Energy-restricted (ER) diets promote weight loss and improve body composition and glycaemic control. Nut consumption also improves these parameters. However, less is known about the combined benefit of these two strategies. This scoping review implemented a systematic search of Medline, Embase and Scopus to identify randomised controlled trials evaluating the effect of ER diets with or without nuts on body mass, body composition and glycaemic control in adults. After reviewing titles and abstracts, twenty-nine full-text articles were screened, resulting in seven studies reported in eight papers that met the inclusion criteria. Energy restriction was achieved by prescribing a set energy target or reducing intake by 1000-4200 kJ from daily energy requirements. Interventions ranged from 4 to 52 weeks in duration and contained 42-84 g/d of almonds, peanuts, pistachios or walnuts. While all studies reported that energy restriction resulted in significant weight loss, the addition of nuts to ER diets demonstrated significantly greater weight loss in only approximately half of the included studies (4/7 studies). There was limited evidence to support additional benefits from nuts for body composition measures or glycaemic control. Although improvements in weight loss and glycaemia were not consistent when nuts were included in ER diets, no study revealed an adverse effect of nut consumption on health outcomes. Future studies could explore the effect of consuming different types and amounts of nuts, combined with various levels of energy restriction on weight, body composition and glycaemic control.

Caesalpinia bonduc (L.) and Gymnema sylvestre (Retz.) are traditional remedies for diabetes management. This study explored their potential synergistic effects in alloxan (ALX)-induced diabetic Wistar rats. Aqueous-methanol extracts of C. bonduc seed kernels (C. bonduc extract [CBE]) and G. sylvestre leaves (G. sylvestre extract [GSE]) were phytochemically characterized. In vivo, experimental diabetic rats were treated with metformin (MET; 150 mg/kg), CBE (400 mg/kg), GSE (400 mg/kg), and a combined dose of CBE + GSE at 400 mg/kg (200 mg/kg of each plant extract) for 28 days. Biochemical analyses revealed significant antioxidant and hypoglycemic effects of the extracts, with the combined treatment (CBE + GSE) demonstrating superior outcomes. This combination improved fasting blood glucose, insulin, glycated hemoglobin A1c (HbA1c), and oxidative stress markers, including superoxide dismutase (SOD) and catalase (CAT) activities. Additionally, CBE + GSE significantly modulated insulin secretion and stress-related gene expression while downregulating the c-Jun N-terminal kinase (JNK)/mitogen-activated protein kinase (MAPK) pathway. Histopathological results further confirmed the enhanced antidiabetic effects of the combination therapy. These findings suggest that the combined use of C. bonduc and G. sylvestre offers a promising therapeutic approach for diabetes management due to the complementary pharmacological activities of their phytochemicals.

Diabetes is a complex metabolic disorder affecting over 37 million people in the United States. Without proper management, diabetes can lead to a myriad of complications, including cardiovascular disease, kidney failure, and vision loss. Obesity is a major contributor to type 2 diabetes, but genetic and physiological factors make weight loss difficult, necessitating medication management for both conditions. Government-approved weight loss medications, including glucagon-like peptide-1 agonists and amylin analogs, have proven to be effective for both conditions. However, intensive glycemic control involving antidiabetic medications, while beneficial for reducing diabetic complications, can often precipitate hypoglycemic events, which are characterized by cardiac arrhythmias, coma, confusion, and even mortality. A new drug under investigation, CagriSema, combines cagrilintide, an amylin analog, with semaglutide, a glucagon-like peptide-1 agonist. This drug is being marketed as a safe and potentially superior medication to lower both Hemoglobin A1c and body weight. In this article, the pathophysiology, current guidelines, and management of diabetes will be reviewed, with an emphasis on the clinical evidence for tight glucose control and avoiding hypoglycemic events. Following this, an overview of recent trials on antidiabetic medications, including those involving CagriSema, will be presented, along with prospects for future trials in this promising area of research.

Diabetes mellitus (DM) prevalence in Qatar is among the highest worldwide. DM has been shown to be associated with reduced performance on numerous domains of cognitive function in elderly population. Here, we sought to determine whether such association also exists in a middle-aged cohort.

A cross-sectional study was conducted using data from 981 participants aged 40-65 years from the Qatar Biobank. We analyzed glycemic indices: HbA1c, serum glucose, insulin levels, waist circumference, and waist-hip ratio. Cognitive function was assessed using two domains of CANTAB: the paired episodic memory (visual memory) and reaction time (motor and mental speed).

We found significant associations between DM and cognitive impairment. Poor reaction speed was linked to DM (beta 36.80, P < 0.01), higher HbA1c levels (beta 10.73, P < 0.05), larger waist circumference (beta 1.70, P < 0.001), and higher waist-to-hip ratio (beta 252.56, P ≤ 0.01). Poor memory performance was also associated with increased waist circumference and waist-to-hip ratio.

The negative association between DM, its biomarkers, and cognitive impairment reported previously in elderly populations also exists in middle-aged individuals. Further research is needed to explore the causality and impact of dysglycemia on other cognitive domains.

Diabetic nephropathy remains a strong risk factor for chronic kidney disease progression. Hemoglobin A1C (HBA1C) has historically been used as a marker for complications related to diabetes. The purpose of this study is to examine the relationship between HBA1C and clinical complications in a patient population with end stage renal disease.

This was a prospective study performed using patients from multiple outpatient dialysis centers in Texas, United States. All patients included patients must have end stage renal disease and were receiving either hemodialysis or peritoneal dialysis. An HBA1C ≥ 6.5% was used as a cutoff to differentiate patients with well controlled versus uncontrolled diabetes in this population.

HBA1C ≥ 6.5% was strongly associated with both minor (P = 0.0014) and major (P = 0.006)amputation. Patients with HBA1C ≥ 6.5% was associated with lower mortality compared to patients with HBA1C < 6.5%, P = 0.007.

HBA1C remains a reliable marker for amputation in patients with end-stage renal disease; however, there is skepticism in using HBA1C as a marker for survival in these patients.

Circannual fluctuations in glycated haemoglobin (HbA1c) levels are recognized among adults, but comparable changes and contributing factors in adolescents with type 1 diabetes (T1D) have not been investigated in depth.

To examine the seasonal changes in HbA1c and their association with body composition in youth with T1D.

This retrospective observational study included adolescents with T1D followed at our paediatric diabetes centre (2021-2023). Seasonal means were calculated for two periods (winter-spring: December to May and summer-autumn: June to November), and ΔHbA1c was calculated as the difference between the values. The patients' body composition (via bioelectrical impedance analysis (BIA)) data were reviewed, and correlation analyses were performed between sex- and age-adjusted z-scores of body composition components [appendicular muscle mass (ASMM) and fat mass (FATM)] and ΔHbA1c.

The seasonal means of HbA1c calculated for 259 adolescents with T1D (56% male, mean age: 16.01 ± 2.23 years) were significantly higher during winter-spring compared to summer-autumn (7.75% vs. 7.24%, p < 0.001, CI: 0.42-0.57), (61.16 mmol/mol vs. 55.72 mmol/mol, respectively p < 0.001, CI: 4.64-6.23). ΔHbA1c displayed a sex-specific association with body composition components in 102 patients (50% males) who underwent BIA. The correlation was significant for only ASMM z-scores in boys (r = 0.277, p = 0.049), while both the ASMM and FATM z-scores significantly correlated with ΔHbA1c (r = 0.301, p = 0.032 and r = 0.284, p = 0.043, respectively) in girls.

There is a seasonal variation in HbA1c levels in adolescents with T1D, with higher values during winter-spring. The link between seasonal variability and body composition components varied by sex, indicating a need for sex-specific strategies in adolescent diabetes management.

Vigna sesquipedalis is traditionally used for the treatment of various disorders including diabetes but without scientific rational. Therefore, the current study was designed to evaluate its anti-diabetic potential. Antioxidant activity was assessed through DPPH and ABTS radical scavenging assays, while α-glucosidase and α-amylase inhibitory activities for anti-diabetic potential. Based on in vitro results, acute toxicity tests were performed, followed by in vivo studies using streptozotocin-induced diabetic model in mice. The ethyl acetate fraction exhibited the highest antioxidant potential, followed by crude extract. The methanolic crude extract showed the strongest in vitro antidiabetic activity. It was also found to be non-toxic up to 2000 mg/kg body weight. In vivo, the crude extract significantly (P < 0.05) improved body weight and displayed significant anti-diabetic effects. Further analysis of liver glycogen, serum insulin, glycosylated hemoglobin, and histopathology supported the extract overall performance. The virtual screening results showed highest binding energy of the Cyanidin-3-0-G (Cyanidin) with the amylase, Daucosterol with the GLP1, and Psoralidin with the Glucosidase. Similarly, MD simulation of the top hits was performed to investigate the dynamic stability and results showed that the ligand-protein system remains stable for during the simulation. The thermodynamic stability of the system was assessed by performing the binding free energy calculation using MM-PBSA/GBSA. The results of the binding free energy calculations showed favorable binding energies ligand-protein system. In short, the results illustrated potential as a pharmaceutical drug for insulin-dependent diabetes mellitus.

The worldwide incidence of diabetes mellitus (DM), as a long-term metabolic condition, continues to rise, creating an urgent need for accurate and efficient diagnostic methods to identify and treat the disease early. Among various analytical technologies, electrochemical biosensors stand out for their exceptional attributes, including precise detection, selective response, quick results, and affordable implementation. The current review study examines the latest developments in electrochemical biosensor technology designed specifically for diabetes detection, emphasizing novel approaches in blood sugar monitoring and tracking key diabetes indicators, including HbA1c, insulin levels, and ketones. The discussion encompasses cutting-edge developments such as sensors incorporating nanomaterials, non-enzymatic detection systems, and portable monitoring devices, emphasizing how these innovations improve both technical capabilities and patient experience. This review also demonstrates how next-generation electrochemical biosensors could fundamentally change diabetes care and monitoring, leading to more widely available and accurate disease tracking methods.

Background/Objectives: The determination of glycated haemoglobin (HbA1c) is a cornerstone of the diagnosis and management of diabetes mellitus, serving as a reliable biomarker for assessing long-term glycaemic control. While high-performance liquid chromatography (HPLC) is regarded as the gold standard for HbA1c measurement, its widespread adoption is limited by high costs, operational complexity, and resource requirements. Alternative methodologies, including immunoturbidimetric assays, have garnered interest as practical solutions. This study evaluates the analytical performance of an immunoturbidimetric method for HbA1c determination and its comparability with a validated HPLC method. Methods: The evaluation process was conducted in accordance with the Clinical and Laboratory Standards Institute (CLSI) guidelines. The results from 178 human sample leftovers, covering the medical decision range, were compared with those obtained using the HPLC-based Menarini ADAMS A1c HA-8180T system. The analytical performance regarding repeatability and within-laboratory imprecision was also assessed. The probability risk of misinterpreting the analytical results was also calculated. Results: The Passing-Bablok regression indicated a strong correlation between the two methods, with a slope of 1.00 (95% CI: 1.00 to 1.04). The Bland-Altman analysis confirmed minimal systematic differences, showing a mean bias of -0.07% for NGSP and -0.74 mmol/mol for IFCC, both falling within the predefined total allowable error (ATE) limits. Imprecision studies demonstrated excellent repeatability and intermediate precision, with coefficients of variation (CV) ranging from 0.68% to 2.4% across all levels. The risk assessment of diagnostic misinterpretation indicated minimal deviation from an ideal analytical system, in which the measurement uncertainty was regarded as zero. Conclusions: The findings establish the immunoturbidimetric method as a reliable and cost-effective alternative to HPLC for routine HbA1c determination. Its strong analytical performance, combined with operational efficiency, makes it a valuable tool for laboratories, particularly in resource-limited settings, enhancing access to high-quality diabetes monitoring.

Effective perioperative blood glucose control is crucial for reducing postoperative complications in patients with diabetes mellitus (DM) who are undergoing total knee arthroplasty (TKA). The aim of this study was to assess the impact of intravenous (IV) dexamethasone on blood glucose levels, insulin requirements, postoperative pain, and postoperative nausea and vomiting (PONV) in patients with well-controlled type-2 DM.

A total of 83 Asian patients with well-controlled type-2 DM (defined as a preoperative glycated hemoglobin level of ≤7.0%) undergoing primary TKA were randomized to receive either IV dexamethasone or normal saline solution. Blood glucose and insulin requirements were monitored postoperatively up to day 5, and pain and PONV were assessed using a numeric rating scale.

Compared with the control, IV dexamethasone transiently elevated blood glucose levels on the day of surgery and on postoperative day 1, with the levels returning to baseline by day 3. Insulin requirements were higher in the intervention group on postoperative day 1 (p = 0.004). While IV dexamethasone did not significantly reduce PONV, it effectively alleviated postoperative pain up to day 3.

In patients with DM who underwent TKA, IV dexamethasone administration transiently increased blood glucose on the day of surgery and on postoperative day 1 and elevated insulin requirements on postoperative day 1. Despite having no impact on PONV, IV dexamethasone provided clinical benefits by reducing early postoperative pain. These findings suggest the potential benefits of IV dexamethasone in enhancing perioperative management strategies for patients with DM who are undergoing TKA.

Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.

Skin cancers are the most common cancers in Caucasians, and their incidence is rising. Although metabolic and anthropometric markers play a role in cancer development, the relationship between metabolic and anthropometric changes in skin cancer remains unclear. This study aimed to examine possible associations between these changes and the risk of skin cancer.

Participants without prior skin cancer history from the Northern Netherlands representative of the general population were included. Histopathology data were obtained from the Dutch Nationwide Pathology Database. Adjusted Cox regression analyzed associations between metabolic changes and time to pathology-confirmed skin cancer incidence over a 7-year follow-up, assessing overall skin cancer risk and subtypes, including melanoma and nonmelanoma skin cancer.

Out of 97,106 participants, 4,195 (4.3%) developed skin cancer. Decrease and increase in body mass index (BMI) were both associated with lower skin cancer risk: adjusted HRs (aHR) of 0.88 (0.80-0.98) and 0.78 (0.72-0.86), respectively. Triglyceride and waist-to-hip ratio decreases were also associated with lower risk: aHR: 0.89 (0.80-0.98) and 0.89 (0.83-0.98), respectively. Increase in Hemoglobin A1c (HbA1c) was associated with a higher risk in individuals below the age of 45 years at baseline: aHR: 1.21 (1.01-1.45). Subtype analysis showed an increase in BMI was associated with lower melanoma risk: aHR: 0.72 (0.58-0.91).

Changes in BMI and decrease in triglycerides and waist-to-hip ratio are related to lower skin cancer risk, whereas an increase in HbA1c may elevate risk in individuals younger than 45 at baseline. These findings highlight the importance of non-sunlight-related risk factors for skin cancer prevention and the need for further research into underlying mechanisms.

This study contributes to the broader understanding of how metabolic health impacts skin cancer development, offering potential avenues for targeted prevention strategies.

The phase angle is a mathematical concept representing the time relationship between two periodic waveforms, and has gained some importance for its potential clinical applications. The purpose of this review was to investigate the role of phase angle in diabetes mellitus.Studies have investigated the relationship between the phase angle and glycemic control, insulin resistance, and diabetes-related complications. Phase angle has demonstrated its potential as a prognostic marker for diabetic complications, enabling early identification and intervention. It might be beneficial for evaluating disease severity, monitoring treatment response, and predicting long-term results in diabetics.

Although the phase angle offers significant advantages, its clinical use in managing diabetes is still in its early stages, and there are certain issues that need to be resolved. Standardization of measurement techniques and interpretation criteria is essential to ensure consistency and comparability across studies and clinical settings. Investigating the role of phase angle in the treatment of diabetes provides significant knowledge about its potential as a non-invasive and informative parameter. Identifying the importance of phase angle in diabetes might help to improve risk stratification, treatment strategies, and patient outcomes. Additional research is required to determine its therapeutic value and discover the mechanisms underlying its association with diabetes and its complications.

Peripheral neuropathy is a common complication of type 2 diabetes, which is strongly associated with obesity1, causing sensory loss and, in some patients, neuropathic pain2,3. Although the onset and progression of diabetic peripheral neuropathy is linked with dyslipidaemia and hyperglycaemia4, the contribution of inflammation to peripheral neuropathy pathogenesis has not been investigated. Here we used a high-fat, high-fructose diet (HFHFD), which induces obesity and prediabetic metabolic changes, to study the onset of peripheral neuropathy. Mice fed the HFHFD developed persistent heat hypoalgesia after 3 months, but a reduction in epidermal skin nerve fibre density manifested only at 6 months. Using single-cell sequencing, we found that CCR2+ macrophages infiltrate the sciatic nerves of HFHFD-fed mice well before axonal degeneration is detectable. These infiltrating macrophages share gene expression similarities with nerve-crush-induced macrophages5 and express neurodegeneration-associated microglial marker genes6, although there is no axon loss or demyelination. Inhibiting the macrophage recruitment by genetically or pharmacologically blocking CCR2 signalling resulted in more severe heat hypoalgesia and accelerated skin denervation, as did deletion of Lgals3, a gene expressed in recruited macrophages. Recruitment of macrophages into the peripheral nerves of obese prediabetic mice is, therefore, neuroprotective, delaying terminal sensory axon degeneration by means of galectin 3. Potentiating and sustaining early neuroprotective immune responses in patients could slow or prevent peripheral neuropathy.

To investigate the effectiveness of maternal hemoglobin A1c (HbA1c) in the diagnosis of gestational diabetes mellitus (GDM) in the second trimester.

A total of 3000 pregnant women between 24 and 28 weeks of gestation were included in the study. Screening for gestational diabetes was performed using maternal HbA1c in 1200 pregnant women who either refused or could not tolerate the OGTT. The HbA1c value for the diagnosis of GDM was set at ≥ 5.7% in accordance with a meta-analysis by Paula B. Renz et al. A total of 154 pregnant women with HbA1c ≥ 5.7% were diagnosed with gestational diabetes, and their data were recorded prospectively. These data were compared with obstetric outcomes in 250 pregnant women diagnosed with diabetes by performing a 100-g OGTT after a 50-g glucose challenge test (GCT).

There were no significant differences between two groups in terms of maternal age, gestational age at diagnosis, gravidity, and parity. Body mass index (BMI) was found to be significantly higher in pregnant women with HbA1c levels ≥ 5.7% (p < 0.001). Polyhydramnios was more common in the HbA1c ≥ 5.7% group and oligohydramnios was more common in the OGTT group (p < 0.001). Neonatal hypoglycemia was found to be significantly higher in the OGTT group (p < 0.05). The median HbA1c value were different in each group (OGTT group 5.6%, HbA1c group 5.8%; p < 0.001).

HbA1c testing has lower accuracy rates than OGTT in diagnosing GDM because it may miss diagnosis in some groups.

SARS-CoV-2 poses significant challenges to people living with diabetes (PLWD). This systematic review aimed to explore the impact of COVID-19 on mortality, complications associated with diabetes and haematological parameters among PLWD.

Systematic review and meta-analysis using the Grading of Recommendations Assessment, Development and Evaluation (GRADE).

EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials and LILACS were searched between 1 December 2019 and 14 January 2025.

Eligible studies included case-control and cohort studies involving PLWD categorised into two groups: those with confirmed SARS-CoV-2 infection and those without.

Meta-analyses estimated the odds ratios (ORs) and mean differences (MDs) of outcomes including mortality, intensive care unit (ICU) admission, diabetic ketoacidosis (DKA), acute kidney injury, hospitalisation length and haematological parameters. We pooled results using random-effects models and assessed study quality with the Newcastle-Ottawa Scale. A funnel plot was used to detect potential publication bias. The overall certainty of evidence was assessed using GRADE.

25 of 7266 unique studies were eligible, including 1 154674 PLWD (561 558 with COVID-19 and 593 116 without COVID-19). SARS-CoV-2 infection in PLWD was associated with significantly increased mortality (OR 2.52, 95% CI 1.45 to 4.36, I2=99%), acute kidney injury (3.69, 95% CI 2.75 to 4.94, I2=0%), random plasma glucose in subjects with type 1 diabetes (MD 20.38 mg/dL, 95% CI 7.39 to 33.36, I2=0%), haemoglobin A1C in subjects with type 2 diabetes (0.21%, 95% CI 0.05 to 0.38, I2=13%), creatinine (0.12 mg/dL, 95% CI 0.04 to 0.19, I2=0%), C reactive protein (38.30 mg/L, 95% CI 4.79 to 71.82, I2=82%) and D-dimer (1.52 µg/mL, 95% CI 0.73 to 2.31, I2=0%). No significant differences were observed in the incidence of ICU admission and DKA, hospitalisation length, haemoglobin, leucocyte, lymphocyte, neutrophil to lymphocyte ratio, platelet, blood urea nitrogen, estimated glomerular filtration rate, procalcitonin, albumin, ferritin and bilirubin among PLWD with and without SARS-CoV-2 infection.

SARS-CoV-2 infection is associated with elevated risks of mortality and acute kidney injury and poor glycaemic control in PLWD, alongside increased levels of inflammatory and coagulation biomarkers. These findings underscore the urgent need for tailored clinical management strategies for PLWD with COVID-19.

CRD42023418039.

Type 2 diabetes is characterized by insulin resistance, which contributes to dysregulated glucose and lipid metabolism and is associated with chronic inflammation. While previous studies have examined the effects of myricitrin in streptozotocin-induced diabetic models, its impact on the db/db mouse, a model that better reflects insulin resistance-associated metabolic disturbances, remains unclear. In this study, mice were divided into three groups (db/+, db/db, and db/db + 0.02% myricitrin) and were fed their respective diets for five weeks. Myricitrin supplementation reduced fat mass, adipocyte size, and plasma leptin levels, which were elevated in db/db mice. Although myricitrin did not affect fasting blood glucose levels, it lowered plasma insulin, hemoglobin A1c, postprandial glucose levels, and the homeostasis model assessment of insulin resistance, suggesting improvements in insulin sensitivity and glucose homeostasis. Enhanced pancreatic insulin expression, along with reduced hepatic gluconeogenic enzyme activities and mRNA expression, contributed to the improved glucose homeostasis observed in myricitrin-supplemented mice. Additionally, myricitrin reduced hepatic triglyceride levels and lipid droplet accumulation by inhibiting hepatic fatty acid synthase activity. It also decreased plasma inflammatory marker levels and their mRNA expression in adipose tissue. These findings suggest that myricitrin may be a promising therapeutic candidate for type 2 diabetes.

Background: Peripheral arterial disease (PAD) is a chronic atherosclerotic disease characterized by atheromatous plaque buildup within arteries of the lower limbs. It can lead to claudication, skin ulcerations, and, in severe cases, chronic limb-threatening ischemia, requiring amputation. There are several plasma protein biomarkers that have been suggested as prognostic markers for adverse events, including major adverse cardiovascular and limb events. However, the clinical benefit and ability to clinically adapt these biomarkers remains uncertain due to inconsistent findings possibly related to heterogenous study designs and differences in methodology. Objectives: This review aims to evaluate the current literature on the prognostic value of plasma protein biomarkers for PAD, their predictive ability for PAD-related adverse outcomes, and their potential roles in guiding PAD management. Methods: To address these challenges, we conducted a systematic review of MEDLINE, Embase, and Cochrane CENTRAL libraries of the current literature (2010-2024). Results: We found 55 studies that evaluated the prognostic value of 44 distinct plasma proteins across various pathophysiological processes. These included markers of immunity and inflammation, markers of metabolism, cardiac biomarkers, markers of kidney function, growth factors and hormones, markers of coagulation and platelet function, extracellular matrix and tissue remodeling proteins, and transport proteins. This review summarizes the existing evidence for prognostic protein plasma biomarkers for PAD and their association with adverse events related to PAD. Conclusions: With this review, we hope to provide a comprehensive list of the prognostic markers and their value as prognostic biomarkers to guide clinical decision making in these patients.

The Glucose Management Indicator (GMI) is a biomarker of glycemic control which estimates hemoglobin A1c (HbA1c) based on the average glycemia recorded by continuous glucose monitoring sensors (CGMS). The GMI provides an immediate overview of the patient's glycemic control, but it might be biased by the patient's sensor wear adherence or by the sensor's reading errors. This study aims to evaluate the GMI's performance in the assessment of glycemic control and to identify the factors leading to erroneous estimates. In this study, 147 patients with type 1 diabetes, users of CGMS, were enrolled. Their GMI was extracted from the sensor's report and HbA1c measured at certified laboratories. The median GMI value overestimated the HbA1c by 0.1 percentage points (p = 0.007). The measurements had good reliability, demonstrated by a Cronbach's alpha index of 0.74, an inter-item correlation coefficient of 0.683 and an inter-item covariance between HbA1c and GMI of 0.813. The HbA1c and the difference between GMI and HbA1c were reversely associated (Spearman's r = -0.707; p < 0.001). The GMI is a reliable tool in evaluating glycemic control in patients with diabetes. It tends to underestimate the HbA1c in patients with high HbA1c values, while it tends to overestimate the HbA1c in patients with low HbA1c.

Most analyses of hemoglobin A1c (HbA1c) and multiple common diseases have focused on European populations, thus there is a need for Mendelian randomization phenome-wide association study (MR-PheWAS) in East Asian populations. We used MR-PheWAS to investigate the potential causal associations between HbA1c and 159 types of diseases in the Biobank Japan dataset, employing the inverse variance weighted as the primary statistical approach, supplemented by MR-Egger and weighted median analyses. Additionally, multiple sensitivity analyses were conducted to assess heterogeneity and pleiotropy. High HbA1c levels are associated with an increased risk of type 1 diabetes (odds ratio [OR] = 4.07; 95% confidence interval [CI]: 2.34~7.07), type 2 diabetes (OR = 4.76; 95% CI: 3.01~7.55), cataract (OR = 1.33; 95% CI: 1.18~1.51), diabetic nephropathy (OR = 5.70; 95% CI: 2.24~14.46), and peripheral arterial disease (OR = 1.62; 95% CI: 1.29~2.04). Conversely, elevated HbA1c levels are associated with a reduced risk of asthma (OR = 0.76; 95% CI: 0.67~0.86), breast cancer (OR = 0.75; 95% CI: 0.65~0.87), and cerebral aneurysm (OR = 0.71; 95% CI: 0.57~0.88). The results of the causal association between HbA1c and numerous diseases in East Asian populations provides insights for the region's specialized glycemic control and disease prevention programs, as well as new preventive and treatment options.

Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels, which lead to the glycation of proteins and the formation of advanced glycation end products (AGEs). These AGEs contribute to oxidative stress, inflammation, and the development of complications such as cardiovascular disease, nephropathy, and anemia, significantly increasing mortality rates among diabetic patients. This Review focuses on the role of glycation inhibitors as a potential strategy to prevent AGE-related pathologies. While synthetic glycation inhibitors have shown promise, their adverse effects highlight the need for safer alternatives. We specifically explore a range of natural compounds-flavonoids, curcuminoids, terpenes, stilbenes, lignans, and coumarins-that have demonstrated significant antiglycating properties. The mechanisms through which these natural products inhibit glycation, including antioxidant activity, metal ion chelation, and direct interference with the glycation process, are discussed in detail. This review underscores the potential of natural products as effective and safer glycation inhibitors, offering a promising avenue for the development of therapeutic strategies against diabetes and AGE-related disorders.

Dementia blood biomarkers are becoming increasingly important. Various factors, such as ischemic lesions and inflammation, can influence the pathomechanism of dementia. We aimed to evaluate the effects of past stroke lesions on blood biomarkers (BMs). Following approval from the institutional ethics committee, patients who were admitted to the memory clinic and were consented to written documents were enrolled (n = 111, average [standard deviation] age: 74.5 [9.1] years-old). Brain magnetic resonance imaging, cognitive function, and neuropsychological symptoms were analyzed. The amyloid-β 42 (Aβ42)/Aβ40 ratio, phosphorylated tau181 (p-tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and Aβ42/p-tau181 ratio were assessed as plasma BMs. The patients were diagnosed with Alzheimer's disease (n = 45), mild cognitive impairment (n = 56), depression (n = 8), and subjective cognitive impairment (n = 4). Bivariate analysis exhibited that all measured BM indicators were significantly associated with cognitive decline in patients without past stroke lesions. Whereas the patients with stroke lesions presented a significant association only between GFAP and cognitive decline (p = 0.0011). Multiple regression analysis showed that NfL significantly correlated with cognitive decline only in patients without stroke lesions (r = 0.4988, p = 0.0003) and with delusion only in those with stroke lesions (r = 0.5492, p = 0.0121). Past stroke lesions should be addressed in the assessment of the correlation between blood biomarkers and cognitive decline in dementia patients.

To compare the magnitude of the benefit of different exercise modalities on glycemic control, including aerobic training (AT), resistance training (RT), combined training (CT), high-intensity interval training (HIIT) and physical activity advice.

A network meta-analysis was conducted. Seven databases were searched from inception to May 2024. We included randomized clinical trials of at least 12 weeks' duration evaluating different types of physical exercise and physical activity advice to reduce HbA1c in people with type 2 diabetes.

158 studies (17,059 participants) were included. Compared with the control group, all types of exercise were associated with lower HbA1c: HIIT [-0.61 % (95 % CrI -0.84; -0.37)], CT [-0.58 % (95 % CrI -0.73; -0.42], AT [-0.58 % (95 % CrI -0.70; -0.45)], RT [-0.40 % (95 % CrI -0.59; -0.21)] and physical activity advice [-0.35 % (95 % CrI -0.53; -0.16)]. HIIT was the most effective treatment for HbA1c reduction (SUCRA = 82 %), followed by CT (SUCRA = 77 %), AT (SUCRA = 76 %), RT (SUCRA = 37 %) and physical activity advice (SUCRA = 29 %).

HIIT was associated with the greatest reduction in HbA1c. Physical activity advice, which is easy to implement, accessible and unsupervised, should also be offered to people with type 2 diabetes to improve glycemic control.

Metabolic syndrome (MetS) encompasses metabolic risk factors like elevated blood glucose, abnormal lipid levels, and hypertension. Nanocurcumin, a nanoscale formulation of curcumin, may offer therapeutic benefits for MetS management. This systematic review and meta-analysis evaluates the impact of nanocurcumin supplementation on key MetS parameters.

A systematic literature search identified 20 randomized controlled trials (RCTs) with 1394 participants. Data were pooled using a random-effects model, and standardized mean differences (SMDs) were calculated for key outcomes.

Nanocurcumin supplementation significantly improved waist circumference (WC) (standardized mean difference (SMD): -0.30 cm), fasting blood sugar (FBS) (SMD: -0.34 mg/dL), HbA1c (SMD: -0.33 %), and quantitative insulin sensitivity check index (QUICKI) score (SMD: 0.73). Lipid profile parameters, including total cholesterol (SMD: -0.18 mg/dL), LDL-C (SMD: -0.16 mg/dL), and HDL-C (SMD: 0.32 mg/dL), also reduced significantly. Improvement in diastolic blood pressure (DBP) (SMD: -0.32 mmHg), total antioxidant capacity (TAC) (SMD: 0.44 mmol/L), malondialdehyde (MDA) (SMD: -0.37 mmol/L), tumor necrosis factor-α (TNF-α) (SMD: -2.30 ng/L), interleukin-6 (IL-6) (SMD: -1.07 ng/L), and high-sensitivity C-reactive protein (hs-CRP) (SMD: -0.34 mg/L) were observed.

Nanocurcumin supplementation significantly improves multiple MetS-related parameters, including anthropometric measures, glycemic control, lipid profile, blood pressure, oxidative stress markers, and inflammatory biomarkers. These findings highlight nanocurcumin's potential as an effective adjunctive therapy for managing MetS. However, the variability in study participant ages, treatment durations, and sample sizes suggests the need for further well-designed RCTs to establish optimal usage guidelines.

Previous research has linked high coffee consumption to an increased risk of metabolic syndrome (MetS). This study aimed to assess the relationship between coffee consumption and MetS components among Saudi adults.

A cross-sectional study was performed on adults who met at least three criteria for a MetS diagnosis. Data concerning demographics, lifestyle, sleeping patterns, medical health, anthropometric measurements, habitual coffee drinking, and lab levels for HDL-C, LDL-C, TC, TGs, HbA1c, and FBG were collected.

Of the 95 participants, 51% were women, 75.8% were >50 years old, 75.8% were obese, 62% were used to practicing physical activity, 74.5% never smoked, 56.4% slept < 7 h/day, and 89.5% were coffee consumers. Of these, 94.7% had high waist circumference, 63.2% had high BP, 47.4% had high FBG, 41.1% had low HDL, and 23.2% had high TGs. For coffee consumers, 37.6% drank a small cup, 34.5% drank coffee once daily, 89.4% drank Arabic coffee, and 75.3% added no additives.

No significant association was found between coffee consumption patterns and any MetS component, with the exception of elevated TGs, which was strongly associated with coffee cup size and number of daily cups. Waist circumference and BMI had a strong positive correlation with coffee cup size, and there was a significant relationship between the number of daily cups, BMI, and TC. Further prospective studies are needed to establish a causal relationship.

Diabetes mellitus (DM) has emerged as a significant global concern that accounts for nearly 90% of type 2 DM cases worldwide and characterized by insulin resistance. Hyperglycemia in diabetes leads to increased fibrinogen levels and activates the coagulation cascade, thereby triggering atherothrombotic events.

The study was designed to evaluate the coagulation profile (activated partial thromboplastin time, prothrombin time, and INR) in type 2 diabetes and to analyze the correlation between glycated hemoglobin (A1C) and coagulation profile among the OPD patients coming to AIIMS Patna.

A total of 234 patients were included in the study who were divided into 3 categories based on their glycemic status. 85 were non-diabetic, 65 were pre-diabetic, and 84 were diabetic. The demographic profile and clinical details were recorded. Fasting blood glucose, glycated hemoglobin, coagulation parameters such as prothrombin time, INR, and activated partial thromboplastin time along with other biochemical parameters were investigated.

There was a statistically significant association found between the coagulation profile and the two groups (Diabetics and Non-diabetics). The present study also found significant correlations between age and the diabetic group as compared to the non-diabetic group. A strong statistical significance was found between the gender and coagulation profile PT/INR. A statistically significant difference was found in the pre-diabetic and diabetic groups for coagulation parameters such as the activated partial thromboplastin time and prothrombin time (APTT and PT).

Clinical tests for prothrombin time, INR, and activated partial thromboplastin time are relatively inexpensive and readily available. The present study shows that a significant association was found between prothrombin time and activated partial thromboplastin time with the glycemic status among the diabetic as compared to non-diabetic or pre-diabetics. These findings can be used as important hemostatic markers in diabetic patients, especially in those at high risk for thrombotic complications.

The primary objective of glycemic control in individuals with diabetes mellitus is to avert or postpone complications, which ultimately leads to an improved quality of life. Nonetheless, achieving the recommended targets for glycemic control in clinical settings often proves challenging. Consequently, it is crucial to ascertain factors that affect glycemic outcomes to enhance the management of diabetes mellitus. This study sought to evaluate the levels of glycemic control and the associated factors among patients with type 2 diabetes receiving care at the Methodist Hospital, Wenchi, Ghana.

A retrospective study was conducted using an existing database. Glycemic control was evaluated by HbA1c measurements with a target of < 7% indicating good control, as per the guidelines established by the American Diabetes Association for nonpregnant adults. HbA1c levels ≥ 7% were classified as poor control. Data analysis was conducted using SPSS version 25 and multivariate logistic regression analysis was employed to determine the factors affecting glycemic control.

The median HbA1c level among the participants was 7.9% (IQR: 5.8-9.9). Majority (59.3%) demonstrated poor glycemic control with HbA1c ≥ 7%. Factors associated with poor glycemic control included advanced age (AOR: 4.32, 95% CI: 0.61-11.21, p = 0.012), duration of diabetes mellitus > 10 years (AOR: 3.60, 95% CI: 1.05-9.82, p = 0.019), insulin therapy (AOR: 3.13, 95% CI: 0.55-11.01, p = 0.009) and hypertension diagnosis (AOR: 2.88, 95% CI: 0.75-5.45, p = 0.030).

The study indicated that a considerable proportion of individuals with diabetes exhibited inadequate glycemic control. Older age, longer duration of diabetes mellitus, insulin therapy and comorbid hypertension were significantly associated with poor glycemic control among the study population. Multidisciplinary interventions as well as customized management strategies are required to ensure effective glycemic control to prevent long-term complications of diabetes mellitus.

Domestic and international migrants along the United States-Mexico border are at increased risk for diabetes due to structural and psychosocial adversities.

This study assessed the prevalence of diabetes and prediabetes in a low-income United States-Mexico border community; examined the relationships between depression, anxiety, andadverse childhood experiences (ACEs) and diabetes prevalence and glucose regulation; and explored indirect effects of social support on these relationships. Results. Participants were 220 adults ages 19-83 years (M.47.2, SD.11.9) of majority Mexican nationality (89.1%). Over 70% reported history of migration to the United States; 56.8% reported deportation from the United States to Mexico. Prevalences of clinically significant depression and anxiety symptoms were 36.9% and 33.3%, respectively. Prevalences of diabetes and prediabetes were 17.3% and 29.1%, respectively. Psychological variables were not associated with diabetes or glucose regulation. Indirect effects were found from depression and ACEs through social support to hemoglobin A1c.

Results suggest the need for diabetes prevention interventions with an integrated biopsychosocial approach.

Glycated hemoglobin (HbA1c) reflects average blood glucose levels over the preceding three months, independent of fasting state. It is widely used for diagnosing type 2 diabetes and prediabetes and monitoring glucose control in patients with diabetes. This study highlights how anthropometry, body composition, and physical fitness affect glycated hemoglobin (HbA1c) levels in a cohort of female university students.

This cross-sectional study, conducted between October 2023 and January 2024 among university female students (n=86; ages 17-22 years) in the United Arab Emirates (UAE), aimed to determine the relationship between HbA1c, anthropometric indices, physical fitness, and body composition. Participants were recruited in person, provided written informed consent, and completed demographic and physical activity questionnaires. Weight, body mass index (BMI), visceral fat, and muscle and fat percentage were measured using a body composition monitor scale (Omron HBF-514C, OMRON Healthcare, Inc., Kyoto, Japan). A stadiometer was used to measure height and an electronic sphygmomanometer to measure blood pressure. The waist and hip circumferences were measured using a measuring tape, and the waist-to-hip ratio was further calculated. Glycated hemoglobin (HbA1c) was measured using an immunofluorescence assay analyzer (Getein 1160 Immunofluorescence Quantitative Analyzer, Getein Biotech, Inc., Nanjing, China).

The main objective of our study was to establish a relationship between anthropometric measurements and body composition with physical fitness levels, including sedentary time, and how it influences HbA1c levels in young female students. Of the 90 participants, data from 86 were analyzed. Significant correlations were found between HbA1c and diastolic blood pressure (BP) (r=0.227) and sedentary hours (r=0.206). Linear regression analysis revealed sedentary behavior (p=0.021) and diastolic BP (p=0.034) as significant predictors of HbA1c levels. In conclusion, our research study provides valuable insights into how lifestyle factors such as sedentary lifestyle and diastolic BP influence glycemic (HbA1c) control in a specific cohort of young female university students of ages 17-22 years. Although BMI was not a significant predictor in our study, sedentary hours and diastolic blood pressure were independently linked to HbA1c levels.

The aim of the study was to examine the effects of diabetes education given to children with Type 1 Diabetes Mellitus with digital game and video animation on quality of life and metabolic control.

The study was an experimental single-blind, randomized controlled design. It was conducted with a total of 55 children with Type 1 Diabetes Mellitus, consisting of a study (n = 27) and a control group (n = 28). Data were collected by the "Introductory Information Form", "Pediatric Quality of Life 3.0 Diabetes Mellitus Module (PedsQL 3.0)" and "Metabolic Control Parameters Monitoring Form". Data were analyzed with Mann Whitney U, Chi square, Friedman and Bonferroni Dunn tests.

The descriptive characteristics of children with type 1 diabetes mellitus were homogeneous. The total mean quality of life scores of children with Type 1 Diabetes Mellitus in the study group were significantly higher than those in the control group (p < 0,05). The average HbA1c scores of the children in the study group decreased (p < 0,05), while the average HbA1c scores of the control group increased (p < 0,05).

Digital game and video animation based education was found to be effective in improving the quality of life of children with Type 1 Diabetes Mellitus and reducing HbA1c.

Providing diabetes education to children with Type 1 Diabetes Mellitus with digital games and video animations can facilitate diabetes management.

Diabetic ketoacidosis (DKA) is an acute complication of diabetes that mainly occurs in type 1 diabetes. However, it can also occur in type 2 diabetes, although less commonly. One of the rare causes of this condition is acute pancreatitis. While hypertriglyceridemia is a known complication of DKA, triglyceride levels higher than 2000 are an unusual finding. We present a case of undiagnosed type 2 diabetes mellitus in a patient who came to the hospital with epigastric pain, nausea, and vomiting. Subsequent blood tests revealed hyperglycemia, ketonuria, metabolic acidosis, and increased levels of amylase and lipase, leading to a simultaneous diagnosis of DKA, acute pancreatitis, and very severe hypertriglyceridemia. In patients experiencing abdominal pain and severe diabetic complications, acute pancreatitis should always be considered as a possible diagnosis, and triglyceride levels should be tested to identify hypertriglyceridemia as a potential cause of pancreatitis or complications of DKA.

The integration of continuous glucose monitoring (CGM) into clinical practice has rapidly emerged in the last decade, changing the evaluation of long-term glucose regulation in patients with diabetes. When using CGM-derived metrics to evaluate long-term glucose regulation, it is essential to determine the minimal observation period necessary for a reliable estimate. The approach of this study was to calculate mean absolute errors (MAEs) for varying window lengths, with the goal of demonstrating how the CGM observation period influences the accuracy of the estimation of 90-day glycemic control.

CGM data were collected from the DIABASE cohort (ZGT hospital, The Netherlands). Trailing aggregates (TAs) were calculated for four CGM-derived metrics: time in range (TIR), time below range (TBR), glucose management indicator (GMI) and glycemic variability (GV). Arbitrary MAEs for each patient were compared between the TAs of window lengths from 1 to 89 days and a reference TA of 90 days, which is assumed to reflect long-term glycemic regulation.

Using 14 days of CGM data resulted in 65% of subjects having their TIR estimation being below a MAE threshold of 5%. In order to have 90% of the subjects below a TIR MAE threshold of 5%, the observation period needs to be 29 days.

Although there is currently no consensus on what is an acceptable MAE, this study provides insight into how MAEs of CGM-derived metrics change according to the used observation period within a population and may thus be helpful for clinical decision-making.

To characterize clinically relevant subgroups of patients with type-2 diabetes mellitus (T2DM) based on adiposity, insulin secretion, and resistance indices.

A cross-sectional study was conducted at Eastern Regional Hospital in Ghana from July to October 2021 to investigate long-term patients with T2DM. To select participants, a systematic random sampling method was employed. Demographic data was collected using a structured questionnaire and fasting blood samples were taken to measure glycemic and lipid levels. Blood pressure and adiposity indices were measured during recruitment. The risk of cardiovascular disease (CVD) was defined using Framingham scores and standard low-density lipoprotein thresholds. To analyze the data, k-means clustering algorithms and regression analysis were used.

The study identified three groups in female patients according to body mass index, relative fat mass, glycated hemoglobin, and triglyceride-glucose index. These groups included the obesity-related phenotype, the severe insulin resistance phenotype, and the normal weight phenotype with improved insulin resistance. Among male patients with T2DM, two groups were identified, including the obesity-related phenotype with severe insulin resistance and the normal weight phenotype with improved insulin sensitivity. The severe insulin resistance phenotype in female patients was associated with an increased risk of high CVD (OR = 5.34, 95%CI:2.11-13.55) and metabolic syndrome (OR = 7.07; 95%CI:3.24-15.42). Among male patients, the obesity-related phenotype with severe insulin resistance was associated with an increased intermediate (OR = 21.78, 95%CI:4.17-113.78) and a high-risk CVD (OR = 6.84, 95%CI:1.45-32.12).

The findings highlight significant cardiometabolic heterogeneity among T2DM patients. The subgroups of T2DM patients characterized by obesity and/or severe insulin resistance with or without poor glycemic control, have increased risk of CVD. This underscores the importance of considering differences in adiposity, insulin secretion, and sensitivity indices when making clinical decisions for patients with T2DM.

Epigenetic clocks use DNA methylation (DNAm) levels to predict an individual's biological age. However, relationships between lifestyle/biomarkers and epigenetic age acceleration (EAA) in Asian populations remain unknown. We here explored associations between lifestyle factors, physiological conditions, and epigenetic markers, including HannumEAA, IEAA, PhenoEAA, GrimEAA, DunedinPACE, DNAm-based smoking pack-years (DNAmPACKYRS), and DNAm plasminogen activator inhibitor 1 level (DNAmPAI1). A total of 2474 Taiwan Biobank (TWB) individuals aged between 30 and 70 provided physical health examinations, lifestyle questionnaire surveys, and blood and urine samples. Partial correlation analysis (while adjusting for chronological age, smoking, and drinking status) demonstrated that 29 factors were significantly correlated with at least one epigenetic marker (Pearson's correlation coefficient |r|> 0.15). Subsequently, by exploring the model with the smallest Akaike information criterion (AIC), we identified the best model for each epigenetic marker. As a DNAm-based marker demonstrated to predict healthspan and lifespan with greater accuracy, GrimEAA was also found to be better explained by lifestyle factors and physiological conditions. Totally 15 factors explained 44.7% variability in GrimEAA, including sex, body mass index (BMI), waist-hip ratio (WHR), smoking, hemoglobin A1c (HbA1c), high-density lipoprotein cholesterol (HDL-C), creatinine, uric acid, gamma-glutamyl transferase (GGT), hemoglobin, and five cell-type proportions. In summary, smoking, elevated HbA1c, BMI, WHR, GGT, and uric acid were associated with more than one kind of EAA. At the same time, higher HDL-C and hemoglobin were related to epigenetic age deceleration (EAD). These findings offer valuable insights into biological aging.

The lack of accurate and affordable monitoring of glycated hemoglobin (HbA1c) is a common issue among patients with diabetes in low- and middle-income countries. We aimed to test a tablet- and smartphone-based point-of-care (TSB POC) device against a local laboratory-based measure of HbA1c for monitoring diabetes under real-world conditions.

For this cross-sectional clinical method applicability study, capillary and venous blood was collected in duplicate and analyzed at local primary health care centers. For a heterogeneity test, the tests were performed by an expert, and by a team of local nurses. The study was conducted in a multicenter design in rural and urban Aceh, Indonesia in 2019, and included a total of 533 adults. We mainly used Bland-Altman plots to assess the number of readings within the 95%-limits of agreement (LoA) and Deming regressions.

The results show a mean difference between capillary HbA1c on the test device and the reference method of -0.54 [CI0.95 = -1.6933; 0.6048] with 5.21% of measurements outside the LoA and a Pearson's r = 0.91 in the Deming Regression. There is no significant difference in test concordance between local nurses and the expert (4.23% versus 5.13% results outside the LoA [CI0.95 = -0.0331; 0.0511]).

TSB POC for analysis of HbA1c is an acceptable alternative for accessible monitoring of diabetes patients under these conditions. This method could provide access to high-quality diagnostic decisions through regular and cost-effective HbA1c monitoring directly in healthcare facilities, thus providing better access to essential health services.

Introduction HbA1c is a biomarker that plays an essential role in the diagnosis and follow-up of diabetic patients. The sensitivity and specificity of the biomarker may be affected by common comorbidities seen in individuals with diabetes mellitus, such as kidney affection, cardiac affection, iron deficiency anemia, hemolytic anemia, hemoglobinopathies, and drug consumption. Aim To assess the role of HbA1c in the follow-up and control of Diabetes Mellitus across different patient populations and clinical scenarios. Methodology A quantitative research design to investigate the impact of residence location (inside or outside the Saudi Arabia). Through an electronic questionnaire in English and translated into Arabic, it was published online using Google Forms (Google, Mountain View, California) and was divided into three sections. Results The number of participating patients was 412 diabetic patients; their average age was from 51 to 60 years, and most of them were male. The study found a high level of awareness among diabetics about the HbA1c test, their knowledge of its importance, and their ability to perform the analysis regularly and periodically every year. However, there is a lack of practice, as most participants only performed follow-up every more than a few months, and the value of the last HbA1c test ranged between seven and ten. The percentage of diabetic patients whose cumulative blood sugar was more than ten and who did not take any action after learning of their high percentage (35.7%). Conclusion Diabetes is one of the most common health problems that continue to spread worldwide. HbA1c testing may continue to be implemented as an essential part of the diagnostic and prognostic tool, resulting in better patient care and successful clinical outcomes. Testing for glycosylated hemoglobin levels should be done every three months. Patients and doctors should be cautioned not to rely exclusively on two-hour post-prandial blood glucose results, particularly in the case of insulin-dependent diabetes.

Hyperglycemia, one of the major risk factors for atherosclerosis, leads to the accumulation of advanced glycation end products (AGEs), contributing to cardiovascular complications. Such accumulation may accelerate the progression of vascular disease in patients with diabetes. Reverse cholesterol transport (RCT) protein, ATP-binding membrane cassette transporters A1 and G1 (ABCA1 and ABCG1) and cholesterol 27-hydroxylase facilitate cholesterol removal from macrophages. AGE inhibits RCT by reducing the expression of ABCA1 and ABCG1. This study aimed to evaluate whether plasma from poorly controlled adolescents with type 1 diabetes (T1D) disrupts cholesterol homeostasis in human monocytes/macrophages. Twenty healthy controls (HCs) and 20 patients with type 1 diabetes mellitus (T1DM), 10-19 years old, were enrolled. Naïve THP-1 macrophages were exposed to plasma from each HC and patient with T1D. Following incubation, mRNA for cholesterol efflux (ABCA1, ABCG1, and 27-hydroxylase) and cholesterol uptake (CD36, ScR-A1, lectin oxidized low-density lipoprotein (LOX)-1, and CXCL16) were isolated. Foam cell formation was quantified to confirm the pro-atherogenic effects of T1D plasma on macrophages. Results showed that T1D plasma had an elevated level of N-(carboxymethyl)-lysine-modified proteins and upregulated CXCL16 and, to a lesser degree, ScR-A1. This change in gene expression in the presence of T1D plasma is associated with increased lipid accumulation and foam cell formation by THP-1 macrophages. In our study, these cells' uptake of an AGE product occurred mainly through the SR-A1 and CXCL16 receptors, leading to increased intracellular oxidized low-density lipoprotein. We conclude that AGEs may contribute to accelerated atherosclerosis in diabetes through effects on both forward and reverse cholesterol movement.

Effect heterogeneity analyses using causal machine learning algorithms have gained popularity in recent years. However, the interpretation of estimated individualized effects requires caution because insights from these data-driven approaches might be misaligned with the contextual needs of a human audience. Thus, a practical framework that integrates advanced machine learning methods and decision-making remains critically needed to achieve effective implementation and scientific communication. We introduce a 2-step framework to identify characteristics associated with substantial effect heterogeneity in a practically relevant format. The proposed framework applies distinct sets of covariates for (i) estimation of individualized effects and (ii) subgroup discovery and shows the subgroups with heterogeneity based on highly interpretable if-then rules. By referring to existing metrics of interpretability, we describe how each step contributes to leveraging a theoretical advantage of machine learning models while creating an interpretable and practically relevant framework. We applied the pragmatic subgroup discovery framework for the Look AHEAD (Action for Health in Diabetes) trial to assess practically relevant and comprehensive insights into the effect heterogeneities of intense lifestyle intervention for individuals with diabetes on cardiovascular mortality. Our analysis identified (i) individuals with history of cardiovascular disease and myocardial infarction had the least benefit from the intervention, while (ii) individuals with no history of cardiovascular diseases and HbA1c < 7% received the highest benefit. In summary, our practical framework for heterogeneous effects discovery could be a generic strategy to ensure both effective implementation and scientific communication when applying machine learning algorithms in epidemiological research.

Inhibition of dipeptidyl peptidase-4 (DPP4) activity has emerged as a promising therapeutic approach for the treatment of type 2 diabetes mellitus (T2DM). Bioinformatics-driven approaches have emerged as crucial tools in drug discovery. Molecular docking and molecular dynamics (MD) simulations are effective tools in drug discovery, as they reduce the time and cost associated with experimental screening. In this study, we employed structure-assisted in-silico methods, including molecular docking and MD simulations, to identify SRT2183, a small molecule that may potentially inhibit the activity of DPP4 enzyme. The interaction between the small molecule "SRT2183" and DPP4 exhibited a binding affinity of -9.9 Kcal/Mol, leading to the formation of hydrogen bonds with the amino acid residues MET348, SER376, and THR351 of DPP4. The MD simulations over a period of 100 ns indicated stable protein-ligand interactions, with no significant conformational rearrangements observed within the simulated timeframe. In conclusion, our results suggest that the small molecule SRT2183 may have the potential to inhibit the DPP4 enzyme and pave the way for the therapeutics of T2DM.Communicated by Ramaswamy H. Sarma.

Precise and timely forecasting of blood glucose levels is essential for effective diabetes management. While extensive research has been conducted on Type 1 diabetes mellitus, Type 2 diabetes mellitus (T2DM) presents unique challenges due to its heterogeneity, underscoring the need for specialized blood glucose forecasting systems. This study introduces a novel blood glucose forecasting system, applied to a dataset of 100 patients from the ShanghaiT2DM study. Our study uniquely integrates knowledge-driven and data-driven approaches, leveraging expert knowledge to validate and interpret the relationships among diabetes-related variables and deploying the data-driven approach to provide accurate forecast blood glucose levels. The Bayesian network approach facilitates the analysis of dependencies among various diabetes-related variables, thus enabling the inference of continuous glucose monitoring (CGM) trajectories in similar individuals with T2DM. By incorporating past CGM data including inference CGM trajectories, dietary records, and individual-specific information, the Bayesian structural time series (BSTS) model effectively forecasts glucose levels across time intervals ranging from 15 to 60 minutes. Forecast results show a mean absolute error of mg/dL, a root mean square error of mg/dL, and a mean absolute percentage error of , for a 15-minute prediction horizon. This study makes the first application of the ShanghaiT2DM dataset for glucose level forecasting, considering the influences of diabetes-related variables. Its findings establish a foundational framework for developing personalized diabetes management strategies, potentially enhancing diabetes care through more accurate and timely interventions.

Enhancing self-management in health care through digital tools is a promising strategy to empower patients with type 2 diabetes (T2D) to improve self-care.

This study evaluates whether the Greenhabit (mobile health [mHealth]) behavioral treatment enhances T2D outcomes compared with standard care.

A 12-week, parallel, single-blind randomized controlled trial was conducted with 123 participants (62/123, 50%, female; mean age 58.25 years, SD 9.46 years) recently diagnosed with T2D. Participants were recruited face-to-face from primary care centers in Barcelona, Spain, between July 2021 and March 2022. They were randomly assigned to 1 of 2 groups: (1) an intervention group (n=61) instructed to use the Greenhabit mobile app alongside standard care, or (2) a control group (n=62) who received advice on maintaining a healthy diet and followed standard care. The Greenhabit app incorporates serious gaming technology. Participants received daily messages and challenges focused on promoting a healthy lifestyle, including nutrition, exercise, relaxation, a positive mindset, and a supportive social environment. The app encouraged participants to set weekly goals and awarded points for completing challenges. Data on nutrition, anthropometrics, and blood and urine samples were collected at baseline, 6 weeks, and 12 weeks. Questionnaires assessing quality of life, work-life balance, and social environment were administered at baseline and during the final visit. The primary outcomes were HbA1c and fasting plasma glucose (FPG). Repeated-measures analysis of variance was used to compare changes over time (baseline to 6 weeks and baseline to 12 weeks) between the 2 intervention groups. Analysis of covariance was performed to evaluate changes at 6 and 12 weeks, adjusted for baseline levels of each variable. Multiple contrasts were corrected using a Bonferroni post hoc test.

Both groups showed significant reductions in HbA1c after 6 and 12 weeks (mean change in the intervention group [n=50] -0.4%, P<.001 vs -0.3% in the control group [n=53], P=.001) and in FPG after 6 weeks (mean change in the intervention group -5.3 mg/dL, P=.01 vs control group -5.8 mg/dL, P=.01). At 12 weeks, the intervention group also showed significant reductions in systolic and diastolic blood pressures (mean change -4.5, P=.049 and -2.4 mmHg, P=.03, respectively), body weight (mean change -0.8 kg, P=.03), BMI (mean change -0.3 kg/m2, P=.03), waist circumference (mean change -1.0 cm, P=.046), and triglyceride concentration (mean change -20.0 mg/dL, P=.03). There was also a significant increase in high-density lipoprotein-cholesterol concentrations (mean change 2 mg/dL, P=.049). Finally, improvements were noted in 3 out of the 5 elements of balance: positivity, social environment, and work-life balance.

The 12-week intervention with the Greenhabit behavioral treatment mHealth app showed beneficial effects on T2D outcomes and reduced the burden of cardiovascular risk factors. Although larger studies are warranted, these results suggest that mHealth apps can be a promising tool for improving T2D self-management.

ISRCTN Registry ISRCTN13456652; http://www.isrctn.com/ISRCTN13456652.