representation is obtained; constructing a time sequence attenuation dynamic graph through the dynamic memory graph, and adding graph convolution gating; an embedded differential equation module simulates inflammation and tumor marker evolution to realize accurate prediction; patient state vectors are constructed based on multi-modal coding, medicines are rapidly selected by using a scoring function, a treatment process is modeled as a Markov decision, and a strategy network, a value network and PPO optimization are combined to realize balance of curative effect and income.

This invention relates to aggregation-induced emission probes with specific responses to tumor markers and their applications, belonging to the field of biochemistry. This invention utilizes molecular structure modulation to prepare a series of molecules possessing large Stokes shifts, resistance to photobleaching, near-infrared II (NIR-II) emission, and aggregation-induced emission properties. Different self-eliminating groups are attached to the dimethylamino group of the molecule via quaternization or to the pyridine group via pyridinium salting. By controlling the structure of these self-eliminating groups, activatable luminescent probes responding to different tumor markers can be constructed. These probes integrate deep NIR-II imaging, aggregation-point luminescence, large Stokes shifts, and marker-specific responses, providing a new approach for precise imaging diagnosis of tumors.

The invention provides an activatable semiconductor polymer as well as a preparation method and application thereof. The activatable semiconductor polymer disclosed by the invention can be efficiently accumulated at a tumor site, due to the existence of a side chain electron withdrawing group, the fluorescence of the polymer is in a quenched state, the fluorescence of the polymer is recovered after tumor markers such as biological mercaptans, active oxygen and cathepsin B are respectively responded, and accurate imaging and sonodynamic therapy can be carried out at the tumor site. Meanwhile, the activatable semiconductor polymer can mark immune cells (such as dendritic cells and macrophages) and track the process of transferring the immune cells from tumors to tumor drainage lymph nodes.

The invention relates to the technical field of biology, in particular to an eccDNA marker and application thereof in prognosis prediction of colorectal cancer. According to the present invention, the chromosome outer circular DNA is adopted as the colorectal cancer prognosis prediction marker, and the colorectal cancer prognosis prediction marker is significantly superior to the common tumor marker when the colorectal cancer prognosis prediction marker is used; a colorectal cancer prognosis prediction model constructed by adopting the eccDNA marker provided by the invention is high in diagnosis accuracy, high in sensitivity and strong in specificity, and has excellent application potential in clinical risk stratification.

The invention discloses a brain tumor real-time identification system and method based on cortical electroencephalogram signals, and relates to the technical field of medical artificial intelligence, and the method comprises the following steps: obtaining multi-channel ECoG signals in real time; the multi-channel ECoG signals are updated in real time, the multi-channel ECoG signals updated in real time are preprocessed, and the preprocessed multi-channel ECoG signals are obtained; performing channel feature extraction on the ECoG signal of each channel to obtain various ECoG signal features under each channel as channel features; calculating segmentation thresholds of different channel characteristics under each channel based on an automatic threshold segmentation algorithm; carrying out confidence evaluation on the segmentation threshold values of different channel characteristics under each channel; and marking the channel of which the confidence coefficient is smaller than a set tumor marking threshold value as a tumor area. Accurate positioning of a tumor area can be achieved, functional state changes of the cerebral cortex can be reflected in real time, and doctors can conveniently master real-time changes of cortex functions in time.

Provided is a methylated tumor marker STAMP-EP2 and uses thereof in preparing a tumor diagnostic reagen. The tumor marker STAMP-EP2 herein is hypermethylated in all tumor types, is hypomethylated in corresponding normal tissue, and has high sensitivity and specificity; primers for detecting STAMP-EP2 may be used to prepare a tumor diagnostic kit.

The present invention provides a protein detection method and detection preparation, which realizes efficient enrichment of target protein through mesoporous silica-graphene oxide composite nanoporous material, completes specific immune capture in combination with magnetic nanoparticles modified with targeted antibodies, and realizes single molecule separation using a microfluidic chip of a three-dimensional hydrogel antibody array. Signal amplification adopts enzyme-labeled secondary antibody-gold nanorod conjugate, enhances the fluorescence signal through the plasma resonance effect, and corrects the background noise in combination with a convolutional neural network algorithm, which significantly improves the detection reliability; experiments show that the detection limit of this method is as low as 0.12pg / mL, the linear range covers 0.5-100,000pg / mL, the single cell detection error is ±7.8%, the batch repeatability (CV=4.2%), the nonspecific adsorption rate is only 1.1%, and the detection time is shortened to 1.2 hours. The detection method of the present invention is suitable for ultra-sensitive detection of tumor markers, especially in the in situ analysis of CTCs with clinical application potential.

This invention relates to the field of biomedical technology, providing the application of glycoprotein tumor biomarkers in the preparation of cancer diagnostic reagents. The glycoprotein tumor biomarker is a CLU_N_291_HexNAc(4)Hex(5) site-specific glycosylation modification. This invention utilizes CLU_N_291_HexNAc(4)Hex(5) site-specific glycosylation modification as a pan-cancer biomarker, combining it with existing conventional tumor markers (CEA, CA19-9, CA50, CA242, CA72-4, CA125, CA15-3, AFP, SCC, CYFRA21-1, PROGRP, NSE, HE-4, or PSA) for early cancer screening, assessment, diagnosis, postoperative monitoring, and / or prognostic analysis, particularly for the diagnosis of pancreatic cancer, cholangiocarcinoma, gastric cancer, lung cancer, breast cancer, or ovarian cancer.

The invention relates to the technical field of biological medicine detection, and particularly discloses an electrochemical luminescence kit for rapidly detecting tumor markers, which comprises a capture molecule, an electrochemical luminescence ECL labeled molecule, a biotin labeled detection antibody, a streptavidin fixed plate and a liquid reagent, according to the present invention, the capture molecule, the ECL labeling molecule, the biotin labeling detection antibody and the streptavidin fixation platform interact to form the novel multi-protein complex, such that each target antigen can initiate multiple signal conversion during the reaction process; theoretically, the tetramolecular structure can obviously improve the signal transmission efficiency, so that the low-abundance tumor marker can be quickly and accurately detected, and the high-specificity recognition of the target tumor marker is realized by capturing molecules and detecting antibodies. The high affinity between biotin and streptavidin is utilized, so that non-specific binding is greatly reduced, background signals are reduced, and the accuracy and reliability of detection are improved.

The invention discloses a tumor specific signal analysis device and equipment for uncertain pulmonary nodules and a storage medium, and relates to the technical field of electrical digital data processing.The device constructs a LungTCR database containing lung cancer tissue enrichment type and blood enrichment type CDR3 sequences through TCR beta chain sequencing and IMGT database comparison, and the LungTCR database is used for analyzing the lung cancer tissue enrichment type and blood enrichment type CDR3 sequences. A basis is provided for tumor specific signal recognition; a Needleman-Wunsch algorithm and an editing distance threshold value are adopted for screening, so that high-precision sequence matching is realized; through quantification of lung cancer tissue scores, blood scores and mutation specificity scores, a TCR feature group with biological significance is formed; and finally, the TCRnodseek plus model trained by clinical and image features is combined, a reliable malignant probability prediction value can be output, the model AUC can reach 0.90 or above, and the model is obviously superior to traditional imaging diagnosis and tumor markers.

The invention belongs to the technical field of medical detection, and particularly relates to an electrochemical device for detecting tumor cells in blood and a preparation method of the electrochemical device. The electrochemical device comprises a biocompatible flexible substrate, a side gate electrode, a source electrode, a drain electrode, an insulating film, a hydrophilic semiconductor and a ligand for capturing a tumor marker, the hydrophilic semiconductor is arranged between the source electrode and the drain electrode, and the biological ligand for capturing the tumor cell marker is arranged on the side gate electrode; the side gate electrode is used for generating induced voltage when a tumor in a blood vessel is captured, so that induced current is generated between the source electrode and the drain electrode; the insulating film is deposited on the part outside the channel and the side gate electrode, so that crosstalk between adjacent electrodes is prevented. The invention also discloses a manufacturing method and a testing method of the electrochemical device. The electrochemical device can realize minimally invasive and real-time detection, and is simple in structure, low in power consumption, high in stability, small in detection wound and high in detection speed.

The invention discloses an SERS (Surface Enhanced Raman Scattering) diagnostic apparatus based on an enzyme-like catalysis Au-graphene nano composite material, and relates to the technical field of spectrum diagnostic equipment, the SERS diagnostic apparatus comprises a display, a shell, an imaging module, a sample loading module, a grating light source module, a host, a laser light source module and a light path module, the sample loading module comprises a disposable micro-fluidic chip box and a sample loading table, an enzyme-like catalysis Au-graphene nano composite material is fixed on the inner channel wall of the disposable micro-fluidic chip box and is used for performing dual-mode signal amplification on tumor markers in urine. Urine sampling-detection can be completed at a time, the whole process is non-invasive, the enzyme-like catalysis Au-graphene nano composite material has high SERS enhancement and peroxidase-like activity, does not agglomerate in high-ionic-strength urine, can be seamlessly connected into a conventional urine detection process through dual-mode signal amplification and high sensitivity in cooperation with a Raman imaging technology and an AI analysis technology, and can be applied to the field of urine detection. And early rapid screening and dynamic monitoring of the malignant tumor of the urinary system are realized.

The invention relates to the technical field of biomedical detection, in particular to a multi-dimensional tumor marker joint detection device and a using method thereof.The device comprises a sample processing module, a sequencing module, a marker extraction module, a feature fusion and detection module and a result output module, and 6 types of markers such as chromosome copy variation, microsatellite instability and the like are extracted respectively. The method comprises the following steps: collecting a body fluid sample to extract cfDNA, directly constructing a library without special treatment, obtaining effective data through whole genome sequencing, synchronously extracting six types of markers through each module of the device, optimizing an algorithm to adapt to low-depth data, inputting an integrated learning model to output a risk score, and finally outputting related information by a result output module. The method does not need special experimental treatment, realizes low-cost and high-accuracy joint detection, and meets the clinical large-scale screening requirements.

The invention relates to the technical field of biological medicine and tumor diagnosis, and particularly discloses a human epididymal protein 4 tumor marker and application thereof. The high expression of the human epididymal protein 4 tumor marker gene is closely related to the prognosis of an ovarian cancer patient, and the human epididymal protein 4 can be used as an ovarian cancer tumor marker and has important significance on the diagnosis, treatment and prognosis evaluation of ovarian cancer; the invention provides a detection primer pair of a human epididymal protein 4 tumor marker and application of the detection primer pair as an ovarian cancer diagnosis kit, ovarian cancer diagnosis can be more accurate and rapid, the early diagnosis level of ovarian cancer is improved, and the invention further provides a human epididymal protein 4 tumor marker expression inhibitor siRNA which can be used for detecting the human epididymal protein 4 tumor marker. When being used for inhibiting the expression of the human epididymal protein 4 tumor marker, the human epididymal protein 4 tumor marker has a good interference effect and has clinical application potential.

The present application relates to the field of tumor markers, in particular to a fascin acetylation modification which can be used as a tumor diagnosis and prognosis analysis marker, a detection reagent and application thereof. The present application is directed to the fact that acetylation modification at K41 site of fascin significantly inhibits the cancer-promoting activity of fascin protein, and in esophageal cancer tissue, the proportion of fascin with acetylation modification at K41 site is significantly lower than that of wild-type fascin in para-cancerous tissue. Based on the acetylation at K41 site of fascin, a specific antibody for acetylation at K41 site of fascin is developed, so as to conduct clinical application research on acetylation at K41 site of fascin, and establish an esophageal cancer prognosis analysis model and targeted treatment.

The application provides a DNA sensor based on gold nanoparticles (AuNPs) for visual detection of miRNA-10b. The sensor is obtained by coupling AuNPs-S1 through mercapto between gold nanoparticles (AuNPs) and probe S1; and coupling AuNPs-S2 through mercapto between gold nanoparticles (AuNPs) and probe S2. The combination of the probe and the gold nanoparticles is more firm due to mercapto modification, so that the stability and detection repeatability of the DNA sensor are improved. The aggregation of AuNPs is triggered by hybridization between the target miRNA-10b and the probe, the transition of AuNPs from dispersion to aggregation in the buffer solution is regulated, and the color change from red to blue is visible to the naked eye, so that the rapid and visual detection of the tumor marker miRNA-10b is realized. The linear range is 10 pM-200 nM, and the sensor has excellent stability in serum environments (1%, 10%) and enzymatic environments (5 U / mL DNase and 2 U / mL DNase), and high selectivity. An efficient tool is provided for cancer diagnosis.

Provided for herein in several embodiments are anti-BCMA binding moieties. These anti-BCMA binding moieties may be used in BCMA-directed chimeric antigen receptors (CARs). Also disclosed herein are immune cell-based compositions comprising the anti-BCMA binding moieties and BCMA-directed CARs. In several embodiments, the immune-cell based compositions also target an additional tumor marker and / or an additional epitope of BCMA. In several embodiments, the BCMA-directed CAR is expressed in a Natural Killer cell. In several embodiments, combinations of BCMA-CAR-expressing NK cells are administered in conjunction with, for example CAR-expressing NK cells and / or CAR-expressing T cells that are directed to an additional cancer marker and / or an additional epitope of BCMA. Also provided for herein are methods and uses of the chimeric antigen receptors in immunotherapy.

This application relates to the field of biotechnology, specifically disclosing the application of immune cell subsets in the preparation of detection products for assessing the efficacy of neoadjuvant therapy and the risk of recurrence and metastasis in breast cancer. The detection method described in this application is non-invasive and convenient, requiring only peripheral blood, and is easy to repeat sampling and dynamic monitoring. This application also provides a predictive model for the efficacy of neoadjuvant therapy in breast cancer, and a predictive model for the risk of recurrence and metastasis in breast cancer treated with neoadjuvant therapy. The constructed predictive model has a high AUC value (0.82-0.87), and good sensitivity and specificity. Furthermore, through regular postoperative monitoring, abnormal dynamic changes in immune cell subsets can be detected, potentially indicating signs of recurrence earlier than imaging and traditional tumor markers. This helps identify advantageous populations before treatment and high-risk populations after treatment, enabling optimization of treatment plans and individualized adjustment of follow-up density.