67 results about "Glucose control" patented technology

The invention discloses a training method of a blood glucose control model and a blood glucose control method and system, and belongs to the technical field of blood glucose control. According to the method, a framework combining a blood glucose control model and a reinforcement learning model is constructed; wherein the blood glucose control model is a full-connection neural network with two layers; the number of neurons in the first layer of the network is 3, and an adopted activation function is a linear function; the number of neurons in the second layer of the network is 1, the adopted activation function is a nonlinear activation function, the output value domain of the nonlinear activation function is bounded, the upper bound is a positive number, and the lower bound is a negative number. The blood glucose control model is a model evolved after a classic PID algorithm is improved based on a blood glucose control task, the parameter space of the model comprises the parameter space of the classic PID algorithm, and the model has a wider range, can extract features with higher expression ability, is more adaptive to a reinforcement learning process, and can simply and efficiently realize accurate control of blood glucose.

The present invention provides a method for improving glycemic control in a patient in need thereof, comprising administering to said patient, tirzepatide, or a pharmaceutically acceptable salt thereof, wherein said patient has failed to reach their HbA1c goal using GLP-1 RA treatment. The present invention provides a method for improving weight management in a patient in need thereof, comprising administering to said patient tirzepatide, or a pharmaceutically acceptable salt thereof, wherein said patient has failed to reach their weight management goal using GLP-1 RA treatment.

The invention relates to the field of intelligent medical monitoring, in particular to a diabetic multi-source data real-time analysis method based on a large language model, and the method mainly comprises the steps: continuously collecting multi-source data of a patient from a CGM device, an intelligent watch and a mobile terminal, and enabling the multi-source data to at least comprise blood glucose data, heart rate and input data; constructing a deep learning model comprising four layers of attention mechanisms, inputting the fusion data into the deep learning model, predicting a blood glucose trend within a preset time by using a sliding time window to obtain a blood glucose prediction result, and pushing the blood glucose prediction result to the mobile terminal or the smart watch; and performing reinforcement learning on the large language model based on a deep Q network architecture, and when the blood glucose control time in the blood glucose data is lower than a preset threshold value, performing parameter updating on the large language model. According to the invention, personalized monitoring and intervention effects on the diabetic patient can be improved.

A diabetes management system optimizes glucoregulatory hormone delivery using a connected glucoregulatory hormone delivery system and a computing device with a processor and non-transitory memory. The system receives glucose management data (glucose, insulin delivery, heart rate, or carbohydrate consumption data) from sensors. A digital twin metabolic model is selected and initialized based on the received data. The system simulates diabetes treatment interventions to predict glucose dynamics and determines an optimized glucoregulatory hormone parameter (e.g., insulin dose or increment that minimizes hyperglycemia and hypoglycemia risk). The determined glucoregulatory hormone parameter is transmitted to the connected glucoregulatory hormone delivery system, which may include an automated insulin delivery (AID) system or a connected insulin pen system, for implementation. By integrating real-time physiological data with predictive metabolic modeling, the system enhances glucoregulatory hormone therapy, providing personalized adjustments to improve glucose control.

The invention provides curcumin-nano-selenium modified Chinese chestnut starch with an irregular granular porous network structure, and belongs to the technical field of starch processing. The preparation method comprises the following steps: mixing a sodium selenite solution and a curcumin solution, and reacting under an alkaline condition to obtain a curcumin-nano-selenium solution; carrying out heat-moisture treatment on the starch suspension, and then freeze-drying to obtain heat-treated starch; preparing the heat-treated starch into a suspension 1, mixing the suspension 1 with the curcumin-nano-selenium solution, performing a constant-temperature oscillation reaction under a dark condition, and after the reaction is finished, cooling and drying to obtain the modified starch. According to the invention, a spherical aggregate of natural starch is reconstructed into an irregular granular porous network structure, so that the freeze-thaw stability, retrogradation stability, oxidation resistance and digestion resistance of the starch are remarkably improved. Moreover, based on a mouse experiment result, the modified starch has a good blood sugar control effect.

Provided are a method, system, and computer-readable medium for optimizing glycemic control of a diabetic subject having Type 1 diabetes through co-administration of sodium-glucose cotransporter inhibitors (SGLTi) and insulin. Such co-administration can be effected by, for example, regulating one or more administration reactions in view of analyses of continuous glucose monitoring (CGM) data that can be indicative of at least the potential for one or more glycemic events including hypoglycemia and hyperglycemia. The aforementioned regulation can occur according to a balancing of insulin infusion and provisioning of SGLTi so as to avoid the occurrence of either of such events while, at the same time, not promoting an instance of diabetic ketoacidosis (DKA).

Provided are methods for treating glucose-related metabolic disorders in a subject. In some aspects, the methods comprise enterally administering an effective amount of a beta-glucan oligosaccharide prior to and / or during the subject consuming a glucose source.

The present application relates to the technical field of mRNA vaccine, and specifically discloses a proinsulin mRNA vaccine for protecting the function and quantity of pancreatic beta cells. The vaccine is composed of a lipid nanoparticle (LNP) and an mRNA wrapped by the LNP; the mRNA is an mRNA sequence encoding proinsulin, and all uridines in the mRNA sequence are replaced by N1-methyl pseudouridine. The mRNA vaccine of the present application realizes the dual protection of the quantity and function of pancreatic beta cells, compared with the existing intervention means which only focus on blood glucose control or immune regulation, the present application delays the occurrence process of type 1 diabetes from the root, and provides a new technical scheme and drug selection for the prevention and early intervention of type 1 diabetes.

The invention relates to the technical field of medical informatics, and provides a diabetic diet optimization recommendation system based on deep learning. According to the system, structural feature construction is conducted on blood glucose, diet and life behavior data, blood glucose response structural decoupling, meal anchoring and cross-day stability features are introduced, and fine description of individual postprandial blood glucose dynamic response is achieved; in the blood glucose response prediction process, a local Dirichlet energy constrained deep learning model is introduced to improve the stability and generalization consistency of a prediction result; and a joint distribution density reasoning mechanism is combined to enhance the robust processing capability of missing follow-up visit data. On the basis, an individualized diet optimization recommendation result is generated by introducing a reinforcement learning method, collaborative optimization of blood glucose control, nutrition balance and patient compliance is achieved, and reliable intelligent decision support is provided for diabetes mellitus follow-up visit management.

The application discloses a personalized closed-loop artificial pancreas system, which comprises a detection module (100) for continuously detecting blood glucose values of a patient, an infusion module (102) for infusing insulin into the patient, and a program module (101) for controlling the detection module (100) and the infusion module (102). The program module (101) generates insulin infusion instructions according to the blood glucose values detected by the detection module (100) and controls the infusion module (102) to perform infusion. The program module (101) comprises a user interface. In response to an input of the patient, the program module (101) executes a corresponding meal mode function. The meal mode comprises a high-carbohydrate mode and a normal-carbohydrate meal mode. According to the input of the patient, the program module (101) executes the function of the high-carbohydrate mode or the normal-carbohydrate mode, so as to be applicable to people with different carbohydrate consumption habits, improve the adaptability of the closed-loop artificial pancreas to different people, and enable people with different carbohydrate consumption habits to maintain a satisfactory blood glucose control effect.

The application discloses a breast reconstruction type recommendation system and method based on multi-modal data, relates to the technical field of breast reconstruction type recommendation, and aims to solve the technical problems of traditional operation type recommendation depending on linear superposition evaluation of a single index, being unable to quantize the nonlinear complex mechanism of metabolic and vascular injury, and leading to inaccurate risk evaluation and lack of targeted recommendation, the system comprising a feature calculation and analysis module, wherein the feature calculation and analysis module comprises a clinical information structured unit, a metabolic and vascular injury index calculation module, an image feature unit and a test feature unit. Through the metabolic and vascular injury index calculation module, the nonlinear normalization function, the standardization function, the interactive effect analysis algorithm and the Sigmoid function are integrated, the true risk difference between patients with short disease duration but poor blood glucose control and patients with long disease duration but good blood glucose control is effectively distinguished, the risk evaluation is more in line with the pathophysiological law, and a scientific quantitative basis is provided for operation type selection.

In at least one embodiment, a hemoglobin measuring device may include a plurality of sensors, a display configured to present information, and a computing device in communication with the sensors and display and having a processor and a memory storing instructions executable by the processor. The instructions may include instructions to receive, from the sensors, measurements of one or more forms of glycated hemoglobin in a blood samples, determine a total fetal hemoglobin value in the blood sample by performing a peak area summation of all forms of fetal hemoglobin, subtract the total fetal hemoglobin value from 100 to derive a total adult hemoglobin value, determine a glycated fetal hemoglobin value, compare the glycated fetal hemoglobin value to a reference range to obtain a comparison, determine a baseline glucose control value based on the comparison, and output the baseline glucose control value and the comparison to a display for medical evaluation.

This invention relates to fusion proteins comprising an insulin receptor agonist fused to the Fc region of human IgG2, and the use of such fusion proteins in the treatment of diabetes. The fusion proteins of this invention have a prolonged duration of action and can be used to provide extended periods of basal glucose control.

To provide protective agents with excellent effects such as starch retrogradation inhibition, prevention or inhibition of the decrease in activity of proteins during storage in a frozen or freeze-dried state, prevention or inhibition of damage or death of microorganisms during storage in a frozen or freeze-dried state, and pH buffering; surfactants with excellent surfactant properties; blood glucose control compositions that do not raise blood glucose levels when administered to individuals; autophagy inducers with excellent autophagy induction properties; staining agents for acid-fast bacteria that can easily and efficiently stain acid-fast bacteria; and protein extractants with excellent protein extraction properties. [Solution] A protective agent, surfactant composition, blood glucose control composition, autophagy inducer, acid-fast bacilli staining agent, or protein extractant characterized by containing a compound represented by general formula (1).

This invention belongs to the field of biomedical technology and discloses the application of NP in the preparation of a glycemic regulator for aging type 2 diabetes. The NP is a nanoscale complex formed by hydrogen bonding of turtle egg peptide with a molecular weight less than 3 kDa and naringenin at a mass ratio of 100:1. The formulation promotes liver glycogen synthesis and repairs pancreatic tissue structure and pancreatic β-cell function by activating the hepatic IRS1 / PI3K / AKT / GSK-3β signaling pathway and upregulating GLUT2 protein expression. The NP provided by this invention can significantly reduce fasting blood glucose levels in aging type 2 diabetic mice, improve oral glucose tolerance, and reduce the area under the blood glucose curve. Simultaneously, by restoring insulin signal transduction, it significantly reduces the insulin resistance index and improves the insulin sensitivity index, with an improvement level approaching that of the classic hypoglycemic drug metformin.

The present invention recognizes that, there is a need for the prophylaxis or treatment of obesity, glycemic control, and other metabolic disorders. A first aspect of the present invention generally relates to methods of prophylaxis or treatment of obesity, glycemic control, and other metabolic disorders, using various pharmaceutical compositions. A second aspect of the present invention generally relates to mono-therapy or combination therapy used for the prophylaxis or treatment of obesity, glycemic controh other metabolic disorders, and combinations thereof

Provided is a wearable medical device that includes a processor or logic circuitry. The wearable medical device may include a memory storing instructions that, when executed by the processor or logic circuitry, configure the wearable medical device to determine, by the processor or the logic circuitry, that an event affecting a blood glucose measurement value trend of a user has occurred. Based on the occurrence of the event, the processor or the logic circuitry may select a mode of operation of the analyte sensor, and generate a signal indicating the selected mode of operation. The mode of operation may correspond to a sampling frequency of a physical attribute or physiological condition of a user of the wearable medical device.

Systems and methods are disclosed for managing a person's blood glucose concentration within a predetermined range by co-administration of insulin and pramlintide using an automated insulin delivery system. A model predictive control (MPC) algorithm that includes a glucoregulatory control model augmented with a compartment model of pramlintide pharmacokinetics and pharmacodynamics is utilized. In some embodiments, the person may announce in advance meals to be consumed and the pramlintide-aware MPC algorithm uses this data as input to the glucoregulatory control model. In other embodiments, an automatic meal detection and size estimation algorithm is incorporated into the system to relieve the person of the burden of meal entry and carbohydrate estimation.

A framework may be provided for automatically converting a history of manual medicament bolus deliveries to a user into modifications of one or more glucose control parameters of a medicament delivery system. This may eliminate the need for the user to manually adjust the glucose control parameter(s); instead the glucose control parameter(s) may be programmatically adjusted automatically. The glucose control parameter(s) may include, for example, a target glucose level, an input base basal delivery rate, cost function coefficients, and / or a constraint on maximum delivery amounts of medicament. The automatic adjustments may help to customize the glucose control parameter(s) to the user and to minimize the need for user interactions with the medicament delivery system to adjust glucose control parameter(s).

The present invention relates to modified or polymer conjugated MetAP2 inhibitors. The present invention also relates to methods of preventing, inducing, causing or increasing weight loss, treating obesity and / or treating metabolic syndrome utilizing the modified or polymer conjugated MetAP2 inhibitors. The present invention also relates to methods of improving insulin sensitivity and glycemic control, reducing insulin levels and / or improving leptin sensitivity utilizing the modified or polymer conjugated MetAP2 inhibitors.

The present application relates to the biomedical field, specifically relates to a glucose-responsive empagliflozin microneedle delivery system and application thereof.The glucose-responsive empagliflozin microneedle delivery system of the present application is characterized in that the microneedle delivery system is a microneedle patch, comprising a substrate and a microneedle array arranged on the substrate; the microneedle in the microneedle array contains glucose-responsive empagliflozin nanoparticles CB@E or PCB@E.The present application has the following technical effects: the empagliflozin nanoparticles of the present application have precise glucose-responsive drug release performance.The microneedle drug delivery system of the present application has the effect of long-term control of blood glucose.In a T2DM rat model, MN@CB@E exhibits long-acting blood glucose control effect, can reduce blood glucose to normal level within 4h and maintain for 24h, and the hypoglycemic duration is significantly better than that of subcutaneous injection of free empagliflozin (only maintains for 6h), and there is no risk of hypoglycemia after administration to healthy rats.

The invention discloses low-GI yoghourt suitable for diabetics and a preparation method of the low-GI yoghourt, and belongs to the technical field of foods. Raw materials of the quinoa milk comprise raw milk, quinoa flour, modified resistant starch, mulberry leaf extract, bitter gourd peptide, compound probiotics and the like, and the quinoa milk is prepared through raw material pretreatment, step-by-step homogeneous sterilization, gradient temperature control fermentation, gradient cooling and after-ripening. The GI value of the product is 12-15, the product is rich in protein, dietary fiber and active ingredients, the activity of probiotics stored for 60 days is larger than or equal to 7 * 10 < 6 > CFU / mL, the bleeding rate is smaller than or equal to 0.4%, the texture is fine and smooth, the flavor is good, blood sugar control and nutrition supply are both considered, and the product is suitable for diabetics to eat.

The present invention provides a method for increasing glycemic control in a patient in need thereof, by administering tirzepatide, or a pharmaceutically acceptable salt thereof. The present invention provides a method for improving weight management in a patient in need thereof, by administering tirzepatide, or a pharmaceutically acceptable salt thereof. Further providing a method for treating a condition selected from atherosclerosis, chronic kidney disease, NAFLD, and NASH. Further provided is a method to prevent or induce remission of diabetes comprising administration of tirzepatide, or a pharmaceutically acceptable salt thereof. Further provided is a dosing regimen for increasing glycemic control, improving weight management, and / or treating dyslipidemia.

The present disclosure provides a blood glucose control device based on electrical stimulation, comprising: a power module for providing an operating voltage; an interactive interface connected with the power module, for detecting user operation and setting electrical stimulation parameters based on the user operation; the electrical stimulation parameters include at least one of the following: frequency or intensity of electrical pulse signal; an electrical pulse generator connected with the interactive interface, for generating corresponding electrical pulse signals based on the electrical stimulation parameters; an electrode connected with the electrical pulse generator, for transmitting the target electrical pulse signal to the target area of the target object.

The invention discloses a blood glucose detection watch for a diabetic patient, which comprises a watchband and a dial plate, the dial plate is provided with a display screen, and the blood glucose detection watch also comprises a motion detection module used for detecting heart rate and blood pressure, generating a dynamic electrocardiogram, displaying the dynamic electrocardiogram on the display screen, and recording and storing heart rate and blood pressure values before motion. The blood glucose detection module is used for combining dynamic blood glucose monitoring, real-time blood glucose observation, high-low value setting and early morning hypoglycemia reminding and can export data; the blood sugar control condition is intelligently analyzed, and a first feeding button is arranged; the blood glucose is automatically marked with other colors, the blood glucose 2 hours after eating, the blood glucose before sleep and the blood glucose in the early morning are recorded, and the blood glucose value is displayed during review. The blood glucose detection watch can remind a user to take medicine according to diet, exercise blood glucose and heart rate of the user and remind the patient of matters needing attention, the physical condition of the patient is detected in real time, and the physical health of the user is guaranteed.

A method of improving glycemic control is provided. The method includes stimulating a cutaneous distribution of a subject's vagus nerve within the subject's ear with a nerve stimulating signal. The method also includes monitoring the subject's blood glucose. The method further includes administering insulin infusions to the subject.

The present invention relates to a pharmaceutical composition and a health functional food composition for regulating and improving blood glucose, each comprising, as an active ingredient, a fermented culture supernatant of a Bacillus velezensis KMU01 strain, a concentrate thereof, a dried product thereof, a fermentation metabolite thereof, or a mixture thereof, and having the effects of regulating insulin secretion in serum and lowering fasting blood glucose.

The present invention provides a method for increasing glycemic control in a patient in need thereof, by administering tirzepatide, or a pharmaceutically acceptable salt thereof. The present invention provides a method for improving weight management in a patient in need thereof, by administering tirzepatide, or a pharmaceutically acceptable salt thereof. Further providing a method for treating a condition selected from atherosclerosis, chronic kidney disease, NAFLD, and NASH. Further provided is a method to prevent or induce remission of diabetes comprising administration of tirzepatide, or a pharmaceutically acceptable salt thereof. Further provided is a dosing regimen for increasing glycemic control, improving weight management, and / or treating dyslipidemia.

The invention discloses a blood glucose level optimal control method and system based on a deep reinforcement learning algorithm, and the method comprises the steps: constructing a blood glucose time-lag optimal control model and a blood glucose control objective function, constructing a deep reinforcement learning dual-network architecture, designing a reward function, and building an experience playback buffer region. And generating an exploration action through a greedy strategy to carry out state-action space exploration, carrying out collaborative iterative optimization on main Q network parameters to convergence based on an experience playback mechanism and a target network, inputting a patient physiological state vector collected in real time into the trained main Q network, outputting a combined administration instruction of insulin and glucagon, and executing blood glucose control. According to the method, the dynamic characteristics of postprandial blood sugar changes can be accurately described, the problems of unstable training and the like in a traditional algorithm are avoided, better control performance is achieved, and a new method is provided for personalized blood sugar level management.