24 results about "Glycated hemoglobin" patented technology

The utility model relates to the technical field of medical detection devices, and discloses a glycosylated hemoglobin detection device, which comprises a sampling mechanism, a detection mechanism and a control mechanism, the sampling mechanism comprises an injection pump set, a sampling needle and a sampling valve, the sampling valve is a six-way sampling valve, the injection pump set is connected with a first port of the sampling valve, and the sampling needle is connected with a second port of the sampling valve; the separation mechanism comprises an eluent group, a mixer and a chromatographic separator, the eluent group is connected with a fifth port of the sample injection valve, the chromatographic separator is connected with a sixth port of the sample injection valve, and two ends of the mixer are connected with a third port and a fourth port of the sample injection valve; the inspection mechanism comprises a filter and an inspector, the filter is arranged between the mixer and the chromatographic separator, and the inspector is connected with the chromatographic separator. According to the utility model, the glycosylated hemoglobin can be rapidly and accurately detected through an accurate sample introduction and separation mechanism, so that the detection efficiency is improved. The automation degree of the detection process is high, the requirement for manual operation is reduced, and the possibility of human errors is reduced.

Provided is a Bifidobacterium bifidum strain, Bifidobacterium bifidum ibiome001, which can significantly reduce body weight gain and white adipose tissue weight gain of high fat diet-induced obese and diabetic mice, and enhances expression of lipolytic genes ATGL and HSL. Moreover, Bifidobacterium bifidum ibiome001 can significantly lower fasting blood glucose levels, area under curves (AUCs) of the oral glucose tolerance (OGTT) curve, plasma glycated hemoglobin levels and insulin levels of diabetic mice. It is suggested that Bifidobacterium bifidum ibiome001 is a promising potential probiotic strain for the treatment of metabolic syndrome such as obesity, diabetes and the like, which is more effective than other Bifidobacterium strains / compositions.

Systems and methods are provided for providing diabetes patient treatment guidance for a patient in which a biochemical data set is obtained. The biochemical data set comprises test results from a single blood draw of the patient including at least three measurements selected from the set: a high-sensitivity c-reactive protein test, an adiponectin level test, an intact proinsulin level test, an insulin level test, a C-peptide test, a HbA1c test, and an eGFR level test. A demographic data set for the patient is also obtained that comprises the patient's gender and diabetes stage. The biochemical data set and demographic data set is run against one or more rules to determine a first patient therapy pattern. Then, a report is prepared based on an identity of the first therapy patient pattern. The report sets priorities among intervention classes for the patient based on the identity of the first patient pattern.

This invention provides a hypoglycemic subspecies of Bifidobacterium animalis (Liver) and its applications. The Bifidobacterium animalis (Liver) subspecies is named Tianshan-1 and is deposited at the China General Microbiological Culture Collection Center (CGMCC) with accession number CGMCC No. 35821 on September 5, 2025. Cell experiments show that Tianshan-1 significantly promotes the secretion of GLP-1 from human colorectal adenocarcinoma cells NCI-H716 and upregulates GCG gene expression levels. Animal experiments confirm that this strain significantly increases serum GLP-1 concentration in diabetic mice and reduces fasting blood glucose and glycated hemoglobin levels, with no significant difference in hypoglycemic effect compared to the positive control. This strain is a food-grade safe probiotic with a clear mechanism of action and stable effects, providing a safe, long-lasting, and industrially viable new probiotic resource for diabetes prevention and treatment, with broad application prospects.

The invention discloses a diabetes mellitus personalized nursing intelligent medical management system based on an AI algorithm, and belongs to the crossing field of intelligent medical treatment and artificial intelligence. According to the system, a three-layer dynamic coupling architecture of data perception, AI decision making and interactive execution is adopted, algorithms such as a space-time diagram convolutional network, hierarchical reinforcement learning and differential privacy federated learning are fused, and multi-source data intelligent fusion, 72-hour complication prospective early warning, minute-level personalized nursing scheme generation and model adaptive evolution are achieved. Clinical verification shows that the system can remarkably reduce the glycosylated hemoglobin level of a patient, improve the blood glucose standard-reaching rate and the scheme execution rate, reduce diabetes related emergency treatment and relieve the workload of medical care, and is low in deployment cost, convenient to operate, high in privacy, suitable for management of various diabetes mellitus and capable of being expanded to other chronic diseases, such as diabetes mellitus, diabetes mellitus, diabetes mellitus and diabetes mellitus. The system is suitable for multiple scenes such as medical institutions, communities and families.

The glycosylated hemoglobin quantitative detection and analysis device comprises a machine body, a detection area and a display control area are preset on the left side and the right side of the machine body, a stand column is installed in the detection area, the stand column is sleeved with a lower ring plate, and the stand column over the lower ring plate is sleeved with an upper ring plate; a plurality of mutually aligned placing holes are formed in the upper ring plate and the lower ring plate, a concave cavity in the radial direction is formed in the part, between the upper ring plate and the lower ring plate, of the stand column, a second movable plate and a first movable plate are installed on the concave cavity and the side face opposite to the concave cavity respectively, and bayonets aligned with the placing holes are formed in the second movable plate and the first movable plate; and an excitation light source and a photoelectric detector which are opposite to each other are respectively arranged in the movable plate II and the movable plate I. A sample is placed in the placing holes of the upper ring plate and the lower ring plate, during detection, the first movable plate and the second movable plate actively approach and surround the sample, a good internal light shielding environment is obtained, and external light is difficult to enter the interior to affect a detection result.

The invention relates to lactobacillus paracasei KXW5 with a hypoglycemic function and application thereof, and belongs to the technical field of microorganisms. In order to excavate a microecological preparation for treating hyperglycemia-related diseases, a strain of lactobacillus paracasei KXW5 is separated, and in-vivo and in-vitro experiments prove that the strain has remarkable blood sugar reducing capacity, including promoting proliferation of high-glucose-induced INS-1 cells, improving the relative expression quantity of MafA genes in the high-glucose-induced INS-1 cells and improving the blood sugar reducing capacity. The fasting blood glucose level, postprandial blood glucose level, insulin resistance level, glycosylated hemoglobin level, liver copper ion level and the expression level of copper death related genes FDX1 and DLAT in the liver of the type II diabetes mellitus patient are reduced, and the oral glucose tolerance of the type II diabetes mellitus patient is enhanced. The strain KXW5 provided by the invention can be used for preparing medicines for reducing blood sugar and preventing and / or treating diabetes mellitus or health-care foods for assisting in reducing blood sugar, and opens up a new way for preventing and treating diabetes mellitus.

Aspects of the present disclosure include methods for treating a subject having a metabolic disorder by neuromodulation. Methods according to certain embodiments include applying electrical stimulation to the spinal cord of a subject (e.g., a subject diagnosed as having or determined to have diabetes or prediabetes) in a manner sufficient to treat at least one symptom of the metabolic disorder in the subject. In some embodiments, neuromodulation is sufficient to treat one or more symptoms of diabetes or prediabetes such as fasting plasma glucose concentration, non-fasting plasma glucose concentration, elevated hbA1c, glucose tolerance and insulin secretion by the subject. Systems having one or more electrodes configured for applying electrical stimulation to the spinal cord of the subject suitable for practicing the subject methods are also described.

The invention relates to the technical field of gestational diabetes mellitus detection, and discloses a gestational diabetes mellitus serum marker detection data analysis system. The system comprises a serum biochemical data acquisition module, a detection device is used for acquiring a serum sample of a pregnant woman, and a serum biochemical data set containing blood sugar concentration, insulin level and glycosylated hemoglobin indexes is constructed; a multi-dimensional index integration module combines a historical detection time sequence and the physiological parameter information of the current detection time period to generate an integrated data set containing time dimension correlation features; the abnormal risk analysis module processes the time dimension correlation features in the integrated data set, and calculates the risk deviation value of gestational diabetes in the current detection period; when the risk deviation value is abnormal, the risk grading module generates a plurality of candidate intervention classification schemes based on the serum biochemical data set, and outputs the intervention influence degree of each candidate scheme; and an intervention scheme generation module screens the candidate scheme with the lowest intervention influence degree and generates an optimal intervention classification scheme in the current detection time period.

The invention relates to a method and system for predicting the anxiety mood prevalence rate of a diabetic child patient, and belongs to the field of artificial intelligence prediction. According to the method, multi-dimensional clinical data such as demographic data, treatment modes, management behaviors and metabolic indexes of diabetic children are collected, evaluation results of a children anxiety mood disorder screening table (SCARED) are combined, single-factor analysis, correlation analysis and multi-factor Logistic regression analysis are carried out, and an anxiety mood prediction model is constructed. The model takes age, an insulin treatment mode and glycosylated hemoglobin as core variables, and can accurately predict the anxiety risk of a child patient. The system comprises a data acquisition module, a psychological assessment module, an analysis modeling module, a risk prediction module and a report generation module, and realizes automatic data integration, model construction and individual intervention suggestion output. Clinical verification shows that the model prediction efficiency is excellent, and the method has good clinical application value and is beneficial to early recognition and intervention of anxiety mood of diabetic children and improvement of physical and psychological health and disease management quality of the diabetic children.

A method of data analysis is provided. The method is used for finding a long-term trend of blood glucose concentration. The method builds a model for estimating long-term glycemic variability and long-term blood glucose trajectory. Based on single-erythrocyte-level glycated hemoglobin distribution, the glycemic variability is analyzed. A first analysis method is to give a number. The number shows the level of the historical glycemic variabilities. A second analysis method is to restore the blood glucose trajectory over the past 20 weeks. Based on the single-erythrocyte-level glycated hemoglobin distribution, the present invention easily assesses blood-glucose-related clinical information for about 150 days. Hence, an important complement is obtained for diabetes-related or glucose-monitoring-related clinical applications.

The invention relates to lactobacillus rhamnosus KXW1 with a hypoglycemic function and application of the lactobacillus rhamnosus KXW1, and belongs to the technical field of microorganisms. In order to excavate a microecological preparation for treating hyperglycemia-related diseases, a strain of lactobacillus rhamnosus KXW1 is separated, and in-vivo and in-vitro experiments prove that the strain has remarkable blood sugar reducing capacity, including promoting proliferation of high-glucose-induced INS-1 cells and increasing the relative expression quantity of MafA genes in the high-glucose-induced INS-1 cells, so that the hyperglycemia-related diseases can be treated. The fasting blood glucose level, postprandial blood glucose level, insulin resistance level, glycosylated hemoglobin level, liver copper ion level and the expression level of copper death related genes FDX1 and DLAT in the liver of the type II diabetes mellitus patient are reduced, and the oral glucose tolerance of the type II diabetes mellitus patient is enhanced. The strain KXW1 provided by the invention can be used for preparing medicines for reducing blood sugar and preventing and / or treating diabetes mellitus or health-care foods for assisting in reducing blood sugar, and opens up a new way for preventing and treating diabetes mellitus.

Disclosed herein are methods of treating diabetic cardiomyopathy (DbCM) using an aldose reductase inhibitor, and methods of inhibiting decline in cardiac functional capacity and / or progression to overt heart failure in a subject with DbCM using an aldose reductase inhibitor. Also disclosed are aldose reductase inhibitors and compositions thereof for use in treating diabetic cardiomyopathy (DbCM), or inhibiting decline in cardiac functional capacity and / or progression to overt heart failure in a subject with DbCM. Subjects treated by the methods and uses are not administered a sodium-glucose cotransporter-2 (SGLT2) inhibitor and / or have an HbA1C value greater than 8.5%.

The present invention relates to an optical sensor and a wearable device comprising the same for non-invasively determining a concentration of blood components, for example, blood glucose and glycated hemoglobin levels. The optical sensor comprises an emitter configured to emit short-wave infrared (SWIR) radiation, an insulator with a channel transparent to the SWIR radiation, the emitter being disposed on top of the insulator and configured to emit the radiation into a biological tissue through the transparent channel, an optical concentrator made from a material with a refractive index of 1.7 or more, and a photodetector disposed in an upper part of the optical concentrator. The invention provides the possibility of non-invasive, instant or continuously monitoring of blood glucose and glycated hemoglobin levels. 2 indep. claims and 13 dep. claims, 15 figs., 2 tables.

A wearable device for determining glycated hemoglobin level, includes at least three radiation sources; at least two radiation detectors configured to detect photoplethysmographic (PPG) signals of the at least three different wavelengths backscattered by the biological tissues; and a processor configured to: activate the radiation sources and the radiation detectors in pairs of measurement channels for the PPG signals; sequentially detect the PPG signals through each of the measurement channels; form, from the detected PPG signals, a dataset representing a time series of absorption of the PPG signals by the biological tissues of the user; generate a pre-processed dataset by carrying out a pre-processing of the dataset; and determine a glycated hemoglobin level based on the pre-processed dataset by a pre-trained machine learning model.

The PPG based NIBG neural network prediction system of the present invention comprises a neural network configured to predict BG level of a subject based on PPG signal obtained from the subject wherein the subject is not undergoing medical treatment and the neural network is trained using training data from subjects not undergoing medical treatment. In another embodiment, the PPG based NIBG neural network prediction system of the present invention predicts BG level of a subject based on HbA1c of the subject measured using conventional finger prick method as well as PPG signal obtained from the subject wherein the subject is not undergoing medical treatment and the neural network is trained using training data from subjects not undergoing medical treatment.

Provided is the use of a compound or a pharmaceutically acceptable salt thereof in the treatment of glucose metabolic diseases. The compound or pharmaceutically acceptable salt thereof can significantly lower the blood glucose level and improve the metabolic phenotype of diseases associated with the glucose metabolism, and can specifically reduce the food intake of mice and improve their blood glucose and glycated hemoglobin levels, glucose tolerance, and insulin sensitivity.

A kind of glycated hemoglobin analyzer chromatography column device, involve medical detection equipment technical field, solve the technical deficiencies of existing device complex structure, chromatography column assembly disassembly inconvenient, seal is not strict, maintenance difficulty, detection is not accurate, the technical scheme that is used includes: heating seat component and the clamping fixing mechanism that can be detachably fixed on it, heating seat component is equipped with first liquid path and the heating element for heating the liquid in first liquid path;Chromatography column cavity is equipped on the clamping fixing mechanism, its operating end can be elastically pushed out axially in chromatography column cavity, and third liquid path is equipped on its operating end;Second liquid path is equipped on chromatography column component, under the elastic pressure of the operating end of clamping fixing mechanism, it is fixed in chromatography column cavity and is connected with the liquid outlet end of first liquid path.This application designs heating seat component and clamping fixing device as integrated modular structure, simple structure, easy to maintain, the elastic clamping fixation mode of chromatography column component also facilitates disassembly, strong adaptability, not easy to leak.

The glycosylated hemoglobin detection analyzer is characterized in that the glycosylated hemoglobin detection analyzer comprises a detection equipment structure and a detection groove structure arranged on the surface of the detection equipment structure, a portable structure is spirally installed on the surface of the detection equipment structure, and a dustproof cover structure is movably installed on the surface of the detection equipment structure; the detection groove structure comprises a detection cabin, a limiting strip, a spring, a clamping strip, a detection hole and a magnetic strip, according to the glycosylated hemoglobin detection analyzer disclosed by the invention, the detection groove structure is arranged, so that the detection plate which is centrally placed on the surface of the detection hole can be clamped and fixed, the displacement of the detection plate is effectively prevented, the stability during detection is ensured, and the detection efficiency is improved. By arranging the portable structure, the device is more portable in the moving process, an additional grip is provided for the device, the situation that the handheld device slips off and is damaged is avoided, meanwhile, the structure can be rapidly detached, and storage of the device is not affected.

The present disclosure relates to systems and methods for measuring glycated A1c hemoglobin. A glycated hemoglobin level measuring system includes a sample testing apparatus having a microchannel that compresses a blood sample traveling through, a first pair of electrodes coupled to the microchannel, and a second pair of electrodes coupled to the microchannel. The glycated hemoglobin level measuring system further includes an analysis apparatus having sensors coupled to the first and second pairs of electrodes and configured to calculate a travel time taken by a red blood cell to pass through the first and second pairs of electrodes. The glycated hemoglobin level measuring system can use the travel time to measure a rigidity of the red blood cells and the corresponding glycated hemoglobin level.

The present invention pertains to the field of medical technology, specifically disclosing the pharmaceutical application of dimyricetin-based diselenide in type II diabetes. After four weeks of continuous administration, compared with the model control group, the test substances DMS-ASD and AQ-C-a demonstrated effects that were basically equivalent to the positive control drug, semaglutide injection, in reducing fasting blood glucose levels after 16 hours of fasting in db / db mice, reducing random blood glucose levels in db / db mice, inhibiting postprandial blood glucose elevations in db / db mice, decreasing the HbA1c content of glycated hemoglobin in db / db mice, and influencing body weight and food intake in db / db mice. The pharmaceutical application of dimyricetin-based diselenide in type II diabetes holds great promise.

A wearable device for determining glycated hemoglobin level, includes at least three radiation sources; at least two radiation detectors configured to detect photoplethysmographic (PPG) signals of the at least three different wavelengths backscattered by the biological tissues; and a processor configured to: activate the radiation sources and the radiation detectors in pairs of measurement channels for the PPG signals; sequentially detect the PPG signals through each of the measurement channels; form, from the detected PPG signals, a dataset representing a time series of absorption of the PPG signals by the biological tissues of the user; generate a pre-processed dataset by carrying out a pre-processing of the dataset; and determine a glycated hemoglobin level based on the pre-processed dataset by a pre-trained machine learning model.

A method, system, and computer-readable medium for providing a real-time estimation of laboratory glycosylated hemoglobin (HbA1c) at one or more intervals. The real-time estimation is conferred as a value of estimated, time variable A1e (eA1c) based on daily continuous glucose monitoring (CGM)-derived time in target range (TIR) (CGM-TIR). The eA1c value is adjusted based on a sole laboratory HbA1c value for an interval preceding an interval corresponding to the eA1c value so as to provide an expected value for a laboratory HbA1c value at the same corresponding interval.

A method of providing personalized treatment for a diabetes patient including a remote device which is configured to receive a first data indicative of an analyte level of a subject during a first time period, retrieve a first glycated hemoglobin level for the subject associated with the first time period, calculate a first personal apparent glycation ratio for the first time period using the received first data and the retrieved first glycated hemoglobin level, compare the calculated first personal apparent glycation ratio to a representative apparent glycation ratio, generate a recommendation based on the comparison, and display a graphical interface comprising the calculated first personal apparent glycation ratio, the representative apparent glycation ratio, and the comparison.