45 results about "Multiple tumors" patented technology

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 present application relates to a multispecific binding molecule that targets BCMA, GPRC5D, and T cell receptors. Specifically, the invention discloses a BCMA-GPRC5D-CD3 multispecific antibody which can activate T cells while being combined with a tumor surface antigen, thereby promoting the specific killing of the T cells on tumor cells, especially BCMA or GPRC5D positive multiple myeloma. The invention also provides a preparation method and application of the multispecific binding molecule.

The invention discloses a brain glioma classification method and device based on multi-mode MRI, and relates to the technical field of image processing. According to the method, multiple tumor sub-regions of the brain glioma are acquired based on a to-be-processed multi-modal MR image, multiple local ROIs are extracted based on the multiple tumor sub-regions, and then the sub-type of the brain glioma is determined based on the multiple local ROIs and a global ROI. The subtype can be determined through the multi-modal MR image, so that on one hand, non-invasive identification of the subtype is realized, and bleeding and infection risks caused by identification of the subtype are avoided; and on the other hand, the classification accuracy can be improved by utilizing complementary information between different modal images and a boundary form between different tumor sub-regions. Besides, through the fine structure features of each tumor sub-region reserved from a plurality of visual angles by the plurality of local ROIs, and in combination with the spatial distribution context information of the whole brain glioma provided by the global ROI, a better balance between the processing precision and the calculation efficiency can be realized.

The invention provides a three-dimensional MRI (Magnetic Resonance Imaging) tumor segmentation method based on boundary perception and tumor diagnosis equipment. The method comprises the following steps: acquiring three-dimensional MRI (Magnetic Resonance Imaging) of multiple tumor patients as a tumor data set, wherein the three-dimensional MRI comprises gadolinium-enhanced T1SC slices; performing tumor segmentation by taking the three-dimensional MRI in the tumor data set as input of a first segmentation model to obtain a category label of a tumor in the three-dimensional MRI; wherein the first segmentation model is a model based on a convolutional neural network CNN, the first segmentation model comprises a first model branch and a second model branch, the first model branch is used for predicting a category label, and the second model branch is used for predicting a surface distance field of a tumor based on boundary perception; the surface distance field is used for describing the nearest distance from each voxel to the tumor surface in the three-dimensional MRI, and training and optimization of the first segmentation model are carried out based on training and optimization of the first model branch and the second model branch.

A method of delivering tumor treating electric fields to a body of a patient. The method includes scanning the body of the patient for identifying at least two tumor-filled areas. The method further includes determining a spatial relationship in between the at least two tumor-filled areas. The method further includes arranging an array of insulated electrode elements on the body of the patient. The method further includes implementing at least two subarray firing configurations for the array of insulated electrode elements to treat the at least two tumor-filled areas depending at least in part upon the spatial relationship in between the at least two tumor-filled areas such that each subarray firing configuration treats a respective tumor-filled area.

This invention provides a dual-modal composite tumor treatment system, belonging to the medical field, which solves the problem of inconvenient tumor examination due to the lack of routine tumor examinations. It includes a feature extraction module, a model construction module, a treatment determination module, and a real-time monitoring module. The feature extraction module extracts the physical characteristics of multiple tumor patients to obtain the frequency ranges of chest pain, cough, and chest tightness. The model construction module constructs a preliminary tumor identification model for each tumor patient. The real-time monitoring module monitors the physical characteristics of the examiner in real time to obtain the real-time frequency of chest pain, cough, and chest tightness. The treatment determination module makes a preliminary determination of the examiner's tumor condition. This invention achieves routine tumor examination based on a dual-modal approach.

The invention discloses an HIV (human immunodeficiency virus) combined hepatocellular carcinoma risk stratification model and a construction method thereof, the construction method comprises the following steps: obtaining clinical data of an HIC-HCC patient, the clinical data comprising demographic information, clinical feature information and treatment and outcome information; taking the total lifetime of the patient as an outcome, performing single-factor analysis on the clinical data, and screening out a plurality of risk factors influencing the total lifetime of the patient; performing multi-factor analysis on the plurality of risk factors to obtain independent prognosis factors of the total lifetime of the patient; the independent prognosis factors comprise organ fatigue and multiple tumors; and establishing a risk layering model based on the independent prognosis factors.

The invention belongs to the field of intelligent medical treatment, and particularly relates to a bladder tumor image segmentation method and device, a medium and a program product. The method comprises the following steps: S101, acquiring an image of a bladder tumor patient; s102, inputting the image into a 2D U-Net for tumor segmentation to obtain a 2D segmentation result; s103, traversing the shape of the tumor based on the 2D segmentation result, inputting the image into 3D U-Net for tumor segmentation to obtain a 3D segmentation result if the shape of the current tumor is regular during traversing, and taking the segmentation result of the current tumor in the 3D segmentation result; if the tumor shape is irregular, the segmentation result of the current tumor in the 2D segmentation result is obtained, and after traversal is completed, the segmentation results of the multiple tumors are output after merging. Through the hybrid 2D-3D method, the segmentation performance can be optimized by using the complementary advantages of the two methods, and a better segmentation result is obtained.

The present invention proposes a method and system for predicting the efficacy of lung cancer immunotherapy based on dual CT images, belonging to the technical field of medical image processing. First, the tumor regions of the baseline CT image and the puncture CT image are labeled. The puncture position in the puncture CT image is registered to the baseline CT image, and the baseline CT image is divided into multiple tumor sub-regions. Based on a spatial attention deep learning model, the PD-L1 expression level at the position of each tumor sub-region is predicted and a PD-L1 map is generated. A dual-task prediction model is constructed, and the clinical information of the patient, the baseline CT image, and the PD-L1 map are input into the dual-task prediction model to predict the efficacy of lung cancer immunotherapy. The present invention can achieve accurate prediction of the efficacy of lung cancer immunotherapy for non-small cell lung cancer patients on the basis of ensuring effective image-pathological spatial matching of non-small cell lung cancer.

The present invention relates to the technical field of medical care, and particularly relates to a tumor prognosis prediction method based on tumor database text recognition, comprising the following steps: S1, data collection and preprocessing: collecting tumor-related medical data from multiple tumor databases; S2, text information extraction: extracting information from clinical text data; S3, tumor metastasis path prediction: using a graph neural network model to predict the metastasis path, predicting the potential metastasis path of the tumor, and analyzing the impact of different metastasis paths on the prognosis of patients; S4, prognosis evaluation and risk prediction: combining the medical data of patients to predict the tumor prognosis risk, and comprehensively evaluating the predicted value of the five-year survival rate and the predicted value of the recurrence risk of patients. The present invention can assist medical institutions in optimizing resource allocation, formulating scientific personalized diagnosis and treatment plans, and significantly improving the survival quality and treatment effect of patients.

The invention discloses a rare earth nanoprobe, a preparation method and application thereof, and belongs to the technical field of biomedical detection.According to the technology, the rare earth nanoprobe with the high fluorescence quantum yield is synthesized, specific recognition of tumor markers is achieved through the aptamer technology, and the detection sensitivity and selectivity are remarkably improved. The fluorescence signal amplification effect of the rare earth nanoprobe and the modern fluorescence detection technology are innovatively combined, so that simultaneous detection of multiple tumor markers such as carcino-embryonic antigen (CEA), prostate specific antigen (PSA) and alpha fetoprotein (AFP) becomes possible. According to the method, the detection limit reaches the pg / mL level, the operation is simple and convenient, the cost is low, and the feasibility of clinical application is greatly improved. Besides, through multiple detection design, the detection efficiency and accuracy are further improved, an effective tool is provided for early diagnosis, curative effect monitoring and prognosis evaluation of tumors, and wide clinical application prospects and market potential are shown.

The application discloses a traditional Chinese medicine gecko miRNA and application thereof. The application screens a traditional Chinese medicine gecko miRNA with potential anti-tumor effect by mining the miRNA from the traditional Chinese medicine gecko, and names the miRNA as gek-miR-2862, and the nucleotide sequence of the miRNA is shown as SEQ ID NO. 1. Research results show that the gek-miR-2862 can regulate multiple tumor-related signal pathways and inhibit liver cancer cell proliferation. Therefore, the traditional Chinese medicine gecko miRNA provided by the application can become a biological preparation for treating tumors and has potential drug development value, and provides a new solution for tumor treatment.

The present invention relates to a method for delivering a tumor treating electric field to a patient's body. The method includes scanning the patient's body to identify at least two tumor-filled regions. The method also includes determining a spatial relationship between the at least two tumor-filled regions. The method also includes positioning an array of insulated electrode elements on the patient's body. The method also includes implementing at least two sub-array transmit configurations of the insulated electrode element array to treat the at least two tumor-filled regions based at least in part on the spatial relationship between the at least two tumor-filled regions, such that each sub-array transmit configuration treats a corresponding tumor-filled region. The present invention also relates to a method for configuring a tumor treating field device and a tumor treating field device including an array of insulated electrode elements coupled to a control device.

The application provides a boundary-aware three-dimensional MRI tumor segmentation method and a tumor diagnosis device. The method comprises: acquiring three-dimensional MRIs of multiple tumor patients as a tumor dataset, the three-dimensional MRIs comprising gadolinium-enhanced T1 SC slices; performing tumor segmentation on the three-dimensional MRIs in the tumor dataset as input of a first segmentation model to obtain a class label of the tumor in the three-dimensional MRI; wherein the first segmentation model is a model based on a convolutional neural network (CNN), the first segmentation model comprises a first model branch and a second model branch, the first model branch is used for predicting the class label, and the second model branch is used for predicting a surface distance field of the tumor based on boundary awareness, the surface distance field is used for describing the nearest distance of each voxel in the three-dimensional MRI to the surface of the tumor, and the training and optimization of the first segmentation model are based on the training and optimization of the first model branch and the second model branch.

A novel bipolar electrode electrochemical luminescence array biosensing platform, namely ML-cBPE, is designed on the basis of a high-flux bipolar electrode chip and a light emitting diode (LED), and is used for realizing multi-target simultaneous detection and visual imaging. As a semiconductor material, the luminous efficiency of LEDs is far higher than that of a traditional luminous reagent. Miniaturization serves as the outstanding advantage of the LED, and seamless connection between the LED and the BPE can be achieved conveniently. An ECL probe Ab2 (at) Au (at) MnO2 with peroxidase activity is introduced into a BPE cathode array through enzyme-linked immunosorbent assay in a BPE sensing array, H2O2 can be accelerated under the action of enzyme, more electrons in a system can flow to an LED report array, and multi-target sensitive detection and visual imaging are achieved. Compared with a solution, the solid-state electrochemical luminescence has lower excitation potential and more obvious luminescence, and plays a role in protecting the electrode to a certain extent. The portable, integration and miniaturization are well embodied, and the requirement for clinical timely detection (POCT) is met.

The utility model discloses a kind of kits for multiple tumor marker detection, it is related to medical instrument technical field, including box and sample liquid preparation component, the box one end is equipped with receiving groove, the sample liquid preparation component is set in receiving groove inside, the sample liquid preparation component includes the needle cylinder being set to outside, needle cylinder inside is filled with blood sample diluent in advance.This application provides a kind of kits for multiple tumor marker detection, the blood sample of examinee is injected by needle cylinder one side middle part injection port using syringe, and mixed with the blood sample diluent filled in advance in needle cylinder, operator handheld needle cylinder and through the cooperation of rotating shaft sleeve and receiving groove side wall connecting port, swing needle cylinder so that blood sample and diluent are mixed uniformly, squeeze needle handle again, and sample liquid flows to detection area through distribution flow channel, the sample liquid preparation component is integrated in the side of box in this application, it is convenient for user to prepare blood sample quickly, and it is more practical.

The utility model discloses a microwell plate for 3D (three-dimensional) culture and function evaluation test of primary cells, belongs to the technical field of microwell plates, and solves the problems that a plurality of tumor organs are different in size and are distributed on different planes due to the fact that the existing primary tumor organ cells are cultured in a plurality of culture dishes. The porous plate comprises a porous plate main body and a plurality of counter bores arranged on the porous plate main body in an array; a plurality of sinking grooves are formed in the bottom face of each counter bore, and each sinking groove is in an inverted regular rectangular pyramid shape. A plurality of tumor organs which are consistent in size and are positioned on the same height plane can be cultured by the plurality of counter bores in the microplate main body, so that subsequent imaging detection and statistics are facilitated. The arrangement of the inverted rectangular pyramid-shaped sinking groove enables primary tumor organoid cells to be uniformly gathered to the bottom of the sinking groove, formation of a more consistent organoid is facilitated, and the rectangular pyramid-shaped sinking groove can guide the organoid or cells to be concentrated at a specific position, so that improvement of imaging consistency is facilitated.

The application discloses a tumor image analysis method based on deep learning, and relates to the technical field of image processing; a plurality of tumor images respectively corresponding to a plurality of tumor types are acquired, tumor images with tumor region areas greater than a preset tumor region area and tumor images with tumor region aggregation degrees greater than a preset aggregation degree are respectively screened out from the tumor images, important tumor images are determined in combination with tumor types respectively corresponding to the tumor images, and important tumor image analysis results are obtained based on the important tumor images. Therefore, the analysis method not only combines tumor images of multiple types, but also realizes analysis and screening of the tumor images in combination with a deep learning algorithm, so that effective analysis of tumor images of multiple tumor types can be realized, and accurate and effective screening of important tumor images can be realized.

This invention provides a method for analyzing tumor-specific gene mutations in subjects with multiple tumors, based on gene mutation information identified by ctDNA testing. [Solution] A step of obtaining first gene mutation information identified by ctDNA testing of the subject, second gene mutation information output by analyzing images of a first target area in the subject, and third gene mutation information output by analyzing images of a second target area in the subject that is different from the first target area, and A step of determining whether a tumor-specific gene mutation included in the first gene mutation information is related to a gene mutation in the first target site for imaging included in the second gene mutation information, or a gene mutation in the second target site for imaging included in the third gene mutation information. A method for analyzing gene mutations, comprising the following:

This invention discloses a tumor marker detection system based on an antibody-modified gold nanoparticle periodic linear array, belonging to the field of biomolecular detection. In this invention, a primary antibody is modified onto gold nanowires, and a nanolabel of antibody molecules modified onto gold nanoparticles is prepared as a detection tag (secondary antibody) for tumor markers. A test solution mixed with the secondary antibody is drop-coated onto the structure, and after a sufficient reaction time, the entire structure is rinsed. When light is incident perpendicularly on the gold nanowire array, surface plasmon resonance (SPR) occurs. The tumor markers (antigens) present in the solution are specifically adsorbed with the primary and secondary antibodies, forming a double-antibody sandwich structure, which changes the macroscopic color of the structure. By observing whether the color changes in different regions of the nanowire array after detection, the presence of tumor markers in the test solution can be determined. This invention's system can simultaneously detect multiple tumor markers and features short detection time, small size, low cost, high sensitivity, and ease of outdoor observation.

The application belongs to the field of intelligent medical treatment, and particularly relates to a bladder tumor image segmentation method, device, medium and program product. The method comprises the following steps: S101, acquiring an image of a bladder tumor patient; S102, inputting the image into a 2D U-Net for tumor segmentation to obtain a 2D segmentation result; S103, based on the 2D segmentation result, traversing the shape of the tumor, if the current tumor shape is regular, inputting the image into a 3D U-Net for tumor segmentation to obtain a 3D segmentation result, and taking the segmentation result of the current tumor in the 3D segmentation result; if the tumor shape is irregular, taking the segmentation result of the current tumor in the 2D segmentation result, and after the traversal is completed, merging and outputting the segmentation results of multiple tumors. The application can optimize the segmentation performance by using the complementary advantages of the 2D-3D method, and obtain better segmentation results.

The invention discloses a method for detecting a tumor marker by a biological chip, and relates to the technical field of tumor detection. The kit has high throughput, can detect multiple tumor markers at the same time, and is suitable for large-scale population screening; the sensitivity is high, and tumor markers at an extremely low level can be detected; high specificity is achieved, non-specific binding is reduced, and the detection accuracy is improved; the product has high stability and can be stored and transported for a long time at normal temperature.

This invention relates to a method for using an antibody-drug conjugate to treat cancer. Specifically, the invention provides a method for using an antibody-drug conjugate, its pharmaceutically acceptable salt, stereoisomer, or metabolite, or a solvate thereof, to treat cancer, and the use of said antibody-drug conjugate in the preparation of medicaments for the prevention and / or treatment of cancer. The method has improved safety and has demonstrated promising antitumor activity in multiple tumor types, meeting medical needs.

This invention discloses an electrochemiluminescence microfluidic chip for the detection of multiple tumor markers, relating to the field of biodetection technology. It includes a substrate and a microfluidic channel system, an electrochemiluminescence detection unit, and a signal acquisition interface integrated on the substrate. The microfluidic channel system includes a sample inlet, a shunt structure, multiple parallel and equally spaced detection channels, and a waste liquid pool connected in sequence. The shunt structure includes a main channel and multiple branch channels integrally formed with the main channel. In this invention, the microfluidic channel system, the electrochemiluminescence detection unit, and the signal acquisition interface are integrated on the same substrate, achieving an integrated design for sample transmission, reaction, detection, and signal export. Compared to traditional distributed detection technologies, this significantly simplifies the detection operation steps, reduces the professional skills required of operators, and shortens the detection cycle, meeting the needs of rapid clinical diagnosis.

The invention provides an intelligent tumor data processing system and method based on a PDX model, and relates to the technical field of data anomaly detection, and the method comprises the steps: setting a plurality of collection features; collecting a plurality of tumor characteristic parameters; performing data analysis on the plurality of tumor characteristic parameters, and establishing a plurality of tumor data analysis results; performing matching of the plurality of anomaly detection channels, performing anomaly detection, and determining a plurality of tumor anomaly data; performing error compensation on the plurality of tumor characteristic parameters to obtain a plurality of tumor correction parameters; and updating the PDX model to obtain an optimized PDX model. Through the method and the device, the technical problem that the simulation accuracy of the PDX model based on incomplete or wrong data in the training process is further influenced due to low anomaly recognition accuracy of an anomaly detection method in the prior art can be solved; the technical aims of improving the anomaly detection accuracy and capturing complex nonlinear changes in tumor parameters are achieved, and the technical effect of optimizing the precision of the PDX model is achieved.

Provided herein are methods for decreasing the toxicity of advanced ablative cancer therapies on neighboring organs. The methods herein provide spacing between single or multiple tumor cites and immediate healthy organs while maintaining or increasing patient quality of life. Such toxicity isolation can be performed by inserting a spacer around the one or more tumor sites.

Provided are a variety of fusion proteins containing truncated forms of TGFβR2 and constructed with the EGFR antibody HPA8, as well as nucleic acids encoding the antibodies (including heavy / light chain variable regions), vectors containing the nucleic acids, pharmaceutical compositions and kits; also provided are fusion proteins of the prepared truncated forms of TGFβR2 receptor proteins and antibodies targeting EGFR and other multiple tumor targets.

A method of delivering tumor treating electric fields to a patient after tumor remission using predictive data in a preventive therapy, which includes the steps of: reviewing a scan of the body; identifying remissive tumor-filled areas on the scan; determining a spatial relationship between remissive tumor-filled areas and predicted locations of tumors; arranging an array of insulated electrode elements on the body, the array of electrode elements being coupled to an electric field generator, a control device configured to send a signal to the generator causing the generator to deliver tumor-preventative electric fields to the electrode elements; determining at least two subarray firing configurations for the array of electrode elements for targeting the remissive tumor-filled areas, the subarray firing configurations depending at least in part upon the spatial relationship between the two remissive tumor-filled areas; and delivering the tumor-treating fields to the remissive tumor-filled areas using the subarray firing configurations.

The invention discloses application of artesunate in preparation of a PRMT1 inhibitor and / or an alpha-ketoglutaric acid supplement, and relates to the technical field of biological medicines. It is found through experiments that artesunate can target and inhibit the activity of arginine methyltransferase of PRMT1, inhibit methylation modification of downstream molecules IDH2 of PRMT1 and reduce expression of the downstream molecules IDH2, and then mitochondrial metabolic disorder in cancer cells is induced, including accumulation of various metabolites such as alpha-ketoglutaric acid. Therefore, a new application of artesunate is provided, and artesunate is used for preparing a PRMT1 inhibitor and / or an alpha-KG supplement. In addition, it is verified that artesunate can significantly inhibit tumor growth of multiple tumor-bearing mice and promote anti-tumor immunity, and artesunate can be used as a PRMT1 inhibitor and / or an alpha-KG supplement to prepare anti-tumor immunotherapy drugs.