40 results about "Tumor type" patented technology

This platform is a privacy-preserving, federated learning system designed to integrate whole-slide digital pathology images with matched molecular profiling and clinical metadata for improved diagnosis, subtyping, and prognostic estimation of gynecologic tumors. The architecture comprises local institutional nodes that retain raw patient data while participating in distributed model training coordinated by a central orchestration server. Each local node preprocesses whole-slide images into patch-level tensors, extracts visual embeddings via convolutional backbones, and processes molecular vectors (e.g., somatic mutations, expression summaries, copy-number measures) via a molecular encoder. A multimodal fusion module - implemented as an attention- based transformer - integrates image and molecular embeddings into a unified representation used by multi-task heads for classification (histologic subtype, diagnostic label) and regression (risk score). The federated learning controller aggregates encrypted model updates (FedAvg) and returns improved global weights without exchanging raw data, enabling cross-site generalization while preserving patient privacy. Explainability components generate attention maps and tile-level saliency (Grad-CAM style) linked to molecular features, providing interpretable morpho- molecular correlations to pathologists. The platform supports API integration with PACS / LIMS, conforms to privacy standards via optional differential privacy and secure aggregation layers, and is extensible to additional omics modalities or transfer / fine-tuning workflows for related tumor types. By combining multimodal fusion, federated training, and clinician-facing interpretability, the system accelerates robust, generalizable AI for precision pathology in gynecologic oncology.

The invention belongs to the technical field of tumor immunity, and particularly relates to a tumor antigen and chemotactic factor co-coding system and application thereof. The invention provides a tumor antigen and chemotactic factor co-coding system. The tumor antigen and chemotactic factor co-coding system comprises a nucleotide sequence for coding a tumor antigen and a nucleotide sequence for coding a chemotactic factor. The tumor antigen and chemotactic factor co-coding system can flexibly replace an antigen sequence and chemotactic factor combination, is adaptive to different tumor types and various immunotherapy requirements, can be expanded to various solid tumor treatment scenes through a customized antigen-chemotactic factor combination in the future, and has a wide application prospect. The broad-spectrum application in tumor treatment means including tumor neoantigen vaccines, adoptive cell therapy and the like is realized.

The invention discloses a tumor tissue segmentation method based on an MR image, and relates to the technical field of image processing, and the method comprises the following steps: processing before segmentation, obtaining the MR image, quantifying texture features, calculating different-dimension feature values of each pixel of the MR image, obtaining a multi-scale texture feature vector of each pixel, and classifying the texture features. The method comprises the steps of dividing a pixel category and an image area of each pixel, enhancing boundary dynamic features and adjusting a threshold value, and has the advantages that double-weight boundary filtering is carried out by adopting confidence and spatial distance, similar texture features in a boundary transition area are amplified, boundary over-segmentation and under-segmentation probabilities are reduced, the judgment accuracy of the pixels in the boundary transition area is improved, and the judgment accuracy of the pixels in the boundary transition area is improved. According to the method, the threshold value of each image can be dynamically adjusted according to the tumor features of the image, manual parameter adjustment is not needed, multi-scene adaptation is achieved, the efficiency is improved, and through combination of multi-scale textures and dynamic double-feature fusion, the segmentation precision of cross-tumor types is guaranteed, and the heterogeneity tumor adaptability is improved.

The invention belongs to the field of medicinal chemistry, and particularly relates to a targeted drug coordinated metal complex as well as a preparation method and application thereof. The metal complex prepared by the invention is a ruthenium (II), iridium (III) and rhodium (III) complex coordinated with a targeted drug, the original biological activity of the ligand is remarkably optimized and improved by virtue of the synergistic effect between central metal ions and the ligand, the specific binding capacity of the ligand with a tumor cell target spot is enhanced, and the tumor cell target spot is further enhanced. The metal complex has a broad-spectrum and efficient anti-tumor activity, the action range of the metal complex can cover multiple common tumor types including but not limited to liver cancer, kidney cancer, breast cancer, ovarian cancer or colorectal cancer and the like, and an important technical support is provided for developing novel anti-tumor drugs with multiple target points and low toxic and side effects. The complex provided by the invention is novel in structure and good in anti-tumor activity, and has a good application prospect in the field of anti-tumor drugs.

The application discloses application of a pharmaceutical composition taking GL-V9 and a chemotherapeutic drug as active ingredients in treatment of tumors. When GL-V9 is combined with a classical chemotherapeutic drug to treat tumors, a drug synergistic effect can be obviously achieved, and the effect is obviously superior to combination of similar drugs and the chemotherapeutic drug. The chemotherapeutic drugs include 5-fluorouracil; and the tumor types include leukemia, colorectal cancer and lung cancer.

This invention discloses an intelligent nutrition recommendation method for cancer patients based on metabolic rhythm synchronization, belonging to the field of nutrition recommendation. This invention integrates temporal physiological data and clinical information, extracts features, and uses a bidirectional long short-term memory network to predict the host metabolic activity curve. Based on a tumor knowledge graph, a conditional generative adversarial network is constructed to infer and generate a tumor metabolic activity curve using the host curve, tumor type, and treatment stage as conditions. A temporal separation potential heatmap is generated by calculating the phase difference and overlap between the two curves. Using the heatmap and clinical labels as states, an integrated constraint proximal strategy optimization algorithm is used for decision-making, outputting a time-segmented nutrient delivery action sequence that satisfies temporal nutritional constraints. Using this sequence as the target, an optimization algorithm performs a multi-objective search on a recipe database to generate a personalized daily recipe that considers both nutritional and taste preferences, providing cancer patients with timely and intelligent decision-making.

This invention discloses an antibody-drug conjugate based on a p16-targeting single-chain antibody, comprising a p16 single-chain antibody, a cell-penetrating peptide, a linker, and a carrier drug. The p16 single-chain antibody and the cell-penetrating peptide are fused together to form a fusion protein, which is further conjugated to the carrier drug via a linker to form the antibody-drug conjugate. This invention provides a novel therapeutic strategy by targeting p16, particularly suitable for tumor types that highly express p16, for which effective treatments are currently lacking. By targeting the p16 site within the cell nucleus, this invention not only enriches the candidate target library for targeted therapy but also provides feasibility validation and technical reference for future drug development targeting nuclear targets.

The application discloses a 3'-deoxyadenosine compound and application thereof in preparation of an antitumor drug. The 3'-deoxyadenosine compound and the pharmaceutical composition thereof have good antitumor proliferation effect. Compared with a parent drug, the 3'-deoxyadenosine compound has better affinity to a cell membrane, so that the half-life of in-vivo metabolism of the drug is longer, and the drug stays in the body for a longer time. Compared with other nucleoside antitumor drugs, the cordycepin derivative and the pharmaceutical composition thereof have a wider range of tumor types and effects, including excellent inhibition effect on gastric cancer, pancreatic cancer, liver cancer, small cell lung cancer, colorectal cancer, melanoma, ovarian cancer and the like, and the side effect is lower and the curative effect is better.

A combination therapeutic strategy employs multiple oncolytic viruses (OVs), grouped and administered based on their virological properties, tumor selectivity, and distinct antigen profiles, to treat malignant tumors. Representative groupings may include members of flaviviruses, each contributing distinct immune modulation and the same modes of tumor cell killing. A predefined treatment schedule involves sequential or concurrent administration of antigenically diverse OVs in multiple cycles, reducing cross-neutralization and sustaining cytolytic pressure on tumors. A pre-characterized OV panel, comprising members from a virus family, RNA and DNA viruses, both wild-type and genetically engineered, serves as a flexible resource for customizing treatment regimens by tumor type, immune landscape, and therapeutic goals. This platform establishes a rational framework for combination OV therapy with improved durability, safety, and clinical effectiveness.

The application discloses application of a pharmaceutical composition with GL-V9 and a chemotherapeutic drug as active ingredients in treatment of tumors, and the GL-V9 can obviously achieve a drug synergistic effect when the GL-V9 is combined with a classical chemotherapeutic drug to treat tumors, and the effect is obviously superior to combination of similar drugs and the chemotherapeutic drug. The chemotherapeutic drugs include PARP1 inhibitors, capecitabine, irinotecan, sorafenib, cisplatin or 5-fluorouracil; and the tumor types include leukemia, colorectal cancer and lung cancer.

The present application relates to a kind of distal anchoring bone cement type prosthesis stem, including stem body, several anchoring blades and piston.The bottom end of the stem body is fixed on prosthesis, top end is inserted into medullary cavity, bone cement channel is provided in the stem body along the axial direction, injection hole is formed on the side wall of the stem body, and the injection hole is communicated with the bone cement channel;The anchoring blade is arranged at the top of the stem body, the bottom of the anchoring blade is rotatably connected with the top end of the stem body, the piston is sleeved in the bone cement channel, and under the driving of bone cement, it slides upward, when the piston slides to the top of the stem body, several anchoring blades are opened, and the anchoring blade is converted from the first state to the second state.The distal anchoring bone cement type prosthesis stem can improve the long-term stability of tumor type prosthesis, reduce the aseptic loosening of prosthesis, and improve the long-term function of limb of patients with malignant bone tumor.

The application discloses a compound with anticancer effect based on 3'-deoxyadenosine modified by chemical modification, and a structure of the compound is shown as formula I. The cordycepin derivative and the pharmaceutical composition thereof have good antitumor proliferation effect. Compared with the parent drug, the cordycepin derivative has better affinity to the cell membrane, so that the half-life of the drug metabolism in the body is longer, and the drug stays in the body for a longer time. Compared with other nucleoside antitumor drugs, the cordycepin derivative and the pharmaceutical composition thereof have a wider range of tumor types and effects, including excellent inhibition effect on gastric cancer, pancreatic cancer, liver cancer, small cell lung cancer, colorectal cancer, melanoma, ovarian cancer and the like, and the side effect is lower and the curative effect is better.

The invention relates to the technical field of tumor tissue discrimination, and discloses a tumor tissue identification method and device and electronic equipment, and the method comprises the steps: obtaining a blood flow index time sequence of a target object; based on the blood flow index time sequence, blood flow characteristics used for reflecting the blood flow dynamic characteristics of the target object are determined; determining a judgment result of the target object based on the blood flow characteristics; and under the condition that the judgment result is the tumor tissue, determining the tumor type and confidence of the tumor tissue. On the basis of the determined target tissue blood flow index, the blood flow index is analyzed from multiple dimensions, the blood flow dynamic characteristics of the target object can be reflected more comprehensively, and the method does not only depend on a single index. The complexity of a blood flow mode can be captured through multi-dimensional feature extraction, so that the tumor can be distinguished more accurately and reliably.

The application discloses a tumor multidimensional evaluation and report generation system and method based on a unified workflow, relates to the technical field of clinical auxiliary decision and medical workflow optimization, and comprises a unified workflow entrance module, a tumor type identification module, a special evaluation engine scheduling module, a special evaluation engine library module, an evaluation result collection module, an intelligent report generation module, a decision support module and a workflow state visualization module, wherein the modules are connected in series. The unified workflow entrance module provides unified data management; the special evaluation engine library module is internally provided with multiple scoring engines for different tumor types and different diagnosis and treatment scenes; and the intelligent report generation module automatically generates a complete evaluation report. The application can effectively solve the problem of fragmentation of the tumor multidimensional evaluation workflow, effectively realize report integration, and enhance the clinical decision support capability.

The application belongs to the technical field of medicine, and particularly relates to a modularly constructed targeted-tumor-killing polypeptide-drug conjugate as well as a preparation method and application. The conjugate has a dendritic six-branch scaffold structure, and the scaffold can realize replaceable combination of a targeting polypeptide and a chemotherapeutic drug through chemical modification, so that precise drug delivery can be realized for different tumor types. Among them, a blood vessel binding peptide and an albumin binding peptide are selected as model polypeptides, and a common clinical drug doxorubicin is selected as a model drug. The polypeptide-drug conjugate has high drug loading and stability, can improve the pharmacokinetic characteristics of poorly soluble drugs, prolong in-vivo circulation, has small molecular weight and strong tissue permeability, can be precisely enriched in tumors, has good structural adjustability and functional expansion potential, and exhibits significant anti-tumor effect and safety.

This invention teaches a tumor-targeting thiocolchicine nanoemulsion wherein the nanodroplets comprising the nanoemulsion are coated with an antinuclear antibody (ANA-nanoemulsion). The nanodroplets are less than 200 nm and will enter the tumor via the Enhanced Permeation and Retention Effect (EPR). Once inside the tumor the antinuclear antibody coating the nanodroplets will bind to extracellular nuclear material released from dead cells and anchor the nanodroplets within the tumor where the drug is released for maximum effect. As all solid tumors have areas of necrosis this means that the ANA-nanoemulsion can target and treat all solid tumors regardless of the tumor type. The ANA-nanoemulsion is formulated to have a phase transition temperature above 8 C. When cooled to below 8 C the ANA-nanoemulsion converts into a suspension of solid lipid nanospheres (ANA-nanospheres) suitable for storage at 4 C or below.

The invention belongs to the field of tumor classification, and particularly relates to a tumor fine classification system fusing multi-dimensional medical data. Comprising a medical data acquisition module, a medical data identification module, a multi-dimensional classification module, a data matching module, a tumor type confirmation module, an output display module, a database, a multi-dimensional data entry module, a data management module, a feedback module, a tumor type analysis platform, an opinion collection module, a comprehensive analysis and judgment module and an identity login module. The medical data acquisition module is connected with the medical data identification module, the medical data identification module is connected with the multi-dimensional classification module, the multi-dimensional classification module is connected with the data matching module, the data matching module is connected with the database, the feedback module and the tumor type confirmation module, and the tumor type confirmation module is connected with the output display module. According to the system, the tumors can be classified according to the medical data, and the management of the medical data is facilitated.

The invention discloses a degradable ceramic marked radiotherapy positioning system based on degradable ceramic, and relates to the technical field of radiotherapy. Comprising a degradable ceramic marker implantation unit, an image acquisition and positioning identification unit, a radiotherapy plan adaptation unit, a marker degradation monitoring unit, a radiotherapy execution verification unit, a safety control unit and a data storage and tracing unit. All the units cooperate to complete marker precise implantation, target region positioning and recognition, radiotherapy plan making, degradation state monitoring, radiotherapy positioning verification, whole-process safety management and control and diagnosis and treatment data encryption, storage and tracing, and precise radiotherapy whole-process clinical application requirements of different tumor types and different radiotherapy schemes are comprehensively met. According to the invention, precise positioning of the radiotherapy target region is realized by means of the degradable ceramic marker, the radiotherapy positioning precision and the dose coverage rate of the target region are improved, and the risk of normal tissue irradiation is reduced; the marker can be completely degraded in vivo without secondary operation, and is suitable for clinical requirements of various tumor radiotherapy.

The invention belongs to the technical field of biological probes, and particularly relates to a high-molecular Fc binding peptide Raman probe as well as a preparation method and application thereof. Compared with the prior art, the precious metal nanoparticles, the Raman reporter molecules and the antibody are efficiently combined by synthesizing the macromolecular linker containing the precious metal nanoparticle binding molecules and the Fc binding peptide, and nanogaps formed among the precious metal nanoparticles generate a hot spot effect, so that a Raman signal can be remarkably amplified; the high-sensitivity and specific detection on the low-concentration circulating tumor cells is realized; meanwhile, an Fc binding peptide is introduced as a universal anchor point of an antibody, so that the adaptability of the probe to antibodies corresponding to different tumor types is improved, and the practicability of the probe in detection of circulating tumor cells in bodies of patients with various tumors is enhanced.

This application provides a multi-level MRI segmentation method for diagnosing tumors. In this application, the tumor type identification process is divided into three stages, from coarse to fine, using different models based on the U-Net framework. For 3D MRI scans of tumor patients, the first stage identifies the first human organ / tissue region using a first segmentation model; the second stage uses a binary segmentation model to identify the tumor region within the first human organ / tissue region; and the third stage uses a multi-class segmentation model to classify different tumors. This three-stage multi-level segmentation improves the accuracy of tumor classification, thereby contributing to the advancement of tumor treatment.

This invention proposes a near-infrared II fluorescent conjugated organic small molecule, its preparation method, and its application, belonging to the field of bioimaging and therapy. The conjugated organic small molecule has a D-A-D structure, with the general formula R1 being a C4-C24 branched or straight chain. After being encapsulated into nanoparticles with an amphiphilic polymer, it can guide in vivo tumor type IPDT and PTT combined therapy under the synergistic diagnosis of PA and NIR-II fluorescence dual-modal imaging.

Among the strategies allowing cancer cells to escape the immune system, the presence of Transforming growth factor beta (TGF-β) in the tumor micro-environment (TME) is one of the most potent immunosuppressive mechanisms for many types of tumors. Thus, depleting TGF-β is regarded as a promising potent therapeutic approach to fight cancers, regardless of the type of tumor. However, the major impediment for achieving this objective is that TGF-β belongs to the few cytokines that must be activated once secreted. Moreover, a systemic targeting of TGF-β is associated with profound side effects due to TGF-β ability to sustain the homeostasis of numerous tissues. Hence, selectively targeting of TGF-β activation within the TME appears as a rational approach to boost the anti-tumor response and avoid side effects. The integrin αvβ8 expressed on Tregs specifically promotes TGF-β activation and impairs the anti-CD8 T cell response within the TME of different cancers in both mice and humans. The inventors generated anti-β8 chain of αvβ8 integrin (Itgβ8) neutralizing monoclonal antibodies which specifically bind to Tregs and selectively neutralize the ability of Tregs to activate the TGF-β. Thus, the present invention relates to isolated anti-Itgβ8 neutralizing antibodies which specifically binds to β8 chain of αvβ8 integrin (Itgβ8) expressed on Tregs, and their uses for treating cancer.

Pancreatic adenocarcinoma has the worst overall mortality of any solid tumor, with only 7% of patients surviving after 5 years. To evaluate the clinical implications of genomic alterations in this low cellularity tumor type, we deeply sequenced the genomes of 101 enriched pancreatic adenocarcinomas from patients who underwent potentially curative resections and used non-invasive approaches to examine tumor specific mutations in the circulation of these patients. These analyses revealed somatic mutations in chromatin regulating genes including MLL and ARID1A in 20% of patients that were associated with improved survival. Liquid biopsy analyses of cell free plasma DNA revealed that 43% of patients with localized disease had detectable circulating tumor DNA (ctDNA) in their blood at the time of diagnosis. Detection of ctDNA after resection predicted clinical relapse and poor outcome, and disease recurrence by ctDNA was detected 6.5 months earlier than with standard CT imaging.

The present disclosure describes a machine learning (ML) framework including a graph convolutional neural network (GCN) for identifying gene expression features associated with cancer driven events. The model is trained to identify the TP53 mutation status of a cancer sample from gene expression using a comprehensive selected gene interaction map structure. A quantitative score is generated to rank the severity of the drive events in each sample. By means of the method, an extremely high AUC result is achieved on unseen data of multiple tumor types. And the gene has strong correlation with protein functions. Based on the annotations established in the literature, a transcriptome feature (STAMP) model associated with the mutant protein can also predict driving events of a variety of important cancer gene / pathway combinations and a variety of tumor types. Therefore, the STAMP model can identify and quantify driving events, which can provide a new way for cancer patients to improve selection and priority ranking of targeted therapy.

The application discloses a compound with an anti-tumor effect based on cordycepin and derived by derivatization, and a structure of the compound is shown as formula I. The cordycepin derivative and the pharmaceutical composition thereof have good anti-tumor proliferation effects. Compared with a parent drug, the cordycepin derivative has better affinity to a cell membrane, so that the half-life of metabolism of the drug in the body is longer, and the drug stays in the body for a longer time. Compared with other nucleoside anti-tumor drugs, the cordycepin derivative and the pharmaceutical composition thereof have a wider range of tumor types and effects, and have excellent inhibition effects on gastric cancer, pancreatic cancer, liver cancer, small cell lung cancer, colorectal cancer, melanoma, ovarian cancer and the like, and have lower side effects and better curative effects.

The application discloses a breast cancer neoadjuvant therapy prognosis multi-modal multi-task probability prediction method and system, and steps are as follows: using training data composed of breast DCE-MRI images and segmentation images of a plurality of breast cancer patients after various neoadjuvant therapies, and clinical information, radiology image reports, pathological reports and case information to perform breast cancer NAT prognosis multi-modal multi-task probability prediction training on a deep learning model; then using deep learning to analyze breast DCE-MRI images and segmentation images matched with the breast DCE-MRI images of a patient to be measured, and clinical information, radiology image reports, pathological reports and case information, generate and output pCR, DFS and OS prediction results of various different NAT schemes, risk probability and recurrence probability evaluation results of breast cancer metastasis to different organs, and benign and malignant tumor type and BI-RADS level identification results. The application can significantly improve the accuracy and comprehensiveness of NAT prognosis evaluation.

The application discloses a breast tumor screening method and device based on wideband ultrasonic echo features, comprising the following steps: S1, ultrasonic signal acquisition; S2, ultrasonic signal labeling: respectively calculating signal envelope and time-frequency spectrum, obtaining ultrasonic image through envelope logarithmic compression, labeling image lesion position and type, constructing breast tumor ultrasonic image dataset and breast tumor ultrasonic signal time-frequency spectrum dataset; S3, image dataset training: training the image dataset to obtain a lesion position detection model; S4, time-frequency spectrum dataset training: training the signal time-frequency spectrum dataset to obtain a breast tumor classification model; S5, model prediction: using the lesion position detection model to mark the tumor area of the test set image, and using the breast tumor classification model to predict the tumor type of the marked area signal; S6, prediction result visualization. The application can realize faster and more accurate lesion positioning and benign and malignant diagnosis effect in breast tumor screening than traditional image diagnosis models, and has wide application prospect.

A method for assisting a neurosurgical operation, wherein at least one image representation of an operating region on a patient is captured by means of a medical visualization system wherein categorical position information describing an anatomical position of a tumor present in the operating region is acquired and / or obtained, wherein the at least one captured image representation and the acquired and / or obtained categorical position information are supplied to a trained machine learning model as input data, wherein a tumor type is predicted by means of the trained machine learning model using the at least one captured image representation and the acquired and / or obtained categorical position information as a starting point, wherein the trained machine learning model provides tumor type information describing the tumor type as output data, and wherein the tumor type information is output. The invention further relates to an arrangement for assisting a neurosurgical operation.

The invention discloses an automatic tumor lesion analysis method and platform, a storage medium and computer equipment, and the method comprises the steps: determining a tumor minimum coverage graph region based on a tumor region marked by an ultrasonic image and a minimum coverage graph corresponding to a tumor type, and subtracting the tumor region from the tumor minimum coverage graph region to obtain a minimum coverage graph region; obtaining a peritumoral region; the method comprises the following steps: sequentially extracting features of a tumor region, a tumor minimum coverage pattern region and a peritumor region, constructing four feature input modes, respectively inputting the four feature input modes into each ML classifier for model training and evaluation, determining an optimal region selection mode on the basis of the feature input modes used when the ML classifiers are in optimal performance, and carrying out model evaluation on the optimal region selection mode. Therefore, a doctor can obtain a lesion analysis result through an optimal performance ML classifier based on the initially marked tumor area and the optimal area selection mode. Through multi-region feature extraction and classifier optimization, accurate analysis of benign and malignant tumors is realized, and ultrasonic image diagnosis efficiency and accuracy are improved.

In accordance with at least one aspect of this disclosure, a method for improving clearance and elimination of tumor targeted anti-cancer drugs from a patient, comprises, administering to a patient an anti-cancer drug that is eliminated into urine, and administering to the patient one or more supplemental therapies at a predetermined time after administering the anti-cancer drug. The predetermined time can be determined as a function of at least one of: the anti-cancer drug, the supplemental therapy, a tumor type, and / or a current physiological condition of the patient.