29 results about "Tumor marker" patented technology

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 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.

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.

This invention discloses a method for identifying intrahepatic cholangiocarcinoma (ICC) based on serum peptide characteristics and its application. The invention collects serum samples from three groups: individuals with ICC, those with benign liver disease, and healthy controls. Peptide characteristic peaks associated with ICC are screened, and a model is constructed using a logistic regression algorithm. This model demonstrates excellent discriminative ability on both the training and independent test sets, with AUCs reaching 0.986 and 0.963, respectively, significantly outperforming traditional tumor markers CA19-9 and CEA. The peptide characteristic peak combination and the discriminative model constructed based on it can be used for early detection of ICC, differentiation between benign and malignant cases, and screening of high-risk populations. It offers advantages such as rapid detection, standardized procedures, strong early ICC identification capability, and low false positive rate, providing a highly sensitive, specific, and widely applicable non-invasive screening tool for clinical use.

The application discloses a chemiluminescence kit for detecting CA72-4 based on an acridinium ester system, which comprises magnetic microspheres connected with anti-CA72-4 monoclonal antibody mAb1, an acridinium ester label of anti-CA72-4 monoclonal antibody mAb2, CA72-4 antigen calibrators, a cleaning solution, an excitation solution and the like. The kit is simple to operate, the whole detection time is 20 min, the detection efficiency is greatly improved, the test precision is relatively high, and the CV is not higher than 5%. In addition, the test results of clinical samples show that the kit has a good clinical coincidence rate, and has important significance for the auxiliary diagnosis of various tumors.

The application discloses a kind of Chinese lung cancer high-risk population risk prediction method based on multi-modal feature fusion, comprising: step 1, data acquisition;Step 2, data preprocessing;Step 3, multi-source risk feature evaluation and screening: verify and evaluate the prediction efficiency of lung cancer epidemiology risk score, tumor marker and lung cancer related multi-gene risk score, and screen out the optimal single dimension score of each dimension from it;Step 4, multi-modal score construction: according to the smoking status of participants, the population is divided, the optimal single dimension score of each dimension screened out is standardized, then the multi-source features are fused using Logistic regression model and the weighted coefficients are optimized, and the multi-modal lung cancer risk prediction score suitable for smokers and non-smokers is constructed respectively.The present application has superior discrimination performance, can accurately identify high-risk individuals, guide subsequent imaging examination and early intervention, and improve the early diagnosis rate and treatment effect of lung cancer.

The present application belongs to the field of biosensing technology and tumor marker instant detection, and particularly relates to a preparation method of a human epididymis protein 4 (HE4) biosensor based on electrochemical principle and detection application thereof. The present application constructs an "antibody-antigen-antibody" sandwich complex structure, realizes simple, accurate and efficient detection of serum HE4; the KB-PEI@AuNPs composite material is used as a base material, which can effectively fix antibody molecules and promote electron transmission of the electrode interface, and significantly improves the conductive performance of the sensor; by using the specific binding principle of antigen and antibody, the CoFeZn-MOF prepared by the present application has peroxidase-like activity as a nanoenzyme; when the electrode modified by the probe CoFeZn-MOF / Ab2 is detected, the nanoenzyme can catalyze H2O2 to decompose to generate active oxygen substances such as hydroxyl radicals; this redox process triggers electron transfer, thereby causing a change in the current signal, thereby exhibiting i-t rapid response characteristics, high sensitivity performance and a lower detection limit.

Embodiments disclosed herein generally relate to identifying necrotic tissue in a multiplex immunofluorescence image of a sample section. In particular, aspects of the present disclosure relate to: accessing a multiplex immunofluorescence image of a sample section comprising a first channel for a nuclear marker and a second channel for an epithelial tumor marker, wherein the sample section comprises one or more necrotic tissue regions; providing the multiplex immunofluorescence image to a machine learning model; receiving an output of the machine learning model, the output corresponding to a prediction that the multiplex immunofluorescence image comprises one or more necrotic tissue regions at one or more particular portions of the multiplex immunofluorescence image; generating a mask for subsequent image processing of the multiplex immunofluorescence image based on the output of the machine learning model; and outputting the mask for the subsequent image processing.

This invention relates to the field of medical data analysis technology, specifically to a patient response assessment method and system based on chemotherapy data analysis. The method includes the following steps: accumulating drug administration time and dose to form a cumulative exposure sequence; matching biomarker time and concentration to form response pairs; extracting adjacent differences and dividing assessment intervals according to correlation; calculating the interval change ratio to obtain an assessment coefficient sequence; and combining the drug administration time window and the response time window to calculate the chemotherapy response result. In this invention, by time matching and difference analysis of cumulative exposure and tumor marker concentration data, the relationship between exposure changes and indicator changes is characterized, reducing fixed threshold assessment bias, improving the utilization of time series data, enhancing the accuracy and individual adaptability of assessment results, improving the reliability of chemotherapy response assessment, and stabilizing assessment consistency.

1. The name of the design product: kit (tumor). 2. The use of the design product: the design product is used in the process of detecting tumor markers in medical treatment. 3. The design points of the design product: the combination of shape and pattern. 4. The picture or photo that best indicates the design points: usage state figure 1.

The embodiments of the present application disclose a tumor marker, a kit and a use method for judging early hepatocellular carcinoma. The kit of the embodiments of the present application takes the first DNA shown as SEQ ID NO. 1 and / or the second DNA shown as SEQ ID NO. 2 as a judgment marker, judges whether the ex vivo sample is a positive sample of early hepatocellular carcinoma by judging the methylation degree of the CpG site in the first DNA and / or the second DNA in the ex vivo sample, thereby prompting whether the organism derived from the ex vivo sample has early hepatocellular carcinoma lesion. The kit of the embodiments of the present application has good specificity and sensitivity for the positive judgment of early hepatocellular carcinoma based on the specific tumor marker, and can be applied to the screening and judgment of early hepatocellular carcinoma.

This invention provides an activatable semiconductor polymer, its preparation method, and its applications. The activatable semiconductor polymer of this invention can efficiently accumulate at tumor sites. Due to the presence of electron-withdrawing groups on its side chains, the polymer's fluorescence is quenched. Upon response to tumor markers—biothiols, reactive oxygen species, and cathepsin B—the polymer's fluorescence recovers, enabling precise imaging and sonodynamic therapy at the tumor site. Simultaneously, the activatable semiconductor polymer of this invention can label immune cells (such as dendritic cells and macrophages) and track their metastasis from the tumor to the draining lymph nodes.

The application relates to the technical field of medical data processing, and discloses an osteosarcoma prognosis risk prediction system. The osteosarcoma prognosis risk prediction system is constructed by integrating non-invasive and easily-obtained multi-dimensional clinical data (including demographic and baseline clinical data, tumor load and malignancy data, and serum tumor marker data) and training an optimized machine learning model (such as a random forest). The osteosarcoma prognosis risk prediction model and system can realize early warning, real-time monitoring and accurate grading, can realize early, real-time and non-invasive evaluation and grading early warning of the prognosis risk of patients, solve the problems that existing monitoring means are lagging, invasive and cannot be frequently performed, provide objective and quantitative basis for clinical identification of high-risk patients and development of individualized strategies, and provide strong technical support for improvement of the management and prognosis of osteosarcoma patients.

The present invention relates to the field of biomedicine and discloses the application of GABRR1 as a tumor marker and a target molecule. The present invention firstly discovers that GABRR1 serves as a marker for tumor invasion and metastasis and participates in the processes of tumor growth, invasion and metastasis. Therefore, GABRR1 can be used as a target in the diagnosis and / or treatment of tumors; the present invention uses the GABRR1 protein as a tumor target to screen tumor therapeutic drugs such as monoclonal antibodies, polypeptides or small molecule drugs that can overexpress GABRR1.

The application provides a kind of CHA@SA-CRISPR / Cas12a system and its application in tumor marker molecular detection, and the CHA@SA-CRISPR / Cas12a system based on catalytic hairpin self-assembly and CRISPR / Cas12a system construction can be used as a self-sustaining isothermal biosensing platform, and the detection of ultra-sensitive biomarker miRNA-155 is realized by combining the CRISPR / Cas12a feedback circuit initiated by catalytic hairpin self-assembly;Through the target-dependent recognition of two split activator promoters, non-specific background is inhibited, and combined with ds-loop DNA reporter design, the reporter gene leakage and inherent signal noise are minimized to achieve amole level sensitivity;And without exogenous primer, while ensuring the recycling of target RNA, the operation is simple.

This invention belongs to the field of biodetection technology and discloses a fluorescence detection method for the prostate cancer biomarker PCA3 based on gold nanorods and CRISPR Cas12a amplification. This invention provides a detection kit for the ultrasensitive detection of the long non-coding RNA PCA3, a tumor marker for prostate cancer. This kit utilizes the paracleavage property of CRISPR Cas12a activated by the target sequence to cleave the fluorescent reporter probe, releasing the fluorophore. This removes the signal quenching effect of the gold nanorods on the fluorophore, restoring the fluorescence signal and achieving ultrasensitive detection of the target sequence. The limit of detection (LOD) of this kit is as low as 1.65 pM, achieving highly selective quantitative detection of PCA3.

The present invention relates to the technical field of bioinformatics, and in particular to a gene sequence screening method and system for tumor markers. The method comprises: acquiring a gene sequence to be analyzed, original gene sequences of each type of tumor marker, and gene data blocks of each original gene sequence at each length; on the basis of data similarity and difference between gene data blocks of each original gene sequence and gene data blocks of other original gene sequences of the same type of tumor markers at the same length, obtaining a partition evaluation value of each original gene sequence at each length; obtaining an optimal length on the basis of differences between the partition evaluation values of all the original gene sequences at each length and the partition evaluation values of all the original gene sequences at an adjacent length; and partitioning the gene sequence to be analyzed, and on the basis of a partition result, performing hash matching between the gene sequence to be analyzed and partition results corresponding to the tumor markers in a database, to obtain a gene sequence screening result of a tumor marker of a patient with a gastrointestinal disease. Therefore, a block length can be adaptively obtained, thereby obtaining a more accurate gene screening result.

This utility model relates to the field of interventional tumor diagnostic and treatment medical device technology, and discloses an umbrella-shaped anchored tumor marker and its implantation system. The umbrella-shaped anchored tumor marker includes an umbrella-shaped anchoring system composed of multiple umbrella ribs with shape memory properties. The proximal ends of the ribs converge to form an axial central tube. The surface of the ribs has micro-barb structures formed by laser etching. The umbrella-shaped anchoring system remains in a contracted state at temperatures below body temperature and autonomously unfolds into a three-dimensional umbrella-shaped anchoring form at body temperature. In this utility model, the distal end of the umbrella ribs integrates a platinum-iridium alloy imaging tip with gradient stiffness (rigid at the proximal end and flexible at the distal end). The barbs are spaced along the length of the umbrella ribs. The shape memory alloy is in one state during delivery at room temperature and can self-unfold in vivo, achieving effective anchoring and imaging, thus aiding in tumor marking.

This invention discloses a multi-marker analysis method for the classification and origin tracing of peripheral blood target cells, relating to the medical field. This method involves capturing target cells from peripheral blood samples, identifying them as tumor cells using tumor markers, and then further analyzing them using tissue-specific markers to achieve classification and origin tracing. This invention not only traces the origin of peripheral blood tumor cells but also confirms the tissue and organ source of the tumor cells, making the classification and origin tracing of target cells possible and more accurate.

The application relates to the marker detection field and specifically relates to a colorectal cancer tumor marker detection device, which comprises a tray, the tray comprises a bottom plate and a plurality of transverse plates and longitudinal plates arranged on the bottom plate, the transverse plates and the longitudinal plates are vertically staggered to form a plurality of rows of placement grooves, and enzyme strips are placed in the placement grooves; a sliding hole is formed in the end of each transverse plate, a sliding groove is formed in the position opposite to each placement groove, and the sliding groove is communicated with the sliding hole and the placement groove; in the application, the designed tray is matched with the enzyme strips, a push rod is arranged in the tray, the push rod is matched with a limiting structure, the enzyme strips are extruded and fixed in the placement grooves, meanwhile, the placement grooves are emptied, the enzyme strips can be conveniently taken out from the placement grooves in an inclined state, and the operation of a detection personnel on a detection process is facilitated.

This invention belongs to the field of biodetection technology and relates to a SERS / FL bioprobe and a method for establishing a breast cancer cell classification model based on it. The SERS / FL bioprobe comprises, from the inside out: gold nanoparticles with a hexahedral morphology, a fluorescent dye molecular layer, a polymer compound layer, and an anti-tumor marker antibody layer. This invention splices together the SERS spectra detected by the two bioprobes to construct a "symphony SERS spectrum." Based on the "symphony SERS spectrum," a breast cancer cell classification model is obtained using the LDA algorithm. This model can accurately distinguish between MCF-7 cells and leukocytes, and can also distinguish between MDA-MB-231 cells and leukocytes. More preferably, it can distinguish between MCF-7 cells and MDA-MB-231 cells, achieving high-precision classification of breast cancer subtypes.

The present invention relates to a long non-coding RNA (LETN) useful as a diagnostic and therapeutic target for cancer. In particular, the present invention discloses that lncRNA RP11-196G18.22 (LETN) is overexpressed in cancer cells, and that such overexpression can promote the proliferation of cancer cells and is associated with a short prognostic survival time in cancer patients. Since reducing the expression of this lncRNA inhibits cancer cell growth, the inhibition of the expression of this lncRNA presents a new strategy for cancer therapy.

The invention discloses an enhanced homologous targeting detection probe as well as a preparation method and application thereof, and belongs to the technical field of biological medicines. The enhanced homologous targeting detection probe is a metal complex, raw materials comprise amino acid, cobalt ions and lanthanide ions, the amino acid is histidine, and the cobalt ions Co and the lanthanide ions are sequentially reacted with the histidine through coordination. The metal complex can be used for preparing a product for detecting circulating tumor cells or tumor extracellular vesicles in plasma in vitro. The invention provides an efficient, accurate and economical circulating tumor marker detection means, and based on the same'super homologous targeting 'core principle, high-sensitivity detection of CTC and tumor EV is realized.

This invention discloses a system for assessing ovarian cancer recurrence based on super-resolution imaging of platelet subcellular structure. The system includes a data acquisition module, a data analysis module, and an evaluation module. The data acquisition module acquires characteristic values ​​of postoperative ovarian cancer patients and submits them to the data analysis module. These characteristic values ​​include the proportion of platelets with a "regularly distributed" α-granule pattern (X1) and the serum CA125 content (X2). The data analysis module inputs the acquired characteristic values ​​into a multivariate logistic regression model to calculate a joint index (y) and submits it to the evaluation module. The evaluation module assesses the risk of postoperative recurrence based on the principle that a higher value of the joint index (y) indicates a higher risk of recurrence. Compared to the clinically used tumor marker CA125, this evaluation system has higher sensitivity and can detect signs of ovarian cancer recurrence earlier, facilitating early intervention by medical staff.

The application discloses a tumor recurrence and metastasis risk prediction method and system based on an anatomical atlas, and the method comprises the following steps: acquiring a patient image report, a chief complaint text and non-equidistant tumor marker data; based on a tumor metastasis knowledge graph, the image report and the chief complaint text are mapped to corresponding anatomical nodes, the semantic alignment weight of objective lesions and subjective symptoms on the nodes is calculated by using a cross-attention mechanism, and multi-modal fusion node features are generated; the biochemical trend features of the marker data are extracted as global state variables by using a continuous time model to inject the graph; finally, the multi-modal fusion node features and the global state variables are input into a graph neural network for feature aggregation and reasoning, and a risk prediction result and a high-risk anatomical region are output. The application realizes early and accurate early warning and an interpretable path reasoning for tumor recurrence and metastasis risk.

The present application relates to the biological field, and particularly to a biomarker related to gynecological malignant tumor and application thereof. The present application discloses the existence of TES complex in ovarian cancer exosome, and provides TrkB protein, EGFR protein and Sortilin protein for non-invasive specific detection of tumor in body fluid of ovarian cancer patients and possible composite diagnosis and treatment means as potential treatment targets. The specific embodiments of the present application disclose that the aforementioned proteins are highly expressed in ovarian cancer cell exosome, and the aforementioned proteins affect the regulation mechanism of anti-anchorage-dependent apoptosis and angiogenesis of ovarian cancer cells by regulating the tumor microenvironment. Therefore, detecting the content of the aforementioned proteins in the plasma exosome of ovarian cancer cells becomes a tumor marker and drug target for early diagnosis and treatment follow-up of ovarian cancer. The present application is expected to break through the core theory and technical difficulties of early diagnosis of ovarian cancer, and become a frontier diagnosis and treatment means for early diagnosis of ovarian cancer.

This invention provides a physiological age prediction model that predicts the physiological age of a subject by detecting physical examination indicators. These indicators include measurements of blood cells, glucose metabolism, tumor markers, urine components, anthropometric measurements, lipids, blood components, and tissue function. Preferably, these indicators include one or more selected from the following: glomerular filtration rate (eGFR), cystatin C, serum creatinine (SCr), blood urea nitrogen (BUN), timed up and go, light reaction time, fasting blood glucose (FBG), insulin-like growth factor (IGF), superoxide dismutase (SOD), insulin (INS), albumin (Alb), alkaline phosphatase (ALP), folic acid, lactate dehydrogenase (LDH), aspartate aminotransferase (AST), and high-sensitivity C-reactive protein (hs-CRP). More preferably, all of the aforementioned physical examination indicators are included. This invention also provides a physiological age prediction device applying the above-mentioned physiological age prediction model and a computer storage medium.