68 results about "Node metastasis" patented technology

The invention belongs to the technical field of medical image processing, and particularly relates to a non-functional pancreatic neuroendocrine tumor preoperative index prediction method and system. According to the method, on the basis of abdomen CT image lesion segmentation, pathological grading (low risk / high risk) and lymph node metastasis (LNM) risks are jointly predicted through a multi-task deep learning framework; according to the method, tumor morphological features, radiomics features and clinical parameters (such as tumor size and position) extracted by a segmentation network are combined, and high-precision prediction of preoperative key indexes is realized by using a feature fusion module and a lightweight classification head; through a cross-modal attention mechanism and multi-center data verification, the model achieves the pathologic classification AUC of 0.75 on an internal verification set, achieves the LNM prediction AUC of 0.78, and is significantly superior to traditional clinical experience judgment. According to the method, reliable decision support is provided for preoperative precise operation planning and personalized treatment.

This invention provides a method, device, and equipment for preoperative risk stratification assessment of endometrial cancer. It involves segmenting and annotating preoperative ultrasound images to extract radiomics feature vectors, and simultaneously performing structured encoding and mapping of pathological biopsy data to generate pathological feature vectors. These two feature vectors are then input into a fusion network containing a cross-modal attention gating module. This gating module automatically generates dynamic weight vectors based on the consistency between the image and pathological features. The two feature vectors are then weighted and modulated separately before being concatenated to obtain a joint feature representation. This automatically reduces the weight of the lower-confidence modality and amplifies the weight of the higher-confidence modality when their assessment conclusions are inconsistent. Finally, the joint feature representation is input into a multi-task prediction network to output the probability of myometrial invasion depth and the probability of lymph node metastasis risk, thereby generating preoperative risk stratification results and surgical plan recommendations.

The invention relates to the technical field of methylation detection site detection, and particularly provides an early gastric cancer lymph node metastasis risk prediction method, system, application and medium, and the method comprises the following steps: obtaining a gastric cancer public data set containing a DNA methylation chip data set and an RNA sequencing data set, and carrying out sample screening, quality control and grouping processing to obtain eight quality control grouping samples; carrying out methylation and RNA difference analysis on the quality control grouped samples to obtain a related gene set of differential methylation sites and differential methylation regions and an RNA differential expression gene set; a gene set of differential methylation sites and an RNA differential expression gene set are integrated and screened to obtain eight target genes. The system comprises a sample acquisition module, a gene analysis module and a gene screening module. Target genes are analyzed and screened on the basis of database biological information, and methylation detection sites for histopathological specimens are screened in combination with lymph node metastasis positive and negative early gastric cancer histological sample verification.

The invention discloses a tumor detection marker and application thereof in medicine preparation, and belongs to the technical field of biomedicine. Clinical sample qRT-PCR (quantitative real-time polymerase chain reaction) shows that ENST00000412203.1 is obviously up-regulated in breast cancer tissues, the area (AUC) under the ROC curve reaches 0.9822, and the diagnosis efficiency is excellent. In addition, the invention further finds that the expression of the polypeptide in lymph node metastasis tissues is obviously improved, and metastasis specificity is displayed. Meanwhile, the expression of ENST00000412203.1 is knocked down through siRNA, it is found that proliferation, migration and invasion of breast cancer cells are remarkably inhibited, and therefore the siRNA can be used for preparing targeted therapy drugs for breast cancer and has important clinical application value.

The application provides a breast cancer patient lymph node metastasis prediction model without clinical pathological characteristics, comprising the following steps: after three-dimensional reconstruction of two-dimensional lung enhanced CT films, an axillary lymph node atlas is established, all axillary lymph nodes in the atlas are selected as ROI regions, and more than 5 combined image features of each axillary lymph node are selected to distinguish whether breast cancer has axillary lymph node metastasis; and a logistic regression machine learning prediction model is used to construct the breast cancer patient axillary lymph node metastasis prediction model. The model established by the application can non-invasively predict whether breast cancer has axillary lymph node metastasis, the clinical pathological characteristics of the patient are not included in the model, and the image cutting in the model is not based on breast tumors, but based on axillary lymph nodes; the model is used to determine a suitable axillary treatment scheme, thereby avoiding unnecessary axillary surgery and complications, and helping to carry out more accurate surgery and adjuvant therapy mode of breast cancer.

The present disclosure relates to a method and apparatus for predicting mediastinal lymph node metastasis in non-small cell lung cancer based on information regarding a patient's age, a histological type of a tumor, a location of the tumor, a size of the tumor, a clinical lymph node stage determined by CT, and a clinical lymph node stage determined by PET-CT. According to an aspect of the present disclosure, a method and apparatus for predicting mediastinal lymph node metastasis in non-small cell lung cancer provides information on the presence of mediastinal lymph node metastasis in potentially operable lung cancer patients, specifically non-small cell lung cancer patients, and thus can be usefully used for decision-making on staging and treatment methods for non-small cell lung cancer patients, such as invasive mediastinal staging.

The invention discloses a collagen feature-based lymph node state judgment method and system, a terminal and a storage medium, and the method comprises the steps: obtaining a pancreatic duct gland data sample, and carrying out the collection of a multi-photon image, and obtaining a target multi-photon image; obtaining a macroscopic collagen feature in the target multi-photon image, and calculating a first score of the macroscopic collagen feature; obtaining a microscopic collagen feature in the target multi-photon image, and calculating a second score of the microscopic collagen feature; constructing a column graph model according to the first score and the second score; and acquiring current pancreatic duct gland data of the patient, and inputting the data into the column graph model to obtain a lymph node metastasis result. According to the method, the macroscopic collagen features and the microcosmic collagen features in the pancreatic duct gland data sample are extracted and combined to obtain the column graph model, and accurate judgment of lymph node metastasis can be achieved.

The present application relates to the technical field of biological medicine, and particularly relates to application of 1-DNJ in treating lymph node metastasis of gastric cancer. The present application firstly finds that 1-DNJ can play a role as a VCAM1 / VLA-4 interaction inhibitor, and further finds that 1-DNJ can be used for treating lymph node metastasis of gastric cancer, expands the application range of 1-DNJ in the field of antitumor, and provides a new technical scheme for prevention and treatment of lymph node metastasis of gastric cancer. 1-DNJ belongs to a small molecule compound, has the characteristics of convenient preparation, good potential tissue penetration ability and flexible drug administration mode, and has good prospects for drug development and clinical application.

This invention provides immunobiomarkers for the auxiliary diagnosis of esophageal cancer lymph node metastasis and their applications. Specifically, this invention provides the use of immunobiomarkers for esophageal cancer lymph node metastasis and their detection reagents, for the preparation of diagnostic reagents or kits for assessing the risk of esophageal cancer lymph node metastasis. Studies have shown that the immunobiomarkers of this invention can serve as markers of esophageal cancer lymph node metastasis with high accuracy.

The invention discloses application of an IGF2BP2-m6A-VCAN-TLR2 (Insulin-like Growth Factor 2BP2-m6A-VCAN-TLR2) signal axis in preparation of a medicine for treating lymphatic metastasis of intrahepatic cholangiocarcinoma. Aiming at the problems of unknown lymphatic metastasis mechanism and lack of effective targets of intrahepatic cholangiocarcinoma, the invention discovers and verifies that mRNA binding protein 2 of insulin-like growth factor 2 is modified by m6A to regulate and control the expression of pluripotent proteoglycan so as to activate a Toll-like receptor 2 signal, promote macrophages to secrete vascular endothelial growth factor C and drive a brand new pathway of lymphatic metastasis. Based on this, the invention provides an inhibitor targeting the signal axis, especially a small molecule compound 8010-8498. Experiments show that the compound can significantly inhibit migration, invasion and epithelial-mesenchymal transition of bile duct cancer cells, reduce macrophage secretion of vascular endothelial growth factors C, effectively inhibit tumor growth and lymphatic metastasis in a nude mouse popliteal lymph node metastasis model and a spontaneous bile duct cancer model, and present a synergistic effect when combined with gemcitabine and cis-platinum.

The invention provides a breast cancer axillary lymph node metastasis load state prediction method and system based on cross-domain ultrasonic data, and relates to the technical field of image processing, and the method comprises the steps: obtaining a training set, training a constructed breast cancer axillary lymph node metastasis load state prediction model through the training set, and obtaining a breast cancer axillary lymph node metastasis load state prediction model; obtaining a trained breast cancer axillary lymph node metastasis load state prediction model; and inputting the ultrasonic images of the breast primary focus area and the axillary lymph node area of a patient to be predicted into the trained breast cancer axillary lymph node metastasis load state prediction model to obtain a breast cancer axillary lymph node metastasis load state fine prediction result. According to the method, the breast cancer axillary lymph node metastasis load state prediction model can be utilized to effectively extract and fuse the features of the cross-domain ultrasonic data, and the fused information is classified and corrected to obtain a fine prediction result of the breast cancer axillary lymph node metastasis load state.

The invention discloses application of a NOD1 truncated splicing isomer as a marker and a target spot in preparation of a thyroid papillary minimal cancer detection reagent, an immune targeting drug and a screening method, and belongs to the technical field of biological medicine. Aiming at the problem of clinical diagnosis and treatment difficulty caused by lack of an effective lymph node metastasis prediction marker for papillary thyroid carcinoma, the invention discovers that a truncated splicing isomer NOD1-S can be used as a key transcription marker. According to the method, the transcriptional instinct of NOD1-S is specifically amplified by a specific primer pair, and a detection reagent or a kit can be prepared on the basis of the transcriptional instinct of NOD1-S; meanwhile, the NOD1-S can be used as a drug target for screening or preparing immune targeting drugs. The kit is mainly used for auxiliary detection of thyroid papillary minimal carcinoma lymph node metastasis and research and development and screening of immune targeting drugs.

The application discloses a method for predicting the lymph node metastasis risk of thyroid papillary carcinoma based on an integrated machine learning model. Specifically, the application provides a training method for an integrated risk prediction model for the lymph node metastasis of thyroid papillary carcinoma, which comprises the following steps: (s1) providing a data set comprising the expression data of marker genes of thyroid cancer patients with and without lymph node metastasis; (s2) training a basic model: training a basic prediction model based on the data set; (s3) training a fusion layer: training a stacked ensemble model and a bagging ensemble model based on the output results of the basic prediction model; (s4) training a decision layer: training a weighted fusion model based on the output results of the stacked ensemble model and the bagging ensemble model, thereby obtaining the integrated risk prediction model. The model can realize accurate prediction of the lymph node metastasis risk of thyroid papillary carcinoma.

The invention discloses a mediastinal region lymph node metastasis identification method and system based on a double-control routing hybrid expert model, and belongs to the technical field of computer intelligent auxiliary diagnosis. The invention aims to solve the problems that the existing mediastinal region lymph node metastasis identification method is low in accuracy and poor in identification effect due to the fact that the mediastinal region lymph node metastasis identification task is complicated and includes multi-dimensional information identification. According to the technical key points, a mediastinal region lymph node metastasis identification task is split into two auxiliary sub-tasks of mediastinal region detection and lymph node metastasis prediction, and the three tasks jointly form a multi-task learning system. Knowledge transmission and complementation are realized through feature sharing between tasks and gradient-based collaborative optimization, so that the feature distinguishability of each task is improved. The method is characterized in that a double-control routing gating mechanism is constructed, similar features and unique features between different tasks are extracted through a feature routing branch and a task routing branch respectively, and correlation and difference between the tasks are balanced; meanwhile, a two-dimensional gradient balance algorithm is designed, multi-task gradient optimization is carried out from two angles of gradient direction alignment and amplitude dynamic balance, and the problems of gradient conflicts and task dominance are solved while gradient feature distribution between tasks is kept.

The application belongs to the technical field of biomedicine, and specifically discloses a gene marker of melanoma and application thereof. The gene marker is a PDP1 gene, and the application proves the correlation between the PDP1 gene and melanoma. The expression amount of the PDP1 gene in melanoma cells is significantly higher than that in normal melanocytes. The PDP1 expression is positively correlated with the pathological stage and the lymph node metastasis condition N value. The PDP1 gene influences the cell proliferation, cell apoptosis, cell migration and cell invasion of melanocytes. Therefore, the PDP1 gene can be used as a potential target for diagnosing and treating melanoma. By detecting the mRNA or protein expression level of the PDP1 gene, melanoma can be detected, and the application has good application value.

The application discloses an IGF2BP2-m6A-VCAN-TLR2 signal axis in the preparation of a drug for treating intrahepatic cholangiocarcinoma lymphatic metastasis. In view of the problems of unknown intrahepatic cholangiocarcinoma lymphatic metastasis mechanism and lack of effective target, the application finds and verifies a new pathway that from insulin-like growth factor 2 mRNA binding protein 2, m6A modification regulates the expression of multi-functional proteoglycan, and then activates Toll-like receptor 2 signal, promotes macrophage secretion of vascular endothelial growth factor C and drives lymphatic metastasis. Based on this, the application provides an inhibitor targeting the signal axis, in particular, a small molecule compound 8010-8498. Experiments show that the compound can significantly inhibit cholangiocarcinoma cell migration, invasion and epithelial mesenchymal transition, reduce macrophage secretion of vascular endothelial growth factor C, and effectively inhibit tumor growth and lymphatic metastasis in a naked mouse popliteal lymph node metastasis model and a spontaneous cholangiocarcinoma model. The compound presents a synergistic effect in combination with gemcitabine and cisplatin.

[Problem] To develop a novel method for determining a positive case of lymphatic invasion and / or a case of lymph node metastasis in a breast cancer patient. [Solution] Provided is a method comprising analyzing gene expression of a lymphatic endothelial cell extracted from breast adipose tissue of a breast cancer patient.

The invention discloses a deep learning-based method and system for predicting lymph node metastasis of esophageal squamous carcinoma at T1 stage. The method specifically comprises the following steps: collecting WSI data of an esophageal carcinoma patient; classifying the collected data; dividing each piece of WSI data into a plurality of image blocks with the same size, and preprocessing the image blocks; constructing the image blocks of each piece of WSI data into a graph structure; inputting the graph structure into a neural network model, and training the neural network model; the trained neural network model is used for evaluating the lymph node metastasis probability of the esophageal squamous carcinoma in the T1 stage. According to the invention, the AUC in an internal test reaches 0.949, and the accuracy rate of external verification reaches 90.1%.

The invention discloses a gene marker combination, a kit and a system for breast cancer lymph node metastasis risk assessment, and belongs to the field of precise medical big data analysis. The gene marker combination is composed of 18 genes, namely ACE2, BPIFB1, CLDN19, CT83, FABP7, FGFBP1, KLK7, KLK8, OCA2, PGLYRP4, PI3, PICSAR, PRSS33, ROPN1, ROPN1B, SCRG1, SERPINA11 and SRARP in total. Based on expression data of the combination, a brand new breast cancer lymph node metastasis risk assessment system (MRA18) is constructed, and breast cancer samples can be divided into eight molecular subtypes with different lymph node metastasis risks. Experiments show that the typing method has extremely strong category distinguishing ability (macro AUC score: 0.981 + / -0.004) and steady comprehensive classification performance (balance accuracy: 0.769 + / -0.027), and survival curves and lymph node metastasis risk grade distribution between different molecular subtypes have significant differences. The invention further provides a corresponding detection kit and an intelligent metastasis risk assessment system integrated with the random forest classification model, and an effective auxiliary diagnosis tool is provided for accurate assessment of the preoperative lymph node metastasis risk of the breast cancer patient and formulation of an individualized operation scheme.

The invention is applicable to the technical field of tumor molecular biology, and provides application of miR-320d in preparation of a nasopharyngeal carcinoma treatment preparation and the preparation, and the sequence of miR-320d is shown as SEQ ID NO.1 in a sequence table; the sequence of the primer group for acquiring the overexpression sequence of the miR-320d is as shown in SEQ ID NO.2-3 in a sequence table. An in-vitro silencing miR-320d experiment shows that proliferation of nasopharyngeal carcinoma cells can be promoted, and proliferation of the nasopharyngeal carcinoma cells can be inhibited by in-vitro overexpression of miR-320d; in addition, an in-vitro silencing miR-320d experiment shows that migration and invasion of nasopharyngeal carcinoma cells can be promoted, and in-vitro overexpression of miR-320d can inhibit migration and invasion of nasopharyngeal carcinoma cells; the overexpressed miR-320d inhibits proliferation, migration and invasion of nasopharyngeal carcinoma cells, transplantation tumor growth and tumor lymph node metastasis, that is, the overexpressed miR-320d can treat nasopharyngeal carcinoma, and has profound clinical significance and important popularization and application prospects.

The invention belongs to the technical field of biomedical engineering and near-infrared molecular imaging, and relates to a method for treating lung cancer based on a VEGFR3 targeted near-infrared diagnosis and treatment polypeptide skeleton platform and application of the method, a probe takes polypeptide with the sequence of SLIGHGRGRRVR-GSG-CGLARGRGC as a core structure, SLIGHGRGRRVR (TMVP1448) is used as a cell-penetrating peptide module, and the VEGFR3 targeted near-infrared diagnosis and treatment polypeptide skeleton platform is used as the core structure. The uptake and tissue penetration of the probe in lung cancer cells and lung tissues are remarkably improved; gSG serves as a flexible connecting peptide and is used for spatially separating functional fragments and weakening interference of upstream labeling groups on receptor binding conformation; the CGLARGRGC is a navigation peptide module with stable conformation through a disulfide bond, can recognize VEGFR3 in a high-affinity manner, and realizes active targeting enrichment of high-expression lung cancer lesions and lymph node metastasis lesions of VEGFR3. The preparation method comprises the following steps: further grafting a croconaine near-infrared dye Croc which is self-synthesized by the applicant at an N end of a polypeptide skeleton, so as to obtain a polypeptide probe with a structure Croc-SLIGHGRGRRVR-GSG-CGLARGRGC.

The present application relates to the medical health technical field, disclose a kind of lung cancer occult lymph node metastasis prediction method and device based on multimodal fusion, comprising: obtaining medical image data and clinical text data as original multimodal data;The original multimodal data is pre-trained with multimodal consistency, and robust multiscale fusion feature is obtained;Cross-modal prediction fine-tuning is carried out to the robust multiscale fusion feature, and cross-modal semantic alignment feature is obtained;The statistical morphological features and spatial geometric features of lung nodule are extracted by double-branch parallel, the statistical morphological features and spatial geometric features are converted into high-dimensional abstract features by depth feature mapping, and multidimensional supplementary features are constructed;The cross-modal semantic alignment feature is combined with the multidimensional supplementary feature, and the lung cancer occult lymph node metastasis prediction result is obtained by multiscale prediction decoding processing.

The invention discloses application of a substance for inhibiting polyamine synthesis in preparation of a medicine for treating or relieving endometrial cancer. According to experimental verification of an endometrial cancer cell model and an animal model, it is found that high-fat culture promotes rise of endometrial cancer cell ODC1 and accumulation of polyamine metabolites; mouse serum polyamine metabolites can be up-regulated by feeding the bilateral ovariectomy mouse with high fat; oA-induced polyamine metabolite accumulation and invasion and migration of endometrial cancer cells can be inhibited by knocking down the ODC1; in an animal model, ODC1 is knocked out, and transplantation tumor growth and lymph node metastasis promoted by high fat can also be inhibited by applying an ODC1 inhibitor DFMO. The DFMO can improve the sensitivity of endometrial cancer patients which are resistant to chemotherapeutic drugs. The invention finds that the serum polyamine can be used as a target for developing a medicine for treating or relieving endometrial cancer, and can also be used as a marker for grouping endometrial cancer patients of mammals.

This invention relates to the field of animal model construction technology, and in particular to a method and application for constructing a mouse model of cholangiocarcinoma lymph node metastasis based on SOX18 gene overexpression. This invention provides the application of the SOX18 gene in constructing a mouse model of cholangiocarcinoma lymph node metastasis, and based on this, provides a method for constructing a mouse model of cholangiocarcinoma lymph node metastasis based on SOX18 overexpression. The method provided by this invention can induce lymph node metastasis in cholangiocarcinoma cells with 100% success rate (n=5). Moreover, the model obtained using this method is stable and reliable, and can be used for research on the mechanism of cholangiocarcinoma lymph node metastasis and screening of potential therapeutic targets, demonstrating significant innovation and clinical application value.

The application belongs to the field of biomedicine and relates to application of reagents and kits for detecting tsRNA for colon cancer diagnosis. The application relates to application of reagents for detecting tsRNA for colon cancer diagnosis in preparation of products for detecting or predicting colon cancer, wherein the sequence of the tsRNA for colon cancer diagnosis is GTAGAATTCTCGCCTGCCACG. The application separates a tsRNA through a large number of experiments, and through verification, the expression level of the tsRNA in colon cancer patients is obviously higher than that in healthy people, and a higher level of exosome tRF-21-S2I7L7P50 is significantly related to patient T stage, lymph node metastasis and TNM stage characteristics, the AUC value of the ROC curve of serum tRF-21-S2I7L7P50 in colon cancer diagnosis is 0.870, and the tRF-21-S2I7L7P50 is expected to become a new type of biological marker for colon cancer screening and individualized treatment, and provides a new direction for colon cancer treatment.

This invention discloses the use of FXR inhibitors in the preparation of drugs for the prevention and / or treatment of lung cancer lymph node metastasis, wherein the FXR inhibitor is Z-Guggulsterone or DY268. The drug comprises a pharmaceutically acceptable carrier and an FXR inhibitor. This invention corrects the pathological remodeling of high endothelial venules (HEVs) within draining lymph nodes by blocking the “FXR-HEV-MDSC” signaling axis with an FXR inhibitor, thereby reducing myeloid-derived suppressor cell (MDSC) recruitment and inhibiting lung cancer lymph node metastasis.

The application belongs to the field of biological medicine, and discloses application of YTHDF3 in preparation of products for diagnosing and treating cervical cancer. Specifically disclosed are: application of YTHDF3 as a biomarker in preparation of reagents for diagnosing cervical cancer and lymph node metastasis of cervical cancer; application of YTHDF3 protein in preparation of a prognostic evaluation kit for cervical cancer, the kit taking the above protein as a prognostic evaluation marker; a drug for treating cervical cancer, including any one of a drug capable of specifically inhibiting SREBF1 gene or protein, a drug capable of specifically inhibiting YTHDF3 gene or protein, a drug for inhibiting translation of an m6A modified transcript of LRP6, and a drug for inhibiting proliferation, migration and invasion of cervical cancer cells. The above products are used for diagnosing and treating cervical cancer, and have good specificity. In addition, YTHDF3 can promote lymph node metastasis of cervical cancer, so products taking the molecule as a marker can effectively treat cervical cancer with lymph node metastasis.

The invention provides a thyroid cancer neck central area lymph node metastasis prediction system based on an ultrasonic image, and relates to the technical field of medical systems, the thyroid cancer neck central area lymph node metastasis prediction system comprises an image information acquisition module, an image processing module, a feature extraction module and a metastasis prediction module, the image processing module is used for processing the ultrasonic imaging image of the thyroid gland, denoising the ultrasonic image to improve the definition, enhancing the contrast of the feature information of the ultrasonic imaging image of the thyroid gland, grading the image features, and outputting the graded image; according to the method, ultrasonic imaging images of feature changes of the lesion and other areas are extracted, features are graded according to lesion levels, calculation is carried out according to feature severity levels, the levels can be adjusted according to feature detail changes, a more accurate prediction result is obtained, and the accuracy of the prediction result is improved.

The invention belongs to the technical field of biology, and provides a melanoma biomarker METTL9 gene and application thereof. The result of the embodiment of the invention shows that the METTL9 gene is highly expressed in melanoma cells and patient tissues, and the expression level of the METTL9 is in positive correlation with lymph node metastasis of melanoma patients. By knocking down the METTL9, the progress of melanoma cells can be regulated and controlled through BCKDHA, proliferation, migration and invasion of the cells are inhibited, and the anti-tumor effect is achieved. Furthermore, the METTL9 gene, as a potential target of melanoma, can be applied to tumor treatment, tumor diagnosis and tumor prognosis evaluation, and provides a new thought and a new strategy for treatment-related drugs and diagnosis products.