Glucose Levels Research Articles

Inhibition of starch hydrolysis during in vitro co-digestion of pasta with phenolic compound-rich vegetable foods

The ability of phenolic compounds to inhibit amylolytic enzymes activities has been investigated, suggesting their possible role in type-2 diabetes management. However, these studies have been carried out with purified enzymes and synthetic substrates and are distant from simulating a real physiological situation. The objective of the present research was to evaluate the ability of phenolic-rich vegetable foods to inhibit starch hydrolysis during in vitro co-digestion with pasta resulting in a potential anti-diabetic effect and mimicking as closely as possible a real scenario. Some tested vegetable foods, such as capers, red-skinned onion, red radish, and olives, determined a decrease in starch hydrolysis by 21.5%–31.7% during in vitro co-digestion with pasta. The quali-quantitative phenolic profiles of in vitro co-digested samples were elucidated and selected standard compounds were tested for their ability to inhibit porcine pancreatic α-amylase and mammalian α-glucosidase. The inhibitory potential of these compounds, especially against α-glucosidase, explained the effect observed during co-digestion experiments. The most active phenolic compounds against α-glucosidase were quercetin-4’-O-glucoside, quercetin-3-O-rutinoside, luteolin-7-O-glucoside and quercetin-3-O-glucoside-4’-O-glucoside with IC50 values of 20.67, 52.23, 68.84 and 87.58 μmol/L, respectively. This is the first report suggesting that these compounds are potent inhibitors of mammalian α-glucosidase. This study indicates that consuming starchy foods (i.e., pasta) with phenolic-rich vegetable foods may result in an inhibition of starch digestion possibly reducing the post-prandial glucose levels.

Nutritional Composition and Effect of Loquat Fruit (Eriobotrya japonica L. var. Navela) on Lipid Metabolism and Liver Steatosis in High-Fat High-Sucrose Diet-Fed Mice.

Loquat (Eriobotrya japonica L.) is a popular fruit known for its sweet and slightly tangy flavor, which is widely consumed both fresh and in various processed forms. This study aimed to analyze the biochemical composition of loquat juice and investigate its metabolic benefits in mice fed a high-fat/high-sucrose diet (HFSD). Mice were fed either a standard diet or an HFSD and received or not the loquat juice at 4 or 8 mL/kg body weight for 8 weeks. Body weight, food efficiency ratio, plasma lipoprotein profile, plasma glucose, and lipid indices were monitored throughout the experiment. At the end of the experiment, additional assessments were performed, including lipid content measurements in liver, adipose tissue, bile, and feces; hepatic antioxidant enzyme activities (superoxide dismutase and catalase); hepatic malondialdehyde content; plasma biomarkers of liver injury; liver histology; and organ relative weight. Feeding mice with the HFSD resulted in a significant perturbation in lipid and glucose metabolism, obesity, liver steatosis, and oxidative stress-related enzymes. However, the concomitant administration of loquat juice significantly corrected this imbalance. Fresh loquat juice is low in fat and protein, moderately sugary, and energetically light; however, it is rich in minerals, vitamin C, and various phytochemicals compounds, such as phenolic acids, flavonoids, and carotenoids. The loquat juice could be considered a functional food and could be valorized through the extraction of active substances and their use as food supplements to prevent lipid metabolism disorders and the resulting health complications.

Associations of polysomnographic measures of obstructive sleep apnea, and nocturnal oxygen saturation with incident type 2 diabetes mellitus in middle-aged and older men.

Obstructive sleep apnea (OSA) has been associated with incident type 2 diabetes mellitus (T2DM); however, few prospective epidemiological studies have accounted for important T2DM predictors including pre-diabetes status and testosterone. Participants in the longitudinal Men Androgens Inflammation Lifestyles Environment and Stress (MAILES) study, who underwent eight-channel home-based polysomnography (PSG) in 2010-2011 (n = 824) and were free of diabetes at baseline were included in the analysis (n = 682). From 2015 to 2021, 78.6% (n = 536) completed at least one follow-up assessment. Incident T2DM was determined by self-reported doctor diagnosis, diabetes medications, plasma glucose (fasting ≥7.0 mmol/L or random ≥11.0 mmol/L) or glycated haemoglobin ≥6.5%. Conservative hierarchical Poisson regression models adjusted associations of PSG metrics (categorical and continuous) for age, waist circumference, baseline fasting glucose and testosterone concentrations. In all, 52 men (9.7%) developed T2DM over a mean (range) of 8.3 (3.5-10.5) years. Significant age- and waist circumference-adjusted association of incident T2DM with rapid eye movement (REM) sleep apnea-hypopnea index (AHI) ≥20 events/h (incidence rate ratio [IRR] 1.5, 95% confidence interval [CI] 0.8-2.8; p = 0.23] and highest quartile of delta index (IRR 2.1, 95% CI 0.95-4.6; p = 0.066) were attenuated after adjustment for baseline glucose and testosterone, and the association with the lowest quartile of mean oxygen saturation persisted (IRR 4.2, 95% CI 1.7-10.3; p = 0.029). Categorical measures of AHI severity, oxygen desaturation index, and hypoxia burden index (HBI) were not independently associated with incident T2DM. Associations with T2DM were similar when continuous PSG variables were used; however, HBI was significant (IRR 1.015, 95% CI 1.006-1.024; p = 0.007). In a sub-sample with OSA treatment data (n = 479), these significant associations persisted after excluding adequately treated OSA (n = 32). Understanding underlying OSA endotypes generating hypoxaemia may identify opportunities for diabetes prevention.

Longitudinal assessment of SNPs rs72552763 and rs622342 in SLC22A1 over HbA1c control among Mexican-Mestizo diabetic type 2 patients

Background: In Mexico, 75% of diabetes mellitus type 2 (DMT2) patients are not in glycaemic control criteria (HbA1c<7%); this entails a significantly variable drug response. Amongst the factors influencing such variability, are genetics, more specifically, single nucleotide polymorphisms (SNPs). Three genes implied in metformin pharmacokinetics are SLC22A1, SLC22A2, and SLC22A3, which are polymorphic. While there have been cross-sectional studies on their SNPs impact over drug response, a longitudinal study would contribute valuable information on their effect over time.Methods: SNPs of SLC22A1 (rs72552763, rs622342, rs12208357, rs2282143, rs594709, rs628031, and rs683369), SLC22A2 (rs316019), and SLC22A3 (rs2076828), were determined through PCR-TR. The clinical records of 69 patients undergoing metformin monotherapy were retrospectively assessed. Metformin is the first line treatment against DMT2. A level of HbA1c <7% (time 0) was considered as an inescapable inclusion criterion. The study’s cases were those patients who reported HbA1c ≥ 7% (time1) after time 0 (t0). Kaplan-Meier curves including a Log-Rank test and a Cox multivariate analysis of proportional risks were performed.Aim: Determining clinical, biochemical, and genetic variables which may affect non-control (HbA1c ≥ 7%) survival time spans amongst DMT2 Mexican-Mestizo patients undergoing metformin monotherapy at Hospital Regional de Alta Especialidad de Ixtapaluca (HRAEI) between October 2013 and December 2023.Results: All 69 patients were monitored over a median period of 642 days (273-1,134). A comparison between time 0 and time 1 (t1) revealed differences in weight (p = 0.036), metformin dose mg/kg/day (p = 0.003), plasmatic glucose mg/dL (p = 0.048), and HbA1c (p < 0.001). The median non-control survival rate was different across the 3 genotypes of rs62552763 in SLC22A1 (p = 0.0034) and the dominant genotypic model GAT/GAT vs. GAT/del + del/del (p = 0.009). There were differences between rs622342 genotypes as well (p = 0.041). In GAT/GAT the Cox model found HR = 0.407 (IC95%: 0.202–0.818, p = 0.011) in the univariate analysis and HR = 0.418 (IC95%: 0.204–0.856, p = 0.034) in the multivariate analysis, adjusted by initial metformin dose (mg/kg/day), initial weight (kg), and final metformin dose (mg/kg/day). Genotype A/A of rs622342 in SLC22A1, reported HR = 0.392 (IC95%: 0.169–0.910, p = 0.029) in the multivariate analysis as well.Conclusion: Among DMT2 Mexican-Mestizo patients undergoing metformin monotherapy the minor allele del in rs72552763 and the minor allele C in rs622342 reported a significantly shorter survival median respect to the wild type variant. Patients carrying del in rs72552763 or C in rs622342, both in SLC22A1, will reach non-control in less time with respect to other patients. Therefore these genotypes may constitute a therapeutic response biomarker for this population.

Effects of glucagon-like peptide-1 receptor agonists on glycated haemoglobin and continuous glucose monitoring metrics as adjunctive therapy to insulin in adults with type 1 diabetes: A meta-analysis of randomized controlled trials.

To conduct a meta-analysis of randomized controlled trials (RCTs) to evaluate the effect of glucagon-like peptide-1 receptor agonists (GLP-1RAs) on glycated haemoglobin (HbA1c) and continuous glucose monitoring (CGM) metrics as an adjunct to insulin therapy in adults with type 1 diabetes mellitus (T1D). A systematic literature search was conducted through Medline (via PubMed), Cochrane Library, and Google Scholar up to 27 May 2024. Dual-independent study selection, data extraction, and quality assessment were performed. Results were summarized using random-effects meta-analysis. Six RCTs were identified, involving a total of 378 individuals with T1D. The use of GLP-1RAs in addition to standard insulin therapy was associated with a significant reduction in HbA1c (mean difference [MD] -0.21%, 95% confidence interval [CI] -0.36 to -0.06; p = 0.007) and a similar time in range (TIR) compared to placebo (MD -0.22%, 95% CI -2.39 to 1.95; p = 0.84). GLP-1RA therapy resulted in a significantly higher time below range (MD 1.13%, 95% CI 0.50 to 1.76; p < 0.001) and a lower time above range compared with placebo (MD -1.83%, 95% CI -2.51 to -1.15; p < 0.001). Nonsignificant differences were noted for the secondary outcomes, including the mean amplitude of glucose excursion, continuous overall net glycaemic action for 60 min, mean daily glucose, coefficient of variation, and mean standard deviation of weekly glucose levels. Our findings suggest that, in individuals with T1D, add-on therapy with GLP-1RAs does not confer significant benefits in terms of CGM metrics and is associated with a longer time below the target glycaemic range.

Incidence of Obesity in Diabetes Mellitus Rates, Profile of Teachers and Employees at SMA X Surabaya

Background: Reduced metabolic function can cause the human body to experience a lack of energy, resulting in the possibility of diseases including diabetes mellitus, hypertension, atherosclerosis, and even coronary heart disease. Objective: This study aims to analyze the incidence of obesity through Body Mass Index on the incidence of diabetes mellitus and Lipid Profile at SMA X Surabaya. Methods: The research design used was cross-sectional. Sampling was carried out using non-probability sampling with a random sampling technique. Data collection was carried out at SMA X Surabaya by 64 teachers and employees of SMA X Surabaya. Respondents were gathered to receive health education, then went through the registration stages, and vital signs, and then 5 mL of venous blood was taken to measure blood sugar levels and lipid profiles, namely total cholesterol and triglyceride levels. This research uses the Chi-Square test statistical test. Result: There is a significant relationship based on the chi square test between body mass index and cholesterol levels and triglyceride levels. because the p-value &lt; 0.05 is 0.041 and 0.050 respectively, but there is no significant relationship between body mass index and glucose levels with a p-value of 0.181. Conclusion: There is a relationship between the incidence of obesity through Body Mass Index and the incidence of Lipid Profile but there is no relationship with the incidence of diabetes mellitus at SMA X Surabaya

Serum Hepatocyte Growth Factor Concentration Correlates with Albuminuria in Individuals with Optimal Blood Pressure and Untreated Arterial Hypertension

Background/Objectives: Hepatocyte growth factor (HGF) is a protective factor against acute renal injury and chronic renal fibrosis. A positive correlation between HGF and blood pressure (BP) has been established. This study aimed to determine the association between serum HGF concentration and albuminuria in subjects with optimal blood pressure (OBP) and untreated arterial hypertension (UAH), as well as its association with BP levels, serum glucose levels, and inflammatory markers. Methods: Data from 563 subjects were analyzed. Albuminuria was normalized to urine creatinine and expressed as the albumin/creatinine ratio (ACR). HGF, serum glucose, C-reactive protein, and blood leucocyte counts were measured. BP was measured and subjects were divided into optimal blood pressure (BP &lt; 120/80 mmHg, N = 295) and untreated arterial hypertension (BP &gt; 140/90 mmHg, N = 268) groups. Results: The subjects with UAH were significantly older and had higher values of body mass index, waist circumference, serum total and LDL cholesterol levels, triglyceride levels, fasting glucose levels, and ACR (all p &lt; 0.001). A significant positive correlation was found between serum HGF concentration and ACR in both groups. There was no difference or correlation between HGF and BP or inflammatory markers in either group. The multivariate regression analysis identified serum HGF concentration as a strong predictor of ACR increase (Beta = 0.376, p &lt; 0.001). Conclusion: This study found that serum HGF concentration is associated with albuminuria not only in individuals with untreated arterial hypertension, but also in those with optimal blood pressure. The results suggest that serum HGF is an independent predictor of ACR increase in both groups.

A single bout of physical exercise improves 1-hour post-load plasma glucose in healthy young adults.

Physical exercise is a key component in the treatment of type 2 diabetes and plays an important role in maintaining a healthy glucose metabolism even in healthy subjects. To date, no studies have investigated the effect of a single bout of aerobic physical exercise on glucose metabolism in young, moderately active, healthy adults. We performed an OGTT 7 days before and 24h after a single bout of physical exercise, to evaluate 1-hour post-load plasma glucose and surrogate indexes of insulin sensitivity and insulin secretion. Glucose levels were significantly reduced after exercise at baseline and one hour after glucose load; similarly, insulin was significantly lower 1h after glucose load. We found a significant increase in the Matsuda index, confirmed by OGIS index, QUICKI index, and by significant reduction in HOMA-IR. Conversely, we observed a trend to increase in HOMA-B. This is the first study to evaluate the effect of a single bout of exercise on 1-hour glucose levels following OGTT. We found a significant reduction in 1-hour glucose levels following OGTT together with an increased insulin sensitivity. A single 30-minute bout of aerobic exercise also seemed to improve the insulin secretion pattern. Modifications in beta cell secretory capacity during exercise are likely secondary to an improvement in insulin action in insulin dependent tissues.

Developing an automated algorithm for identification of children and adolescents with diabetes using electronic health records from the OneFlorida+ clinical research network.

To develop an automated computable phenotype (CP) algorithm for identifying diabetes cases in children and adolescents usingelectronic health records (EHRs) from the UF Health System. The CP algorithm was iteratively derived based on structured data from EHRs (UF Health System 2012-2020). We randomly selected 536 presumed cases among individuals aged <18 years who had (1) glycated haemoglobin levels ≥ 6.5%; or (2) fasting glucose levels ≥126 mg/dL; or (3) random plasma glucose levels ≥200 mg/dL; or (4) a diabetes-related diagnosis code from an inpatient or outpatient encounter; or (5) prescribed, administered, or dispensed diabetes-related medication. Four reviewers independently reviewed the patient charts to determine diabetes status and type. Presumed cases without type 1 (T1D) or type 2 diabetes (T2D) diagnosis codes were categorized as non-diabetes/other types of diabetes. The rest were categorized as T1D if the most recent diagnosis was T1D, or otherwise categorized as T2D if the most recent diagnosis was T2D. Next, we applied a list of diagnoses and procedures that can determine diabetes type (e.g., steroid use suggests induced diabetes) to correct misclassifications from Step 1. Among the 536 reviewed cases, 159 and 64 had T1D and T2D, respectively. The sensitivity, specificity, and positive predictive values of the CP algorithm were 94%, 98% and 96%, respectively, for T1D and 95%, 95% and 73% for T2D. We developed a highly accurate EHR-based CP for diabetes in youth based on EHR data from UF Health. Consistent with prior studies, T2D was more difficult to identify using these methods.

PHARMACODYNAMIC OF METFORMIN IN TYPE 2 DIABETES MELLITUS PATIENTS: REVIEW OF THE PRKAA2 AND SLC22A3 GENES

Type 2 diabetes mellitus (type 2 DM) is a disease including on metabolic disorder that characterized by an increase in glucose levels above normal. This glucose increase is caused by reduced insulin function which can be in the form of abnormalities in insulin secretion, impaired insulin action in peripheral tissues, or both. Metformin is one of the recommended therapies for type 2 DM. AMPK is the main pathway of metformin's mechanism. AMPKa2 encoded by PRKAA2 gene is an AMPK subunit that plays an important role in AMPK activation. OCT3 encoded by SLC22A3 plays a role in the metformin transport mechanism. OCT3 is needed in the metformin pharmacokinetic like absorption and elimination, this process determines metformin bioavailability, clearance, and its pharmacological effects. Mutations in PRKAA2 and SLC22A3 cause variations in the pharmacodynamic effects and pharmacokinetic of metformin in individuals directly. These changes will ultimately affect the effectiveness of metformin in type 2 DM patients.

Relationship between Lipid and Blood Glucose Levels with Stroke Risk in Dupak Surabaya

Background: Stroke is a syndrome characterized by rapidly developing symptoms and/or clinical signs in the form of focal or global brain functional disorders lasting more than 24 hours which are not caused by causes other than vascular. Stroke is the number one cause of disability and the main cause of death in Indonesia (19.42% of total deaths). Dyslipidemia and diabetes mellitus are two-fold risk factors for stroke.This research is to determine the relationship between lipids and blood glucose and a high risk of stroke. Methods: This research uses descriptive analytical methods with a cross sectional approach. The population is residents in Dupak Surabaya. The sampling method is random sampling technique. The total research sample was 53 participants. The statistical test used is Chi Square. Result: Statistical results show that there is no relationship between high cholesterol levels and the risk of stroke and there is a relationship between high triglyceride and blood sugar levels and the risk of stroke.Conclusion:This research concluded that there was a significant relationship between high levels of triglycerides and blood glucose and the risk of stroke and there was no significant relationship between high cholesterol levels and the risk of stroke. This lack of significant association could be due to the heterogeneous population and the presence of previous anti-cholesterol medication.

Dynamic glycolytic reprogramming effects on dendritic cells in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma tumors exhibit resistance to chemotherapy, targeted therapies, and even immunotherapy. Dendritic cells use glucose to support their effector functions and play a key role in anti-tumor immunity by promoting cytotoxic CD8+ T cell activity. However, the effects of glucose and lactate levels on dendritic cells in pancreatic ductal adenocarcinoma are unclear. In this study, we aimed to clarify how glucose and lactate can impact the dendritic cell antigen-presenting function and elucidate the relevant mechanisms.MethodsGlycolytic activity and immune cell infiltration in pancreatic ductal adenocarcinoma were evaluated using patient-derived organoids and resected specimens. Cell lines with increased or decreased glycolysis were established from KPC mice. Flow cytometry and single-cell RNA sequencing were used to evaluate the impacts on the tumor microenvironment. The effects of glucose and lactate on the bone marrow-derived dendritic cell antigen-presenting function were detected by flow cytometry.ResultsThe pancreatic ductal adenocarcinoma tumor microenvironment exhibited low glucose and high lactate concentrations from varying levels of glycolytic activity in cancer cells. In mouse transplantation models, tumors with increased glycolysis showed enhanced myeloid-derived suppressor cell infiltration and reduced dendritic cell and CD8+ T cell infiltration, whereas tumors with decreased glycolysis displayed the opposite trends. In three-dimensional co-culture, increased glycolysis in cancer cells suppressed the antigen-presenting function of bone marrow-derived dendritic cells. In addition, low-glucose and high-lactate media inhibited the antigen-presenting and mitochondrial functions of bone marrow-derived dendritic cells.ConclusionsOur study demonstrates the impact of dynamic glycolytic reprogramming on the composition of immune cells in the tumor microenvironment of pancreatic ductal adenocarcinoma, especially on the antigen-presenting function of dendritic cells.

Diagnostic Value of Serum Apolipoprotein B100 Combined With Hippocampal Volume in Alzheimer's Disease.

To explore the diagnostic value of serum apolipoprotein B100 (Apo B100) combined with hippocampal volume in Alzheimer's disease (AD). A total of 59 AD patients and 59 healthy subjects were selected. The Mini-Mental State Examination (MMSE) was used for neuropsychological assessment. Blood glucose and serum lipid levels were detected by biochemical analyzer. Polymerase chain reaction (PCR) was used to detect apolipoprotein E (Apo E) ε3/ε4 genotypes in the plasma. Hippocampal volume was calculated using Slicer software. Independent-sample t test or Mann-Whitney U test were used to compare the levels of various indicators between the two groups. Spearman's correlation analysis was used to analyze the correlation between each level. The receiver operating characteristic curve (ROC) was plotted, and the area under the curve (AUC) was calculated to compare the diagnostic efficacy of individual and combined detection of serum Apo B100 levels and hippocampal volume in AD. Compared with the healthy control group, the levels of serum total cholesterol (TC), low-density lipoprotein (LDL), Apo B100, and plasma Apo E ε3/ε4 were higher in the AD group, and serum high-density lipoprotein (HDL) level was lower in the AD group (both p<0.05). The hippocampal volume in the AD group was lower than in the control group (p<0.01). The serum Apo B100 level was negatively correlated with MMSE score (r=-0.646), whereas hippocampal volume was positively correlated with MMSE score (r=0.630). ROC curve analysis showed that the AUC of the combined serum Apo B100 level and hippocampal volume for AD was higher than that of either alone (AUC=0.821, p<0.01). Serum Apo B100 level is elevated, and the hippocampal volume is reduced in AD patients. The combined detection of the two has a higher diagnostic efficiency for AD than other alone and has the potential to become an important indicator for the diagnosis of AD in the future.

TO STUDY THYROID DYSFUNCTION IN PATIENTS WITH METABOLIC SYNDROME

Background: Metabolic syndrome (MetS) is a cluster of risk factors associated with increased cardiovascular disease and diabetes risk. Thyroid dysfunction (TD), especially hypothyroidism, has been observed more frequently in individuals with MetS. However, the relationship between thyroid function and metabolic syndrome components remains debated. This study aimed to explore the prevalence of thyroid dysfunction and its association with metabolic syndrome components in patients. Methods: A cross-sectional study was conducted at Sri Aurobindo Medical College &amp; P.G. Institute, Indore. A total of 120 patients meeting the International Diabetes Federation (IDF) criteria for metabolic syndrome were included. Detailed history, anthropometric measurements, blood pressure recordings, fasting blood sugar, lipid profile, and thyroid assays were performed. Statistical analysis using SPSS22 and Excel was employed to assess thyroid dysfunction prevalence and its correlation with metabolic syndrome components. Results: Among 120 patients with metabolic syndrome, 28% had thyroid dysfunction. Hypothyroidism was predominant, with subclinical hypothyroidism being the most common type. Females and older individuals (&gt;45 years) showed a higher prevalence of thyroid dysfunction. Patients with thyroid dysfunction exhibited altered metabolic syndrome components, including increased waist circumference, decreased HDL-C, elevated blood pressure, fasting glucose, and triglyceride levels. Conclusion: The study highlights a high prevalence of thyroid dysfunction, especially hypothyroidism, among patients with metabolic syndrome. These findings suggest a potential association between thyroid status and metabolic syndrome components. Screening for thyroid dysfunction in individuals with metabolic syndrome could aid in optimizing clinical management strategies. Further research with larger sample sizes and prospective designs is warranted to explore the impact of thyroid dysfunction management on metabolic syndrome outcomes.

Comparison of Classification Results of SVM, KNN, Decision Tree, and Ensemble Methods in Diabetes Diagnosis

This study aims to determine which algorithms and test techniques are the most optimal in detecting diabetes mellitus and obtaining the best results based on the value of accuracy, precision, and recall. In this study, approaches were used in early diagnosis of diabetes using KNN, SVM, Decision Tree, and Ensemble Majority Voting methods in Percentage Split and K-Fold Cross Validation methods. Diabetes is a disease characterized by high blood sugar (glucose) levels and can cause a variety of disease complications and damage to the body's organs if not treated immediately. Early diagnosis of diabetes is becoming crucial so that people can take immediate action to the hospital for immediate treatment. The data used is Healthcare-Diabetes from Kaggle. The results of this study have found that the K-Fold Cross Validation method is better because it can provide an average improvement in Ensemble accuracy of 13.42% compared to the Percentage Split method which only gives an average increase in Ensamble accuracy of 9.15%. The best algorithm for classifying diabetes disease is the Ensemble Majority Voting algorithm using the K-Fold Cross Validation method with a 98.81% accuracy rate. These excellent research results may contribute to detecting early symptoms of diabetes before it become too severe.

Remission and relapse of diabetes after sleeve gastrectomy and one-anastomosis gastric bypass: The Tehran Obesity Treatment Study.

To evaluate the rates and predictors of remission and relapse of type 2 diabetes mellitus (T2DM) in individuals with T2DM undergoing sleeve gastrectomy (SG) or one-anastomosis gastric bypass (OAGB). An observational prospective study with 5 years of follow-up was conducted in a total of 891 patients (82.5% female) with concomitant T2DM and obesity (body mass index ≥ 30.0 kg/m2) undergoing SG or OAGB between March 2013 and March 2021. T2DM remission was defined as achieving a glycated haemoglobin (HbA1c) level < 48 mmol/mol and a fasting plasma glucose (FPG) level <7 mmol/L, and being off glucose-lowering agents/insulin. T2DM relapse was defined as when FPG or HbA1c reverted to the diabetic range (≥7 mmol/L and ≥48 mmol/mol, respectively), or there was a need for pharmacotherapy. After bariatric surgery, the overall T2DM remission and relapse rates were 61.4 per 1000 person-months (95% confidence interval [CI] 56.8-66.4) and 5.7 per 1000 person-months (95% CI 4.1-7.9), respectively. These rates were similar in the SG and OAGB groups. Multivariate hazard ratio analysis identified history of insulin therapy and T2DM duration prior to surgery as predictors of remission, while treatment with ≥2 glucose-lowering agents was the only relapse predictor. Additionally, patients undergoing SG experienced either remission or relapse within a significantly shorter time frame compared to those undergoing OAGB. After 5 years of follow-up, there were no significant differences between the SG and OAGB groups with regard to T2DM remission and relapse. Bariatric surgery was less likely to result in remission in patients with a history of insulin therapy and longer durations of T2DM prior to surgery. Furthermore, patients who received ≥2 glucose-lowering agents, despite possible remission, were at a higher risk of experiencing late relapse.

Utilization of Smart Healthcare for Gestational Diabetes Mellitus Management

Gestational diabetes mellitus (GDM) poses significant health risks to both mothers and newborns, requiring rigorous self-management and frequent medical consultations. Advances in information and communications technology (ICT) have shown promising results in reducing the number of in-person visits for GDM management. ICT enhances patient self-care engagement, with some studies reporting reductions in average blood glucose and HbA1c levels. ICT for GDM management has demonstrated benefits such as fewer in-person visits, improved adherence to self-monitoring of blood glucose, increased global user satisfaction, and maintenance of blood glucose control and perinatal outcomes. Common barriers to ICT for GDM include technological literacy, inadequate education, limited technical support, the additional burden of non-customized applications, and restricted interoperability. Further research is needed on the impact of technology on GDM management to optimize digital health solutions.

Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset

Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable risk of long-term death, especially among the elderly, demanding urgent medical attention. Accurate prediction of SH remains challenging due to its multifaced nature, contributed from factors such as medications, lifestyle choices, and metabolic measurements. In this study, we propose a systematic approach to improve the robustness and accuracy of SH predictions using machine learning models, guided by clinical feature selection. Our focus is on developing long-term SH prediction models using both semi-supervised learning and supervised learning algorithms. Using the action to control cardiovascular risk in diabetes trial, which includes electronic health records for over 10,000 individuals, we focus on studying adults with T2DM. Our results indicate that the application of a multi-view co-training method, incorporating the random forest algorithm, improves the specificity of SH prediction, while the same setup with Naive Bayes replacing random forest demonstrates better sensitivity. Our framework also provides interpretability of machine learning models by identifying key predictors for hypoglycemia, including fasting plasma glucose, hemoglobin A1c, general diabetes education, and NPH or L insulins. The integration of data routinely available in electronic health records significantly enhances our model’s capability to predict SH events, showcasing its potential to transform clinical practice by facilitating early interventions and optimizing patient management. By enhancing prediction accuracy and identifying crucial predictive features, our study contributes to advancing the understanding and management of hypoglycemia in this population.

A Probiotic Mixture Decreases Neuropathy and Oxidative Stress Markers in Diabetic Rats

Diabetic neuropathy (DN) is a type of nerve damage caused by long-term hyperglycemia in diabetes mellitus (DM). The gut microbiota alters in DM. Therefore, improvement of the gut flora may affect neuropathic pain and oxidative biomarkers' responsiveness to the probiotic treatment. The present study aimed to assess the effects of probiotic supplementation on neuropathic pain and oxidative stress biomarkers in diabetic rats’ serum. Forty-eight rats (200-250 g) were randomly divided into four groups (n = 12 per group) to examine the effects of the probiotics mixture as follows: the control group (CO), and the diabetic groups received 1 ml probiotics mixture (DP) containing &lt;em&gt;Lactobacillus rhamnosus&lt;/em&gt;, &lt;em&gt;Lactobacillus acidophilus&lt;/em&gt;, &lt;em&gt;Lactobacillus delbrueckii&lt;/em&gt;, &lt;em&gt;Lactobacillus plantarum&lt;/em&gt;, and &lt;em&gt;Bifidobacterium bifidum&lt;/em&gt; (10&lt;sup&gt;9&lt;/sup&gt; CFU of each), 100 mg/kg Gabapentin (DG), or normal saline (DM) daily. The study used animals with plasma glucose concentrations between 70 and 100 mg/dl. Behavioral tests, including mechanical allodynia, cold allodynia, and thermal hyperalgesia, were used to evaluate the pain on days 1, 4, 7, 14, and 21 of the study. After that, the serum's biochemical analysis was completed. Taking the probiotics mixture decreased mechanical and cold allodynia as well as thermal hyperalgesia. The probiotics group also showed significant reductions in lipid peroxidation levels and increases in total antioxidant capacity (TAC) and glutathione peroxidase (GPx) and superoxide dismutase (SOD) activities compared to the DM group. Our results showed that supplementation with the probiotics mixture could reduce pain-related behaviors in diabetic rats by enhancing the antioxidant capacity in their serum.

The impact of an oral glucose load on IFN-γ-release in persons infected with Mycobacterium tuberculosis

Background and objectiveTo diagnose tuberculosis infection (TBI), whole blood is incubated with M.tuberculosis (Mtb)-specific peptides and the release of interferon-γ (IFN-γ) is measured in IFN-γ-release assays (IGRAs). Hyperglycaemia and fluctuations in blood glucose may modulate IFN-γ-release. Here, we investigated if glucose intake affects IFN-γ-release or IGRA results in IGRAs taken during an oral glucose tolerance test (OGTT).MethodsPersons with TB disease (TB) or TBI underwent a standard 75-g OGTT at the start and end of treatment for TB or TBI. Blood for the IGRA QuantiFERON-TB Gold Plus (QFT) containing Mtb-specific tubes (TB1 and TB2), a non-specific mitogen tube (MIT) and an empty control tube (NIL) was drawn at sample-timepoints -15 (baseline), 60, 90, 120 and 240 min during the OGTT. Blood glucose was measured in parallel at all timepoints. IFN-γ-release (after subtraction of NIL) at each timepoint was compared with baseline using linear-mixed-model analysis.ResultsTwenty-four OGTTs from 14 participants were included in the final analysis. Compared to baseline, IFN-γ-release was increased at sample-timepoint 240 min for TB1; geometric mean (95% confidence interval) 3.0 (1.5–6.2) vs 2.5 (1.4–4.4) IU/mL (p = 0.047), and MIT; 182.6 (103.3–322.9) vs 146.0 (84.0–254.1) IU/mL (p = 0.002). Plasma glucose levels were not associated with IFN-γ-release and the QFT test results were unaffected by the OGTT.ConclusionIngestion of glucose after a 10-h fast was associated with increased IFN-γ-release after 240 min in the MIT tube. However, there was no association between plasma glucose levels at the QFT sampling timepoint and IFN-γ-release. Furthermore, the QFT test results were not affected by glucose intake. The overall effect of an OGTT and prevailing plasma glucose levels on IFN-γ-release in IGRAs seem limited.Trial registrationTrial registration ID: NCT04830462 (https://clinicaltrials.gov/study/NCT04830462). Registration date: 05-Apr-2021.