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Incretins

Incretins are a group of hormones produced in the gastrointestinal tract that stimulate the release of insulin from the pancreas.
These hormones play a crucial role in regulating blood glucose levels and have become an important area of research in the field of diabetes and metabolic disorders.
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Most cited protocols related to «Incretins»

The NHIS was initiated in 1963 in Korea according to the National Health Insurance Act, and all Korean citizens were mandated to participate in this program [12 ]. Currently, the Korean NHIS maintains and manages all databases of Korea’s health service utilization. The detailed structure and function of NHIS is described elsewhere [12 ].
In the present study, we used data from the NHIS-NSC 2002–2013, which were released by the Korean NHIS in 2014. The data comprise a nationally representative random sample of 1,025,340 individuals, which accounts for approximately 2.2 % of the entire population in 2002 [12 ]. The data were built by using probabilistic sampling to represent an individual’s total annual medical expenses within each of 1476 strata defined by age, sex, eligibility status (employed or self-employed), and income level (20 quantiles for each eligibility status and medical-aid beneficiary) combinations via proportional allocation from the 46,605,433 Korean residents in 2002 [12 , 13 (link)]. The NHIS-NSC is a semi-dynamically constructed cohort database; the cohort has been followed up to either the time of the participant’s disqualification from receiving health services due to death or emigration or until the end of the study period, whereas samples of newborn infants are included annually [12 , 13 (link)]. The database contains eligibility and demographic information regarding health insurance as well as data on medical aid beneficiaries, medical bill details, medical treatment, disease histories and prescriptions; such data were constructed after converting insurance claim information to the first day of medical treatment.
From this cohort, we selected subjects recorded to have type 2 diabetes between 2002 and 2004. Type 2 diabetes was defined if anti-diabetic drugs were prescribed and the 10th revision of International Statistical Classification of Diseases, International Classification of Diseases (ICD)-10 codes E11 (non-insulin-dependent diabetes mellitus), E12 (malnutrition-related diabetes mellitus), E13 (other specified diabetes mellitus), or E14 (unspecified diabetes mellitus) was assigned as either principal or additional diagnosis. Antidiabetic drugs dispensed in the pharmacy during the study period in Korea consisted of six classes (i.e., sulfonylureas, biguanide, alpha-glucosidase inhibitor, thiazolidinediones, meglitinide and insulin) [14 (link)]. Incretin-based therapies (i.e. glucagon-like peptide -1 receptor agonists and dipeptidyl peptidase-4 inhibitors) were not introduced during the study period.
This diabetic cohort was followed up from the index date until the end of the study period (i.e., December 31, 2013), until the last year of qualification for those who were alive, or until the date of death for those who died. This study was approved by the NHIS inquiry commission. The personal privacy of each participant was protected by de-identification of the national insurance claims data for analysis. This study was also approved by the Institutional Review Board of the Asan Medical Center (IRB-No 2016-0149).
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Publication 2016
agonists alpha-Glucosidase Inhibitors Antidiabetics Biguanide Diabetes Mellitus Diabetes Mellitus, Non-Insulin-Dependent Diagnosis Dipeptidyl-Peptidase IV Inhibitors Eligibility Determination Glucagon-Like Peptide-1 Receptor Health Insurance Incretins Infant, Newborn Insulin Koreans Malnutrition meglitinide National Health Insurance Pharmaceutical Preparations Prescriptions Sulfonylurea Compounds Thiazolidinediones
All data are presented as means ± SE. The results of glucose tolerance tests and incretin stimulation tests were statistically evaluated by ANOVA (linear mixed models; SAS 8.2; PROC MIXED), taking the fixed effects of group (wild type, transgenic), time (relative to glucose or hormone application), and the interaction group × time as well as the random effect of animal into account (35 ). Results of the linear mixed models analysis are shown in supplementary Table 1. The same model was used to compare body weight gain of GIPRdn transgenic and control pigs. Pancreas weight and the results of quantitative stereological analyses were evaluated by the general linear models procedure (SAS 8.2) taking the effects of group (wild type, transgenic), age (11 weeks, 5 months, or 1–1.4 years), and the interaction group × age into account. Results of the general linear models analysis are shown in Table 1. Calculation of areas under the curve (AUCs) was performed using Graph Pad Prism 4 software. Statistical significance of differences between transgenic and wild-type pigs was tested using the Mann-Whitney U test in combination with an exact test procedure (SPSS 16.0, Chicago, IL). P values <0.05 were considered significant.
Publication 2010
Age Groups Animals Animals, Transgenic Glucose Glucose Tolerance Test Hormones Incretins neuro-oncological ventral antigen 2, human Pancreas prisma Sus scrofa
After the 4 weeks of vildagliptin administration with or without infusions of incretin receptor blockers, the systolic blood pressure (SBP) and pulse rate were measured using indirect tail-cuff equipment. Blood samples were collected after a 6-hour fast. Plasma levels of glucose, total cholesterol, high-density lipoprotein (HDL) cholesterol, triglyceride, and nonesterified fatty acids (NEFA) were measured by enzymatic methods. Non-HDL cholesterol was calculated by subtracting HDL cholesterol from total cholesterol. HbA1c was measured by the quick test (A1CNow+ ® 20test-kits; Bayer Yakuhin, Osaka, Japan). Plasma levels of active GLP-1, total GLP-1, total GIP, and insulin were determined by an enzyme-linked immunosorbent assay (ELISA Kit, Millipore, MA; Ultra Sensitive “PLUS” Mouse Insulin ELISA Kit, Morinaga, Yokohama, Japan). Only total GIP was measured, as no test kit for measuring active GIP was commercially available. The plasma levels of total GIP in the Pro3-infused animals remained undetermined, as the test kit for total GIP was cross-reacted with Pro3. Oral glucose tolerance tests were performed on nondiabetic Apoe−/− mice with or without vildagliptin treatment after a 6-h fast. Glucose (1.5 mg/g body weight) was administered orally through a gavage tube, and blood glucose levels were measured by the glucose oxidase method using the Glucose Monitor System (Sanwa Kagaku, Nagoya, Japan).
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Publication 2013
Aftercare Animals Apolipoproteins E BLOOD Blood Glucose Body Weight Cholesterol Enzyme-Linked Immunosorbent Assay Enzymes Glucagon-Like Peptide 1 Glucose High Density Lipoprotein Cholesterol Incretins Insulin Mice, House Nonesterified Fatty Acids Oral Glucose Tolerance Test Oxidase, Glucose Plasma Pulse Rate Systolic Pressure Tail Test, Quick Triglycerides Tube Feeding Vildagliptin
SPSS version 23.0 (IBM statistics) was used for all statistical analyses. Categorical variables were presented as frequencies (percentages) and continuous variables as mean ± SD. For the general population of diabetics and non diabetics we calculated a sample size using a power of 80% and confidence of 95%. For comparison among diabetic never-incretin-users and diabetic current-incretin-users, a propensity score matching (PSM) was developed from the predicted probabilities of mortality and MACE by a multivariable logistic regression model. Diabetic never-incretin-users were matched to diabetic current-incretin-users on the basis of PSM. In all matched patients, the balancing property was satisfied. Overall survival and event-free survival were presented using Kaplan–Meier survival curves and compared using the log-rank test. Univariable Cox models were then used to compare event risks. Within all the diabetic and non-diabetic groups, all cause of deaths, cardiac deaths, and MACE were assessed by using multivariable Cox models with adjustment for statistically different variables at baseline and follow-up: hypertension, dyslipidemia, current smoking, ace-inhibitors, calcium inhibitors, thiazide diuretics, aspirin, statin, BMI, heart rate, HDL-cholesterol, LDL-cholesterol, triglycerides levels, hs-CRP, M1/M2, and GLP-1 levels. The resulting hazard ratios (HRs) and 95% confidence intervals (CIs) were reported. To investigate the effects of GLP1 levels on cardiovascular endpoints, we evaluated STEMI outcomes at 1-year follow-up stratified by GLP-1 quartiles. A 2-tailed p value < 0.05 was considered statistically significant.
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Publication 2018
Angiotensin-Converting Enzyme Inhibitors Aspirin Calcium Cardiac Death Cardiovascular System Cholesterol, beta-Lipoprotein C Reactive Protein Dyslipidemias EHMT1 protein, human Glucagon-Like Peptide 1 High Blood Pressures High Density Lipoprotein Cholesterol Hydroxymethylglutaryl-CoA Reductase Inhibitors Incretins inhibitors Myristica fragrans Patients Rate, Heart ST Segment Elevation Myocardial Infarction Thiazide Diuretics Triglycerides
We used descriptive statistics to evaluate trends in the utilization of each therapy of interest. We focused on eight medication classes depicted in Table 1: sulfonylureas (glucotrol XL), biguanides (metformin HCl), glitazones (pioglitazone), DPP-4 inhibitors (sitagliptin), incretins (liraglutide), meglitinides (repaglinide), α-glucosidase inhibitors (acarbose), insulins (insulin glargine), and amylin analogs (pramlintide). We classified drugs within these therapeutic groups based on their chemical composition, using the IMS Health Universal System of Classification (USC) codes. We counted fixed-dose combination products as contributing to each of their constituent classes when computing total compounds; for example, a combination product such as Janumet (sitagliptin and metformin) was counted as contributing once to biguanides and once to DPP-4 inhibitors. Thus, our analysis of trends in DPP-4 use includes visits where they were used as fixed-dose combination products containing DPP-4 inhibitors as well as where they were used as an individual product. We also calculated therapeutic intensity, which we assessed by dividing total number of compounds used by the total number of unique treatment visits in a given year. For these calculations, a visit with a fixed-dose combination would be considered as similarly intense as a treatment where two separate products were used, since both would similarly reflect the use of two compounds during a single visit. For estimates from the NDTI, we calculated 95% CIs using tables of relative standard errors that are derived accounting for the survey’s complex sampling design. Because the NPA is based on such a large sample of pharmacies, the uncertainty surrounding estimates of national prescription expenditures is small.
Publication 2014
Acarbose alpha-Glucosidase Inhibitors Amylin Biguanides chemical composition Dipeptidyl-Peptidase IV Inhibitors Glucotrol Group Therapy Incretins Insulin Insulin Glargine Janumet Liraglutide meglitinide Metformin Metformin Hydrochloride Pharmaceutical Preparations Pioglitazone pramlintide repaglinide Sitagliptin Sulfonylurea Compounds Thiazolidinediones

Most recents protocols related to «Incretins»

The IpGTT was conducted instead of the OGTT because of its ease of use, while also being less stressful for animals than the intragastric gavage technique during OGTT. Add to that, it circumvented the incretin response that might amplify GSIS[90, 91] and activate TRPM4/5 channels.[47] IpGTT was first carried out on three groups of 25 mice per group (three independent experiments): WT, WT with Pyr10 (specific TRPC3 inhibitor),[24] and Trpc3−/− mice. Pyr10 (Sigma‐Aldrich, St. Louis, MO, USA) was acutely administered (i.p.) 10 min prior to the IpGTT, at a dose of 8 µg kg−1 by analogy to previously described daily doses.[14, 92] For TRPC3 activation testing, two additional mouse groups were used: WT (n = 11) and WT acutely administered (i.p.) 10 min before IpGTT with a specific TRPC3 small‐molecule activator GSK1702934A[44] (kindly provided by Pr. Klaus Groschner, Gottfried‐Schatz‐Research‐Centre‐Biophysics, Medical University of Graz, Austria) at a dose of 35 µg kg−1 (n = 11). Similarly, insulin secretion was assessed following an i.p. injection of arginine (1 g kg−1) in another set of mice: WT (n = 25), WT previously administered with Pyr10 (n = 25), and Trpc3−/− mice (n = 25) (three independent experiments). For TRPC6 inhibition experiments, SAR7334 (Tocris Bioscience, Bristol, UK) was used at a dose of 5 mg kg−1 in vivo (i.p.)[28] and two groups of mice (n = 6 each) were studied, WT and WT SAR7334. Plasma insulin was measured according to Crystal Chem's Ultra‐Sensitive Mouse Insulin ELISA Kit (IL, USA).
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Publication 2023
Animals Arginine Enzyme-Linked Immunosorbent Assay Incretins Insulin Insulin Secretion Mice, House Oral Glucose Tolerance Test Plasma Psychological Inhibition SAR7334 TRPC6 Cation Channel Tube Feeding

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Publication 2023
Biological Markers Bones Glucose Incretins Insulin Males Metabolism Oral Glucose Tolerance Test
Routine biochemical parameters (glucose, HbA1C, insulin, C-peptide) were measured by an automated analyzer Cobas 8000 (Roche) on the day of blood collection. Concentrations of incretins and glucagon were measured in sample aliquots stored at − 80 °C for no longer than 6 months.
Glucose levels were determined using the hexokinase method (GLUC3, Roche Diagnostics GmbH, Mannheim, Germany). Levels of HbA1C were measured by ion exchange chromatography using the Arkray Adams HA-8180 V analyzer (Arkray Corporation, Kyoto, Japan). Insulin and C-peptide levels were determined with commercially available kits (Immunotech, Marseille, France) using an immunoradiometric assay with specific antibodies. Based on fasting glucose and insulin levels the homeostasis model assessment of β-cell function (HOMA-β), homeostasis model assessment of insulin resistance (HOMA-IR) indexes [22 (link)], and quantitative insulin sensitivity check index (QUICKI) [23 (link)] were calculated.
Plasma glucagon, GLP-1, and GIP concentrations were measured by commercial multiplex assay (Human Metabolic Hormone Magnetic Bead Panel, HMHEMAG- 34 K, Merck Millipore, USA). Sensitivity was 13.0 pg/mL for glucagon, 1.2 pg/mL for GLP-1 and 0.6 pg/mL for GIP. Intra- and inter-assay variabilities for the kits were < 10% and 15%, respectively.
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Publication 2023
Antibodies Biological Assay BLOOD C-Peptide Diagnosis Glucagon Glucagon-Like Peptide 1 Glucose Hexokinase Homeostasis Homo sapiens Hormones Hypersensitivity Immunoradiometric Assays Incretins Insulin Insulin Resistance Insulin Sensitivity Ion-Exchange Chromatographies Physiology, Cell Plasma
We retrieved from our patient database a retrospective cohort of 398 children and adolescents diagnosed with type 1 diabetes between January 1997 and December 2018 and followed up in the pediatric diabetes clinic of our tertiary health care center (Cliniques universitaires Saint-Luc, Brussels). The study was approved by the local ethical committee (reference CHE:11/JUI/274) and conducted in accordance with the Declaration of Helsinki. Patients eligible were aged between 1 and 18 years and were diagnosed with new-onset T1DM. T1DM was established according to ISPAD guidelines,3 based on symptoms of insulinopenia, elevated blood glucose (BG), positive anti-islet autoantibodies (i.e. GAD65, IA2, and insulin), and lack of family history of genetic diabetes. Exclusion criteria were diabetes onset before the age of 1 year, presence of severe chronic medical conditions before the diagnosis of T1DM (i.e. autoimmune diseases other than type 1 diabetes, active cancer, kidney, liver, or adrenal insufficiency) and use of medication that may affect insulin secretion and/or glucose homeostasis (i.e. corticosteroids, sulfonylurea, incretins, diazoxide, somatostatin, immunomodulatory drugs). Patients with a PR less than 3 months, above 14 months or ongoing at the time of study were also excluded. All patients performed carbohydrate counting and underwent similar dietary education at diagnosis.
Medical records of each patient were reviewed to collect demographic data at diagnosis [i.e. age, gender, date of diagnosis, height, weight, body mass index (BMI)] as well as quarterly follow-up data until 24 months. This included routine clinical and biological parameters [HbA1C levels (%), insulin doses in total daily dose in IU and IU/kg body weight, IDAA1C and GTAA1C scores, number of severe hypoglycemia] and data from glucose monitoring devices [using either continuous glucose monitoring (CGM) or self-monitoring of blood glucose (SMBG)]. The parameters retrieved from CGM or BG meter were average glucose (mg/dl), glucose variability [glycemic SD (mg/dl)], coefficient of variation of glucose (CV, %)], number of glucose measurements, time spent in hypoglycemia (below 70 mg/dl, % total time), number of severe hypoglycemia, time spent in hyperglycemia (above 180 mg/dl, % total time), and time spent in normoglycemia (70–180 mg/dl; % total time) also called time in range (TIR). Body mass index (BMI) was calculated using the formula = body weight (kg)/[height (m)].2Z scores for height and BMI were assessed using Belgian Flemish reference charts.34 (link) Severe hypoglycemia was defined as an alteration of consciousness (with or without coma or convulsion) requiring external assistance from a tier person to actively administer carbohydrates, intramuscular glucagon, or other corrective measures, as described by ISPAD.35 (link)
Publication 2023
Adolescent Adrenal Cortex Hormones Autoantibodies Biopharmaceuticals Blood Glucose Blood Glucose Self-Monitoring Body Weight Carbohydrates Child Chronic Condition Comatose Consciousness Diabetes Mellitus Diabetes Mellitus, Insulin-Dependent Diagnosis Diazoxide Diet Gender Glucagon Glucose glutamate decarboxylase 2 (pancreatic islets and brain, 65kDa) protein, human Homeostasis Hyperglycemia Hypofunction, Adrenal Gland Hypoglycemia Immunomodulating Agents Incretins Index, Body Mass Insulin Insulin Secretion Kidney Liver Malignant Neoplasms Medical Devices Patients Pharmaceutical Preparations Seizures Somatostatin Sulfonylurea Compounds
Women aged between 30 and 65 years and diagnosed with T2DM (fasting blood sugar (FBG) ≥126 mg/dl [32 (link)]) that satisfy the inclusion criteria will be recruited. The inclusion criteria will be considered as follows: diagnosed with T2DM at least 6 months, body mass index (BMI) > 25 and < 35 kg/m2, no weight changes during the last three months, use of glucose-lowering drugs (including sulfonylureas, glinides, biguanides, thiazolidinediones, dipeptidyl-peptidase 4 inhibitors, sodium-glucose transporter 2 inhibitors, alpha-glucosidase inhibitors, amylin mimetics, and incretin mimetic), dietary fiber intake of < 25 g per day, and propensity to take bitter almond gum supplement during the study. Patients will be excluded if they use insulin, glucocorticoids, laxatives, anti-obesity drugs, nonsteroidal anti-inflammatory drugs (NSAIDs), antidepressants, and antibiotics; take supplements including multivitamins, n-3 fatty acids, Ginkgo biloba, antioxidants, probiotics, and other prebiotics in the previous 3 months before the recruitment; have a history of weight loss or dieting in the last 6 months; have cancers and gastrointestinal, thyroid, heart, kidney, liver, lung, and infectious diseases; consume alcohol and smoke; and are pregnant or lactating.
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Publication 2023
Almonds alpha-Glucosidase Inhibitors Amylin Mimetics Anti-Inflammatory Agents, Non-Steroidal Anti-Obesity Agents Antibiotics Antidepressive Agents Antioxidants Biguanides Blood Glucose Communicable Diseases Dietary Supplements Dipeptidyl-Peptidase IV Inhibitors Ethanol Fibrosis Ginkgo biloba Glucocorticoids Glucose Heart Incretins Index, Body Mass Insulin Kidney Laxatives Liver Lung Malignant Neoplasms Omega-3 Fatty Acids Patients Pharmaceutical Preparations Prebiotics Probiotics Smoke Sodium-Glucose Transporter 2 Inhibitors Sulfonylurea Compounds Thiazolidinediones Thyroid Gland Woman

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More about "Incretins"

Incretins are a group of hormones produced in the gastrointestinal tract that play a crucial role in regulating blood glucose levels.
These hormones, such as glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), stimulate the release of insulin from the pancreas, helping to maintain healthy blood sugar control.
Incretins have become an important area of research in the field of diabetes and metabolic disorders.
Researchers in this field often utilize a variety of protocols and tools to study the mechanisms and effects of incretins.
For example, DPP4 inhibitors, which prevent the breakdown of incretins, are a class of medications used to treat type 2 diabetes.
The EZRMGIP-55K assay is a GIP-specific enzyme-linked immunosorbent assay (ELISA) that can be used to measure GIP levels, while the GLP-1 (active) ELISA kit allows for the quantification of active GLP-1 in biological samples.
To enhance the reliability and reproducibility of their research, scientists may turn to AI-powered platforms like PubCompare.ai.
This innovative solution provides easy access to a wide range of protocols from the literature, preprints, and patents, while leveraging AI-driven comparisons to help identify the best protocols and products.
By streamlining the research process and improving the reliability of their findings, researchers can enhance their understanding of incretins and their role in metabolic health.
Additionally, researchers may utilize statistical software like PASW Statistics version 20.0 or SPSS Statistics version 21 to analyze their data, or tools like the RAPIDPoint 500 blood gas analyzer to measure relevant physiological parameters.
Pefabloc SC is a serine protease inhibitor that can be used to prevent the degradation of incretins during sample preparation.
By incorporating these various tools and techniques, researchers in the field of incretins can advance our understanding of these important hormones and their implications for the treatment of diabetes, obesity, and other metabolic disorders.