1380 results about "Metastasis" patented technology

The invention provides a correlation analysis method for a lung CT image, and the method comprises the steps: obtaining a lung multi-modal image which comprises a computed tomography image and a positron emission tomography image, and carrying out the denoising, enhancement and standardization preprocessing of an original image according to the imaging principles and image characteristics of different modals; extracting a lung lesion region of interest from the registered multi-modal image, sketching and segmenting the lesion, and quantitatively analyzing the volume and shape geometric morphological characteristics of the lesion; based on a curative effect result, correlation between radiomics features and patient prognosis is analyzed, recurrence and metastasis risks and lifetime under different feature expressions are estimated, a curative effect prediction model is constructed in combination with image features and clinical indexes, and long-term individualized evaluation is performed on patient prognosis.

The invention discloses a double-layer microneedle patch and a preparation method thereof.The preparation method of the double-layer microneedle patch comprises the following steps that firstly, 3D printing is conducted through polydimethylsiloxane, and a PDMS mold similar to a machining microneedle is obtained; dispersing the medicine into the sericin solution to serve as an outer layer solution; dispersing germanium nanoparticles into the polycaprolactone solution to obtain an inner layer solution; and finally, adding the outer-layer solution into the needle-shaped groove of the PDMS mold, so that the needle-shaped groove is filled with the outer-layer solution, drying, adding the inner-layer solution, drying, and demolding to obtain the double-layer microneedle patch. When the double-layer microneedle patch is used for drug delivery, drugs can be dissolved and released in a short time, the inner layer is polycaprolactone (PCL) carrying photo-thermal agent germanium nanoparticles, degradation is slow, a photo-thermal effect is generated under irradiation of 808nm near-infrared light, residual tumor cells are induced to die immunogenicity, an immune microenvironment is programmed in a time sequence, and the double-layer microneedle patch has the advantages of being high in sensitivity, high in sensitivity and good in stability. Postoperative recurrence and metastasis of tumors are efficiently inhibited, and meanwhile operative wound repair is promoted.

Presented herein are systems and methods that provide for improved computer aided display and analysis of nuclear medicine images. In particular, in certain embodiments, the systems and methods described herein provide improvements to several image processing steps used for automated analysis of bone scan images for assessing cancer status of a patient. For example, improved approaches for image segmentation, hotspot detection, automated classification of hotspots as representing metastases, and computation of risk indices such as bone scan index (BSI) values are provided.

The invention discloses a colorectal cancer metastasis risk prediction method and system fusing radiomics and clinical characteristics, and the method comprises the steps: S1, collecting image data and clinical risk factor data of a patient, carrying out the preprocessing, and carrying out the feature extraction; s2, performing data expansion, and fusing expanded features and original features; s3, constructing and training a multi-modal large model, and outputting a first prediction result of the colorectal cancer metastasis risk of the patient; s4, layering the patients according to the first prediction result, and performing dynamic prediction; s5, performing interpretable analysis on a dynamic prediction result and generating a report; and S6, verifying the multi-modal large model. According to the method, the aspects of data fusion, prediction performance, dynamic assessment, clinical interpretation and the like are remarkably improved, key problems in the prior art are solved, an efficient, accurate and easy-to-use transfer risk assessment tool is provided for clinicians, and the method has important academic value and wide clinical application prospects.

The invention provides a thyroid cancer auxiliary diagnosis and metastasis risk prediction method based on deep learning, and relates to the technical field of artificial intelligence auxiliary medical treatment, and the method comprises the steps: extracting ultrasonic image multi-scale features through a self-adaptive neural architecture search network, combining clinical examination data, fusing diagnosis and treatment knowledge through a neural symbol inference device, and carrying out the prediction of the metastasis risk. Generating a knowledge enhancement feature map; constructing a feature propagation field by using a dynamic neural field network, solving a dynamic evolution equation, and generating a spatial-temporal feature field representing the dynamic change of focus features; constructing a tumor diffusion kinetic model by using an implicit neural representation network and a nerve ordinary differential equation network, calculating a transition probability based on an optimal transmission algorithm, solving an optimal control equation, and outputting a metastasis risk prediction result of each organ; the thyroid cancer diagnosis accuracy and metastasis risk prediction reliability can be effectively improved, and doctors can be assisted in accurate diagnosis and treatment.

The present invention belongs to the field of medical equipment, and in particular, relates to a medical bed for patient transfer and treatment and a method of using the same. The medical bed includes a treatment bed and a transfer bed that can be docked and separated, a guide mechanism for guiding when the two are connected is provided between the transfer bed and the treatment bed, and a transfer bed locking mechanism is provided between the transfer bed and the treatment bed, and the transfer bed locking mechanism is used to lock the transfer bed and the treatment bed when docked and unlock when separated. The beneficial effects of the present invention are: the docking of the transfer bed and the treatment bed is simple and convenient, and the docking is stable and accurate, which is convenient for the transfer and treatment of patients, and the patient does not need to move frequently, which reduces the difficulty of patient transfer treatment.

Provided in the present invention are a marker combination for predicting thyroid cancer metastasis and the use thereof. Specifically, provided in the present invention is the use of the gene, mRNA, cDNA or protein of the risk marker combination for evaluating thyroid cancer metastasis or a detection agent thereof in the preparation / establishment of a diagnosis agent or kit / device for evaluating the risk of thyroid cancer metastasis. Research shows that the risk marker combination of thyroid cancer metastasis can be used as a marker for the early evaluation of thyroid cancer metastasis in a patient with thyroid cancer, has a high sensitivity and specificity, can be used to rapidly diagnose thyroid cancer metastasis at a relatively early stage of disease progression, and provides strong assistance for early treatment intervention of diseases.

The invention relates to paclitaxel ganoderma lucidum spore oil self-nanoemulsion composite particles with ganoderma lucidum spores as a carrier and a preparation method of the paclitaxel ganoderma lucidum spore oil self-nanoemulsion composite particles, and belongs to the technical field of medicines. Pretreated Ganoderma lucidum spores (GLS) are obtained through process screening and serve as a drug carrier, and paclitaxel-loaded Ganoderma lucidum spore oil self-nanoemulsion (PGS) is loaded into the Ganoderma lucidum spores (GLS) to obtain paclitaxel-loaded composite particles (PGS (at) GLS). An in-vitro release curve shows that the PGS-atGLS has the characteristic of slow release after reaching the intestinal tract; in-vivo pharmacodynamic experiments show that PGS-atGLS can significantly inhibit development and metastasis of mouse colorectal cancer; tumor tissue slice immunofluorescence analysis shows that PGS-atGLS can effectively play a role in treating colon cancer. The paclitaxel self-nanoemulsion-loaded ganoderma lucidum spore composite particles synergistically promote cancer immune circulation by inducing immunogen cell death and immunoregulation, significantly improve the treatment effect of colon cancer, and have good biological safety.

The invention relates to the technical field of medical image processing and tumor diagnosis, in particular to a tumor recognition method based on multi-modal information fusion. The method comprises the following steps: acquiring tumor multi-modal information of a target object, wherein the multi-modal information comprises tumor image data, tumor genomics data and individual tumor related information; the tumor-related information comprises a vascular structure, a blood flow velocity, fluid viscosity and fluid pressure of the target object; determining a tumor cell density, a diffusion coefficient and a cell proliferation rate according to the tumor image data and the tumor genomics data; predicting a diffusion path of the tumor in the local tissue according to the tumor cell density, the diffusion coefficient and the cell proliferation rate; predicting a metastasis path of tumor cells through a vascular system according to the individual tumor related information; and according to the diffusion path of the tumor in the local tissue and the metastasis path of the tumor cells through the vascular system, identifying the potential metastasis site of the tumor.

Provided herein are systems, compositions, and methods for generating immunogenic peptides or epitopes from tumor associated antigens (e.g., in vivo or ex vivo). Polynucleotides (e.g., genes) encoding the tumor associated antigens may be edited at selected target sites by nucleobase editors comprising a catalytically-inactive Cas9 and a cytosine deaminase, leading to the expression of heteroclitic or cryptic peptides that are more immunogenic than the native peptide derived from the tumor associated antigens. The heteroclitic or cryptic peptide elicit strong tumor-specific immune response (e.g., T-cell response or B-cell response), which inhibits tumor growth and metastasis.

The present invention relates to a use of a novel compound for the prevention, alleviation, or treatment of breast cancer, the novel compound of the present invention not only being capable of notably inhibiting the growth, proliferation, migration, carcinogenicity, and metastasis of breast cancer cells, but also being capable of simultaneously inhibiting ANO1 and EGFR in breast cancer cells, thereby being capable of exhibiting a stronger anticancer effect through the dual inhibition of the two proteins. In addition, the compound, when used in combination with an anticancer agent, may further enhance the efficacy of the anticancer agent, and may inhibit the resistance of the cancer. Thus, the compound itself may be used as a dual-target anticancer agent against ANO1 and EGFR, and may also be utilized as a combined preparation of an anticancer agent, and thus is expected to be utilized in various ways in the field of breast cancer prevention and treatment.

The invention discloses a human-derived ampulla cancer cell line DPC-X3 and application thereof, and belongs to the field of microbial animal cell lines. The human-derived kettle belly cancer cell line is named as a human-derived kettle belly cancer cell line DPC-X3, and the preservation number is CCTCC (China Center For Type Culture Collection): C2024317. The human-derived ampulla cancer cell line DPC-X3 can be applied to establishment of a cell model for occurrence, development or metastasis of ampulla cancer. The human-derived ampulla cancer cell line DPC-X3 can be applied to cell models for researching the differentiation mechanism, cell morphology and dysfunction and tumor infiltration and metastasis mechanism of ampulla cancer and guiding clinical comprehensive diagnosis and treatment. The human-derived ampulla cancer cell line DPC-X3 can be applied to research on the occurrence mechanism of the ampulla cancer and screening of drugs for preventing and treating the ampulla cancer. The ampulla cancer cell line DPC-X3 can be applied to establishment of an ampulla cancer animal model.

The present invention discloses the application of liver cancer cell ferroptosis inducer miR‑11085‑5p in the preparation of liver cancer treatment drugs, and innovative applications in the field of liver cancer treatment, specifically to the application of liver cancer cell ferroptosis inducer miR‑11085‑5p in the preparation of liver cancer treatment drugs. The present invention adopts lentiviral transfection technology to synthesize miR‑11085‑5p in vitro, and introduce it into liver cancer cells, and effectively induce liver cancer cells to undergo ferroptosis by precisely regulating the key signaling pathway of intracellular AMPKα / Nrf2, significantly inhibiting its proliferation activity. Therefore, for the disadvantages of low efficiency, large side effects and easy recurrence and metastasis of existing treatment methods for liver cancer, the miR‑11085‑5p provided by the present invention may become a biological preparation for the treatment of liver cancer, with potential drug development value, and provide a new solution for the treatment of liver cancer.

The invention discloses a class of radiopharmaceutical labeled precursors targeting prostate specific membrane antigens, the structure of the radiopharmaceutical labeled precursors is shown as the following: # imgabs0 #, a precursor reagent RESCA-PSMA-1802 targeting prostate specific membrane antigens is synthesized for the first time, the reagent can be labeled by using an 18F-Al method to prepare a positron imaging agent 18FAl-RESCA-PSMA-1802, and the reagent can be used for preparing the prostate specific membrane antigens. The polymer has good stability and biological activity in vivo and in vitro, has good targeting property on prostate cancer cells, can reflect tumor recurrence or metastasis conditions, and is very suitable for PET imaging.

The invention discloses a colorectal cancer metastasis prediction method and system and a storage medium, and belongs to the technical field of medical data analysis. The method comprises the following steps: S1, preprocessing multi-modal data; s2, performing training and fine tuning on the prediction model by using the preprocessed multi-modal data; s3, performing modal fusion and external knowledge query; s4, inputting a to-be-predicted sample into the classifier to obtain a transfer prediction result, and outputting description information of the transfer prediction result by using a language encoder; s5, performing evaluation through an expert system according to professional knowledge to obtain a feedback value; when a new feedback value arrives, the prediction model carries out parameter updating through a reinforcement learning algorithm, and a prediction strategy is adjusted; model parameters are updated through a feedback value and a Bellman equation, and are gradually adjusted through multiple iterations. According to the invention, by fusing the medical image data and the electronic health record, the image information, the text information and the clinical data of the patient are effectively integrated, and the prediction precision and robustness are improved.

The invention relates to the technical field of medical care, in particular to a tumor prognosis prediction method based on tumor database text recognition, which comprises the following steps: S1, data collection and preprocessing: collecting medical data related to tumors from a plurality of tumor databases; s2, text information extraction: performing information extraction on clinical text data; s3, predicting a tumor metastasis path: predicting the metastasis path by utilizing the graph neural network model, predicting a potential metastasis path of the tumor, and analyzing the influence of different metastasis paths on the prognosis of the patient; s4, prognosis evaluation and risk prediction: predicting the tumor prognosis risk in combination with the medical data of the patient, and comprehensively evaluating the five-year survival rate and the recurrence risk of the patient. According to the method, the medical institution can be assisted in optimizing resource allocation, a scientific personalized diagnosis and treatment scheme is formulated, and the life quality and the treatment effect of the patient are remarkably improved.

The invention discloses a tumor stem cell targeting virus-like drug carrier as well as a preparation method and application thereof. The drug carrier provided by the invention can improve the cell uptake efficiency by simulating the physical surface characteristics of a biological system, and can directly target tumor stem cells. Besides, the drug carrier has targeting property, so that healthy tissues can be protected, the side effects of the loaded drug such as PTC209 in high-dose independent use are obviously reduced, the reaction to tumor stem cells is effectively enhanced, tumor proliferation and metastasis are inhibited, and the drug resistance of drug combination such as cis-platinum is reduced.

The invention discloses a VEGF / TIE-2 dual-targeting polypeptide and application thereof in preparation of antitumor drugs, and relates to the technical field of biological medicines. The VEGF / TIE-2 dual-targeting polypeptide (named as RTP) provided by the invention is formed by combining an amino acid sequence capable of identifying VEGF and TIE-2 in a targeting manner, an amino acid sequence capable of forming beta-sheet nanofibers through self-assembly, an amino acid sequence capable of identifying carbonic anhydrase IX in a targeting manner and an enzyme reactive amino acid sequence capable of realizing MMP-2 specific shearing. The RTP can be subjected to allosteric and self-assembly in tumor cells to form stable water-insoluble nanofibers, the formation and metastasis of tumor neovascularization are strongly inhibited through VEGF and TIE-2 double signal channels, and the tumor progress is inhibited.

The present invention relates to a use of a novel compound for the prevention, amelioration, or treatment of head and neck cancer. The novel compound of the present invention not only significantly inhibits the growth, proliferation, migration, and metastasis of head and neck cancer cells, but also simultaneously inhibits ANO1 and EGFR in head and neck cancer cells, thereby exerting a stronger anticancer effect through dual inhibition against these two proteins. In addition, when used in combination with an anticancer agent or the like, the compound can enhance the efficacy of the anticancer drugs and suppress drug resistance. Accordingly, the compound can be used as a dual-target anticancer agent for ANO1 and EGFR on its own, or as a combination agent with anticancer drugs, and is expected to be widely applicable in the field of prevention and treatment of head and neck cancer.

The invention discloses an abdominal lymph node metastasis prediction method, system and device based on comparative learning, belongs to lymph node metastasis prediction in the technical field of artificial intelligence, and aims to solve the technical problem of low lymph node metastasis prediction accuracy caused by the fact that a model is not guided to focus on a certain type / kind of tags during model training in the prior art. The method comprises the following steps: firstly, migrating parameters in a feature extraction module subjected to supervised comparative learning pre-training to a feature extractor, inputting features extracted by the feature extractor into a simple transfer prediction network, and outputting a lymph node transfer probability by the simple transfer prediction network; calculating the contribution degree of each sample image according to the lymph node metastasis probability; and finally, during actual training of the lymph node metastasis prediction model, sorting is performed according to the contribution degree of each sample, positive samples with high contribution degrees are learned preferentially, then negative samples with high contribution degrees are learned, and finally the samples which are difficult to classify clearly are processed. Therefore, the lymph node metastasis prediction accuracy can be greatly improved.

The invention discloses a novel polypeptide, a polypeptide derivative and application thereof, and belongs to the technical field of biological medicine. The invention specifically relates to a specific sequence, a discovery process, a specific anti-tumor type, a long-acting modification mode and application of the novel polypeptide. The tumors comprise one or more of brain glioma, neuroblastoma, head and neck cancer, esophagus cancer, thyroid cancer, lung cancer, liver cancer, kidney cancer, breast cancer, cervical cancer, uterine cancer, ovarian cancer, colon cancer, small intestinal cancer, ileocecum cancer, stomach cancer, bladder cancer, pancreatic cancer, prostate cancer, bile duct cancer, melanoma, sarcoma, myeloma, lymphoma and leukemia; the compound has the specific effect of inhibiting proliferation and / or metastasis of tumor cells, is wide in treatment spectrum and has important treatment value in various tumors.

The invention provides a halogenated indolone compound and a preparation method and application thereof, a halogenated indolone derivative and application thereof, and a pharmaceutical composition and application thereof, and relates to the technical field of biological medicines. Kinase spectrogram analysis shows that the halogenated indolone compound provided by the invention not only has VEGFR (vascular endothelial growth factor receptor), FGFR (fibroblast growth factor receptor) and PDGFR (plasma derived growth factor receptor) kinase inhibitory activity, but also has very strong AXL kinase inhibitory activity, and the IC50 value reaches a low nanomole level and is 45 times of the AXL kinase inhibitory activity of nintedanib. The halogenated indolone compound provided by the invention shows better anti-tumor activity than nintedanib at a cellular level and in an animal body, has better effects of inhibiting tumor invasion and metastasis than nintedanib, and can effectively treat malignant tumors and invasion and metastasis thereof.

The invention relates to the technical field of biomedicine, in particular to a method for constructing a plasma ctDNA organ distribution characteristic spectrum of advanced colorectal cancer. The method comprises the following steps: collecting a peripheral blood sample at multiple time points, separating plasma by adopting a double-centrifugal method, and extracting circulating tumor DNA (Deoxyribose Nucleic Acid); carrying out whole exome sequencing based on ctDNA to obtain genome variation information and calculating variation allele frequency, and synchronously detecting the expression quantity of immune-related proteins by adopting an Olink proteomics technology; integrating the genome data, the protein expression data and the clinical pathological features, and constructing a multi-dimensional feature data matrix; and taking the organ metastasis condition confirmed by iconography as a supervision label, training a model by applying a machine learning algorithm, screening key prediction factors, constructing a quantitative prediction model, and finally generating a visual organ metastasis tendency prediction map. According to the method, early and accurate prediction of the advanced colorectal cancer organ metastasis tendency is realized through multi-omics data collaborative analysis and machine learning modeling.

The invention relates to a hepatocellular carcinoma gene knockout target library based on multiple omics and a screening method of the hepatocellular carcinoma gene knockout target library, and the gene knockout target library for precise treatment of hepatocellular carcinoma is finally obtained through data collection and integration, data screening and target verification in sequence. According to the invention, through multi-omics data integration and bioinformatics analysis, key driving genes of hepatocellular carcinoma are systematically screened, and the important effects of the genes in occurrence, development, metastasis, drug resistance and immune escape of hepatocellular carcinoma are disclosed; the genes not only deepen the understanding of the hepatocellular carcinoma molecular mechanism, but also provide important theoretical basis and potential intervention targets for the development of targeted therapy and personalized therapy strategies.

There are currently no effective biomarkers to select chemotherapy, immunotherapy, and radiotherapy for treating lung cancer patients. This study identified genetic networks containing major immune-checkpoint inhibitors CD27, PD1, and PDL1, and their associated prognostic genes and proliferation genes in lung cancer tumors. A co-expression network that was missing in tumor B cells was discovered that can promote lung cancer proliferation. A 5-gene and a 9-gene prognostic models were developed and validated in extensive cohorts to select patients at a high risk for developing metastasis. CRISPR-Cas9 and RNA interference screening data were used in the selection of proliferation genes. These genes were associated with chemoresponse and radio-therapy response in lung cancer cell lines and patient tumors. These immune-omics networks led to the discovery of repositioning drugs for improving lung cancer treatment.

The present invention relates to combined therapy of cancer using an epithelial cell adhesion molecule (EpCAM) inhibitor and a Wnt signaling inhibitor. Specifically, the EpCAM inhibitor is an antibody which is directed to an extracellular domain (EpEX) of EpCAM. The combined therapy is effective in inducing apoptosis of cancer cells, inhibiting cancer sternness properties, tumor progression and / or metastasis, and / or prolonging survival of a cancer patient.

The invention discloses an exosome engineered targeted drug delivery system and a preparation method and application thereof, and belongs to the field of biomedices.The exosome engineered targeted drug delivery system is prepared by mixing and reacting surface modified exosome and pH response type drug controlled release nanoparticles; the pH response type drug controlled release nanoparticles react with the surface modified exosome through a click chemical reaction; the surface of the membrane of which the surface is modified with the exosome is modified with a maleimide group and an azide group; the novel nano-drug has pH responsiveness; the click chemical reaction is thiol-ene click reaction. Bifunctional groups (MAL and N3) are directionally grafted on the surface of an exosome membrane, uniform drug particles are prepared in combination with a micro-fluidic technology, an efficient bimodal targeting drug delivery system is successfully constructed, and remarkable technical advantages are shown in the aspects of improving targeting precision, enhancing antitumor activity, controlling drug release, inhibiting tumor metastasis and the like; and a new technical approach is provided for precise treatment of adenoid cystic carcinoma.

The invention discloses a liver metastasis monitoring system based on big data, belongs to the technical field of medical treatment, and aims to solve the problems of high subjectivity, low accuracy and difficulty in meeting the requirements of clinical precision medical treatment when the clinical symptoms of a patient are pre-estimated, and the liver metastasis monitoring system comprises a data acquisition and integration module and a data preprocessing module, a liver metastasis risk prediction model construction module, a real-time risk assessment and early warning module and a decision assistance and suggestion module; through big data analysis and a machine learning algorithm, accurate prediction of the liver metastasis risk is realized, the diagnosis accuracy is improved, high-risk patients are found in time, accurate prediction and early warning of the liver metastasis risk of the patients are realized, and improvement of the early discovery rate and the treatment success rate of liver metastasis is facilitated; through an automatic processing flow, manual operation is reduced, unnecessary image examination is reduced, economic burden of a patient is reduced, doctor-patient contradiction is relieved, and patient management efficiency and service quality are improved.

The invention relates to a pharmaceutical composition for treating pancreatic cancer, and belongs to the technical field of biological medicines. The mass ratio of the resveratrol to the glucosamine is (2.28 mg-45.6 mg): (179.17 mg-895.85 mg), and the pharmaceutical composition group is applied to preparation of products for treating pancreatic cancer or preventing pancreatic cancer metastasis. Compared with a single medication group, the combined application of the resveratrol and the glucosamine has the advantages that the metastasis and invasion capability of pancreatic cancer cells can be more obviously inhibited, and the influence on normal cells is smaller. Researches show that the resveratrol realizes an anti-tumor effect by inhibiting the expression of a ligand in a TGF-beta (Transforming Growth Factor-beta) pathway; and the glucosamine inhibits N-glycosylation modification and further inhibits the stability of a receptor in a TGF-beta pathway so as to realize an anti-tumor effect. And a synergistic interaction effect is achieved through multiple targets on the same path. Therefore, the method has good practical application value.

The invention relates to application of a combination of FGGY, DSG1 and CUSTOS proteins in prognosis of pancreatic neuroendocrine tumors, and belongs to the field of disease prognosis, the abundance of the combination of FGGY, DSG1 and CUSTOS proteins can be firstly found to be used for judging postoperative recurrence and metastasis risks of PNETs patients, and prognosis in a disease-free survival (DFS) curve of a high-risk group is remarkably poorer than prognosis in a low-risk group; 0.0001) of the method.