1199 results about "Dieting" patented technology

The invention discloses a chronic disease patient personalized diet and exercise guidance system and method, and relates to the technical field of medical health information, and the system comprises a data sensing module which continuously collects the dynamic physiological data, behavior data and environment variable data of a patient through an intelligent sensing device, the dynamic physiological data comprises a heart rate time sequence, a step number time sequence and a blood glucose concentration time sequence monitored by the wearable device, and the behavior data comprises a medication operation record with a timestamp and a patient's daily symptom self-grading number. According to the personalized diet and exercise guidance system and method for the chronic disease patient, the time synchronization precision of multi-source data is effectively improved, the accuracy of medication compliance monitoring and physiological index correlation analysis is ensured, and by establishing the dynamic correlation model of the environment temperature and the human body metabolic rate, the accuracy of medication compliance monitoring and physiological index correlation analysis is improved. The timeliness and safety of clinical intervention are improved, and powerful support is provided for health management of chronic disease patients.

The invention provides a time sequence fusion and health state prediction method and system for multi-dimensional physiological data, and relates to the technical field of electrical digital data processing.The method includes the steps that high-precision sensing equipment and a parameter calibration model are adopted to calibrate data, time synchronization and error compensation are achieved through a weighted fusion algorithm, and the accuracy of physiological parameters is improved; meanwhile, a fatigue index and a pressure index are corrected in real time by using a closed-loop feedback mechanism, and a comprehensive state index is generated based on an evaluation result for further analysis and prediction; the change trend of the comprehensive state index is predicted through a machine learning technology, and a targeted dynamic rehabilitation scheme including training intensity optimization, diet adjustment, rest cycle planning and the like is provided in combination with physiological data of the user; and a timing feedback mechanism is established, so that the user can obtain health state change and adjustment suggestions in real time, thereby improving scientificity and timeliness of a rehabilitation scheme, remarkably optimizing the rehabilitation effect and efficiency, and realizing intelligent health management at the same time.

A method for using a local large language model (LLM) within a user's secure computing environment is disclosed. The LLM operates behind a firewall to prevent transmission of sensitive data, and utilizes an encrypted vector database and artificial intelligence techniques for content retrieval, response generation, and task anticipation. This system can be used on mobile, wearable, vehicle, or IoT devices and offers various services such as health monitoring, financial advice, automated communications handling, and personalized daily activity optimization. It also has the ability to detect fraud, fine-tune responses using augmented user data, assist in negotiations, identify personal interests, and provide health recommendations based on dietary and physical activity data.

A method for using a local large language model (LLM) within a user's secure computing environment is disclosed. The LLM operates behind a firewall to prevent transmission of sensitive data, and utilizes an encrypted vector database and artificial intelligence techniques for content retrieval, response generation, and task anticipation. This system can be used on mobile, wearable, vehicle, or IoT devices and offers various services such as health monitoring, financial advice, automated communications handling, and personalized daily activity optimization. It also has the ability to detect fraud, fine-tune responses using augmented user data, assist in negotiations, identify personal interests, and provide health recommendations based on dietary and physical activity data.

The invention discloses a dynamic blood glucose monitoring and intelligent pump speed adjusting system and method, and relates to the technical field of biomedical engineering.The dynamic blood glucose monitoring and intelligent pump speed adjusting method comprises the steps that precise monitoring is conducted through a multi-mode sensing module, an enzyme electrode sensor adopts an anti-interference coating, a Raman spectrum dynamic correction algorithm is combined, and motion artifacts and temperature drift are restrained; the metabolic feature fusion calibration module is integrated with a time convolution network, time sequence modeling is carried out on diet, exercise and historical blood glucose data, an individualized metabolic parameter database is constructed, and self-adaptive signal drift compensation is achieved; the self-adaptive pump control module innovatively designs a double-layer fuzzy PID controller, a base layer generates an infusion rate according to a real-time blood glucose state and insulin activity, an optimization layer introduces an LSTM metabolism prediction model, and the slope of an infusion curve is dynamically adjusted in combination with future behavior pre-judgment; in the edge-cloud collaborative architecture, a lightweight TCN model is locally deployed to guarantee real-time control, and a cloud end optimizes a global digital twinborn model through federal learning and generates a multi-dimensional metabolic risk early warning report.

The invention discloses a chronic disease intervention safety detection system and method based on large model multi-agent cooperation, and relates to the technical field of natural language processing and multi-agent cooperation in the medical health field. A standardized interface and an adaptive cleaning algorithm are adopted to realize data desensitization, missing value filling and format unification, and a dynamically updated patient health portrait is constructed; complex tasks are decomposed based on a chain reasoning technology, special tools such as a drug interaction detection tool and a nutrition gap calculation engine are developed, and a clinical knowledge base is integrated for parallel analysis; suggestion conflicts are eliminated through a multi-agent debate mechanism, the priority is calculated in combination with a weight rule, manual auditing is triggered to process low-confidence disputes, and finally a structured health report containing medication adjustment, diet optimization and behavior intervention is generated. The limitation of a traditional method in data integration, cross-domain reasoning and conflict resolution is solved.

The utility model discloses an intelligent straw which is characterized in that an induction electrode is coated and attached in the pipe wall of a hollow pipe along the length direction of the hollow pipe to collect the data of the amount of liquid passing through the hollow pipe, the hollow pipe can be made of food-grade materials such as silica gel and food-grade plastics, and the intelligent straw has the function of digitizing drinking water. The system can transmit data to a mobile phone or a cloud end, carries out health analysis through the data, achieves recording reminding, affects healthy diet of young people from behaviors, serves as an intelligent terminal of the Internet of Things, builds a digital connection between a merchant and a user, and further optimizes customer services better.

The invention discloses a hospital obese patient intelligent weight loss dynamic matching intervention method and decision making system based on multi-modal data fusion, and relates to the field of medical health, and the method comprises the following steps: S1, carrying out the real-time collection and fusion of multi-modal data; s2, dynamic metabolism modeling and plateau period breakthrough; s3, generating a hierarchical intervention strategy; s4, performing psychological-physiological linkage intervention; and S5, performing real-time safety control and feedback optimization. By collecting multi-dimensional data, constructing the model, accurately predicting the metabolic rate, the metabolic plateau period and the sudden eating tendency, dynamically adjusting the exercise intensity and the diet scheme according to the conditions of different patients, triggering a low-intensity exercise mode for the obese patients with cardiac insufficiency and calibrating diet, ensuring the exercise safety, and improving the exercise efficiency. Operation suggestions are generated on the basis of the standard, precise preoperative evaluation is conducted, postoperative rehabilitation is optimized in combination with nerve stimulation data, dangerous postures are monitored, the sport injury risk is reduced, and personalized, safe and efficient intelligent weight reduction intervention for obese patients is achieved.

The invention discloses a personalized medical health service recommendation system based on big data analysis, and belongs to the technical field of medical health services. The synchronization module is used for generating a standardized data stream according to dynamic blood glucose monitoring data and an original heart rate variability signal; the analysis module is used for generating a diet time sequence data stream according to the intake event timestamp; the blood glucose feature extraction module is used for extracting data from the standardized data stream; the insulin sensitivity analysis module is used for generating an insulin sensitivity factor matrix; the nutrition analysis module is used for generating a carbohydrate equivalent time distribution vector and a dietary fiber intake intensity value; the feature fusion module is used for generating a fusion feature vector according to the blood glucose drift trend coefficient, the insulin sensitive factor matrix and the carbohydrate equivalent time distribution vector; the risk assessment module is used for generating a hypoglycemia risk probability value according to the fusion feature vector; and the recommendation generation module is used for generating a personalized service recommendation set according to the hypoglycemia risk probability value.

According to the clinical nutrition intelligent management system and method disclosed by the invention, nutrition status evaluation is carried out by applying a nutrition comprehensive evaluation formula, the standardization and objectivity of evaluation are greatly improved, the formula quantifies multiple key factors and gives weights, different evaluators carry out calculation based on the same information and formula, and the consistency of evaluation results is ensured; besides, the comprehensive nutrition evaluation formula comprehensively considers the body mass index, the disease-related nutrition influence coefficient, the nutrition-related index comprehensive score, the diet health degree score and other aspects adjusted by age and gender, accurately reflects the actual nutrition condition of the patient, and solves the problem of insufficient accuracy of traditional evaluation. And the nutrition plan generation module can customize nutrition plans for patients according to the nutrition comprehensive evaluation indexes in combination with a preset rule base, so that individual requirements of different patients are fully met, and a scientific, accurate and personalized solution is provided for clinical nutrition management.

The invention discloses a system and a method for intelligently monitoring blood sugar of a patient before and after diet based on food components, and belongs to the technical field of blood sugar monitoring, and the system comprises a food component quantification module which is used for converting a food image or description into accurate macro nutrient and micronutrient data; the multi-modal data fusion module is used for preprocessing and fusing the multi-modal data of the patient; the patient blood sugar prediction module is used for constructing a patient blood sugar prediction model to analyze the multi-modal fusion data of the patient and predicting the blood sugar of the patient; and the difference analysis optimization module is used for comparing actual blood glucose with predicted blood glucose after meal and analyzing difference reasons. The problems that blood glucose of a patient before and after eating cannot be intelligently monitored, and accurate quantification and prediction of the relation between diet and blood glucose cannot be achieved are solved. The system can intelligently monitor the blood glucose of the patient before and after eating, can help the diabetic to realize accurate quantification and prediction of the relationship between diet and blood glucose, and can effectively control the blood glucose and reduce the risk of complications.

The embodiment of the invention discloses a skeleton health dynamic tracking and intervention method and system based on movement and nutrition. The method comprises the following steps: acquiring gait information, bone metabolite information and bone state measurement parameters of a target user by adopting wearable equipment; processing the gait information, the bone metabolite information and the bone state measurement parameters based on an artificial intelligence (AI) model to obtain bone state prediction parameters; according to the bone state prediction parameter and the health data of the target user, performing bone health state evaluation of the target user to obtain a health state prediction parameter; the health state prediction parameters comprise a bone health state instant evaluation index and bone health dynamic trend data; generating a targeted exercise plan and a diet plan according to the health state prediction parameters; wherein the target motion planning is used for guiding the motion of the target user; the diet planning is used for guiding the diet of the target user.

The invention relates to a diabetes exercise rehabilitation and diet collaborative management method, device and equipment and a medium. The method comprises the following steps: acquiring individual feature data, physiological data and daily behavior data of a diabetic patient, and constructing a personalized portrait of a user; generating an exercise plan and a diet plan according to a set period based on the personalized portrait of the user; in response to the obtained real-time user data, dynamically correcting the exercise plan and the diet plan to obtain an exercise and diet collaborative plan; the real-time user data comprises blood glucose data, diet intake data and exercise data; the exercise and diet collaborative plan comprises exercise items arranged based on time points and diet arrangement; generating a corresponding push instruction according to the time point; the pushing instruction is used for indicating to push corresponding exercise items or diet arrangements to the terminal of the diabetic patient. By adopting the method, the problem of inadaptation caused by a rigid fixed plan can be avoided by an exercise-diet collaborative intervention mechanism, and the management response capability of external variable change is improved.

The invention discloses a gout diet education system based on multi-modal interaction and an intelligent teaching aid. The system comprises a registration module, an intelligent recommendation module, a multi-modal interaction module, a diet recording module, a health monitoring module and a cloud server. The registration module receives personal information input by a user through intelligent equipment; the intelligent recommendation module generates a preliminary personalized diet scheme based on personal information by using a deep learning algorithm in combination with a medical knowledge base and a gout diet management guide; the multi-modal interaction module displays gout diet education content in a multi-modal mode; the diet recording module records diet data in real time and provides instant feedback according to the diet data and the preliminary scheme; the health monitoring module collects physiological indexes through a wearable sensor and synchronously uploads the physiological indexes and diet data to the cloud server; and the cloud server generates a diet and health association result and transmits the diet and health association result to the intelligent recommendation module to optimize the preliminary scheme. The system can provide quasi diet management support for gout patients.

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 provides a hypoglycemic peptide which is prepared by taking bovine whey protein as a raw material and is stable in gastrointestinal digestion and absorption. In an in-vitro cell experiment, the peptide fragment can improve the uptake of insulin-resistant HepG2 hepatocytes and synthesize glycogen by using glucose, can promote intestinal endocrine cells NCI-H716 to secrete GLP-1, has a certain synergistic effect, and can further play the effects of promoting GLP-1 secretion and activating a GLP-1 receptor through combined use. An insulin resistance mouse model is constructed by utilizing high-fat diet, and the peptide fragment is adopted for intervention, so that the hypoglycemic peptide is further proved to have obvious effects on losing weight, reducing lipid accumulation and assisting in reducing blood fat, and meanwhile, the hypoglycemic peptide can be used for improving insulin resistance related symptoms. The milk peptide provided by the invention has gastrointestinal digestion stability and hypoglycemic activity, can be used as a functional milk base material for developing food, medicines or health care products with the effect of regulating blood sugar, and is wide in application prospect.

The invention relates to an AI personalized nutrition evaluation and guidance method based on individual continuous diet data. The AI personalized nutrition evaluation and guidance method comprises the following steps: (1) calculating individual single meal food and nutrient intake; individual health indexes are collected, the individual daily energy demand amount is calculated, and the daily food and nutrient demand amount is determined; (2) carrying out instant personalized nutrition evaluation on food and nutrients ingested by an individual in a single meal according to a domestic public recommendation standard; (3) on the basis of individual nutrition and health data continuously recorded in the longitudinal direction of time, establishing a personalized nutrition intake-health model taking an individual as a unit, and carrying out personalized nutrition evaluation and health risk prompting; and (4) simulating the idea of nutrition guidance of professionals to create an AI nutrition guidance algorithm, and generating AI guidance. By adopting the AI personalized nutrition evaluation and guidance method based on the individual continuous diet data, a sustainable AI-assisted diet self-management solution suitable for daily life scenes is effectively provided.

The invention relates to a weight loss intervention method and device for chronic renal failure and obesity patients based on an individualized prescription. The method comprises the following steps: constructing a multi-modal dynamic time sequence feature vector of a patient; identifying and quantifying potential causal effects of different weight loss intervention measures on physiological outcomes of renal functions, electrolyte balance, anemia states, bone mineral metabolism and weight indexes of the CKD patient according to a dual robust estimator; dynamically constructing a weight loss intervention measure causal model according to the potential causal effect of the physiological outcome of each patient and the physiological and pathological background; and inputting the multi-modal dynamic time sequence feature vector of the patient into a weight loss intervention measure causal model, and generating a daily diet scheme, an exercise scheme and corresponding high-confidence risk early warning and causal explanation of the patient. The method overcomes the limitation that the traditional method only pays attention to correlation and cannot clearly determine the intervention effect, ensures that the causal atlas and the intervention scheme are optimized according to the real-time change state of the patient, and realizes a real dynamic prescription.

The invention relates to the technical field of behavior feature recognition, in particular to a beef cattle oestrus state monitoring method based on dynamic gait analysis. According to the method, multi-source data acquisition, such as dynamic gait video and body temperature data, video preprocessing, such as frame extraction, denoising, abnormal frame recognition and restoration, target tracking, dynamic gait characteristic parameter extraction, such as step length, step frequency, step speed, joint angle change and body gravity center offset, and life data acquisition, such as diet, body weight change and drinking water. A large oestrus monitoring and recognition model integrating attitude analysis, behavior analysis, living state analysis and an integration module is constructed, and after training and iterative optimization, accurate judgment of oestrus, non-oestrus and wig oestrus states of beef cattle is achieved in combination with ear tag identity recognition. By monitoring the dynamic gaits and behavior modes of the beef cattle and combining daily life data of the beef cattle, the problem of misjudgment caused by wig oestrus is greatly avoided, and the monitoring accuracy is improved.

The invention discloses a postoperative monitoring system and method for a metabolic weight loss surgery patient, and the system comprises a multi-source data collection module which is used for obtaining physiological parameters, behavior data and environment data of the patient in real time, the physiological parameters comprise body weight, blood sugar and body composition indexes, and the behavior data comprise exercise amount and diet records; the environment data comprises temperature, humidity and geographic position; the central processing platform is connected with the multi-source data acquisition module and comprises a data fusion unit for performing space-time alignment and dimension reduction processing on the multi-source heterogeneous data by adopting a feature level fusion algorithm; the dynamic risk assessment unit is used for constructing a patient personalized metabolism model based on the fused data, and dynamically generating nutrition loss and complication recurrence risk indexes through a machine learning algorithm; and the intelligent early warning module triggers a graded early warning signal according to the risk index, generates a personalized intervention scheme and pushes the personalized intervention scheme to the doctor-patient terminal.

Systems, devices and methods are provided for determining a medication dose for a patient or user. The dose determination can account for recent and / or historical analyte levels of the patient or user. The dose determination can also take into account other information about the patient or user, such as physiological information, dietary information, activity, and / or behavior. Many different dose determination embodiments are set forth, pertaining to a wide array of different aspects of the system or environment in which the embodiments can be implemented.

The invention relates to the technical field of artificial intelligence, and discloses a system of a nutrition recipe recommendation system based on artificial intelligence in chronic disease intervention management and an application method. Comprising a data acquisition module, a data preprocessing and feature engineering module, a knowledge base management module, a personalized nutritional requirement modeling module, a recipe generation and optimization module, a user interface module and a model training and updating module which are in communication connection through a network. According to the method, personalized health data such as physiological indexes, chronic disease characteristics, diet preference, allergy and intolerance information of a user are collected in multiple dimensions, a nonlinear relation between the characteristics of the user and nutritional requirements is deeply mined in combination with a deep learning model, and an accurate personalized nutritional requirement model is generated according to specific illness conditions and body indexes of different chronic disease patients; therefore, recipe recommendation conforming to individual differences is provided, and the risk of aggravating the illness state due to improper diet is reduced.

The invention belongs to the field of medicines, and discloses application of pyroglutamic acid in preparation of products for inhibiting fat deposition. The invention has the following advantages: 1, obesity induced by high fat diet is prevented; 2, pyroglutamic acid is a natural amino acid derivative, widely exists in animal and plant bodies, and has good biological safety; meanwhile, the invention further discloses a product for inhibiting fat deposition.

The invention relates to the technical field of biotechnology and gene function and application, and provides application of SNHG8 in preparation of drugs for preventing and treating non-alcoholic fatty liver diseases. The medicine is used for preventing and treating the non-alcoholic fatty liver disease by promoting SNHG8 gene expression. The SNHG8 is applied to preparation of the medicine for preventing and treating the non-alcoholic fatty liver disease, the medicine can effectively reduce the content of triglyceride in the liver by promoting SNHG8 gene expression, liver lipid accumulation increase and lipid metabolism related protein expression up-regulation induced by high-fat and high-cholesterol diet are relieved, and therefore the non-alcoholic fatty liver disease is prevented, treated or relieved. The purpose of preventing and treating the non-alcoholic fatty liver disease is achieved.

The invention belongs to the technical field of medical treatment, and discloses a chronic fatigue syndrome screening and diet-exercise intervention method which has the advantages of being high in individuation degree, low in rehabilitation cost, flexible in intervention implementation field, flexible in intervention training time and small in space requirement. And the compliance of the patient in completing the exercise and diet combined intervention rehabilitation task is greatly improved. The method can effectively cope with patient low compliance challenges caused by infrastructure deficiency and motivation disorder, significantly improves training enthusiasm and participation willingness of CFS patients, has significant effect on promoting rehabilitation of the CFS patients, enables the patients to obtain efficient medical services without going to medical rehabilitation institutions personally, and has good application prospects. Therefore, the current situation that basic medical resources are extremely deficient is relieved to a certain extent, and favorable conditions are created for implementation and popularization of exercise and diet combined intervention training.

The application discloses a Weizmannia coagulans with fat-reducing and weight-reducing functions, and belongs to the technical field of microorganisms. The Weizmannia coagulans screened by the application can inhibit the content and activity of fat synthesis enzyme on the basis of reducing blood fat and weight, can relieve liver damage caused by high-fat diet, has excellent acid tolerance, bile salt tolerance and high fat hydrolysis capacity, and is a multifunctional Weizmannia coagulans, and has a wide application prospect in the preparation of fat-reducing, weight-reducing and weight-losing products.

The invention relates to a healthy diet index evaluation method and system based on a diabetic patient. The method comprises the steps that a multi-modal data set of a patient is obtained, the multi-modal data set comprises diet image data, continuous blood glucose monitoring data and medicine use parameters, and mixed food material component analysis processing is conducted on the diet image data to obtain layered nutrition quantification data; performing synergistic effect analysis according to the drug use parameters and the pharmacokinetic model to generate a nutrition absorption correction coefficient; performing time sequence alignment processing on the layered nutrition quantification data and the continuous blood glucose monitoring data, and establishing a blood glucose response prediction model; and generating a diet health assessment report according to the blood glucose response prediction model and the nutrition absorption correction coefficient. According to the method, through the synergistic effect of the multi-modal data, the blood glucose response prediction model and the drug absorption correction coefficient, the diet effect of the diabetic patient can be accurately evaluated, nutrient absorption is optimized, and the scientificity and individuation degree of diet health management of the diabetic patient are effectively improved.

The invention belongs to the field of microorganisms, and provides lactobacillus paracasei Jlus660321 with a function of assisting in reducing blood fat and cholesterol and application of the lactobacillus paracasei Jlus660321, and the preservation number of the lactobacillus paracasei Jlus660321 is CGMCC No. 33962. The lactobacillus paracasei Jlus 660321 has the functions of assisting in lowering blood fat and lowering cholesterol, shows excellent cholesterol lowering performance in a cholesterol degradation experiment, and can degrade 61.60% of cholesterol in the experiment. A hemolysis experiment result is gamma-hemolysis, namely, hemolysis is avoided, and toxic and side effects are small. Rat in-vivo experiments show that the lactobacillus paracasei Jlus 660321 can effectively slow down the increase of body weight, liver weight, liver index, low-density lipoprotein content and triglyceride content caused by high-fat diet, and further show that the lactobacillus paracasei Jlus 660321 has the function of assisting in reducing blood fat and cholesterol; the compound can be used for preparing medicines, nourishment or health care products for assisting in reducing blood fat and / or reducing cholesterol.

Disclosed is a strain of Bifidobacterium longum subsp. longum named dipro-O. The Bifidobacterium longum subsp. longum dipro-O used in the present invention has the ability to overproduce BSH, the ability to reduce cholesterol, and the ability to metabolize tryptophan into indole-3-lactic acid, can effectively reduce body weight, significantly lower insulin resistance levels resulting from high-fat diets, reduce the expression of the inflammatory cytokine TNF-α, significantly lower the levels of total cholesterol (TC) and low-density lipoprotein (LDL) in the blood, and increase the level of high-density lipoprotein (HDL), and can ameliorate disorders of the gut microbiome structure. In addition, the strain can also have an ameliorating effect on other lipid metabolism-related diseases such as hyperlipidemia, thereby providing health interventions for the host's body weight, liver, intestinal health, and blood lipid levels. Moreover, pasteurized dipro-O can also have the effect of regulating lipid metabolism, further extending the range of applications of the strain.

The invention discloses a composition for assisting in reducing blood sugar and blood fat as well as a preparation method and application thereof, and relates to the technical field of functional compositions. The composition comprises highland barley powder and modified inulin, the preparation method of the highland barley powder comprises the following steps: soaking highland barley grains in a weakly alkaline aqueous solution, and sequentially carrying out first pulse microwave treatment, enzyme deactivation treatment and segmented baking treatment; the segmented baking treatment comprises first-stage baking treatment and second-stage intermittent infrared irradiation treatment; the temperature of the first-stage baking treatment is 40-60 DEG C; the temperature of the second-stage intermittent infrared irradiation treatment is 60-80 DEG C, and the emission wavelength is 2.5-4 microns; the preparation method of the modified inulin comprises the following steps: performing acidolysis treatment on inulin in a weakly acidic aqueous solution, and then drying. The highland barley powder and the modified inulin in the embodiment can synergistically improve glycometabolism and lipid metabolism, effectively reduce the body weight, blood sugar, blood fat and the like under high-glucose and / or high-fat diet, and protect and repair the pancreas islet function.