6883 results about "Pathology" patented technology

This disclosure provides a method for treating a subject afflicted with a lung cancer, which method comprises administering to the subject therapeutically effective amounts of: (a) an antibody or an antigen-binding portion thereof that specifically binds to a Programmed Death-1 (PD-1) receptor and inhibits PD-1 activity; and (b) an antibody or an antigen-binding portion thereof that specifically binds to a Cytotoxic T-Lymphocyte Antigen-4 (CTLA-4) and inhibits CTLA-4 activity.

The invention belongs to the related technical field of brain image processing, and provides an Alzheimer's disease classification method and system based on topology perception and a group hypergraph in order to solve the problem of inaccurate classification of the Alzheimer's disease in the prior art. Constructing a dynamic function connection network sequence through a sliding window strategy; a local topology perception encoder and a global topology perception encoder are respectively used for extracting local topology features and global topology features of each time window, deep interaction and fusion are carried out, and comprehensive feature representation of a tested level is generated; according to the method, each subject is used as a hypergraph node, hyperedges are constructed on the basis of comprehensive feature representation of a subject level and by combining feature similarity calculated by diffusion tensor imaging features and clinical embedded features of the subject, then a group hypergraph is constructed, a classification result is obtained by using a hypergraph neural network, and the early classification diagnosis accuracy of the Alzheimer's disease is effectively improved.

The invention discloses a lung cancer gene mutation classification method based on frequency domain multi-scale fusion guidance, and relates to the technical field of medical image processing and gene detection. According to the MFHA mechanism provided by the invention, the pathological image is decoupled into low-frequency global and high-frequency detail sub-bands through wavelet transform, and extraction of key high-frequency features such as cell nucleus morphology and local texture is enhanced by combining multi-scale convolution and up-sampling guided by high-frequency information; the problems of insufficient feature detail mining and low feature fusion efficiency in a traditional pathological image analysis method are solved; key features are screened and focused through a channel, frequency domain-space feature deep fusion is realized through up-sampling, robust representation is constructed by combining space attention with cosine similarity and multi-dimensional statistical features, a frequency domain analysis-space focusing collaborative optimization mechanism is formed, information redundancy caused by simple feature splicing is avoided, and the robustness of the system is improved. And the classification stability of the model in a complex pathological scene is improved.

The invention relates to the technical field of computer vision, image recognition and intelligent medicine management, in particular to a medicine bottle label content recognition method based on multiple cameras and YOLOv8. The method at least comprises the following steps: S1, deploying a medicine bottle label generation system, and generating a label; s2, multi-camera image acquisition and preprocessing; s3, carrying out chessboard calibration and space positioning; s4, medicine bottle label detection and label character recognition and structured analysis; and S5, system integration and application. According to the invention, through combination of multi-camera and multi-angle acquisition and checkerboard calibration positioning and combination with YOLOv8 label detection and OCR identification, high precision, high efficiency, end-to-end automation and system integration of medicine bottle label identification are realized, the defects of precision, efficiency, environmental adaptability and management integration in the prior art are overcome, and the system is suitable for popularization and application. The method has obvious technical advantages and practical value.

The invention discloses a lung cancer lifetime prediction system based on prognosis factor multi-data fusion, and belongs to the technical field of lung cancer prognosis prediction, and the system comprises a multi-source data collection module which is used for collecting prognosis multi-source data of a patient; the multi-source data processing module is used for carrying out preprocessing and feature extraction on the prognosis multi-source data of the patient; the multi-source data fusion module is used for carrying out cross-modal alignment and fine-grained fusion on the extracted multi-modal feature vectors, and capturing a dependency relationship between modals based on a hierarchical attention mechanism to form patient prognosis fusion data; and the survival analysis and prediction module is used for analyzing the prognosis fusion data of the patient according to the lung cancer lifetime prediction model, automatically predicting the lifetime of the patient and displaying the lifetime in a visual form. The problems that existing lung cancer lifetime prediction is low in accuracy and cannot provide support for personalized treatment are solved. The lung cancer lifetime prediction accuracy can be improved, and support can be provided for personalized treatment.

The invention relates to a novel application of animal bifidobacterium subsp. Lactis BGI-N3, in particular to an application of the animal bifidobacterium subsp. Lactis BGI-N3 in preparation of a preparation for relieving skin allergy. The invention finds that the bifidobacterium animalis subsp. Lactis BGI-N3 has a very remarkable effect in the aspect of relieving skin allergy, and the effect is specifically shown as follows: in an atopic dermatitis animal model, the dermatitis score, scratching times and percutaneous water loss are remarkably reduced, and the atopic dermatitis skin tissue damage condition is relieved; the immune organ edema condition is improved, the levels of Th2 type cell factors and inflammatory factors IL-6, TNF-alpha and IFN-gamma related to dermatitis are reduced, and the immune balance of the body is recovered; expression of fibroin and endothelial protein in skin tissue is improved, and the skin barrier is repaired; the level of antibacterial peptide in skin tissues is recovered, and the antibacterial activity of the skin is enhanced. Meanwhile, compared with a traditional chemical medicine for treating atopic dermatitis, the animal bifidobacterium subsp. Lactis BGI-N3 has no side effects such as weight loss, immune organ atrophy, immune imbalance and the like.

The invention provides a pourable tumor organoid vascularization model and a construction method thereof, and relates to the technical field of organoid culture. A temperature-sensitive degradable material and a photo-crosslinking modified temperature-sensitive material are used, the composite stent is printed through two channels, a multi-component gel mask partition curing process is combined, the stability of a perfusion pipeline is improved, and a partitioned highly-bionic complex microenvironment is accurately constructed in a macroscopic three-dimensional space; and constructing to obtain the perfusion tumor organ vascularization model. The model is high in bionic degree and stable in structure, can be applied to deepening cell and microenvironment interaction research and tumor-related drug screening, and has a good application prospect.

The invention relates to the technical field of infrared thermal imaging, in particular to a human body analysis method and system based on an infrared thermal image. The method comprises the following steps: acquiring an infrared thermal image sequence of a limb to be detected in a thermal relaxation process; segmenting the image sequence, constructing a topological center line of an effective contour, and defining a heat flow reference direction based on the geometric width change of a cross section along the center line; a temperature gradient vector field is calculated, and an area with the gradient direction and the heat flow reference direction in reverse distribution and containing a closed isotherm is screened out to serve as a thermal topology abnormal area; establishing a biological heat transfer model taking the surface temperature as a boundary condition, performing inverse solution on the thermal topology abnormal region, and performing inverse calculation on a heat source parameter corresponding to the subcutaneous depth; and when the heat source parameter exceeds a threshold value, generating a damage early warning. According to the method, by quantifying metabolic heat abnormality caused by inflammation in tissues, accurate positioning and quantitative evaluation of deep injury of limbs are realized, and the accuracy of human injury detection is remarkably improved.

The invention relates to the technical field of biological medicines, discloses application of circPDK1 protection, and particularly relates to application of a reagent for specific detection of circPDK1 in preparation of products for detection of esophageal cancer or prognosis evaluation of esophageal cancer. According to the application of the protected circular RNA in preparation of the esophageal cancer detection product, the circular RNA is circPDK1, and the nucleotide sequence of the circular RNA is shown as SEQ ID NO: 1. Experiments prove that circPDK1 is highly expressed in esophageal cancer tissues, growth, proliferation and migration of esophageal cancer cells are promoted, occurrence of esophageal cancer is promoted, knock-down of the circular RNA can significantly inhibit growth, proliferation and migration of esophageal cancer tumors, and the average survival time of esophageal cancer patients with low circPDK1 expression is longer than that of esophageal cancer patients with high circPDK1 expression. And a new research direction is provided for esophageal cancer detection, treatment and prognosis.

The invention provides an EGFR wild-type lung adenocarcinoma prognosis risk assessment method based on multi-omics and machine learning, and the method comprises the steps: obtaining multi-omics and clinical data of lung adenocarcinoma, obtaining a data set, and carrying out the multi-omics consensus clustering, and obtaining a molecular typing result; high-risk subtype specific candidate genes are identified, a candidate prognosis gene set is obtained, multi-algorithm machine learning comparison optimization is carried out, and a modeling strategy is obtained; performing feature screening and model training to obtain a multi-omics feature model so as to calculate an individual risk score of the to-be-tested sample; the individual risk score and the clinical staging information are utilized to obtain a clinical column diagram and a survival prediction result, then the flow of the multi-omics feature model, the individual risk score and the survival result is Web to obtain a clinical system, and a lung adenocarcinoma prognosis risk assessment result is output. The invention can realize an objective, accurate, generalizable and multifunctional prognosis evaluation and treatment guidance tool, and has important clinical application value and wide industrialization prospect.

The invention provides a breast cancer recurrence risk prediction method, system and device based on an ultrasonic image, and relates to the field of intelligent medical treatment, the method uses a deep convolutional neural network to perform deep network feature extraction on a breast ultrasonic image, and uses a deep learning semantic segmentation algorithm to perform accurate positioning and automatic segmentation on a breast tumor region of interest, thereby improving the accuracy of breast cancer recurrence risk prediction. Meanwhile, habitat analysis is carried out on the ultrasonic images to extract tumor heterogeneity features, multi-level and multi-mode features such as deep learning features, radiomics features and habitat analysis features are fused, a breast cancer recurrence risk prediction model is constructed, breast cancer recurrence risk prediction is carried out, and a breast cancer recurrence risk assessment result is output. And a quantitative basis is provided for clinical treatment decisions. The accuracy and robustness of recurrence risk prediction are remarkably improved through multi-feature fusion, and standardization and objectification of breast cancer prognosis evaluation are achieved. In addition, the method further has the advantages of being easy and convenient to operate, low in cost, noninvasive, nonradiative, good in repeatability and the like.

The invention discloses a sugar chain marker combination for predicting prognosis of liver cancer transarterial chemoembolization and application of the sugar chain marker combination. The invention discovers and verifies that the combination composed of NA3Fb, NA4Fb and NA4F2b can be used as a novel marker for evaluating TACE treatment reaction and prognosis by analyzing a serum sugar chain map of a liver cancer patient for the first time. Based on the marker combination, a TACE-GT prognosis scoring model and system are established, and the progression risk of a patient within 12 months after a TACE operation can be effectively distinguished by noninvasively detecting the expression levels of three carbohydrate chains in serum of the patient and calculating a specific score. The detection method provided by the invention is based on a blood sample, and has the advantages of noninvasiveness and convenience, and a risk assessment system can provide individualized curative effect prediction and decision support for clinicians before and after TACE treatment, and has important values for realizing precise treatment of liver cancer and improving prognosis of patients.

The invention belongs to the technical field of biological medicine, and particularly relates to a kit for breast cancer diagnosis and application thereof. The kit comprises an elisa plate coated with a captured antibody and an HRP labeled antibody working solution, the capture antibody is a monoclonal antibody T2X-1 of an anti-PSTPIP1 protein; the HRP labeled antibody is a monoclonal antibody Z4Y-2 of an anti-PSTPIP1 protein, and the HRP labeled antibody is a monoclonal antibody Z4Y-2 of an The heavy chain amino acid sequence of the monoclonal antibody T2X-1 is as shown in SEQ ID NO.1, and the light chain amino acid sequence of the monoclonal antibody T2X-1 is as shown in SEQ ID NO.2; the heavy chain amino acid sequence of the monoclonal antibody Z4Y-2 is as shown in SEQ ID NO.3, and the light chain amino acid sequence of the monoclonal antibody Z4Y-2 is as shown in SEQ ID NO.4. The kit for breast cancer diagnosis provided by the invention can be used as an auxiliary diagnosis means for breast cancer with high expression of PSTPIP1 protein, and has high diagnostic value.

The invention provides a sustained-release microneedle for treating ill-conditioned pregnancy and a preparation method and application thereof, and relates to the technical field of biological medicines.The sustained-release microneedle for treating ill-conditioned pregnancy comprises a base and a needle tip on the base, the needle tip part of the gel microneedle is made of heparin medicine, and the needle tip part of the gel microneedle is made of gelatin. The heparin medicine comprises heparin, heparin sodium, low-molecular heparin, low-molecular heparin sodium or low-molecular heparin calcium; the needle point part comprises a heparin photo-crosslinking monomer, and the base comprises a biocompatible polymer matrix. The sustained-release microneedle for treating pathological pregnancy provided by the embodiment of the invention has good mechanical strength, skin permeability and anticoagulant activity, can reduce skin bruises caused by subcutaneous injection of heparin, improves abortion caused by infection and inflammation and abortion caused by APS (anti-phospholipid antibody syndrome), can realize sustained release of drugs and increase of drug loading capacity, and has good application prospects. Sustainable drug delivery is achieved, and frequent injection is avoided.

Aspects of the disclosure relate to methods of reducing expression or activity of DUX4 (e.g., DUX4 protein and / or mRNA) and / or methods of treating facioscapulohumeral muscular dystrophy (FSHD) in a subject. In some embodiments, the methods comprise administering to the subject a composition comprising complexes (e.g., muscle targeting complexes) comprising an oligonucleotide (e.g., an RNAi oligonucleotide such as an siRNA) covalently linked to an antibody (e.g., anti-TfRl antibody).

The invention relates to the technical field of biology, in particular to a swelling hippocampal peptide as well as a preparation method and application thereof. Comprising a polypeptide with an amino acid sequence as shown in SEQ ID NO.1. The hippocampus antioxidative peptide is prepared by adopting an ultrahigh pressure pretreatment and enzymolysis technology, the adopted extraction process is simple in route, and the time and the production cost are effectively saved; an animal model is utilized to prove the antioxidation effect and the effect of improving male reproductive disorder and testis injury of the hippocampal swelling peptide; and on the basis, a novel peptide fragment with high activity, no toxicity and no sensitization is obtained.

The invention discloses a diluent for whole blood lateral immunochromatography detection as well as a preparation method and a detection method thereof, and belongs to the technical field of immunochromatography detection. The diluent solves the technical problems of unsmooth chromatography, background interference, poor stability of detection results and the like caused by red blood cells during direct detection of whole blood samples. The diluent comprises a buffer system, an osmotic pressure regulator glycine, a nonionic surfactant polysorbate, an erythrocyte aggregation inducer polyvinylpyrrolidone, a dynamic viscosity regulator trehalose, a blocking protein, a stabilizer combination L-methionine and L-histidine, and a composite formula of water. Red blood cells are effectively induced to gather and intercept on the sample pad through the synergistic effect of all the components, and meanwhile the stability of the chromatography process and the activity of the detection reagent are maintained. The diluent is mainly used for lateral immunochromatography quantitative detection of markers such as pro-enkephalin, C-reactive protein, cardiac troponin I or N-terminal pro-brain natriuretic peptide in a whole blood sample.

The invention provides a full-automatic indirect immunofluorescence interpretation method and system, a storage medium and a program product, and relates to the technical field of indirect immunofluorescence detection.The method comprises the steps that when identification information of a target sample is obtained, a plurality of sealed antigen slides are placed in slide carrying groove positions of a bearing platform in batches, and the target sample is obtained; driving the bearing platform through the transmission mechanism to sequentially move the plurality of antigen slides to the imaging area, and performing positioning and fixing operation on the antigen slides entering the imaging area by using the positioning and clamping device; sequentially carrying out multi-view scanning on the antigen slides entering the imaging area to obtain multi-view fluorescence images, and splicing the fluorescence images to generate a fluorescence panoramic image; performing feature extraction on the panoramic image, determining a fluorescence karyotype category and a target fluorescence intensity value, and determining an antibody titer according to the category, the intensity value and dilution information; and performing association mapping on the titer, the category and the panoramic image according to the identification information to generate a fluorescence interpretation result.

The invention discloses a macrophage-targeting inhalable nano material, a preparation method thereof and application of the inhalable nano material in treatment of sepsis myocarditis, and belongs to the technical field of medicines. The nano-material is a nano-liposome, the nano-liposome comprises a mannose modified nano-liposome microsphere, and the mannose modified nano-liposome microsphere comprises a liposome skeleton shell layer, a drug and a targeting layer; the liposome skeleton shell layer comprises soybean lecithin and cholesterol; the medicine comprises quercetin and TPPU (Thermoplastic Polyurethane); and the targeting layer is formed by connecting mannose modified DSPE-PEG2000 to the outer surface of the liposome skeleton shell layer. The nano material can accurately target macrophages at a cardiac inflammation part, has a multi-target-point synergistic effect, is more convenient and faster in administration, remarkably improves the safety and comprehensively improves the treatment effect.

The invention provides a cancer risk level distinguishing method and system, and relates to the technical field of prostate cancer, the method comprises the following steps: obtaining personal information of a screening object and a prostate specific antigen inspection result of the screening object; based on the personal information of the screening object and the prostate specific antigen inspection result of the screening object, determining a risk value of antigen inspection of the screening object; if the risk value of the antigen examination of the screening object is greater than a preset threshold value, obtaining a prostate magnetic resonance scanning image of the screening object; constructing a graph structure; processing the graph structure based on a graph convolutional network to determine prostate cancer analysis information; based on the prostate magnetic resonance scanning image of the screened object and the prostate cancer analysis information, using a generative adversarial network to generate a prostate cancer simulated growth video; the prostate cancer risk level is determined based on the prostate cancer simulated growth video, and the method can accurately evaluate the risk of prostate cancer.

The invention discloses a breath anomaly detection method and system based on gas monitoring, and relates to the technical field of breath anomaly detection.The breath anomaly detection method comprises the steps that mouth and nose gas signals in the breath process of a user are collected and preprocessed, and gas component separation is conducted through a microfluidic gas separation module; and performing differential analysis on separated gas components, calculating fluctuation of nasal cavity and oral cavity gas components, performing breathing mode recognition through 1D SNN, and establishing a personalized breathing mode library in combination with long-term health data of a user. Compared with the prior art, the method has the advantages that more accurate breathing mode recognition and anomaly detection are realized by combining differential analysis of multi-dimensional gas components and a deep learning model with a personalized breathing mode library, so that a more intelligent health management scheme is provided, and particularly, the method has remarkable advantages in coping with complex personalized differences and long-term health trends.

The invention relates to the technical field of medical artificial intelligence, and discloses a non-small cell lung cancer immunotherapy risk assessment method and system and a storage medium, and the method comprises the steps: constructing an optimal strategy tree model capable of dividing a patient into a plurality of subgroups based on a historical patient data set, and determining an initial optimal treatment strategy for each subgroup; determining a subgroup to which a new patient belongs and an initial treatment strategy thereof according to the model; in the treatment process, the deviation degree between the individual response trajectory of the patient and the average response trajectory of the subgroup to which the individual response trajectory belongs is calculated; and when the deviation degree exceeds a preset threshold value of the subgroup, triggering an adaptive adjustment mechanism, and outputting an updated treatment suggestion. By establishing a dynamic monitoring and closed-loop feedback mechanism based on the subgroup benchmark, the technical problem that an existing scheme is difficult to carry out prospective identification and dynamic intervention on individualized risks is solved, so that the accuracy, safety and individualized level of non-small cell lung cancer immunotherapy are improved.

The invention relates to the technical field of data processing, and discloses a method and system for predicting a hypotension risk in dialysis based on machine learning. The method comprises the following steps: calculating an ultrafiltration rate-blood pressure decreasing amplitude coupling coefficient by collecting ultrafiltration rate, blood flow volume, transmembrane pressure and blood pressure data in a dialysis process, obtaining a dialysis tolerance index in combination with a vascular compliance parameter, and constructing a stage weighting function according to dialysis duration to determine a weight coefficient of each period; and performing weighted calculation with individual baseline dialysis tolerance to set a personalized risk threshold value, and establishing a sliding window prediction mechanism to predict the probability of occurrence of hypotension in the future. The problems that a static prediction mode cannot adapt to dynamic changes in the dialysis process and is lack of personalized risk assessment are solved, and the accuracy and timeliness of hypotension risk prediction in dialysis are improved.

The invention discloses a method for predicting the curative effect of brain stimulation on MCI based on a multi-modal image, and belongs to the technical field of medical data process.The method comprises the steps that through a multi-modal MRI feature fusion model, structure and functional MRI indexes are synchronously integrated, feature selection and dimension reduction are conducted through comparison between independent sample t test groups and LASSO regression, and the curative effect of brain stimulation on MCI is predicted; compared with the existing method, the method has the advantages that the obvious contribution of the change of the collaborative structure image index and the functional image index to the predicted curative effect is verified through the structure-function coupling analysis, and the prediction model is constructed, so that the prediction efficiency is improved. The contribution direction and strength of each image feature to curative effect prediction are analyzed and quantified in combination with SHAP values, feature weights are automatically optimized according to SHAP value distribution, and model high-contribution feature brain regions are revealed through SHAP so as to clarify curative effect biomarkers.

The invention discloses a plateau newborn rare disease multi-mode combined screening system and a storage medium, and belongs to the technical field of medical software development. The plateau adaptability newborn rare disease multi-mode combined screening system is constructed, the plateau adaptability of the screening system is enhanced, the cost is remarkably reduced, and the screening system has a good application prospect.

The invention relates to a double-framework self-developing embolism system based on iodine modified PNIPAM gel and cross-linked albumin microspheres, which simulates a brick wall-concrete effect through a microsphere-gel composite structure and synergistically improves the embolism strength. A novel TACE treatment system is designed and constructed, multiple effects of tracing, embolism, hypoxia enhanced chemotherapy and tumor microenvironment improvement are achieved through the self-developing temperature-sensitive gel-drug carrying microspheres, and the anti-tumor effect is cooperatively improved.

Theranostic targeted ultrasonic blasting nano-bubbles, a preparation method therefor, and use thereof, wherein the nano-bubbles are the targeted drug-gene nano-bubbles miRNA / FTY720 / PFP@PEI-T7 NBs. The nano-bubbles can be used for preparing a thyroid ultrasound diagnostic agent or a drug for treating thyroid cancer.

A blood cell analyzer (100) and a blood cell analysis method (300). The blood cell analysis method (300) comprises: sucking a blood sample to be tested; preparing a first determination sample and obtaining first optical information; preparing a second determination sample and obtaining second optical information; generating a first leukocyte classification scatter diagram and a second leukocyte classification scatter diagram; determining a first counting result of neutrophils of the to-be-detected blood sample based on the first leukocyte classification scatter diagram and the second leukocyte classification scatter diagram; determining an actual distribution area of neutrophils from the first leukocyte classification scatter diagram; based on a reference distribution region of neutrophils of a reference leukocyte classification scatter diagram of the normal blood sample, determining a leaf-division nucleophore distribution region from the actual distribution region; determining a second counting result of the cells falling into the leaf-separating nucleogranulocyte distribution area; and based on the first counting result and the second counting result, determining a counting result of the rod-shaped nuclear granulocytes in the to-be-detected blood sample.

Provided herein are compositions and methods for treating patients with Usher syndrome associated retinitis pigmentosa (UARP) comprising identifying that the subject has UARP and administering to the animal or human an effective amount of an N-acetylcysteine amide (NACA) sufficient to protect vision and inhibit degradation of Ellipsoid Zone (EZ) area and retinal sensitivity. In one example, the NACA formulation is doses at 50, 100, 200, 201, 210, 225, 250, 275, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, or 1,000 mg / day.