698 results about "Immunome" patented technology

The invention discloses a breast cancer immunohistochemical index and typing prediction method and system. The prediction method comprises the following steps: acquiring a breast ultrasound image and a breast magnetic resonance image of a patient; performing preprocessing and quality control on the mammary gland ultrasonic image and the mammary gland magnetic resonance image; performing breast lesion area segmentation by adopting a deep learning model to obtain segmented lesion areas; based on the segmented lesion area, extracting multi-modal radiomics characteristics of the breast ultrasonic image and the breast magnetic resonance image; fusing the multi-modal radiomics characteristics of the breast ultrasound image and the breast magnetic resonance image, constructing a machine learning model, and performing immunohistochemical index prediction to obtain an immunohistochemical index prediction result; and performing breast cancer molecular typing analysis according to the immunohistochemical index prediction result. By fusing the multi-modal image information, the tumor features can be described more comprehensively, and the accuracy of biomarker prediction is improved.

The invention provides a tumor patient clinical test matching system and method based on a large language model and an OCR technology, and is applied to the field of medical data processing. The method comprises the following steps: analyzing clinical data and test information, processing an unstructured text, and generating structured clinical feature data through context association analysis; key data is extracted and subjected to double verification correction, and structured data supplementary information is generated; enhancing the structured clinical feature data and supplementary information based on a multi-modal processing assembly line module, extracting an image quantitative index, analyzing an immunohistochemical result, and generating a comprehensive matching score; through a rule engine and semantic similarity calculation, item-by-item comparison of patient features and entry and exhaust conditions is realized, and a preliminary matching result is generated; edge case misjudgment is corrected through context-aware multi-round reasoning, sorting is adjusted in combination with clinical test priority weights, and an optimized clinical test matching list is generated; and generating a clinical test matching report based on the data.

The invention discloses a monoclonal antibody BY017 combined with African swine fever virus P30 protein and application of the monoclonal antibody BY017. The invention provides an IgG antibody which is composed of a light chain and a heavy chain. CDR1, CDR2 and CDR3 in the heavy chain variable region are sequentially shown as the 47 to 54 , the 72 to 79 and the 118 to 126 in SEQ ID NO: 1; cDR1, CDR2 and CDR3 in a light chain variable region are sequentially as shown in the 49 to 60 , the 78 to 80 and the 117 to 124 in SEQ ID NO: 3. The invention also protects the application of any one of the IgG antibodies in preparation of products. The product has the functions that the product is used for being combined with an African swine fever virus P30 protein fragment; the antibody is used for binding African swine fever virus P30 protein; the antibody is used for binding African swine fever virus. The IgG antibody provided by the invention can be used for multiple purposes of western blot, immunohistochemistry, flow cytometry, ELISA (Enzyme-Linked Immunosorbent Assay) and the like, and can be used as an important tool for ASFV detection and structural analysis of P30 protein of ASFV detection.

The invention provides an automatic tumor budding identification method fusing pathological staining migration and YOLO target detection. The method comprises the following steps: training Hamp by using a CUT model; a staining migration model is established from the E image to the immunohistochemical image, and the staining migration model is utilized to carry out Hamp; e, converting the dyed full-width pathological section into a cytokeratin dyed full-width pathological section; and performing tumor budding detection on the generated full-width pathological section dyed by the cytokeratin by using a TB-YOLO model improved on the basis of YOLOv10. According to the method, the CUT is combined for pathological image staining migration, the IHC image generated through TB-YOLO analysis is used for tumor budding detection, meanwhile, accurate translation and detection of positive signals are ensured, richer diagnosis information is provided for pathologists, the diagnosis accuracy is improved, the pathological examination cost of patients is reduced, and the purpose that only Hamp is used for diagnosis is achieved. And E, the tumor budding is accurately detected by the dyed image, so that the comparability of medical images in different dyeing modes and the applicability of a cross-dyeing method are improved.

The invention relates to an anti-VIM nano antibody and application thereof, belongs to the technical field of biology, and aims to solve the problem of Vimentin VIM detection, and has the key points that a complementary determining region CDR of the nano antibody comprises CDR1, CDR2 and CDR3 sequences: (I): (1) the amino acid sequence of the CDR1 is shown as SEQ ID NO.27, and (2) the amino acid sequence of the CDR2 is shown as SEQ ID NO.33; and (3) the amino acid sequence of the CDR3 is shown as SEQ ID NO.39. The nano antibody and the polypeptide thereof have the effects that the nano antibody and the polypeptide thereof have very high affinity and activity, can specifically recognize and combine with VIM, can be used for capturing and detecting VIM positive cells, and can be applied to immunofluorescence analysis or immunohistochemical analysis and the like through a proper antibody labeling technology.

The invention discloses a PD-L1 immunohistochemical quality control product and a preparation method thereof, and relates to the technical field of biology. The PD-L1 immunohistochemical quality control product comprises cell slices prepared from a plurality of different types of tumor cells, the cell section comprises a positive quality control product and a negative quality control product which are marked by different colors. In the invention, different tumor cells are creatively adopted as raw materials of the quality control product, the quality control product can be efficiently and quickly prepared, and the limitation of the source of a human tissue sample is overcome; a BSA sealing buffer solution is used for soaking the section, so that long-term stable production of a quality control product can be realized, the dyeing background is reduced, and the dyeing effect is enhanced; besides, by preparing the cell slices with various proportions and different staining intensities, the quality control on the staining of the antibody can be ensured, and guidance can also be provided for accurate interpretation, namely comprehensive and accurate quality control and interpretation guidance are provided for the staining of the antibody, false negative and false positive are effectively eliminated, and the method has great clinical significance.

The invention discloses a pharmaceutical composition for reversing pancreatic cancer gemcitabine drug resistance and application of the pharmaceutical composition, and belongs to the technical field of biological medicine. The composition comprises a generic FGFR inhibitor delatinib and gemcitabine, the concentration of the delatinib is 25 to 50 mg / kg, and the concentration of the gemcitabine is 20 to 30 mg / kg. By inhibiting an FGFR2 / FGFR3 signal channel and reducing the expression of FGFR protein in drug-resistant cells, the chemosensitivity of gemcitabine is synergistically enhanced, the apoptosis induction rate is increased by more than two times, and the synergic index (CI) is less than 1. In-vitro and nude mouse transplantation tumor experiments prove that the composition can significantly inhibit the proliferation of gemcitabine drug-resistant pancreatic cancer cells. The Gemcitabine drug-resistant pancreatic cancer drug can be used for preparing a drug for treating Gemcitabine drug-resistant pancreatic cancer with high FGFR3 expression, patients are screened through immunohistochemistry or gene sequencing, intravenous injection or oral administration is adopted, dosage forms comprise freeze-dried powder injection, capsules or tablets, and a new strategy is provided for pancreatic cancer drug-resistant treatment.

The method and system for evaluating the curative effect of hepatocellular carcinoma based on immune microenvironment characteristics are high in accuracy and reliability of evaluating the curative effect of hepatocellular carcinoma. The method comprises the following steps: (1) preparing a sample; (2) carrying out multiple immunohistochemical staining; (3) image acquisition and analysis; (4) analyzing spatial distribution characteristics; (5) multiplying the input image voxel signal numerical value by the weight vector of the convolution kernel, transmitting the multilayer convolution kernel, and finally obtaining a calculation result output by each network; and (6) establishing a prediction model: based on the spatial distribution characteristics and clinical characteristics of immune cells, constructing the prediction model by using the positive rate of CD8 + PD-L1 + and CD103 + CD8 + cells in the total area and the number of CD103 + cells within 30 microns around tumor cells so as to predict the immunotherapy curative effect of the HCC patient.

The invention provides a breast cancer HER2 immunohistochemical digital slice automatic interpretation method, device and equipment and a storage medium. Relates to the technical field of digital pathological image analysis. Acquiring a full-slice image, automatically identifying an external contrast area and a tissue area through a multi-task head real-time instance segmentation model, and segmenting an ROI (Region of Interest) area of tumor cell aggregation; extracting image blocks by adopting a fixed sliding window based on the ROI region, and constructing a double-branch multi-task feature extraction model containing a backbone network: realizing HER2 expression pattern classification by an image block classification head, and outputting a continuous protein expression intensity quantized value by a dyeing intensity numerical head through regression analysis; and establishing a slice-level interpretation model, integrating the classification results and the intensity quantized values of all the image blocks, and outputting an automatic HER2 interpretation result. According to the invention, end-to-end analysis from cell-level characteristic quantification to slice-level diagnosis is realized, and an objective and quantifiable intelligent interpretation scheme is provided for HER2 immunohistochemical evaluation.

A specific antibody and an antigen binding fragment thereof against a CD228 protein, used for testing and treating multiple tumors, such as melanoma, mesothelioma, and colorectal cancer. An antibody binding fragment facilitates the diagnosis and treatment of cancer by specifically binding to CD228. The present invention further comprises antibody-drug conjugates (ADCs) in which drugs bind to antibodies by means of linkers, aiming to improve the treatment effect and reduce the impact on normal cells. Additionally, the present invention provides a nucleic acid encoding an antibody or an antigen binding fragment thereof, so as to produce a recombinant antibody or fragment. In addition, the present invention further provides a kit, used for laboratory research, clinical diagnosis and treatment effect monitoring, facilitating determination of whether tissues or cells express CD228, providing a new strategy for personalized and accurate treatment of cancer.

The invention provides a PD-L1 immunohistochemical section tumor identification detection method and system, and the method comprises the steps: collecting various organ PD-L1 sections of a clinical pathological experiment, carrying out high-resolution scanning, pre-identification screening and cloud data storage, and obtaining a PD-L1 section data set of various organs; automatically labeling each tumor cell labeling pixel-level mask, automatically generating a labeling bounding box, and obtaining a tumor cell region labeling data set; according to the tumor cell region labeling data set, preprocessing all positions labeled as effective regions, creating a YOLO v8 deep learning model, training to gradually adjust network weight, and outputting a prediction result of the YOLO v8 deep learning model; and analyzing and calculating whether the prediction evaluation index information of the YOLO v8 deep learning model accords with a training target evaluation index, completing model training, and carrying out accurate positioning and pixel-level region identification detection on PD-L1 immunohistochemical pathological section tumor cells.

The invention relates to the technical field of plants, in particular to a paraffin embedding method for reducing plant RNA degradation. In the plant paraffin embedding method provided by the invention, a stationary liquid for fixing plant tissues is prepared from absolute ethyl alcohol and acetic acid in a volume ratio of (2-5): (1-4); buffer I used for dehydration is absolute ethyl alcohol and n-butyl alcohol with the volume ratio of (1-3): (1-2); buffer II used for waxing is n-butyl alcohol and low-temperature paraffin wax with the volume ratio of (1-3): (1-2), and the melting point of the paraffin wax is 20-50 DEG C. According to the method, low-temperature paraffin with the melting point of 20-50 DEG C is adopted, and a reagent for paraffin embedding and a paraffin embedding process are adjusted, so that the plant section with relatively high RNA integrity and relatively high tissue structure integrity is obtained. The paraffin embedding method provided by the invention is suitable for different types of molecular biology experiments of space transcriptome, immunohistochemistry, immunofluorescence and the like.

The invention discloses application of a cell surface adhesion molecule CD22 as a target spot in preparation of drugs for treating spinal cord injury related diseases. The change of gene expression in the glial scar formation process is represented by space transcriptome sequencing, and the specific expression of CD22 in the glial scar region is up-regulated. According to single cell sequencing, in-situ hybridization and immunohistochemistry, specific high expression CD22 of part of microglial cells in a glial scar area is found. CD22 is knocked out through a genetic means, and it is found that formation of glial scars after spinal cord injury is remarkably reduced through inhibition of CD22. Behavioral detection finds that the error rate of irregular horizontal ladders is remarkably reduced by inhibiting CD22, and fine movement recovery of hind limbs of mice after spinal cord injury is promoted. The siRNA specifically targeting CD22 is injected into the sheath, so that the expression of microglial cells CD22 is inhibited, the error rate of irregular horizontal ladders of hind limbs can be reduced, and the recovery of the fine movement function of the hind limbs of the mouse after spinal cord injury is promoted. The invention provides a new possibility for development of drugs for spinal cord injury and treatment of spinal cord injury.

The invention relates to a CACNA1A-based mental patient heart death intelligent identification system and method, the system comprises an immunohistochemical staining device, an image acquisition unit, an image analysis unit and an intelligent identification unit, the immunohistochemical staining device is used for performing CACNA1A immunohistochemical staining on formalin-fixed paraffin-embedded heart tissue slices; the image acquisition unit is used for shooting and obtaining a heart tissue CACNA1A immunohistochemical staining image; the image analysis unit is used for processing the heart tissue CACNA1A immunohistochemical staining image so as to determine a tissue staining region and image features thereof; and the intelligent identification unit outputs an identification prediction result of heart death of the mental patient according to the image features of the tissue staining region. Compared with the prior art, the mental patient heart death identification system can intelligently and accurately identify mental patient heart death.

Disclosed are novel pharmaceutical, animal feed compositions and methods of treating non-human animals comprising at least one component selected from the extract(s), fraction(s), active compound(s) and phytochemical(s), or mixtures thereof, derived from non-woody plants of the genus Hesperaloe. Animal feed compositions may comprise a basal animal feed and water soluble solids extracted from Hesperaloe and comprising at least one saponin. The water soluble solids may comprise from about 5 to about 30 wt % saponin. The compositions of the present invention can be used for the treatment of non-human animals, such as poultry and more particularly for preventing and treating coccidiosis. An embodiment provides an immunological composition useful for inducing the production of antibodies to an antigen in a non-human animal comprising an antigen, preferably a coccidia, and a saponin composition extracted from Hesperaloe. The saponins extracted from Hesperaloe biomass may comprise 25(27)-dehydrofucreastatin, 5(6),25(27)-disdehydroyuccaloiside C, 5(6)-disdehydroyuccaloiside C, furcreastatin and yuccaloiside C.

The invention discloses a correction method of PCR (Polymerase Chain Reaction) preference, a DNA (Deoxyribose Nucleic Acid) artificially synthesized sequence combination of a TCR-beta immune repertoire, a primer combination for amplifying the TCR-beta immune repertoire, a quantitative analysis method of the TCR-beta immune repertoire of a gDNA sample, a detection kit and application of the detection kit. The PCR preference correction method can effectively correct the preference generated in the PCR amplification process, the DNA artificially synthesized sequence combination can effectively adjust the primer concentration ratio of the multiple PCR primer combination, and the primer combination can efficiently and quantitatively amplify a TCR-beta immune repertoire without mutual interference as much as possible. According to the method, the immune repertoire can be accurately and quantitatively analyzed at the DNA level.

The invention relates to the field of image analysis, in particular to a colon cancer lymph node metastasis risk prediction method and system based on image analysis. The method comprises the following steps: acquiring a pathological section scanning image, carrying out layer-by-layer downsampling and feature reconstruction, and generating pathological section topological features; carrying out adaptive clustering analysis and multi-parameter fusion evaluation on the basis of the pathological section topological features to obtain independent migration evaluation values of individual tumor cells; performing tumor metastasis branch analysis according to the independent migration evaluation value, and constructing a metastasis branch path distribution diagram; extracting an immunohistochemical staining image of a patient to obtain immune cell space distribution data; and performing multi-region lymphatic metastasis simulation and metastasis risk situation prediction based on the immune cell spatial distribution data and the metastasis branch path distribution diagram to obtain a final metastasis risk assessment result. According to the method, the lymph node metastasis risk is accurately and efficiently analyzed, and the credibility of a pathological analysis result is improved.

The invention discloses a pathology grading method and system based on HER2 immunohistochemical pictures, belongs to the technical field of immunohistochemical (IHC), bioinformatics and medical diagnosis, is used for carrying out pathology grading on a test sample, and comprises the following steps: collecting and processing a plurality of original HER2 immunohistochemical pictures of the test sample, and obtaining a sample picture set for pathology grading; reading a sample picture set and converting an RGB color space in the sample picture set into an HSV color space; determining the staining intensity and range of the cell membrane based on the immunohistochemical picture in the sample picture set converted to the HSV color space; extracting and determining the membrane rate based on the characterization of the dyeing intensity and range of the cell membrane, and carrying out test treatment on the membrane rate to obtain the membrane rate of the test set; the film rate is the ratio of the pixel where the film is located to the background pixel; evaluating the test sample based on the corrected membrane rate data, and performing pathological grading on HER2 expression in the test sample based on a grading system. The invention further discloses a system, electronic equipment and a computer readable storage medium.

The invention relates to the technical field of antibodies, and provides an anti-CD45 antibody and application thereof, the antibody comprises at least one of the following CDRs: a heavy chain variable region CDR: an amino acid sequence of SEQ ID NO: 1-3 or a conservatively modified form thereof; and a light chain variable region CDR: SEQ ID NO: 4-6 or an amino acid sequence in a conservative modification form thereof. The antibody or the antigen binding fragment thereof can efficiently and specifically recognize CD45, can effectively detect CD45, and can be used for immunohistochemistry exemplarily.

The invention belongs to the technical field of medical diagnosis, and discloses a quantum multicolor immune digital pathological diagnosis analysis system, which comprises the following steps: acquiring high-resolution digital images of an immunohistochemical or immunofluorescence slice and a slide, and analyzing multicolor signal distribution in the images to obtain a quantum chromatographic image set; pixel-level color separation and intensity quantization are carried out on the quantum chromatographic image set, and a quantum intensity index set of each pixel is generated; performing multi-target color overlay analysis and post-translational modification protein specificity evaluation on the quantum intensity index set to construct a multi-color modification index set; identifying a single cell boundary and a multi-cell community based on the multicolor modification index set, and extracting a cell morphological parameter and a spatial adjacency relation to obtain a cell quantum analysis set; performing consistency correction and traceable recording by applying an automatic quality control mechanism, and generating a digital diagnosis report; the accuracy of accurate qualitative and quantitative analysis of immunohistochemistry and immunofluorescence is greatly improved.

The invention belongs to the technical field of veterinary vaccines, and particularly relates to porcine rotavirus nanoparticles as well as a preparation method and application thereof. The invention provides a porcine rotavirus nano-particle. The porcine rotavirus nano-particle comprises a porcine rotavirus VP8 protein fragment, a dioxo tetrahydropteridine synthase and a linker, wherein the linker comprises a porcine rotavirus VP8 protein fragment and a dioxo tetrahydropteridine synthase; the porcine rotavirus VP8 protein fragment is connected with the dioxo tetrahydropteridine synthase through the linker, and the linker is connected with the dioxo tetrahydropteridine synthase; the amino acid sequence of the porcine rotavirus VP8 protein fragment is as shown in SEQ ID NO. 1. The porcine rotavirus nanoparticles can display more antigens at a time, so that the immunogenicity of vaccines is improved, and animals can be induced to generate higher antibody level. Results of the embodiment show that the prepared porcine rotavirus nanoparticle vaccine can cause a higher specific antibody level, and compared with a porcine rotavirus VP8 protein fragment monomer immune group, the porcine rotavirus nanoparticle vaccine can cause a higher neutralizing antibody level.

The invention relates to the technical field of antibodies, and provides an anti-CD45 antibody and application thereof, the antibody comprises at least one of the following CDRs: a heavy chain variable region CDR: an amino acid sequence of SEQ ID NO: 1-3 or a conservatively modified form thereof; and a light chain variable region CDR: SEQ ID NO: 4-6 or an amino acid sequence in a conservative modification form thereof. The antibody or the antigen binding fragment thereof can efficiently and specifically recognize CD45, can effectively detect CD45, and can be used for immunohistochemistry exemplarily.

The invention belongs to the technical field of biomedicine, and discloses an immortalized cell line for human kidney suspected cell carcinoma as well as a culture method and application of the immortalized cell line. The immortalized cell line for the human kidney suspected cell carcinoma, disclosed by the invention, is named as a human kidney suspected cell carcinoma cell line Loya a-710 (Homo sapiens), the classification name of the Latin name of the immortalized cell line is Chromophore sensor cell carcino: Loya a-710, and the preservation number of the immortalized cell line is CCTCC (China Center for Type Culture Collection) NO: C2025123. The human kidney suspected cell carcinoma cell line Loya-710 disclosed by the invention is used as an in-vitro model to rapidly grow in tissue culture, and mitochondrial mutation characteristics, a vesicle structure and a classical immunohistochemical marker of ChRCC are reserved. The invention provides a precious tool for further research on ChRCC heredity, molecules and biological characteristics, and also provides a powerful new model for mitochondrial diseases.

The invention discloses a method for constructing a lung cancer early screening model based on TCR sequencing, which comprises the following steps of: firstly, constructing a TCR-enriched sequence database based on TCR sequencing data from samples of lung cancer patients and healthy people, then performing TCR sequencing on each sample, and acquiring TCR characteristics of each sample; comprising proportion characteristics of V gene and J gene, statistical characteristics of a TCR immune repertoire, convergence sequence characteristics, TCR sequence amino acid proportion characteristics, proportion characteristics of TCR sequences with different lengths, proportion characteristics of TCR sequences with different frequencies and TCR enriched sequence characteristics; screening the TCR features of each sample by using a feature screening method, and constructing a machine learning model in combination with other information of the samples to obtain a lung cancer early screening model; a lung cancer early screening detection device is constructed based on the lung cancer early screening model, and lung cancer early screening can be achieved based on TCR sequencing information of a sample.

The invention belongs to the field of medicines, and provides application of indole-3-formaldehyde in preparation of an enteric nerve protection medicine. A loperamide-induced C57BL / 6J mouse constipation model is adopted, it is found that indole-3-carboxaldehyde can accelerate the small intestine propulsion rate of a model mouse, increase the water content of excrement and the excretion number of excrement particles in unit time and improve the intestinal motility of the model mouse, and HUC / DmRNA expression of mouse colon tissue treated by indole-3-carboxaldehyde is remarkably increased compared with a model group; protein expression of HUC / D and HSP90AA1 is remarkably increased compared with that of a model group, immunohistochemistry and immunofluorescence show that the number of HUC / D dyed neurons and fluorescence intensity of colon tissue treated by indole-3-formaldehyde are remarkably increased compared with that of the model group, and therefore, the indole-3-formaldehyde can promote intestinal motility by protecting HUC / D intestinal neuronal cells.

The invention relates to the technical field of immune repertoire sequencing, in particular to a sequence data analysis method and device for biological system state modeling and a storage medium. According to the method, high-throughput sequencing data of B / T cell receptors are acquired, nonlinear gain correction and V-J gene combination preference feature extraction are performed, structured feature nodes are constructed, features are coded by using a Transform model, a system state vector is generated in combination with weighted average pooling, adversarial training is introduced to realize feature decoupling, and signal interference among functional categories is inhibited. And calculating a multi-dimensional immune intensity score based on the system state vector, and quantifying immune response active degrees of different function categories. According to the method, high-sensitivity and multi-dimensional parallel modeling and dynamic evaluation of the immune system state are achieved, the method is suitable for large-scale population immune monitoring and system biological research, and the analysis capacity and application value of immune group library data are remarkably improved.

The invention discloses DLL3 serving as a cervical neuroendocrine cancer treatment target and application of the DLL3, and belongs to the technical field of biology. The invention discloses specific expression of a DLL3 gene in cervical neuroendocrine carcinoma (NECC) and application of the DLL3 gene as a therapeutic target. Single cell sequencing and immunohistochemistry find that a DLL3-NOTCH1 / 2 signal axis is activated in NECC, and functional experiments prove that the DLL3-NOTCH1 / 2 signal axis drives malignant progression by promoting tumor proliferation and inducing T cell depletion. In addition, the invention also constructs an NECC organ-TILs co-culture model, and verifies the synergistic effect of the DLL3 targeted drug AMG757 combined with EP chemotherapy. The invention provides new target selection and theoretical basis for precise diagnosis and treatment of NECC, and has important clinical transformation value.

The invention relates to the field of image processing, in particular to a multi-immunohistochemical image processing and analyzing method and system. The method comprises the following steps: acquiring multiple immunohistochemical images at a plurality of time points, and performing sequential serialization fitting to obtain an immunohistochemical image sequence; performing depth visual semantic recognition and frame-by-frame segmentation reconstruction on the immunohistochemical image sequence, and constructing an image frame sequence of each marker; performing cell spatial distance change calculation and spatial expression correlation mining according to the image frame sequence of each marker to generate a time sequence behavior feature of each marker; and carrying out frame-by-frame organization structure analysis on the image frame sequence of each marker to obtain a three-dimensional organization structure model of each region. According to the method, accurate and efficient tissue structure evaluation is realized, and a personalized quantitative diagnosis result is provided.

The invention discloses pyruvate carboxylase (PC) serving as a biomarker for detecting endometriosis and application of the pyruvate carboxylase (PC) to treatment of the endometriosis. The biomarker can be used for detecting the expression level of PC in an endometrial tissue sample through an immunohistochemical method, and when the IHC score is greater than or equal to 4, a subject is judged to be at a high risk of endometriosis or suffered from the endometriosis. Meanwhile, the invention provides an application of drugs (including specific siRNA, ZY-444, octyl gallate and the like) for inhibiting PC expression in treatment of endometriosis, and a corresponding treatment method. The invention provides a new biomarker, target spot and scheme for detection and treatment of endometriosis, and has important clinical application value.

The monoclonal antibody of the glycoprotein Gn of the severe fever with thrombocytopenia syndrome virus is screened on the basis of immune repertoire sequencing, and the biological characteristics of the monoclonal antibody are identified. The method comprises the following steps: taking purified SFTSV-Gn as bait, taking virus specific B cells from an immunized female BALB / c mouse B cell bank, selecting an antibody sequence with potential binding activity by utilizing a 10 * immune repertoire sequencing method in combination with bioinformatics analysis, constructing the antibody sequence to an eukaryotic expression vector pcDNA3.4, expressing and purifying a monoclonal antibody, and identifying the biological activity of the monoclonal antibody. 14 antibodies are selected from 3544 captured B cells, functional verification shows that 12 antibodies can be combined with SFTSV-Gn glycoprotein, and the Gn-5 antibody and the Gn-7 antibody have high combining capacity; western blot, indirect immunofluorescence test and flow cytometry prove that the antibody can specifically recognize the SFTSV, the effective concentration is as low as 2 mu g / mL, and a foundation is laid for development of a rapid diagnosis reagent for the SFTSV.