Abnormal Blood Glucose Levels Research Articles

The associations of maternal liver biomarkers in early pregnancy with the risk of gestational diabetes mellitus: a prospective cohort study and Mendelian randomization analysis

BackgroundAssociations of liver function with the risk of gestational diabetes mellitus (GDM) remain unclear. This study aimed to examine the relationship and the potential causality between maternal liver biomarkers and the risk of subsequent GDM, as well as to evaluate the interaction between liver biomarkers and lipids on GDM risk.MethodsIn an ongoing Zhoushan Pregnant Women Cohort, pregnant women who finished the first prenatal follow-up record, underwent liver function tests in early pregnancy, and completed the GDM screening were included in this study. Logistic regression models were used to investigate the association, and the inverse-variance weighted method supplemented with other methods of two-sample Mendelian randomization (MR) analysis was applied to deduce the causality.ResultsAmong 9,148 pregnant women, 1,668 (18.2%) developed GDM. In general, the highest quartile of liver function index (LFI), including ALT, AST, GGT, ALP, and hepatic steatosis index, was significantly associated with an increased risk of GDM (OR ranging from 1.29 to 3.15), especially an elevated risk of abnormal postprandial blood glucose level. Moreover, the causal link between ALT and GDM was confirmed by the MR analysis (OR=1.28, 95%CI:1.05-1.54). A significant interaction between AST/ALT and TG on GDM risk was observed (Pinteraction = 0.026).ConclusionElevated levels of LFI in early pregnancy were remarkably associated with an increased risk of GDM in our prospective cohort. Besides, a positive causal link between ALT and GDM was suggested.

Kigelia africana (Lam.) Benth. fruit inhibits iron-induced lipid peroxidation and ?-amylase enzyme activity

Insufficiencies in insulin secretion and/or action cause diabetes mellitus (DM), a complex condition characterized by abnormal blood glucose levels. Diabetes is often treated by modifying either glucose metabolism, lipids metabolism, or both. A direct correlation has been found between high levels of lipid peroxide in individuals with diabetes and lower intracellular antioxidant activity. Therefore, this study was designed to investigate the effect of the aqueous extract of Kigelia africana fruit on the carbohydrate hydrolyzing enzyme, ?-amylase, and FeSO4-induced lipid peroxidation in the rat pancreas. The in vitro antioxidant potential, including assays for (1,1 diphenyl-2-picryl hydrazyl (DPPH), ferric reducing antioxidant property (FRAP), nitric oxide (NO), hydroxyl (OH) scavenging, and Fe2+ chelating abilities, of the fruit extract was also evaluated. The effect of the fruit extract on the ?-amylase enzyme, and FeSO4-induced lipid peroxidation in the rat pancreas was also evaluated. K. africana at a concentration of 0.5 mg/mL and 1 mg/mL scavenged DPPH radicals, with the lower concentration showing significant differences compared to the control. The K. africana fruit extract reduced ferric compounds significantly compared to the standard. The OH* radical scavenging results revealed that all concentrations of K. africana fruit scavenged OH* radicals without significant differences compared to the control. K. africana fruit also chelated iron significantly compared to the control. The fruit extract inhibited iron-induced lipid peroxidation in the rat pancreas and ?-amylase activity compared to the control. K. africana fruit displayed promising potential in inhibiting ?-amylase activity and associated lipid peroxidation in diabetics. Therefore, it holds strong promise for use in diabetes treatment, validating its traditional use for managing the condition.

Aged oolong tea manages type 2 diabetes mellitus by inhibiting fat ectopic deposition and alleviating insulin resistance in db/db mice

AbstractAn important concern for tea consumers is whether appropriate storage can effectively improve the ability of oolong tea to alleviate type 2 diabetes mellitus (T2DM). In this study, the antidiabetic effects of three aged oolong tea (2001, 2011, and 2020) extracts (aged TEs) in db/db T2DM mice were investigated and compared for the first time. The results showed that aged oolong tea extracts (aged TEs) alleviated the abnormal fasting blood glucose levels, lipid profiles, insulin resistance, and reduced ectopic fat deposition in liver. Moreover, aged TEs alleviated T2DM‐related tissue damage and activated insulin receptor (INSR)/insulin receptor substrate (IRS)/phosphatidylinositol‐3 kinase (PI3K)/phosphatidylinositol‐3 kinase (AKT)/glycogen synthase kinase 3 beta (GSK‐3β)/glycogen synthase (GYS)‐mediated hepatic glycogen synthesis signaling pathway. In addition, aged TEs altered gut microbiota composition and gut metabolite profiles associated with T2DM. Together, all three aged TEs (400 mg/kg/day in mice, a human equivalent dose of 7 g/60 kg/day), especially 2011, can effectively alleviate T2DM, and proper storage can effectively improve the ability of oolong tea to alleviate T2DM.

Detection and management of perioperative blood glucose abnormalities†

Abstract Diabetes mellitus is a common chronic disease. With the improvement of living standards, the prevalence of diabetes mellitus in China is increasing. There are now more people with diabetes in China (>100 million) than in any other country. About half of these people with diabetes need to undergo at least one procedure in their lifetime. Diabetic patients have a much higher probability of perioperative dysglycemia than the normal population, which has a great impact on their prognosis. In addition, non-diabetic patients may also have abnormal blood glucose levels due to various reasons during the perioperative period, which will also lead to a series of adverse consequences. This article reviews the perioperative blood glucose management of patients to provide a reference for improving their health status.

An IoT-fuzzy intelligent approach for holistic management of COVID-19 patients

In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the present study is to develop an integrated tool that combines IoT and fuzzy logic to provide timely healthcare and diagnosis within a smart framework. This system tracks patients' health by utilizing an Arduino microcontroller, a small and affordable computer that reads data from various sensors, to gather data. Once collected, the data are processed, analyzed, and transmitted to a web page for remote access via an IoT-compatible Wi-Fi module. In cases of emergencies, such as abnormal blood pressure, cardiac issues, glucose levels, or temperature, immediate action can be taken to monitor the health of critical COVID-19 patients in isolation. The system employs fuzzy logic to recommend medical treatments for patients. Sudden changes in these medical conditions are remotely reported through a web page to healthcare providers, relatives, or friends. This intelligent system assists healthcare professionals in making informed decisions based on the patient's condition.

Novel α-Glucosidase Inhibitory Peptides Identified In Silico from Dry-Cured Pork Loins with Probiotics through Peptidomic and Molecular Docking Analysis.

Diabetes mellitus is a serious metabolic disorder characterized by abnormal blood glucose levels in the body. The development of therapeutic strategies for restoring and maintaining blood glucose homeostasis is still in progress. Synthetic alpha-amylase and alpha-glucosidase inhibitors can improve blood glucose control in diabetic patients by effectively reducing the risk of postprandial hyperglycemia. Peptides of natural origin are promising compounds that can serve as alpha-glucosidase inhibitors in the treatment of type 2 diabetes. Potential alpha-glucosidase-inhibiting peptides obtained from aqueous and saline extracts from dry-cured pork loins inoculated with probiotic LAB were evaluated using in vitro and in silico methods. To identify the peptide sequences, liquid chromatography-mass spectrometry was used. For this purpose, in silico calculation methods were used, and the occurrence of bioactive fragments in the protein followed the ADMET approach. The most promising sequences were molecularly docked to test their interaction with the human alpha-glycosidase molecule (PDB ID: 5NN8). The docking studies proved that oligopeptides VATPPPPPPPK, DIPPPPM, TPPPPPPG, and TPPPPPPPK obtained by hydrolysis of proteins from ripening dry-cured pork loins showed the potential to bind to the human alpha-glucosidase molecule and may act effectively as a potential antidiabetic agent.

A Feasibility Study of Diabetic Retinopathy Detection in Type II Diabetic Patients Based on Explainable Artificial Intelligence.

Diabetic retinopathy (DR) is vision impairment and a life-threatening condition for diabetic patients. Especially type II diabetic people have higher chances of getting retinal problems. Hence, early prediction of DR is necessary for preventing the diabetic patients from vision impairment. The main aim of this feasibility study is to identify the most critical risk features that could lead to diabetic retinopathy. This study investigated type II diabetic patients' socio-analytical, diabetes, behavioral, and clinical risk factors. We conducted a self-individual questionnaire session for all participants. Our questionnaire asked about the reliability of results, feeling comfortable during the screening test, willingness to participate in future screenings, overall perspective, and satisfaction with the DR screening test. We proposed a random forest model for predicting the prevalence of DR risk among diabetics. Further explanations of the model were conducted using more robust SHAP eXplainable Artificial Intelligence (XAI) tools. The SHAP method makes it possible to understand how input variables interact with their representative output records, as well as how input variables are ranked. In addition, various descriptive and inferential statistical analyses were performed on the data and evaluated the significant relationship between the factors discussed above via hypothesis testing. This feasibility study involved 172 type II diabetic patients (73 males and 99 females). Therefore, we found that 81 (47.09%) out of 172 participants had referable DR. The average age of the patients was determined as 55.08, with a standard deviation of ± 9.770 (ranging from 40 to 79). Type II patients were affected by mild, moderate, severe, and advanced proliferative diabetic retinopathy (PDR) stages with 23.83%, 13.95%, 5.81%, and 3.48%, respectively, of the total samples. The developed RF model obtained high accuracy of 94.9% using clinical dataset. Our results showed that the formation of tiny microminiature lesions was noticeable in type II diabetic patients with aged people, abnormal blood glucose levels, and prolonged diabetes duration.

One-step integrated coronary–carotid–cerebral computed tomography angiography to evaluate cardiovascular and cerebrovascular atherosclerosis

PurposeThis study aims to develop a low-radiation dose, one-step integrated coronary–carotid–cerebral computed tomography angiography (ICCC-CTA) technique to analyze the relationship between cardiovascular and cerebrovascular atherosclerosis and evaluate the risk factors of plaque to provide an early-stage treatment to patients and reduce vascular events.MethodsA total of 300 consecutive asymptomatic patients with cardiovascular risk factors who underwent ICCC-CTA were enrolled in this prospective study. The association between coronary and carotid-cerebrovascular atherosclerosis was assessed. The primary cardiovascular risk factors for various plaque types in cardiovascular or cerebrovascular disease were evaluated using multivariate analysis.ResultsAmong 300 patients, 189 (63%) had plaques in their coronary and cerebral arteries. The presence of calcified and mixed plaques in the carotid-cerebral and coronary arteries was strongly correlated (χ2 = 20.71, P = 0.001; χ2 = 8.96, P = 0.003, respectively). Multivariate logistic regression analysis revealed that abnormal blood glucose [OR = 1.44, 95% CI 0.12–0.62, P = 0.01] and abnormal total cholesterol [OR = 1.28, 95% CI 0.07–0.46, P = 0.01] are risk factors in all the models in the coronary artery, non-calcified plaque group. Abnormal blood glucose [OR = 1.43, 95% CI 0.11–0.61, P = 0.01] and abnormal systolic blood pressure [OR = 1.02, 95% CI 0.01–0.04, P = 0.02] are risk factors in all the models in the coronary artery calcified plaque group. Abnormal blood glucose level [OR = 1.44, 95% CI = 0.12–0.62, P = 0.01] was only a risk factor in the non-calcified plaque carotid–cerebral artery group.ConclusionsWe confirm that elevated blood glucose and total cholesterol levels are associated with coronary and carotid-cerebrovascular plaques using the novel one-step low dose cerebral-carotid-cardiac CTA technique. These findings will provide insights for further studies focusing on developing low-radiation dose one-step ICCC-CTA to screen cardiovascular/cerebrovascular plaques in general population with cardiovascular risk factors.Advances in knowledgeWe developed a low–radiation dose, one-step ICCC-CTA technique to detect cardiovascular and cerebrovascular atherosclerosis. We evaluated the risk factors for plaque burden for the early treatment and reduction of vascular events. These findings supported the development of low–radiation dose one-step ICCC-CTA to screen for cardiovascular/cerebrovascular disease in general population with cardiovascular risk factors.

The risk factors analysis of diabetes mellitus and hypertension in the population of district Swabi, Khyber Pakhtunkhwa, Pakistan

Diabetes is the major non-contagious, long-lasting epidemic disease caused by abnormal blood glucose levels resulting from the disablement in insulin action and secretion. The objective of the study is to estimate diabetes mellitus and risk factors of diabetes mellitus in the population of district Swabi, Khyber Pakhtunkhwa, Pakistan. A total of 150 blood samples are collected from March-July 2021. All diabetic patients are screened randomly using a spectrophotometer (Micro Lab 300). At the same time, data regarding subjective information, socioeconomic status, and behavioural risk factors are collected by personal interviews, which are further statistically analysed. Results show that the frequency distribution of diabetes is n= 107 (71.3%) while n= 43 (28.7%) of the total n=150 are normal. Mean±sd of the data is 1.29±0.45. There is a significant association between diabetes mellitus and hypertension (n= 95, 63%, Cl 95%, and P-value 0.041). Hyperglycaemia is n= 109 (72.7% and P-value 0.00), and anxiety/depression is n= 95 (63% and P-value 0.004). Gender, age, education, and smoking (p-value > 0.05) are non-significant risk factors for diabetes. The findings show a significant association among diabetes mellitus, hypertension, hyperglycaemia, and depression.

SGLT2 inhibitors can reduce the incidence of abnormal blood glucose caused by statins in non-diabetes patients with HFrEF after PCI

BackgroundTaking statins for a long time is associated with an increased risk of new-onset diabetes mellitus. Sodium-glucose cotransporter-2 (SGLT2) inhibitors can reduce insulin resistance and improve pancreatic β-cell function.Methods and resultsIn total, 333 non-diabetes patients with heart failure with reduced ejection fraction (HFrEF) after percutaneous coronary intervention (PCI) are included. The enrolled patients are divided into a matched group (n = 198) and an SGLT2 inhibitors group (n = 135). There are no statistical differences in general information between the two groups before treatment. After a mean follow-up time of 13 months, abnormal blood glucose levels are significantly higher in the matched group than in the SGLT2 inhibitors group (6.06 vs. 0.74%, P < 0.05). There are no statistically significant differences in the alanine aminotransferase (ALT), uric acid (UA), and estimated glomerular filtration (eGFR) levels between the two groups.ConclusionSGLT2 inhibitors play a significant protective role in reducing the risk of statins-induced abnormal blood glucose in non-diabetes patients with HFrEF after PCI, without increasing the burden on the heart, kidneys, and liver.

Gymnema sylvestre extract ameliorated streptozotocin‐induced hyperglycemia in T2DM rats via gut microbiota

AbstractGymnema sylvestre (GS) has been traditionally used to treat diabetes mellitus (DM) and consumed as both food and medicine. The present work aimed to reveal the arresting hypoglycemic properties of GS leaves on type 2 DM (T2DM) rats meditated by gut microbiota pathway. After administration for 30 days, GS treatment observably improved the abnormal fasting blood glucose (FBG) levels, lipid profiles, and the glucose tolerance of the T2DM rats in a dose‐dependent manner. Furthermore, GS treatment reversibly restored the gut microbiota diversities in the T2DM rats based on the decreased Firmicute abundance and boosted Bacteroidetes abundance and Firmicutes/Bacteroidetes ratio. Particularly, the KEGG pathway suggested that GS treatment strongly interfered with the glucose metabolism processes, such as the glycolysis from glucose 6‐phosphate and glucose, along with the changes in the relative abundances of the beneficial bacteria of Clostridium, Lactobacillus, and Bacteroides. In addition, the GS treatment dramatically promoted the contents of the acetic acid, the total short‐chain fatty acids in the T2DM rat feces. This study showcased the remarkable amelioration of GS on the metabolic disorders of blood glucose and lipids via the regulation of gut microbiota in T2DM rats, which could offer a new mechanism of GS as a potential natural antidiabetic food supplement for T2DM.

Visual Evoked Potentials for the Detection of Diabetic Retinal Neuropathy.

Visual evoked potentials (VEP) are visually evoked signals that extract electroencephalographic activity in the visual cortex that can detect retinal ganglion cells, optic nerves, chiasmal and retrochiasmal dysfunction, including optic radiations, and the occipital cortex. Because diabetes causes diabetic retinopathy due to microangiopathy and neuropathy due to metabolic abnormalities and intraneural blood flow disorders, assessment of diabetic visual pathway impairment using VEP has been attempted. In this review, evidence on the attempts to assess the visual pathway dysfunction due to abnormal blood glucose levels using VEP is presented. Previous studies have provided significant evidence that VEP can functionally detect antecedent neuropathy before fundus examination. The detailed correlations between VEP waveforms and disease duration, HbA1c, glycemic control, and short-term increases and decreases in blood glucose levels are evaluated. VEP may be useful for predicting postoperative prognosis and evaluating visual function before surgery for diabetic retinopathy. Further controlled studies with larger cohorts are needed to establish a more detailed relationship between diabetes mellitus and VEP.

Pathophysiology and diagnosis of diabetic retinopathy: a narrative review.

Diabetes is an endocrine disorder which is known by abnormal high blood glucose levels. There are two main categories of diabetes: type I (10%-15%) and type II (85%-90%). Although type II is more common, type I is the most common form in children. Diabetic retinopathy (DR), which remains the foremost cause of losing vision in working-age populations, can be considered as the main complication of diabetes mellitus. So choosing the best method for diagnosing, tracking, and treating the DR is vital to enhance the quality of life and decrease the medical expenses. Each method for diagnosing DR has some advantages and the best way must be selected according to the points that we need to find. For writing this manuscript, we made a list of relevant keywords including diabetes, DR, pathophysiology, ultrawide field imaging, fluorescein angiography, optical coherence tomography, and optical coherence tomography-angiography, and then we started searching for studies in PubMed, Scopus, and Web of Science databases. This review article covers the pathophysiology of DR and medical imaging techniques to monitor DR. First, we introduce DR and its pathophysiology and then we present the medical imaging techniques to monitor it.

Characteristics of the oral glucose tolerance test in women with different pre-pregnancy body mass index and the effect of gestational diabetes mellitus on twin pregnancy outcomes

ObjectiveThis study aimed to investigate the mid-pregnancy blood glucose levels of women with singleton or twin pregnancies. MethodThe relationship between blood glucose levels and Gestational Diabetes Mellitus (GDM) was studied in women with different pre-pregnancy Body Mass Index (BMI), and the effect of GDM on twin pregnancy outcomes was analyzed. Women with twin (n = 1,985) and singleton (n = 1,985) pregnancies were categorized into underweight (BMI < 18.5 kg/m2, n = 597), normal weight (BMI: 18.5–23.9 kg/m2, n = 2,575), and overweight/obese (BMI ≥ 24 kg/m2, n = 798) groups. ResultsThe incidence of GDM was 21.01% in women with twin pregnancies. Among the women with GDM in twin pregnancies, 38.37% had at least two abnormal blood glucose levels. The incidence of these parameters increased with preconception BMI, and the incidence of twin pregnancies was higher than that of singleton pregnancies (p < 0.001). In the normal weight and overweight/obese group, the oral glucose tolerance test glucose level and incidence of GDM were higher in women with twin than singleton pregnancies (p < 0.05). For twin pregnancies, the prevalence of selective fetal growth restriction was higher and anemia was lower in the GDM group than in the non-GDM group (all p < 0.05). ConclusionTherefore, a greater emphasis should be placed on BMI before conception, and well-controlled GDM does not increase adverse pregnancy outcomes for twin pregnancies.

Magnetic Resonance Imaging and Spectroscopy Methods to Study Hepatic Glucose Metabolism and Their Applications in the Healthy and Diabetic Liver.

The liver plays an important role in whole-body glucose homeostasis by taking up glucose from and releasing glucose into the blood circulation. In the postprandial state, excess glucose in the blood circulation is stored in hepatocytes as glycogen. In the postabsorptive state, the liver produces glucose by breaking down glycogen and from noncarbohydrate precursors such as lactate. In metabolic diseases such as diabetes, these processes are dysregulated, resulting in abnormal blood glucose levels. Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) are noninvasive techniques that give unique insight into different aspects of glucose metabolism, such as glycogenesis, glycogenolysis, and gluconeogenesis, in the liver in vivo. Using these techniques, liver glucose metabolism has been studied in regard to a variety of interventions, such as fasting, meal intake, and exercise. Moreover, deviations from normal hepatic glucose metabolism have been investigated in both patients with type 1 and 2 diabetes, as well as the effects of antidiabetic medications. This review provides an overview of current MR techniques to measure hepatic glucose metabolism and the insights obtained by the application of these techniques in the healthy and diabetic liver.

Proteomics profiles of blood glucose-related proteins involved in a Chinese longevity cohort

BackgroundHigh blood glucose level is one of the main characteristics of diabetes mellitus. Based on previous studies, it is speculated longevity families may have certain advantages in blood glucose regulation. However, limited information on these items has been reported. The purpose of this study was to profile differences of plasma proteomics between longevity subjects (with normal fructosamine (FUN) level) and non-longevity area participants (with exceeding standard FUN level).MethodsIn this study, a TMT-based proteomics analysis was used to profile differences of plasma proteomics between longevity subjects (with normal FUN level) and non-longevity area participants (with exceeding standard FUN level). Results were validated by Luminex detection.ResultsA total of 155 differentially expressed proteins (DEPs) were identified between these two groups. The DEPs related to blood glucose regulation were mainly involved in glycolysis/gluconeogenesis, pyruvate metabolism and propanoate metabolism, and most of the DEPs were contained in carbohydrate metabolism, PI3K-Akt pathway, glucagon signaling pathway and inflammatory response. Validation by Luminex detection confirmed that CD163 was down-regulated, and SPARC, PARK 7 and IGFBP-1 were up-regulated in longevity participants.ConclusionsThis study not only highlighted carbohydrate metabolism, PI3K-Akt pathway, glucagon signaling pathway and inflammatory response may play important roles in blood glucose regulation, but also indicated that YWHAZ, YWHAB, YWHAG, YWHAE, CALM3, CRP, SAA2, PARK 7, IGFBP1 and VNN1 may serve as potential biomarkers for predicting abnormal blood glucose levels.

AAL and Internet of Medical Things for Monitoring Type-2 Diabetic Patients.

Due to an aging population, assisted-care options are required so that senior citizens may maintain their independence at home for a longer time and rely less on caretakers. Ambient Assisted Living (AAL) encourages the creation of solutions that can help to optimize the environment for senior citizens with assistance while greatly reducing their challenges. A framework based on the Internet of Medical Things (IoMT) is used in the current study for the implementation of AAL technology to help patients with Type-2 diabetes. A glucose oxide sensor is used to monitor diabetic elderly people continuously. Spectrogram images are created from the recorded data from the sensor to assess and detect aberrant glucose levels. DenseNet-169 examines and analyzes the spectrogram pictures, and messages are sent to caregivers when aberrant glucose levels are detected. The current work describes both the spectrogram image analysis and the signal-to-spectrogram generating method. The study presents a future perspective model for a mobile application for real-time patient monitoring. Benchmark metrics evaluate the application's performances, including sensitivity, specificity, accuracy, and F1-score. Several cross--validations are used to evaluate the model's performance. The findings demonstrate that the proposed model can correctly identify patients with abnormal blood glucose levels.

Chest X-Ray pattern and lung severity score in COVID-19 patients with diabetes mellitus: A cross sectional study

BackgroundDiabetes mellitus is a chronic hyperglycemic condition that can affect the body's immune response to SARS-CoV-2 This study aimed to determine the relationship between diabetes mellitus and lung severity in COVID-19 patients. Methods: A cross-sectional design was conducted at Hasan Sadikin General Hospital during the January–May 2021 period. Data were based on medical records of patients aged 18 years and over with COVID-19. The chi-square test was performed to assess the relationship between diabetes mellitus and lung severity based on the BRIXIA score. Results: This study included 538 subjects, mostly aged <60 years (71.9%) and female (60.2%). A total of 125 subjects had abnormal blood glucose levels with an average HbA1c of 9.00 ± 1.77% in patients with diabetes mellitus and a median HbA1c of 5.85% (4.5–6.4%) in patients with reactive hyperglycemia. Lung abnormalities were found in 357 subjects (66.4%). The results of the BRIXIA score to assess lung severity found as many as 77 subjects (14.3%) had a score of 11–18 with 14 people with diabetes mellitus, five people with reactive hyperglycemia. In the population aged ≥60 years, as many as 32 people had a score of 11–18 with three people with diabetes mellitus, two with reactive hyperglycemia and 27 with normal blood glucose. A significant relationship was found between diabetes mellitus and lung severity (p = 0.024). Conclusion: There is a significant relationship between diabetes mellitus and lung severity in COVID-19 patients aged ≥60 years.

Implementation of Transtheoretical Model Nutrition Education and Chromium Picolinate Supplementation on Improved Dietary Adherence Behavior, Chromium Consumption Pattern and Blood Glucose Level Diabetes Mellitus Patients

Bali is one of the provinces in Indonesia that has a Diabetes Mellitus rate above the national prevalence. According to the results of the 2020 study, 56.9% of DM patients did not understand diet education and did not comply with the diet by 56.9% with abnormal blood glucose levels of 63.9%. The results confirmed that repeated exposure with the right method, especially with The theoretical model is very effective in increasing knowledge and adherence to diet and chromium consumption patterns in DM patients. Chromium is effective in improving blood glucose levels in people with Diabetes Mellitus (Types 1 and 2). Chromium improves glucose metabolism in patients with prediabetic glucose intolerance and all women with gestational diabetes. The purpose of this study was to determine the role of nutrition education using a transtheoretical model and the effect of chromium picolinate supplementation on dietary adherence behavior, chromium consumption patterns, and blood glucose levels in patients with diabetes mellitus. This type of research is quasi-experimental. The research design used was one group pretest-posttest. This design does not use a comparison group (control) but uses the first observation (pretest) which allows testing the changes that occur after the experiment or program (Notoatmodjo, 2010). The study was conducted at the Denpasar Health Center. The results showed that there were differences in the level of knowledge and consumption of chromium and blood glucose levels in DM patients. However, there was no difference in the attitude and level of dietary compliance of DM patients.

The Gut Mycobiome Characterization of Gestational Diabetes Mellitus and Its Association With Dietary Intervention.

Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The active interface between gut microbiota and diet contributes to metabolic homeostasis in GDM. However, the contributions of gut mycobiome have been neglected. Here, we profiled the gut fungi between GDM and healthy subjects at two time points and investigate whether variations in gut mycobiome correlate with key features of host metabolism and diet management in this observational study. We identified that Hanseniaspora, Torulaspora, Auricularia, Alternaria, and Candida contributed to GDM patient clustering, indicating that these fungal taxa are associated with abnormal blood glucose levels, and the causality needs to be further explored. While Penicillium, Ganoderma, Fusarium, Chaetomium, and Heterobasidion had significant explanatory effects on healthy subject clustering. In addition, spearman analysis further indicated that blood glucose levels were negatively correlated with polysaccharide-producing genera, Ganoderma, which could be reshaped by the short-term diet. The Penicillium which was negatively correlates with metabolic parameters, also exhibited the antimicrobial attribute by the fungal-bacterial interaction analysis. These data suggest that host metabolic homeostasis in GDM may be influenced by variability in the mycobiome and could be reshaped by the diet intervention. This work reveals the potential significance of the gut mycobiome in health and has implications for the beneficial effects of diet intervention on host metabolic homeostasis through regulating gut fungal abundance and metabolites.