1726 results about "Cancer" patented technology

Provided herein are compounds, or salts, esters, tautomers, prodrugs, zwitterionic forms, or stereoisomers thereof, as well as pharmaceutical compositions comprising the same. Also provided herein are methods of using the same in modulating (e.g., inhibiting) KRAS (e.g., KRAS having a Q61H, G12D, G12V, G12C, G12S, G12A, G12R, or G13D mutation or wild-type KRAS, including wild-type amplified KRAS) and treating diseases or disorders such as cancers in subjects in need thereof.

The disclosure provides compounds, e.g., compounds of Formula I, and their use in treating medical diseases or disorders, such as cancer. The compounds are contemplated to be modulators of Ras (e.g., K-Ras).

The present invention relates to a compound as shown in formula (A) having a pan-RAS inhibitory effect, or an isotopic derivative or stereoisomer thereof, or a pharmaceutically acceptable salt thereof, and a pharmaceutical composition containing the compound, and the use of the compound of formula (A) in the prevention and / or treatment of cancers, tumors, inflammatory diseases, autoimmune diseases or immune-mediated diseases.

The invention relates to the technical field of assessment and early warning systems, and particularly discloses a rectal cancer operation risk assessment and early warning system based on multi-modal data fusion, which comprises a multi-modal data acquisition module, a data preprocessing module, a cross-modal fusion module, a dynamic risk assessment module, an intelligent early warning module and a system self-checking module. By integrating multi-modal data and dynamically allocating weights, real-time risk updating in the whole operation period is achieved, the comprehensiveness, timeliness and precision of risk assessment are comprehensively improved by combining the grading early warning function, the autonomous detection calibration function and the risk tracing and countermeasure matching function, long-term reliable operation of the system is guaranteed, powerful support is provided for clinical decision making, and the risk assessment method is suitable for clinical decision making. The surgical risk and the complication occurrence rate are effectively reduced.

Provided are a compound represented by formula (I) and a pharmaceutical composition comprising the compound, and a use of a compound of formula (A) for preventing and / or treating cancer, tumor, inflammatory disease, autoimmune disease, or immune-mediated disease.

This disclosure describes proteins that specifically bind human sperm protein 17 (Sp17) with nanomolar affinity and high specificity. These proteins include a recombinant human anti-Sp17 IgG that is suitable for use as a therapeutic antibody to treat cancers that ectopically express Sp17. Other Sp17-binding proteins are described including antibody fragments, antibody conjugates, and fusion proteins.

Disclosed are approaches to data acquisition, analysis, and computational forecasting that employs quantitative MRI data to predict the response of cancer to therapy. Example protocols detail how to acquire needed images followed by registration, segmentation, quantitative perfusion and diffusion analysis, model calibration, and prediction. The response of individual cancer patients to therapy is forecast by application of a biophysical, reaction-diffusion model to these data. Application of the protocol results in coregistered MRI data from at least two scan visits that quantifies an individual tumor's size, cellularity and vascular properties. This enables a spatially resolved prediction of how a particular patient's tumor will respond to therapy. A modified therapy can be determined based on predicted response.

Described herein are methods such as multi-omic methods for assessing a disease such as cancer. The multi-omic methods may integrate proteomic, transcriptomic, genomic, lipidomic, or metabolomic data. The method screening diseases or disease states. Also described herein are methods for screening for diseases or disease states from biological samples. The methods may include assessing whether a nodule, mass, or cyst is cancerous.

To provide a device and a method for treating at least one of hypertension, pulmonary arteries, diabetes, obesity, heart failure, end-stage renal disease, digestive disease, urological disease, cancers, tumors, pain, asthma or chronic obstructive pulmonary disease by delivering an effective amount of a formulation to a tissue.SOLUTION: In embodiments of the present invention, the formulation may include at least one of a gas, a vapor, a liquid, a solution, an emulsion or a suspension of one or more ingredients. In embodiments of the present invention, amounts of the formulation and / or energy are effective in injuring or damaging tissue, nerves and nerve endings in order to relieve disease symptoms.SELECTED DRAWING: Figure 3B

The invention relates to the field of medical health and artificial intelligence, and discloses a cancer patient low-molecular heparin individualized dose dynamic optimization method based on reinforcement learning, and the method comprises the steps: S1, collecting multi-dimensional clinical data of a cancer patient, carrying out the preprocessing, carrying out the enhancement of the preprocessed data, and generating time sequence synthesis data; s2, based on the multi-dimensional clinical data and the time sequence synthesis data, constructing a reinforcement learning environment, including defining a state space, an action space and a reward function; s3, constructing an environment adaptive deep reinforcement learning EA-DRL model as a dose optimization model; performing model training and optimization in the reinforcement learning environment until convergence and obtaining an optimal dose decision strategy; and S4, inputting real-time dynamic clinical data of a patient to be decided into the trained dosage optimization model, and outputting individualized low molecular heparin LMWH administration dosage recommendation. Individualized precise administration is realized, and the treatment effect and the clinical medication safety are improved.

The present disclosure relates to compositions and methods for reducing expression of MYC gene in a cell. In some embodiments, an expression repressor comprises a targeting moiety that binds a MYC promoter, anchor sequence, or super-enhancer. In some embodiments, the expression repressor comprises an effector moiety that represses transcription or methylates DNA. Systems comprising two expression repressors are also disclosed. The compositions can be used, for example, to treat cancers such as HCC.

The present disclosure provides compounds and their methods of use. In particular, the compounds of the present disclosure may be useful for inhibiting RAS proteins, such as KRAS proteins. The disclosed compound may be used in the treatment of cancer and be highly selective for KRAS proteins having the G12D mutation. Alternatively or additionally, said compounds may have broad spectrum activity across a range of KRAS proteins.

The invention provides a whole-course nursing management system combining traditional Chinese medicine and western medicine for tumor patients, and relates to the field of intelligent health management.The whole-course nursing management system comprises the steps that physiological, exercise, diet and psychological condition data of the tumor patients are collected at first, and then potential health risks of the tumor patients are recognized by analyzing the physiological, exercise and diet data; meanwhile, the enthusiasm of the patient is evaluated according to psychological condition data, and then all collected data and recognition and evaluation results are input into a Chinese and western medicine combined nursing health management suggestion engine based on a large language model to generate a Chinese and western medicine combined nursing health management suggestion conforming to the actual condition of the tumor patient. Therefore, comprehensive and personalized health management service can be provided for tumor patients.

The invention relates to the technical field of medical information, in particular to a tumor patient adverse drug reaction intelligent follow-up visit system based on an internet hospital, which comprises a patient file module for acquiring medical data, identifying bad data and recording the bad data in a medical record file to form an abnormal symptom report; the intelligent analysis module is used for comprehensively analyzing the abnormal symptom report by utilizing a trained machine learning model and outputting analysis data; according to the system and the method, continuous monitoring and active early warning of extrahospital adverse reactions of tumor patients are realized, the timeliness of finding the adverse reactions is remarkably improved, intervention measures can be taken before symptoms of the patients deteriorate, and the treatment safety of the patients is improved. And secondly, through intelligent analysis and grading, the burden of manually screening the patient condition by medical staff is greatly reduced, the system automatically finds abnormity from massive follow-up visit data, and the efficiency and accuracy of follow-up visit management are improved.

The application provides a novel DNA methylation marker TAGMe-3 for tumor identification and use thereof. The TAGMe-3 gene sequence region has significant methylation difference between cancer tissues and paracancer tissues. As long as abnormal high methylation state of the TAGMe-3 gene sequence region is detected, the subject is determined to belong to a tumor high-risk population. Moreover, the significant difference of the TAGMe-3 presented between tumor tissues and non-tumor tissues exists in different types of tumors (Pan-cancer) in a wide range.

The invention relates to the technical field of psychosomatic health management, in particular to a psychological immune system evaluation system and intervention method for cancer patients. And the data acquisition module is used for acquiring and fusing the immune biochemical indexes of the patient, the continuous physiological time sequence signals generated by the wearable device, the digital psychological assessment data and the clinical treatment stage marks, and outputting a structured multi-dimensional time sequence data set through time alignment and feature extraction operation. Through multi-modal data fusion and integrated machine learning analysis, the psychosomatic health risk of the patient can be predicted based on the continuous physiological and psychological data change trend of the patient, and corresponding intervention measures can be triggered before the patient has obvious clinical symptoms by outputting the quantized risk coefficient and the multi-stage early warning signal, so that the accuracy of the patient is improved. Therefore, an intervention mode is promoted to be converted from traditional intervention after evaluation to predictive and preventive intervention.

The present invention relates to anti-DDR2 antibodies. More specifically, the present invention relates to nano-antibodies binding to DDR2 and various derivatives of the nano-antibodies. The present invention also relates to pharmaceutical compositions comprising these antibodies and derivatives and pharmaceutical uses thereof. The anti-DDR2 nano-antibodies of the present invention have strong binding activity and can be used for diagnosis, prevention and / or treatment of diseases mediated by abnormal DDR2 expression (such as cancer and inflammatory diseases), as well as imaging of cells expressing DDR2, such as biopsy navigation and intraoperative navigation.

The disclosure relates to radiolabeled aromatic electrophile prosthetic groups, which can be used to prepare bioactive ligands containing PET, SPECT, alpha- or beta-emitting radioisotopes, and their use in treating and / or imaging cancer.

The invention discloses an acid responsive nanoprobe as well as preparation and anti-tumor application thereof. The nanoprobe has a core-shell structure, takes a nanoparticle self-assembled by a polycation aggregation-induced emission (AIE) photosensitizer and functional nucleic acid as a core, and takes a hyaluronic acid modified metal polyphenol network as a shell. The nanoprobe utilizes the acid responsiveness and broad-spectrum absorption performance of the metal polyphenol network and the diagnosis and treatment advantages of the polycation AIE photosensitizer to realize the acid responsiveness'switch 'controllable diagnosis and treatment of the tumor nanoprobe. In a neutral environment, the fluorescence is weak, the generation of ROS is less, and the background noise signal of the nanoprobe and the toxicity of non-targeted tissues are reduced; in an acid environment, fluorescence is enhanced, the ROS yield is improved, and the treatment efficiency and the curative effect monitoring accuracy are improved. The nano diagnosis and treatment probe is ingenious in design and simple to prepare, and can realize PDT and gene therapy synergistic anti-tumor, in-situ real-time report of early tumor treatment effect and assistance in precise cancer treatment.

The invention discloses an old-age tumor patient early-stage weakness risk prediction system based on an improved population algorithm, and the system comprises a data collection module which constructs an old-age tumor patient data set; the data preprocessing module is used for generating a fused elderly tumor patient feature matrix; the feature processing module forms an initial feature set; the feature screening module inputs the initial feature set into a discrete empire butterfly optimization algorithm to generate a key feature subset; the multi-scale Markov chain modeling module is used for constructing a multi-scale Markov chain model based on the key feature subset to form a risk state sequence; and the dynamic risk prediction module is used for judging whether the early-stage weakening risk of the old tumor patient reaches an early-warning standard or not and generating corresponding risk early-warning information. A layered prediction mechanism is established, so that the model can perform comprehensive analysis from short-term health fluctuation and medium-term change trend to long-term risk evolution.

The present invention relates to the technical field of chemical pharmacy, and in particular to a compound for degradation of a targeted interleukin-1 receptor-associated kinase 4 (IRAK4), and a pharmaceutically acceptable salt of the compound. The compound can be used for treating or preventing IRAK4-mediated immune diseases, inflammatory diseases, and cancers.

The invention discloses a pyridone type coumarin derivative as well as a preparation method and application thereof. The invention autonomously designs and synthesizes a novel pyridone type coumarin derivative. Experimental results show that the pyridone type coumarin derivative has a remarkable inhibition effect on KYSE-70 and KYSE-150 cells, and the pyridone type coumarin derivative has a very good application value in anti-inflammatory, anti-virus, antibacterial or anti-cancer aspects.

The invention provides an intratumoral bacterium detection and analysis method based on circular DNA enrichment sequencing and related model construction, and belongs to the field of molecular biology. The intratumoral bacterium detection method provided by the invention comprises the following steps: extracting total DNA of cancer tissue or para-carcinoma tissue, carrying out linear digestion, purifying a linear digestion product, and enriching to obtain circular DNA; the method comprises the following steps: amplifying circular DNA, and breaking a DNA amplification product to 300-500bp; purifying DNA fragments, constructing a library, and sequencing; and performing genome comparison according to a sequencing result to obtain information of the intracellular bacteria. According to the method, complete bacterial genome and plasmid genome information can be captured, and the detection sensitivity of the intracellular bacteria and the richness of the bacterial genome information are improved. The invention further provides an intratumoral bacterium analysis method which can be used for screening generic cancer bacterial markers, and provides a cancer risk assessment machine learning model based on the intratumoral bacterium, so that the clinical application possibility of the intratumoral bacterium is improved.

The present disclose provides a method for classifying a sample derived from a subject. The method may comprise obtaining a sample comprising nucleic acid molecules from the subject. The method can comprise assaying the nucleic acid molecules to generate a data set comprising methylation states of one or more genomic regions. The one or more genomic regions can comprise differentially methylation regions (DMRs). The method can comprise processing at least a portion of the data set to generate an output indicative of cancer in the subject. The portion of the data set can pertain to a set of DMRs specific to the subject.

The invention relates to a preparation method of a microwave-assisted synthesized near-infrared electrochemical luminescence gold nanocluster and application of the gold nanocluster in miRNA (micro Ribonucleic Acid) detection. The preparation method comprises the following steps: under a stirring condition, adding a gold source and alkali into a Met solution to obtain a mixed solution, carrying out microwave irradiation reaction, and carrying out solid-liquid separation to obtain a Met-Au NCs solution; the preparation method comprises the following steps: activating a Met-Au NCs solution by using EDC and NHS, adding a DNA solution, mixing, and dialyzing to obtain a Met-Au NCs-DNA compound, namely the near-infrared electrochemical luminescence gold nanocluster. Compared with Au NCs prepared by a common mild method, the Met-stable Au NCs prepared by a microwave-assisted method has the advantage that the fluorescence and electrochemical luminescence efficiency at 835 nm is improved. The invention also provides a'signal closing 'ECL (electron cyclotron ligand) biosensor for high-sensitivity detection of the miRNA-107 (MicroRNA-107), and a method for detecting the miRNA-107 (MicroRNA-107). The sensor is simple to operate and good in repeatability, and has important scientific significance and application value for clinical early diagnosis of cancers.

Borylated Amino Acid compositions comprising tyrosine derivatives BTS and BTS(OMe) and novel methods of making BTS and BTS(OMe) are disclosed herein. Consequently, the BTS and / or BTS(OMe) can be scaled up to commercial scale and administered to patients as a Neutron Capture Agent and provide a method of treating cancer, immunological disorders, and other disease by utilizing a Neutron Capture Therapy modality.

A method includes receiving natural language input text characterizing clinical data for a patient. The method also includes receiving a prompt composition that includes adjudication rules for performing lines of therapy adjudication and an instruction parameter that specifies a task for a LLM to synthesize a group of multiple synthetic experts that each use the adjudication rules to perform chain-of-thought reasoning for making lines of therapy (LoT) adjudication decisions. The method also includes structuring an adjudication prompt by concatenating the prompt composition to the natural language input text, processing, using the LLM, the adjudication prompt to cause the LLM to synthesize the group of multiple synthetic experts and generate a respective group answer. The method also includes determining a final answer based on the respective group answer generated from the group of multiple synthetic experts.

The invention discloses an imidazo [4, 5-b] pyridine compound capable of blocking mRNA translation of tumor cells and an application of the imidazo [4, 5-b] pyridine compound in preparation of antitumor drugs for blocking mRNA translation of tumor cells, and the imidazo [4, 5-b] pyridine compound has a structure shown in a formula (I) or a pharmaceutically acceptable salt of the imidazo [4, 5-b] pyridine compound. The mRNA translation of cancer promoting protein is crucial to the occurrence and development of malignant tumors, but a small molecular compound for targeted inhibition of mRNA translation is lacked clinically at present. The invention provides an imidazo [4, 5-b] pyridine compound, which can be combined with a translation initiation factor eIF4A and inhibit the ATP-dependent RNA helicase function of the translation initiation factor eIF4A so as to block the translation of mRNA and present proliferation inhibition and apoptosis promotion functions in various tumor cells. # imgabs0 #

The invention discloses a genetic state cancer clustering analysis method based on deep learning, which comprises the following steps: S1, constructing a single cell sequencing data set which comprises a gene expression matrix; s2, constructing a deep neural network composed of an input layer, a hidden layer and an output layer to obtain converted low-dimensional high-variation gene expression features; s3, constructing a gridding preprocessing model, and performing networked preprocessing including grid segmentation and isolated point removal on the low-dimensional high-variation gene expression features; constructing a clustering algorithm model, inputting the preprocessed low-dimensional high-variation gene expression features into the clustering algorithm model, and designing an optimization strategy based on a target function by the clustering algorithm model to enhance label entropy on a KL divergence index and amplify the ratio weight of auxiliary probability distribution and clustering distribution of the gene features; and iteratively realizing clustering result optimization as the output of the clustering algorithm model. Compared with the prior art, the clustering precision can be improved.

The invention provides a cross-omics sparse feature selection system and method based on hierarchical causal modeling, and the system comprises a data input and preprocessing module which is used for receiving multi-omics original data of a multivariate sample; the hierarchical causal structure learning module is connected with the data input and adaptive preprocessing module and is used for constructing a cross-omics hierarchical causal topology; the causal-oriented sparse feature selection module is connected with the hierarchical causal structure learning module; and the model retraining and integration module is used for constructing a three-layer weighted integration discrimination model based on the screened markers, optimizing the fusion weight of each layer through a gradient descent algorithm, and outputting a final prediction result. According to the method, the protein-metabolism biological hierarchy relationship and serum-urine complementary information are fully utilized, and the method has good generalization ability and can be widely applied to marker mining and prediction modeling of cancers, metabolic diseases and the like, so that the accuracy and reliability of precise medical treatment are improved.