92 results about "Metabolic state" patented technology

The invention provides a Bi-BDO fermentation pH dissolved oxygen dynamic optimization method based on an online Raman spectrum, belongs to the technical field of biological fermentation process control, and aims to solve the problems of unstable process and low efficiency caused by fermentation control lag and incapability of sensing the real metabolic state of cells in the prior art. The method comprises the following steps: acquiring the concentrations of a target product BDO and key byproducts such as acetic acid and ethanol in the fermentation liquor in real time through an online Raman spectrum; according to the method, a metabolic stress index is originally proposed and constructed, the index is obtained by performing weighted operation on the instantaneous generation rate of the by-product and the target product, and the index is used for quantitatively characterizing the intrinsic metabolic stress level of the cells in real time. The control strategy of maintaining the metabolic stress index in the preset optimal stable interval is taken as a core control strategy, the conversion from passive response to active prediction in the fermentation process is realized, and the yield, the stability and the batch repeatability of Bi-BDO production are remarkably improved.

The invention relates to the technical field of medical health management, in particular to a chronic kidney disease and diabetes collaborative nutrition monitoring and early warning method and system.The method comprises the steps that multi-dimensional physiological indexes, nutrition intake and sleep data of a patient are obtained, and a dynamically-coupled metabolic state topological space is constructed; based on the space, constructing a dual-disease metabolism coupling matrix, analyzing stability characteristics of a metabolism state trajectory, identifying stable and unstable attractors, and calculating a multi-dimensional risk score; a sleep-metabolism synchronism risk prediction model is introduced, and a personalized early warning threshold value is dynamically adjusted; when the risk score exceeds a threshold value, early warning is triggered, and intervention suggestions are generated, the interactive influence of protein metabolism and glycometabolism is quantitatively described from the metabolic mechanism level, and the contradiction of chronic kidney disease and diabetic patients in nutrition management is solved; limitation of a static threshold is broken through, and dynamic risk assessment is realized; sleep factors are creatively integrated, and a new way for improving the metabolic state is provided.

The invention relates to the technical field of health management, and discloses an intelligent food recommendation and diet optimization system based on body temperature change, and the system comprises a body temperature dynamic fluctuation curve generation module which collects data in real time through a multi-source temperature sensor of wearable equipment, and is used for generating a body temperature dynamic fluctuation curve; the metabolism state label acquisition module is used for matching the time-frequency domain characteristics with a preset metabolism mode library so as to acquire corresponding metabolism state labels; the calculation module is used for calling nutrient element intake records in the historical diet database of the user and a preset health target and is used for calculating a current metabolic rate deviation value and a nutrition gap; the diet scheme generation module is used for generating a suggested diet scheme containing a recommendation priority score and a real-time eating suggestion based on the metabolic rate deviation value, the nutrition gap and a preset health target; and the monitoring module is used for monitoring body temperature change data after the user executes the recommended diet scheme. The accuracy of health management can be improved.

The invention relates to an intelligent decision-making system for nutrition metabolism collaborative management of elderly chronic disease patients, in particular to the field of nutrition metabolism collaborative management of elderly chronic disease, which is characterized in that drug molecule characteristics and nutrient metabolism paths are dynamically integrated through a multi-modal knowledge graph, and a cross-domain associated three-dimensional knowledge network is constructed; based on a reinforcement learning real-time optimization rule confidence threshold value, the early warning sensitivity is adaptively adjusted according to the degree that the metabolic index of the patient deviates from the safety interval; the streaming conflict detection engine accurately identifies the potential risk of asynchronously input medication and diet data, and triggers graded early warning through space-time alignment and sub-graph matching; the closed-loop evolution mechanism fuses patient compliance feedback and blood potassium change trend, drives the taboo rule base to continuously and autonomously evolve under the constraint of renal function layering, and realizes personalized risk prevention and control and metabolic state collaborative optimization.

The invention relates to the technical field of medical information processing, in particular to a liver, gall and pancreas postoperative intelligent support system and method for dynamic nutrition metabolism analysis, and the system comprises a multi-source metabolism data collection module which obtains the body composition, stool spectrum and enteral nutrition parameter data of a patient in real time, the dynamic metabolic state modeling module constructs a patient postoperative metabolic state model by using the data and evaluates the patient postoperative metabolic state model, the multi-objective optimization decision module calculates and generates an optimal nutrition scheme through a multi-level objective function based on an evaluation result, and the precise nutrition formula generation module generates a detailed nutrition formula and infusion parameters according to the optimal nutrition scheme. The complication early warning and feedback module calculates complication risk levels, sends early warning information and feeds back and adjusts a nutrition scheme according to the collected data and evaluation results, the metabolic state of the patient is evaluated comprehensively and accurately, precise nutrition support and complication early warning are achieved, and the nursing level of the liver, gall and pancreas postoperative patient is improved.

A computer implemented method matching an individual's continuous metabolite monitoring traces with another individual's continuous metabolite monitoring traces begins by identifying a concentration level of a metabolite for a subject. Dividing metabolic states into ranges of concentration levels allows for transforming a concentration level into a symbol from a set of symbols, wherein the symbol represents a category of concentration levels. The method identifies one or more strings of symbols, wherein each string of symbols represents a series of one or more symbols corresponding to a series of transformed concentration levels represented by the symbols. A computer is programmed to determine a lexical distance between a first string from the one or more strings of symbols and a second string, wherein the lexical distance corresponds to a degree of similarity between the first string and the second string. The computer provides a search result for a search query based on the determined lexical distance.

The present invention relates to an in vitro method for predicting the response to immunotherapy treatment of hepatocellular carcinoma in a subject, comprising the following steps: 1) A step of determining the energy metabolic state of a liver tissue sample from a subject, wherein the sample comprises pathological tissue and optionally non-pathological tissue, 2) A step of detecting the presence or absence of energy conversion resulting from a reduction in mitochondrial respiration in the pathological tissue by comparing it with a liver tissue sample of the subject or a non-pathological tissue from a standard non-pathological liver sample, Here: - If mitochondrial respiration is reduced in pathological tissue, the subject is less likely to respond to immunotherapy treatment, and - If mitochondrial respiration is not reduced in the pathological tissue, the subject is highly likely to respond to immunotherapy treatment.

The application discloses a metabolic equivalent driven endurance training intensity gradient generation system and method thereof, and belongs to the technical field of intelligent sports training. The system comprises a non-contact physiological signal acquisition module, a multi-dimensional metabolic state modeling module, a floating threshold generation module, a multi-channel feedback regulation module and an edge abnormality filtering module. Respiratory and heart rate and other multi-dimensional physiological parameters are collected through the fusion of a millimeter wave radar and a PPG sensor. A three-dimensional metabolic state dynamic evaluation model is constructed based on a GRU network, and real-time MET values are output. Intensity adjustment threshold values are adaptively generated according to MET deviation. The exercise intensity is cooperatively regulated through the tactile feedback of intelligent running shoes and the slope adjustment of a treadmill. Abnormal data are filtered at the edge by using a LOF algorithm. The application solves the problems of single physiological signal dimension, static metabolic state evaluation and abnormal data interference in the prior art, and realizes the precise real-time regulation of endurance training intensity.

The application discloses application of a Fructus Mume pill in preparation of a medicine for treating diabetic encephalopathy, and finds that there is a clear correlation between the Fructus Mume pill and the diabetic encephalopathy. Research results show that the Fructus Mume pill can improve the abnormal metabolic state of a diabetic model mouse, reduce learning and memory dysfunction and cognitive impairment under a diabetic state, and has a good prevention and treatment effect on the diabetic encephalopathy. The application clearly defines the pharmacological effect of the Fructus Mume pill in preventing and treating the diabetic encephalopathy and a possible action mechanism, and provides an experimental basis for TCM intervention on the diabetic encephalopathy. The application provides a new train of thought for research and development of a medicine related to the diabetic encephalopathy, and has a good application prospect.

The invention discloses an aesthetic and plastic vulnerability detection method based on dynamic and static analysis, and relates to the technical field of medical cosmetology, and the method comprises the following steps: constructing a biological energy conversion model based on patient cell mitochondria, converting a steady state value into a gRNA sequence of light-operated CRISPR by encoding energy, delivering the gRNA sequence to a target tissue, and generating an anchoring site; on the basis of the anchoring points, a metabolic oscillation spectrum of a preoperative tissue area of the patient is collected in real time, a dynamic risk coefficient of operation energy equipment is calculated by adopting a quantum Monte Carlo algorithm, and a risk gradient instruction matrix is generated; according to the risk gradient instruction matrix, high-precision optical detection is carried out in combination with an anchoring point, metabolic activity indexes of an operation area are collected according to a dynamic regulation threshold value, and meanwhile, signal response characteristics of a biomarker are captured; according to the method, quantization migration analysis is carried out by utilizing metabolic activity indexes and a biological energy conversion model, and seamless mapping from a microscopic biological metabolic state to macroscopic equipment control is realized.

The disclosure provides, in various embodiments, systems, devices and methods relating to ex-vivo organ care. In certain embodiments, the disclosure relates to maintaining an organ ex-vivo at near-physiologic conditions. The present application describes, for example, a method for using lactate measurement in the arterial and the venous blood lines of the Organ Care System Heart perfusion device to evaluate, for example, the: 1) overall perfusion status of an isolated heart; 2) metabolic status of an isolated heart; and 3) overall vascular patency of an isolated donor heart. This aspect of the present disclosure may use, for example, the property of myocardial cell's unique ability to produce / generate lactate when they are starved for oxygen and metabolize / utilize lactate for energy production when they are well perfused with oxygen.

Systems and methods are provided for reconciling untrusted data of a subject using trusted data pertaining to the subject. Systems and methods are directed to evaluating differences in predicted data with respect to corresponding received data. Systems and methods estimate metabolic states from a combination of trusted and untrusted metabolic inputs, along with optionally using a personalized mathematical model with parameter optimization. Systems and methods provide for reconciled untrusted inputs with their measured impact of the glycemic signals that is consistent with a metabolic model. Estimation of future metabolic states for decision support and automated insulin dosing is enabled. Replay of scenarios with estimated or reconciled data is also provided.

A patient health management platform accesses a metabolic profile for a patient and biosignals recorded for the patient during a current time period comprising sensor data and / or lab test data collected for the patient. The platform receives patient data recorded during the current time period comprising food items consumed, medications taken, and symptoms experienced by the patient. The platform implements a machine-learned metabolic model to determine a metabolic state of the patient at a conclusion of the current time period by comparing a true representation of the metabolic state and a prediction of the metabolic state. The true representation and the prediction are determined based on the recorded biosignals and the recorded patient data, respectively. The platform generates a patient-specific treatment recommendation outlining instructions for the patient to improve their metabolic state and provides the patient-specific treatment recommendation to the patient device for display to the patient.

Techniques for predicting an amount of at least one biomaterial produced or consumed by a biological system in a bioreactor are provided. Process conditions and metabolite concentrations are measured for the biological system as a function of time. Metabolic rates for the biological system, including specific consumption rates of metabolites and specific production rates of metabolites are determined. The process conditions and the metabolic rates are provided to a hybrid system model configured to predict production of the biomaterial. The hybrid system model includes a kinetic growth model configured to estimate cell growth as a function of time and a metabolic condition model based on metabolite specific consumption or secretion rates and select process conditions, wherein the metabolic condition model is configured to classify the biological system into a metabolic state. An amount of the biomaterial based on the hybrid system model is predicted.

The invention relates to the technical field of neonatal inherited metabolic disease screening, and discloses a neonatal inherited metabolic disease screening auxiliary system. The system comprises a multi-source information acquisition module, an information standardization module, a dynamic metabolism image construction module, an anomaly detection and analysis module and a screening management optimization module. The system integrates blood metabolites, gene variation, clinical signs and other multi-source information of newborns, constructs a metabolic function image showing dynamic changes and interaction relations of the metabolites, recognizes metabolic abnormality areas and development situations according to the metabolic function image, and generates a personalized screening management plan. Metabolic network visualization analysis is realized through a dynamic image, and an anomaly detection algorithm is continuously optimized by utilizing planned execution feedback data. According to the system, the trend evaluation of the metabolic state and the self-adaptive iteration of the screening strategy are realized, and the screening accuracy and the management individualization level are improved.

The invention relates to associated faecalis and application thereof, the associated faecalis is preserved in Guangdong Microbial Culture Collection Center on November 10, 2025, and the preservation number is GDMCC No: 67255. The strain is high in self-aggregation capability, beneficial to adhesion to intestinal tracts and high in customization capability; the strain shows a good safety characteristic and has relatively strong gastrointestinal tract environment adaptability; the strain has remarkable antioxidant activity; the strain can generate gamma-aminobutyric acid, is helpful for improving the metabolic state of a host and regulating the neurological function, and has the probiotic effects of regulating lipid, resisting inflammation and improving the metabolic state of the host, namely improving sleep; besides, the bile salt hydrolase of the strain is remarkable in activity, contributes to bile acid metabolism and promotion of cholesterol excretion, has the effects of reducing and regulating blood fat, and can improve obesity, hyperglycemia, hyperlipidemia and non-alcoholic fatty liver disease.

The invention discloses an ergothioneine trimethylamine lyase mutant and application of the ergothioneine trimethylamine lyase mutant in detection of histidine betaine in saliva. L-histidine betaine is catalyzed by ergothioneine trimethylamine lyase to be hydrolyzed into urocanic acid, the light absorption value of the urocanic acid at 290 nm is detected by a colorimetric method, and the content of L-histidine betaine in saliva can be determined. The method is high in sensitivity, and detection of 12.5-100 mg / L histidine betaine in a saliva sample can be completed within 1.5 hours. The method is simple and convenient to operate and can be used for quickly judging the metabolic state of human ergothioneine.

The application discloses a method for predicting different metabolic states of cells in cancer and metabolic characteristic subtypes of the cells based on a metabolite-protein interaction network, and the method comprises the following steps: (1) identifying the classification and metabolic state of the cells: preprocessing data, filtering low-quality cells; performing twice principal component analysis according to key genes; performing twice dimension reduction clustering on the cells respectively; (2) predicting metabolic characteristic subtypes of a queue according to the proportion of different metabolic states of cells in the sample. The method can identify the metabolic state of the cells and metabolic subtypes, and provides a new perspective for cancer research.

The invention belongs to the technical field of biomedical detection, and particularly discloses a nerve injury early warning method and system for abnormal metabolism of iron ions, and the method comprises the steps: synchronously obtaining the steady-state real-time dynamic data of the iron ions and the multi-dimensional biomarker data of the autophagy activity of ferritin; a data basis for comprehensively reflecting the iron metabolism state is constructed; the complex coupling relation between the iron ion steady state and the ferritin autophagy is deeply analyzed through an iron metabolism abnormality coupling analysis model, a nonlinear pathological mode under the synergistic effect of the iron ion steady state and the ferritin autophagy is disclosed, and the accuracy and reliability of early warning decision making are improved; by analyzing the specific mode of iron ion metabolism abnormal state coding, identifying key driving factors causing risks, combining with the early warning level of nerve injury and matching with an individualized intervention scheme, closed-loop design from early warning to accurate intervention is realized, operable guidance is provided for clinical practice, and the method is suitable for popularization and application. And conversion from passive treatment to active defense is realized.

A device for detecting metabolic states in the eye comprises a frame (10) for wearing the device on the head of a human or animal and a light emission and evaluation unit (20). The frame (10) has a holder (11) for holding the light emission and evaluation unit (20). The light emission and evaluation unit (20) is configured to emit light to excite molecules that are to be detected in the tear film (30) of the eye (2). The light emission and evaluation unit (20) is configured to generate an output signal depending on the detection of interference from a portion of the light reflected back from the eye (2) to the light emission and evaluation unit (20).

This invention relates to an ex vivo method for predicting the response to immunotherapy for hepatocellular carcinoma in a subject, the method comprising the steps of: 1) determining the energy metabolic state of a liver tissue sample from the subject, the sample comprising pathological tissue and optionally non-pathological tissue; 2) detecting the presence or absence of energy transitions consisting of reduced mitochondrial respiration in the pathological tissue compared to non-pathological tissue from the subject's liver tissue sample or non-pathological tissue from a standard non-pathological liver sample, wherein: - if mitochondrial respiration is reduced in the pathological tissue, the subject is unlikely to respond to immunotherapy; - if mitochondrial respiration is not reduced in the pathological tissue, the subject is likely to respond to immunotherapy.

To provide a toilet system which is highly convenient in daily life.SOLUTION: A toilet device includes a toilet seat on which a user is seated, a skin gas sensor provided on the toilet seat and configured to detect skin gas released from skin of the user seated on the toilet seat, a controller configured to estimate a metabolic state or a fatigue state of the user based on a detection result of the skin gas sensor, and a notifier configured to notify an estimation result of the controller. The skin gas sensor is provided in the hollow portion to be positioned lower than the upper surface of the seating part.SELECTED DRAWING: Figure 4

The invention relates to the technical field of oral implantation guidance, and provides a digital auxiliary positioning device and method for accurate positioning of false teeth. The method comprises the following steps: acquiring bone structure data and soft tissue data of an oral cavity of a patient and physiological data of the patient to form oral cavity internal structure data; performing segmentation processing on the oral cavity internal structure data through a segmentation model to obtain a gingival tooth boundary feature model in the oral cavity of the patient; on the basis of the oral cavity internal structure data, through a prediction sub-model matched with the metabolic state of the patient in a multi-modal time sequence prediction network, predicting the positioning offset of the patient according with the metabolic state change condition of the patient in a future preset duration; and based on the positioning offset, optimizing the spatial relationship between the false tooth in the gingival tooth boundary feature model and the surrounding oral cavity environment, and outputting false tooth positioning auxiliary information based on the gingival tooth boundary feature model to serve as a positioning reference for making a false tooth model by the oral cavity model printer, thereby improving the positioning accuracy and long-term stability.

A patient health management platform accesses a metabolic profile for a patient and biosignals recorded for the patient during a current time period comprising sensor data and / or lab test data collected for the patient. The platform encodes the biosignals into a vector representation and inputs the vector representation into a patient-specific metabolic model to determine a metabolic state of the patient at a conclusion of the current time period. The patient-specific metabolic model comprises a set of parameter values determined based on labels assigned to the previous metabolic states and a function representing one or more effects of the plurality of biosignals of the personalized metabolic profile. The platform compares the determined metabolic state of the patient to a threshold metabolic state representing a target metabolism. The platform generates a patient-specific treatment recommendation outlining instructions for the patient to improve the determined metabolic state to the functional metabolic state.

The application discloses an intelligent first-aid evaluation system for fall injury of the elderly, which comprises a data acquisition module for acquiring fall impact parameters, bone metabolism markers, bone density historical data and patient clinical characteristics; a joint feature space construction module for generating a mechanical impact feature vector, a bone metabolism state feature vector and a six-dimensional cross-coupling feature, which are spliced into a joint feature space after being weighted by part-specific conditional features; a probability prediction module adopting a multi-task integrated learning model composed of a shared bottom layer and five part-specific task-specific layers to output the probability of occult fracture of each part; a risk stratification module for dividing into four risk grades according to a preset threshold; and an image examination recommendation module for generating a differentiated image examination strategy. Through cross-fusion of mechanical parameters and bone metabolism data, the problems of long-term separation of the two types of data, lack of an acute phase prediction model and lack of part-specific evaluation in the prior art are solved, and early quantitative prediction of occult fracture after falling and accurate image examination guidance are realized.

The invention relates to the technical field of lung function evaluation, in particular to an atomization image analysis method for lung ventilation function evaluation. The method comprises the following steps: firstly, acquiring lung atomization images under various concentrations by changing the concentration of aerosol; based on image block level analysis, the lung is divided into different functional regions (such as lung lobe and airway regions), particle distribution difference characteristics of different image blocks are compared to quantify deposition indexes, and regional ventilation uniformity is reflected; sub-regions are further divided in combination with density clustering, the number change of atomized particles is analyzed across time points, and a metabolic rate index is calculated to represent local metabolic activity; and finally fusing the deposition index and the metabolic rate index to generate a ventilation obstruction evaluation value. According to the method, through space-time sequence multi-parameter coupling, the breathing mode and individual difference interference are effectively reduced, the ventilation function and the metabolism state are synchronously analyzed, a quantitative basis is provided for pulmonary ventilation disorder analysis, and evaluation comprehensiveness and clinical decision accuracy are remarkably improved.

The invention discloses a microwave high-energy cytometer, which belongs to the technical field of microwave high-energy rehabilitation equipment, and comprises a box body I and a box body II, and the box body I is fixedly connected with the box body II. Through the synergistic effect of multiple chips and the terahertz energy light wave instrument, inert and dormant cells of a human body can be activated, damaged cells and visceral organ functions are repaired, channels and collaterals and lymph clogging are dredged, and microcirculation and metabolism states are improved. The traditional Chinese medicine composition can specifically expel cold and clear damp, remove thrombus, eliminate edema, relieve inflammation pain such as arthritis and pain in neck, shoulders, waist and legs, regulate intestines and stomach and endocrine, assist in reducing weight, reduce blood fat and blood sugar, improve skin problems such as color spots and whelks, improve immunity and yang qi, achieve softening and knotting, synchronously meet the needs of multiple people for physical therapy, give consideration to deep conditioning and convenience, and is high in penetration depth and free of toxic and side effects. The problems of shallow penetration, non-uniform effect, application limitation and the like of traditional physical therapy are solved, and comprehensive and efficient non-invasive health care experience is provided for sub-health people.

The method for predicting the severe brain injury probability of the newborn is used for predicting the severe brain injury probability of a selective fetal growth limited double-fetal newborn, and the selective fetal growth limited double-fetal newborn comprises a to-be-detected large fetus and a to-be-detected small fetus. The method comprises the following steps: acquiring a meconium sample of a large fetus to be detected and a meconium sample of a small fetus to be detected; the method comprises the following steps: pretreating and detecting a meconium sample of a large fetus to be detected and a meconium sample of a small fetus to be detected to obtain the concentration of marker metabolites in the meconium sample to be detected; according to the concentration of the marker metabolite of the big fetus and the concentration of the marker metabolite of the small fetus, the probability of severe brain injury of the big fetus and the small fetus is predicted; wherein the big fetus marker metabolite is different from the small fetus marker metabolite; according to the embodiment of the invention, the characteristic of recording the intrauterine metabolism state of the fetus in the whole gestation period by virtue of meconium is utilized, and the severe brain injury risk can be predicted in the early stage after birth. Different specific markers are screened for fetuses of different sizes, a prediction model is established, and the prediction result is accurate.

The present application relates to the technical field of medical diagnosis system, specifically to a kidney stone composition intelligent identification and individualized prevention and treatment scheme generation system, which comprises a stone type identification module, a composition correlation determination module, an acid-base state division module, a metabolic behavior ordering module and a path scheme construction module.In the present application, the linkage characteristics of the local structure and energy state of the stone surface are extracted through the corresponding relationship of the image texture and the spectral peak position in space, the continuous form of the composition change on the time axis is captured through the period comparison mode of the consistent trend direction, the structural change of the metabolic state in the stage is drawn through the collaborative control of the multiple biochemical trends of lactic acid and bicarbonate in the unified time scale, the mode track of the metabolic behavior is tracked through the difference of the behavior direction change frequency in the period, the path sequence of the metabolic correlation behavior is constructed through the step-by-step promotion of the trend relationship in the period, and the dynamic linkage recognition ability between the data and the stage adaptation ability of the individual intervention path are enhanced.

The application provides a Bi-BDO fermentation pH dissolved oxygen dynamic optimization method based on online Raman spectrum, belongs to the technical field of biological fermentation process control, and aims to solve the problems of fermentation control lag, inability to perceive the real metabolic state of cells, process instability and low efficiency in the prior art. The method realizes real-time acquisition of the concentrations of target products BDO, acetic acid, ethanol and other key by-products in the fermentation broth through online Raman spectrum. A metabolic stress index is creatively proposed and constructed. The index is obtained by weighting operation on the instantaneous generation rates of the by-products and target products, and is used for real-time and quantitative characterization of the intrinsic metabolic stress level of cells. The method does not take conventional parameters as the target, but takes maintaining the metabolic stress index in the preset optimal stable interval as the core control strategy. The application realizes the transformation from passive response to active foresight in the fermentation process, and significantly improves the yield, stability and batch-to-batch repeatability of Bi-BDO production.