51 results about "Disease patient" patented technology

The application relates to a blood biomarker for evaluating and diagnosing Parkinson's disease and an application thereof. The blood biomarker is SERPINA3 and / or alpha-Syn. By using the biomarker as a diagnostic biomarker for Parkinson's disease, early diagnosis of Parkinson's disease can be assisted by detecting the SERPINA3 level and the alpha-Syn level in a blood sample, the trauma is small, the operation is simple, and the method is suitable for most patients and has high patient acceptance; and the SERPINA3 and alpha-Syn levels in the blood sample can be determined by a photochemical luminescence detection method, the detection sensitivity is high, the accuracy is high, and early, efficient and high-precision diagnosis of Parkinson's disease can be realized.

The present invention relates to a system and method for recommending health functional foods to elderly patients with geriatric chronic diseases. According to the present invention, a method for recommending health functional foods, performed by a system for recommending health functional foods, comprises the steps of: receiving, from a target patient with a geriatric chronic disease, response data obtained from responses to a medical inquiry form or questionnaire; performing natural language processing on the response data; inputting the natural-language-processed response data into a first learning model to classify a mental disorder and a severity level of the target patient; receiving personal information and EMR data of the target patient; and inputting the personal information, EMR data , and information on the mental disorder and severity level of the target patient into a second learning model to recommend one or more health functional foods to the target patient.

The application provides a gender stratified lung nodule disease identification and diagnosis model and system. Specifically, based on a machine learning method, six male characteristic indexes and six female characteristic indexes are used to construct a gender stratified identification and diagnosis system. The results show that the model based on support vector machine has an AUC greater than 0.8 in the training set and the validation set, has good identification ability, and can accurately identify and judge whether the patient with normal serum angiotensin converting enzyme level is a lung nodule disease patient. The system effectively solves the short board of the existing diagnosis method of lung nodule disease, and realizes the identification and diagnosis by using a small amount of characteristic indexes, greatly shortens the diagnosis time, and has a wide clinical application prospect.

Disclosed in the present application are a method and drug for preventing or treating a neurodegenerative disease, whereby a therapeutically effective amount of gliclazide or a pharmaceutically acceptable salt thereof or a combination of gliclazide or a pharmaceutically acceptable salt thereof and acetaminophen or a pharmaceutically acceptable salt thereof is used or comprised. The method and drug of the present invention can significantly alleviate symptoms such as hyposmia, cognitive dysfunction, and psychiatric symptoms in patients with neurodegenerative diseases that cannot be treated with existing drugs, and can be particularly used for controlling the progression of neurodegenerative diseases.

The application discloses a DNA methylation site marker for detecting hepatocellular carcinoma, a multiplex dPCR kit and a diagnostic model construction method. The DNA methylation site marker comprises cg02829688, cg13080379, cg03760839, cg10703826, cg12664119, cg16990168 and cg23371746 sites. The application designs a primer probe group for the above sites, constructs a multiplex dPCR kit of a double reaction system, realizes quantification of target DNA methylation sites, takes the methylation levels of the 7 sites as characteristic variables, adopts an XGBoost algorithm and / or an LR algorithm to construct a diagnostic model. Experimental verification shows that the model can effectively distinguish hepatocellular carcinoma patients from liver cirrhosis, chronic hepatitis B, metabolic dysfunction-related fatty liver disease patients and healthy individuals, especially shows good efficiency in auxiliary diagnosis of early hepatocellular carcinoma, and provides a new technical scheme for clinical diagnosis and screening of hepatocellular carcinoma.

The application discloses an Alzheimer's disease stage recognition method and system based on an interpretable multi-modal, and the method comprises the following steps: acquiring and preprocessing sMRI images of Alzheimer's disease patients and corresponding clinical texts to generate a clinical data set; constructing a multi-modal enhancement fusion model comprising an image feature extraction channel, a text feature extraction channel, a Mamba global sequence module embedding an image feature extraction channel and a feature fusion module based on a gating mechanism; extracting image features and text features of the clinical data set, and performing cross-modal interaction by using a multi-head attention mechanism to generate a feature fusion sequence; inputting the feature fusion sequence into a convolution-based multi-layer perceptron for feature enhancement, performing an Alzheimer's disease classification task and generating a classification result; and using a test set of the clinical data set and a ten-fold cross-validation method to quantitatively analyze the model performance on the Alzheimer's disease classification task, and integrating post-hoc interpretability technology to analyze the model classification result.

The present invention pertains to the treatment of diseases associated with a dysregulated immune response such as auto immune disorders, inflammatory diseases or pathological immune responses as adverse effects of medical treatments. In particular the invention provides a combined use of inhibitors of Receptor-interacting serine / threonine-protein kinase (RIPK1) and inhibitors of Inhibitor of κB (IκB) Kinase (IKK) in subjects suffering from such disorders. The invention provides such inhibitory compounds and their combinations for use in medical applications, as well as pharmaceutical compositions comprising the compounds of the invention.

The application provides a biomarker dopamine-3-O-sulfate (DA3S) for evaluating the risk of movement complications of Parkinson's disease patients. The application also provides a cerebrospinal fluid kit for evaluating the risk of movement complications of Parkinson's disease patients. The application is based on the concentration of DA3S in cerebrospinal fluid, and combines with clinical variables such as daily dose of levodopa (LEDD), disease duration, etc. to construct a joint prediction model, so as to realize early and quantitative individualized evaluation of the risk of movement complications of Parkinson's disease patients. The application also provides a plasma kit and a urine kit for evaluating the risk of movement complications of Parkinson's disease patients.

This invention discloses the application of ephedrine in the preparation of drugs for the prevention or treatment of peritoneal fibrosis, relating to the field of biomedical technology. The key technical point is: a pharmaceutical preparation for the prevention or treatment of peritoneal fibrosis, the active ingredient of which is ephedrine. This pharmaceutical preparation can achieve preventive and therapeutic effects on peritoneal fibrosis by inhibiting the mesothelial metastatic process (MMT) in peritoneal mesothelial cells, downregulating the expression of fibrosis-related proteins, and improving peritoneal ultrafiltration and solute transport functions, thus providing a new drug option for the treatment of end-stage renal disease patients undergoing peritoneal dialysis.

This application relates to the field of speech signal processing technology, providing an acoustic feature processing method, apparatus, computer device, readable storage medium, and program product. The method includes: extracting acoustic features from speech data of healthy individuals and Huntington's disease patients to obtain acoustic feature sets; evaluating the stability of the acoustic features in the acoustic feature sets to obtain candidate acoustic feature sets; evaluating the significant independent contribution of the candidate acoustic features in the candidate acoustic feature sets to obtain multiple target acoustic features and their corresponding weights; performing weighted and scaled processing on the multiple target acoustic features based on their weights to obtain speech index features; and using the speech index features to characterize the severity of Huntington's disease. This method can integrate the multidimensional language impairments of Huntington's disease into clinically interpretable speech index features that are significantly correlated with the severity of Huntington's disease, improving the robustness of tracking Huntington's disease progression.

Provided herein are systems comprising Class 2, Type V CRISPR proteins and guide nucleic acids (gRNA) useful in the modification of a target nucleic acid of a lipoprotein (a) (LPA) gene. The systems are also useful for introduction into cells, for example eukaryotic cells. Also provided are methods for treating subjects having a LPA-related disease and methods for optimizing the encoding sequences.

This invention provides a kit comprising: (1) a pharmaceutical composition containing a therapeutically effective amount of eugenol hydrochloride and a pharmaceutically acceptable carrier; and (2) a detection reagent for detecting vasoactive intestinal peptide (VIP) mRNA and / or protein. This invention reveals for the first time that eugenol hydrochloride (HH) has a highly effective therapeutic effect on specific Parkinson's disease patients characterized by abnormally elevated VIP levels. The pharmaceutical composition and kit of this invention can specifically reduce the expression of pro-inflammatory VIP, thereby precisely intervening in the VIP-mediated microglial-related neuroinflammatory pathway, thus significantly treating Parkinson's disease and providing a novel targeted treatment option for the clinical intervention of Parkinson's disease.

Set forth herein are methods useful for identifying disease biomarkers, particularly for diseases such as clear cell renal cell carcinoma (ccRCC). In some examples, the methods set forth herein are useful for monitoring the prognosis of patients having disease such as ccRCC.

The application discloses a lumbar degenerative disease patient treatment expectation evaluation system and relates to the technical field of medical health information processing; the system comprises a data acquisition unit, a expectation evaluation unit, an influence factor analysis unit and a report generation unit; the data acquisition unit is used for collecting multidimensional information of a lumbar degenerative disease patient; the expectation evaluation unit is connected with the data acquisition unit and is used for quantitatively evaluating the treatment expectation of the patient based on the collected information; the influence factor analysis unit is connected with the expectation evaluation unit and is used for analyzing key factors influencing the treatment expectation of the patient; the report generation unit is connected with the expectation evaluation unit and the influence factor analysis unit and is used for integrating evaluation and analysis results and generating a visual evaluation report. The application integrates various evaluation tools that have been tested for reliability and validity, converts subjective inquiries that are originally scattered and depend on the personal experience of medical staff into a unified, standardized and multidimensional quantitative evaluation process, and ensures the scientificity and comparability of evaluation results.

The present disclosure relates to the treatment of patients with mid- to late-stage Parkinson's Disease using subthalamic nucleus deep brain stimulation (STN-DBS) to a target a defined region of the brain. In particular, by positioning and / or programming the DBS electrode to stimulate cortical input fibers from the primary motor and supplementary motor areas (but not the pre-SMA), improved therapeutic benefits are obtained.

The application discloses a kind of single-cell transcriptome analysis methods and application of Crohn's disease creeping fat microenvironment, belong to the field of biological medicine technology.The method is by obtaining the single-cell and batch transcriptome data of mesenteric adipose tissue of Crohn's disease patient and healthy control, constructs relevant gene set and carries out data quality control, clustering and cell annotation;Mesenchymal stem cells are subpopulation identified, abundance analysis and function typing, combined with signal path analysis and cell communication analysis, and the key factor of regulating creeping fat microenvironment is screened out.The application first systematically analyzes the cell heterogeneity and MSC subpopulation characteristics of Crohn's disease creeping fat microenvironment, and determines the key signal path and regulating molecule, which can provide efficient and reliable technical means for the pathogenesis research, treatment target screening and creeping fat related molecule identification of Crohn's disease, and has high scientific research and clinical application value.

The application relates to the field of biomedical technology, and discloses a Parkinson disease subtype staging inference system based on a corneal nerve image and a SuStaIn algorithm, which comprises an image data acquisition module, a health control module, an abnormality division module, a SuStaIn model construction module and an output module. The image data acquisition module acquires an original image data set, and extracts core effective features after preprocessing the original image data set. The health control module calculates the Z scores of each feature in the corresponding core effective features of Parkinson disease patients through a standardization method. The abnormality division module divides abnormality grades based on the calculation results of the Z scores, and constructs a feature event matrix. The SuStaIn model construction module constructs a disease progression model based on the feature event matrix, inputs the patient feature Z score matrix, sets related parameters, completes model training, and then determines the optimal subtype number through multi-index evaluation. The output module outputs the model prediction results. The application realizes accurate identification of Parkinson disease patient subtypes and objective inference of disease stages, and provides strong support for early diagnosis, individualized treatment and drug research and development of diseases.

This invention relates to the fields of medical auxiliary diagnosis and computer vision technology, specifically to a multimodal video-assisted diagnostic method and system for Parkinson's disease based on Transformer and attention fusion. First, video data of the subject's hand pinching motion and linear back-and-forth walking motion are acquired and a unified sample label is established. Then, video preprocessing is completed through preprocessing, sliding time window segmentation, and data augmentation. Next, the preprocessed temporal image sequence is input into a spatiotemporal modeling network, where a visual Transformer is used to extract frame-level spatial features. A multi-layer long short-term memory network is then combined to capture long-term temporal motion dynamic information. Finally, a modality-level spatiotemporal attention fusion method adaptively learns modality weights and achieves feature fusion. Finally, the fused features are input into a classification network, outputting prediction results for Parkinson's disease patients or healthy controls. This invention comprehensively characterizes the motion features of the disease through multimodal fusion and accurate spatiotemporal modeling, improving diagnostic accuracy and robustness.

This invention discloses a bivalent ligand molecule targeting EGFR and its applications, belonging to the field of drug development technology. Its general structural formula is: [Formula omitted for brevity], where L is a linking group, and M1 and M2 are EGFR protein ligands. This invention forms a bivalent EGFR ligand molecule by covalently linking two EGFR ligands through a linking group. This bivalent ligand molecule can induce additional protein-protein interactions between EGFR monomers, which greatly enhances the binding strength and stability of the drug to EGFR, thereby overcoming the drug resistance problem of traditional EGFR inhibitors and providing a new treatment strategy for cancer patients carrying EGFR mutations and other patients with other diseases.

The application discloses a same-disease patient matching method and system based on pathological characteristics and treatment cycles, and the method comprises the following steps: acquiring multi-dimensional data of objective medicine, social demography and platform behavior of a user; pre-processing and extracting features of the multi-dimensional input data, and constructing a multi-dimensional rehabilitation feature model comprising biological, social demographic and behavior cognitive feature vectors; based on dynamic weight matching calculation of the whole treatment cycle, matching and calculating the multi-dimensional rehabilitation feature model of the target user with a candidate user database; according to the calculation result of the matching calculation, combining the calculation result of the time sequence prognosis guidance logic, generating a sorted patient friend recommendation list, and pushing it to the target user. The application can accurately recommend the same-disease patient friends with the same gene mutation, treatment path coverage and survival guidance value for the critical patients by mining multi-dimensional medical data and dynamic behavior characteristics.

The application discloses an Alzheimer's disease patient intelligent assistance method and system based on multi-modal perception and a double-layer AI architecture. The method comprises the following steps: a wearable terminal collects multi-modal input data and sends the multi-modal input data to an edge computing server; the edge computing server serves as a first computing node, generates a restricted structured service call instruction through a lightweight large language model, and executes a first service; a user question and an execution result are sent to a cloud-side workflow for checking; if the first execution is insufficient to answer the question, the cloud-side workflow outputs a hybrid protocol response containing a natural language carrier and a machine-readable correction load; the edge node extracts the correction load and reuses a frozen multi-modal data segment to perform compensation; and the compensation result is submitted to the cloud side to generate a final reply and broadcast the final reply. Through the double-layer architecture of edge computing and cloud-side workflow cooperation, and in combination with an automatic error correction closed loop mechanism, the application realizes low-delay and high-reliable Alzheimer's disease patient intelligent assistance.

The present invention relates to a new variant of EPO. In this study, the inventors identified a particular EPO differing from kidney-type EPO due to a different glycosylation pattern in patients with different diseases (for example idiopathic erythrocytosis, liver / kidney disorder, tumors...). This new EPO is similar to pre-term newborn EPO produced by the liver that differs from the normal EPO produced from renal interstitial cells due to different post-translational modifications (glycosylations). This new EPO shows an increased biological activity via activation of the EPO receptor (EPOR), that can explain the origin of erythrocytosis. The detection of this specific liver-like EPO could be used as a diagnostic tool to better adapt and follow the treatments of erythrocytosis patients or in other diseases associated with the overproduction of red blood cells. Thus, the invention relates to a specific EPO protein which differs from the EPO with kidney-type glycosylation pattern.

This application relates to a blood biomarker for the differential diagnosis of patients with Parkinson's disease and multiple system atrophy, and its uses. The blood biomarker contains at least SERPINA3. This blood biomarker can assist in the early diagnosis and continuous monitoring of patients with Parkinson's disease and multiple system atrophy. It is low-cost, simple to operate, fast to detect, minimally invasive, and readily accessible, making it suitable for most patients and possessing high clinical application value.

This invention relates to the field of Mongolian medicine technology and discloses a Mongolian medicine composition for treating skin diseases caused by damp-heat and toxin accumulation. It aims to address the problem that existing technologies struggle to balance the efficacy of skin lesion treatment with the safety of systemic medication when treating patients with damp-heat and toxin accumulation skin diseases complicated by chronic diseases such as hypertension and asthma. This invention limits the specific weight ratio range between the heat-clearing and blood-cooling herbs and the harmonizing and strengthening herbs in the composition, and optimizes the synergistic relationship between the principal herbs and other adjuvant herbs. Under specific proportions, the composition maintains its basic effects of clearing heat and detoxifying, removing dampness and cooling blood, while enhancing its ability to clear damp-heat and toxins from the local skin. Furthermore, through the mutual restraint of the internal compatibility, it reduces potential interference with the patient's cardiovascular and respiratory systems. Therefore, this invention provides a new Mongolian medicine preparation that can safely and effectively treat skin diseases caused by damp-heat and toxin accumulation, especially suitable for patients with related chronic underlying diseases.

This invention proposes a clinical prediction model and design method for the probability of developing anal fistula in Crohn's disease patients, belonging to the field of clinical medical technology. The risk prediction model includes: an input module receiving patient parameters consisting of age at diagnosis, biological agent mode switching, and Montreal manifestation classification at initial diagnosis; a processing module connected to the input module, calculating the assessment and prediction probability of anal fistula in Crohn's disease patients based on the age at diagnosis, biological agent mode switching, and Montreal manifestation classification data at initial diagnosis, according to the following formula; and an output module connected to the processing module, outputting the risk probability of anal fistula in Crohn's disease patients obtained from the risk prediction model. The prediction model is validated on the training and validation sets using the area under the receiver operating characteristic (ROC) curve and a calibration curve to determine its discriminative power and calibration. It can accurately predict the risk of anal fistula in Crohn's disease patients before treatment.

The present invention relates to a speech-voice evaluation and treatment protocol determination software system for a speech-voice disorder digital therapeutic device of a Parkinson's disease patient and, more specifically, to a speech-voice evaluation and treatment protocol determination software system for a speech-voice disorder digital therapeutic device of a Parkinson's disease patient, which can provide non-pharmacological treatment for a speech-voice disorder. In order to evaluate a speech-voice disorder and provide a user-customized treatment, the present invention may evaluate (diagnose) a speech-voice function of a user for each detailed evaluation item by using a preset automation process for the speech-voice disorder of the user, and provide a treatment protocol to the user for each detailed treatment module on the basis of a result of the evaluation.

The present application belongs to the field of life science, and particularly relates to a functional probiotic strain Pediococcus pentosaceus. The Pediococcus pentosaceus WMU002 strain of the present application is derived from human body, and is high in safety after screening, domestication and verification. The Pediococcus pentosaceus WMU002 strain selected by the present application can obviously improve the motor disorder caused by Parkinson's disease and improve the behavior ability, overcome the defects and deficiencies of the prior art, and creatively apply the Pediococcus pentosaceus to the prevention and treatment of Parkinson's disease, and further develop a probiotic preparation for preventing or treating Parkinson's disease. The Pediococcus pentosaceus preparation composition of the present application can be used as a drug for preventing and treating Parkinson's disease, has no toxic side effects, and can be used for the auxiliary treatment of clinical Parkinson's disease patients. The present application has good social and economic benefits, and is worth popularization and application.

This invention belongs to the field of image processing technology and relates to a functional-structural brain network representation learning method for brain disease diagnosis, including: 1. Multimodal brain network data acquisition and preprocessing; 2. Topology-aware hypergraph modeling; 3. Attention mask generation based on structural topological distance; 4. Joint representation learning of topology-aware hypergraph and attention; 5. Graph-level representation and brain disease diagnosis output. In clinical applications, this invention can be used for auxiliary screening and classification of patients with brain diseases such as ASD, and provides doctors with reference and basis through the output classification labels and key brain regions, supporting earlier risk assessment, follow-up monitoring, and individualized intervention decisions. This invention provides strong and effective technical support for the early diagnosis and precision treatment of brain diseases, and has broad clinical application prospects and important medical research value.

Genomipulated human anti-CD40L antibodies to lack the ability to activate platelets and methods for treating patients with a human CD40L-associated disease.

This invention relates to the fields of intelligent agents and computer vision technology, specifically to a method and system for guiding Parkinson's disease hand rehabilitation training based on visual features and intelligent agents. It integrates hand movement videos captured by high frame rate event cameras, physiological sensor data, and prior medical knowledge to construct a closed-loop rehabilitation guidance system centered on a medical intelligent agent. This system utilizes deep neural networks to extract spatiotemporal features of key hand points, combines Euclidean distance error and joint angle error to construct a two-dimensional comprehensive evaluation index, and dynamically adjusts the evaluation weights according to the patient's UPDRS stage. Through a medical intelligent agent based on the Transformer architecture, combined with a multi-objective reinforcement learning strategy, personalized, multimodal rehabilitation feedback instructions are generated. This invention achieves precise quantitative assessment and personalized guidance of hand movements in Parkinson's disease patients, effectively distinguishing between Parkinson's tremor and essential tremor, and significantly improving the accuracy, compliance, and individual adaptability of rehabilitation training.