Global and societal implications of the diabetes epidemic

Liquidambaric acid as a non-competitive α-glucosidase inhibitor: multi-level evidence from enzyme kinetics, molecular docking, molecular dynamics simulations, and a Drosophila hyperglycaemic model

Liquidambaric acid, a pentacyclic triterpenoid from Liquidambar formosana Hance, was evaluated as a novel α-glucosidase inhibitor for type 2 diabetes mellitus (T2DM) management. Enzyme kinetic assays revealed its potent non-competitive inhibition (IC50 = 0.12 mM). Molecular docking showed stable hydrogen bonding at an allosteric site, altering enzyme conformation, while 100 ns molecular dynamics (MD) simulations confirmed the stability of the protein-ligand complex. In vivo, a Drosophila melanogaster hyperglycaemic model demonstrated significant glucose reduction, confirming its hypoglycaemic potential. ADMET analysis predicted favourable bioavailability and low toxicity, supporting its development as a safe therapeutic agent. These findings integrate enzyme kinetics, molecular modelling, MD simulations, and in vivo validation, highlighting liquidambaric acid's potential as a multifunctional and cost-effective agent for T2DM management.

Effect of type 2 diabetes mellitus microenvironment on osteogenic capacity of bone marrow mesenchymal stem cells

Type 2 diabetes mellitus (T2DM) often leads to delayed bone regeneration such as slow healing of fractures and bone defects. The number, status and osteogenic differentiation capacity of bone marrow mesenchymal stem cells (BMSCs) are extremely important in bone healing and bone regeneration. The T2DM microenvironment can have irreversible negative effects on BMSCs. In this paper, we review the molecular expression and altered proliferation, migration, and osteogenic differentiation capacity of BMSCs in the microenvironment of T2DM, it provides a new perspective to restore the normal function of T2DM-BMSCs, so as to save the damaged bone regeneration capacity.

A Body Shape Index (ABSI) as a risk factor for all-cause mortality among US adults with type 2 diabetes: evidence from the NHANES 1999-2018

Background and objective

A Body Shape Index (ABSI) serves as a potential indicator of fat distribution, offering a more reliable association with all-cause mortality compared to overall adiposity. The present cohort study aims to explore the relationship between ABSI and all-cause mortality in US adults with Type 2 Diabetes (T2D).

Methods

For this cohort study, we extracted information on 5,461 US adults with T2D from the National Health and Nutrition Examination Survey (NHANES) and the NHANES Linked Mortality File. Trends in ABSI from 1999 to 2018 were calculated and analyzed using partial Mann-Kendall tests. To assess the relationship between ABSI and all-cause mortality, as well as the robustness of the association results, we employed weighted restricted cubic splines (RCS), weighted Cox proportional hazards models, sensitivity analyses, and stratified analyses. Additionally, we conducted time-dependent receiver operating characteristic (ROC) curve analysis to evaluate ABSI's predictive capability for all-cause mortality over 3, 5, and 10 years.

Results

Among US adults with Type 2 Diabetes (T2D), the mean ABSI gradually increased from 0.08333 to 0.08444 between 1999 and 2018. Following a median follow-up period of 90 months, 1,355 deaths (24.8% of the participants) occurred due to all causes. A left J-shaped association was observed between ABSI and all-cause mortality, with a 39% increased risk among US adults with T2D who had an ABSI below 0.08105 after full adjustment.

Conclusion

Our research has demonstrated a significant association between an elevated ABSI and the risk of all-cause mortality among US adults with T2D. These findings support the potential use of ABSI as a noninvasive tool to estimate mortality risk among US adults with T2D.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-025-01570-3.

DPP-IV and FAS inhibitory peptides: therapeutic alternative against diabesity

Diabesity is a modern epidemic that indicates a strong association between obesity and diabetes. Key enzymes have been identified in the development and progression of both diseases, DPP-IV in glucose uptake and FAS in fatty acid synthesis. In both cases, the molecular mechanisms of how each one acts separately have been described, and which are the key inhibitory drugs and molecules for each one. However, although it is known that there is an association between both clinically and molecularly, the mechanism has not been elucidated; therefore, this review focuses on proposing a mechanism of convergence of DPP-IV and FAS in diabesity, and the possible mode of action in which bioactive peptides obtained from plant and animal sources can inhibit these two enzymes in a similar way as drugs do.

Assessment of postprandial C peptide in obese patients with prediabetes and type 2 diabetes before and after sleeve gastrectomy

Obesity is a complicated, multifactorial, and highly avoidable disease. There is a complicated relationship between type 2 diabetes mellitus (T2DM) and obesity. Surgical intervention is regarded as one of the greatest efficacious treatments for morbid obesity, where T2DM exhibits remarkable amelioration and remission. The objective of this work is to evaluate endogenous insulin by measuring postprandial C-peptide before and 6 months after LSG. We will also assess metabolic improvement, including remission of T2DM and prediabetes, 6 months after LSG. A total of 60 Egyptian patients, aged 18-60 years, with a body mass index (BMI) > 35, prediabetes, or type 2 diabetes, were recruited from bariatric outpatient clinics at Cairo University Hospitals. The study assessed the postprandial C-peptide, fasting blood sugar, HbA1C, and lipid profile before and 6 months following LSG. A significant improvement was observed in the metabolic profile in the form of reduction of BMI, HbA1c, lipid profile, and control of hypertension 6 months postoperatively. There was a significant reduction of postprandial C-peptide 6 months postoperatively. Fifty-five patients (91.7%) achieved complete remission of prediabetes and diabetes 6 months postoperatively, while 4 patients showed only improvement of diabetes and 1 patient in the prediabetic group did not achieve remission. In conclusion, LSG demonstrates encouraging outcomes in terms of metabolic profile enhancement, insulin resistance improvement as indicated by significant reduction in C-peptide level, remission of prediabetes and T2DM, and effective weight loss.

Metabolic syndrome and bladder cancer risk: a comprehensive evidence synthesis combining bibliometric and meta-analysis approaches

OBJECTIVE

This study employed bibliometric analysis to explore global research on metabolic syndrome (MetS) and bladder cancer (BC), focusing on characteristics and research trends. Additionally, a meta-analysis was conducted to comprehensively evaluate the association between MetS and its components with the risk of BC.

METHODS

We conducted a comprehensive search of publications from 2002 to 2022 in the Web of Science Core Collection (WoSCC). Visualization analysis was performed using the Open Scientometrics Data Analysis and Visualization Platform, VOSviewer software and the R package "bibliometrix". For the meta-analysis, data from PubMed, Embase and the Cochrane Library up to March 22, 2022, were utilized. Literature from PubMed, Embase, Cochrane and Web of Science up to March 25, 2022, were retrieved, and data extraction was independently performed by two authors. A random-effects model was used to calculate pooled odds ratios (ORs) and 95% confidence intervals (95% CIs). Meta-analysis was conducted using RevMan 5.4 software.

RESULT

In the bibliometric analysis, 147 papers were included, and information on countries, institutions, authors, journals and keywords from Web of Science was analyzed and visualized. For the meta-analysis, 11 studies involving 665,164 patients were included. The pooled analysis of six case-control studies showed that patients with MetS had a higher risk of BC compared to the non-MetS control group (OR = 1.62, 95% CI: 1.08-2.43, P < 0.01). Analysis of MetS components revealed that diabetes (OR = 0.44, 95% CI: 0.32-0.61, P < 0.01), low high-density lipoprotein (HDL) (OR = 0.29, 95% CI: 0.19-0.44, P < 0.01) and high triglycerides (OR = 0.59, 95% CI: 0.39-0.88, P < 0.01) were associated with an increased risk of BC. In contrast, hypertension (OR = 0.84, 95% CI: 0.62-1.12, P > 0.05) and obesity (OR = 0.8, 95% CI: 0.44-1.45, P > 0.05) showed no significant association with BC risk.

CONCLUSION

This study provided valuable insights into the association between MetS and BC risk by identifying past research trends and hotspots. MetS and its components, such as diabetes, low HDL and high triglycerides, were associated with an increased risk of BC.

Effects of neonicotinoid pesticide exposure in the first trimester on gestational diabetes mellitus based on interpretable machine learning

BACKGROUND

Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and seriously threatens the health of mothers and offspring. Neonicotinoids (NEOs) is a new class of pesticide and widely used worldwide. Prenatal NEOs exposure had negative effects on fetal growth, but the potential effect of NEOs exposure on pregnancy complications remain unclear.

OBJECTIVES

To examine the individual and jointed effects of serum neonicotinoids (NEOs) pesticide exposure on gestational diabetes mellitus (GDM), and explore the application of NEOs exposure levels as predictor of GDM.

METHODS

We conducted a prospective cohort study based on Guangxi Zhuang Birth Cohort, China. A total of 1450 mather-infant pairs were included from 2015 to 2019. Ten NEOs were measured by UPLC-MS. Maternal serum samples were collected during gestational age 0-12 weeks. Individual and jointed effects of NEOs on GDM were assessed through binomial regressions, Bayesian Kernel Machine Regression and quantile g-computation. Prediction of GDM using XGboost machine learning and SHapley Additive exPlanations (SHAP).

RESULTS

A total of 122 (8.4%) mothers were diagnosed with GDM. In the individual exposure models, sulfoxaflor and thiamethoxam exposure in the first trimester significantly increased the risk of GDM (OR = 1.48, 95%CI: 1.21, 1.82; OR = 1.42, 95%CI: 1.14, 1.78). Moreover, GDM risk increased significantly with NEOs mixture concentration was above 75th percentile, compared with the 50th percentile. Sulfoxaflor and thiamethoxam as the main positive contributing factors in NEOs mixture to increase the GDM with a weight of 29.3% and 27.6%, respectively. Furthermore, sulfoxaflor and thiamethoxam were the most important contributing factors for predicting GDM after combining traditional risk factors in machine learning model, with predicted contribution values of 0.79 and 0.46, respectively.

CONCLUSION

Our findings suggested that elevated maternal serum sulfoxaflor, thiamethoxam and NEOs mixture were positively associated with GDM, and sulfoxaflor, thiamethoxam were the important contributing factors for predicting GDM.

A Novel, Multifunctional Resistant Starch-Phenol Complex with Potential for Better Glycemic Control

Resistant starch (RS) with added functional properties, for example, starch-phenol complex, has considerable promise for reducing the risks of diet-related diseases such as type 2 diabetes (T2D). In this study, a novel starch-phenol complex was prepared with amylose (AM) and 10-gingerol (10G) to study the potential beneficial effects on blood glucose control. The AM and 10G self-assembled into an AM-10G complex with V6- and V7-type crystallites. The rate of amylolysis of the AM-10G complex was much slower than that of the AM-lauric acid (LA) complex. During enzymic digestion of the AM-10G complex, the α-amylase activity was inhibited greatly and approached zero at 45 min. In separate experiments, 10G suppressed glucose transport rate by 60% across a Caco-2 cell monolayer and also downregulated the expression of mRNA for the two glucose transporter genes, GLUT2 and SGLT1. In vitro fecal fermentation analyses showed that AM-10G complex promoted the proliferation of Lachnospiraceae_NK4A136_group and Lachnospiraceae_UCG_004 associated with improved postprandial glycemia. The present study demonstrates that AM-10G complex has potential for glycemic control due to the inhibitory effects on the amylolytic process and glucose transporters involved in uptake of glucose into the bloodstream, as well as the modulation of gut microbiota associated with glycemic control.

Improvement of Glucose Metabolism by Pennogenin 3-O-β-Chacotrioside via Activation of IRS/PI3K/Akt Signaling and Mitochondrial Respiration in Insulin-Resistant Hepatocytes

SCOPE

Insulin resistance (IR), which causes chronic hyperglycemia, has been one of the most prevalent components of metabolic syndrome over the centuries. Pennogenin 3-O-β-chacotrioside (P3C), the main steroid glycoside derived from Paris polyphylla, has been found to exert various biological activities. However, the exact role of P3C on glucose metabolism in the IR state remains unexplored.

METHODS AND RESULTS

To induce IR, AML12 cells were exposed to glucose (27 mM) and insulin (10 µg/mL) and then incubated with P3C (0.25 or 0.5 µM) for 24 h. The effects of P3C on glucose metabolism in insulin-resistant AML12 cells were evaluated through glucose consumption assays, real-time quantitative polymerase chain reaction (qPCR), Western blotting, and metabolic analysis for extracellular acidification rate (ECAR) and oxygen consumption rate (OCR). Our data showed that P3C significantly improved insulin sensitivity in AML12 hepatocytes with high glucose-induced IR. P3C stimulated insulin sensitivity and glucose uptake by activating the IRS/PI3K/Akt signaling pathway, which enhances glycogen synthesis and suppresses gluconeogenesis in insulin-resistant AML12 cells. In addition, P3C treatment increased the protein expression of p-AMPK and PGC1α, as well as the expression of oxidative phosphorylation complex proteins, potentially enhancing mitochondrial oxidative respiration.

CONCLUSIONS

Our findings imply that P3C could be a therapeutic option for improving metabolic abnormalities associated with IR.

Metabolic imbalance and brain tumors: The interlinking metabolic pathways and therapeutic actions of antidiabetic drugs

Brain tumors are complex, heterogeneous malignancies, often associated with significant morbidity and mortality. Emerging evidence suggests the important role of metabolic syndrome, such as that observed in diabetes mellitus, in the progression of brain tumors. Several studies indicated that hyperglycemia, insulin resistance, oxidative stress, and altered adipokine profiles influence tumor growth, proliferation, and treatment resistance. Intriguingly, antidiabetic drugs (e.g., metformin, sulfonylureas, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, and thiazolidinediones) have shown promise as adjunctive or repurposed agents in managing brain tumors. Metformin can impair tumor cell proliferation, enhance treatment sensitivity, and modify the tumor microenvironment by activating AMP-activated protein kinase (AMPK) and inhibiting mammalian target of rapamycin (mTOR) signaling pathways. DPP-4 inhibitors and GLP-1 receptor agonists can target both metabolic and inflammatory aspects of brain tumors, while thiazolidinediones may induce apoptosis in tumor cells and synergize with other therapeutics. Consequently, further studies and clinical trials are needed to confirm the efficacy, safety, and utility of metabolic interventions in treating brain tumors. Here, we review the evidence for the metabolic interconnections between metabolic diseases and brain tumors and multiple actions of anti-diabetes drugs in brain tumors.

Impact of Tagatose on Physicochemical, Nutritional, and In Vitro Digestive Properties of Toast Bread

It is more attractive to develop effective strategies to reduce sugar intake without compromising food quality with the rising prevalence of obesity and diabetes around the world. Due to its high cost, tagatose has not been widely adopted as a sucrose substitute in toast bread. In the present research, five types of toast containing different proportions (0%, 4%, 8%, 12%, and 16%) of tagatose with sweetness similar to that of sucrose were prepared. The effects of tagatose on microstructural, textural, physicochemical, nutritional, and sensory properties and in vitro digestion were evaluated using techniques such as Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), rheological test, textural profile assay (TPA), and gas chromatography-mass spectrometry (GC-MS) analysis. The results indicated that after the substitution of tagatose for sucrose, the water-holding capacities of the dough were increased, whereas the specific volume of toast was decreased from 4.74 to 3.01 mL/g (p < 0.05), and the acidity of toast was increased from 1.92 to 2.69°T (p < 0.05). The content of flavor substances, especially alcohols, in the toast was significantly increased by the addition of tagatose. However, the glycemic index (GI) of toast was decreased from 94.39 to 67.96 (p < 0.05). Overall, the addition of 12% or more tagatose will significantly reduce the GI of toasted bread and enrich the flavor, but it will lead to a decrease in specific volume and an increase in acidity. Tagatose is a promising alternative sweetener with low calorie.

Therapeutic potential of GLP-1RAs in sleep apnea with genetic associations to type 2 diabetes

BACKGROUND

Some observational studies found that there is an epidemiological association between type 2 diabetes (T2D) and sleep apnea (SA) and glucose-lowering drugs may lower SA risk. However, the causative relationship among them remains unclear.

METHODS

Linkage Disequilibrium Score Regression (LDSC) was utilized to assess the genetic correlation between T2D and SA. Mendelian Randomization (MR) was applied, primarily using the inverse variance weighted (IVW) method, to evaluate the causal relationship between T2D and SA. Additionally, we performed Drug-target MR analysis to evaluate the impact of Glucagon-like Peptide-1 Receptor Agonists (GLP-1RAs) on SA. We used two kinds of genetic instruments to proxy the exposure of GLP-1RAs, including expression quantitative trait loci of drugs target genes, and genetic variants within drugs target genes associated with glycated hemoglobin A1c(HbA1c) from genome wide association study. Summary-data-based MR (SMR) and IVW were used to calculate the effect estimates. A two-step MR analysis was further employed to explore potential mediating factors in the T2D-SA relationship.

RESULTS

A genetic correlation and bidirectional causal association were found between T2D and SA. GLP-1RAs-mediated reductions in HbA1c levels showed associations with decreased SA risk in two independent datasets: (odds ratio (OR)1 = 0.48 [95% confidence interval (CI) 0.28-0.83], P1 = 9.21 × 10-3; OR2 = 0.21 [95% CI 0.05-0.92], P2 = 3.89 × 10-2); a higher expression of GLP-1R was associated with a decreased risk of SA (OR1 = 0.98 [95% CI 0.96-1.00], P1 = 4.55 × 10-2; OR2 = 0.95 [95% CI 0.92-0.99], P2 = 1.71 × 10-2). Body mass index (BMI) and current tobacco smoking mediated 20.28% and 6.65%, respectively, of the total effect of GLP-1RAs on SA risk.

CONCLUSION

This study suggested a bidirectional causal relationship between T2D and SA, with GLP-1-RAs potentially serving as a therapeutic target for SA. The reduction of SA risk by GLP-1RAs may be partially mediated by decreases in BMI and current tobacco smoking.

Community-based diabetes self-management and support program: addressing quality of life and social vulnerability

BACKGROUND

In the United States, 38.4 million people have been diagnosed with diabetes, and it continues to rise. The increasing rate of diabetes has become a significant public health challenge due, in part, to the association between diabetes and decreased levels of physical and emotional well-being. Currently, there are few assessments of the impact of diabetes self-management programs on individuals with diabetes quality of life and social vulnerability. This study examined pre- to post-program quality of life outcomes for participants in a community-based diabetes-self management and support (DSMS) program and assessed the association between the change in quality of life pre- to post-program and social vulnerability.

METHODS

Health Extension for Diabetes (HED) is a 4-month, community-based DSMS program delivered in the Southeast region of the United States. HED includes standardized education and personalized support to help participants manage their diabetes. The 12-Item Short Form Health Survey (SF-12) was utilized to assess participants' physical and mental quality of life pre- and post-program participation. The Centers for Disease Control and Prevention's (CDC) Social Vulnerability Index (SVI) was used to determine individuals' social vulnerability level (low: 0-0.25, low-to-moderate: 0.2501-0.5, moderate-to-high: 0.501-0.75, high: 0.7501-1.0). Wilcoxon sign-ranked tests assessed changes in SF-12 pre- and post-HED and linear regressions examined the association between quality of life and social vulnerability level.

RESULTS

SF-12 scores indicated significant positive changes in physical and mental quality of life for all program participants (N = 1,006). All SVI subgroups were observed to have significant improvements in physical health scores. Individuals with moderate-to-high and high SVI scores showed significant improvement in mental health scores, while individuals with low and low-to-moderate SVI scores did not.

CONCLUSION

Participants of the community-based diabetes self-management and support program experienced improvements in quality of life across varying levels of social vulnerability, as measured by the SVI. While integrating upstream social determinants of health considerations into DSMS program design and delivery addresses health disparities, future research should consider the implementation of more general mental health resources to address the psychological burden associated with living with chronic disease.

The physiological characteristics of inward rectifying potassium channel Kir4.2 and its research progress in human diseases

Kir4.2 is a member of the inward rectifying potassium channel family, encoded by the KCNJ15 gene. The Kir4.2 protein is expressed in various organs including the kidneys, liver, pancreas, bladder, stomach, and lungs. Kir4.2 not only forms functional homomeric channels, but also heteromeric channels with Kir5.1. An increasing number of studies indicate that the function of the Kir4.2 channel should not be underestimated. Kir4.2 participates in cell electrotaxis chemotaxis by sensing extracellular electric fields and functions as a K + sensor in the proximal tubules of the kidney, playing a crucial role in maintaining acid-base and potassium balance. This article provides a comprehensive review of the main physiological characteristics of the Kir4.2 channel, the various pathological processes it is involved in, and the human diseases resulting from Kir4.2 dysfunction.

Insulin resistance aggravates myocardial fibrosis in non-diabetic hypertensive patients by altering the function of epicardial adipose tissue: a cardiac magnetic resonance study

BACKGROUND

The effect of insulin resistance (IR) on epicardial adipose tissue (EAT) remains uncertain. This study aimed to investigate how early-stage IR influences EAT, contributing to myocardial fibrosis and left ventricular dysfunction in non-diabetic patients with hypertension.

METHODS

A total of 166 hypertensive patients who underwent cardiovascular magnetic resonance (CMR) treatment at two medical centers in China from June 2015 to August 2024 were included. Triglyceride-glucose index (TyG) was calculated, cardiac MRI parameters and EAT were measured. Patients were divided into two groups based on the median TyG. Binary logistic regression model, subgroup analysis and causal mediation analysis were used to evaluate the correlation between EAT, TyG and CMR parameters. Thirty healthy volunteers served as the control group.

RESULTS

The high TyG group exhibited greater EAT volume, higher Native T1, and increased ECV (All P < 0.001) compared to the low TyG group. Additionally, significant differences were observed in GRS (P = 0.025), GLS (P = 0.015), and GCS (P = 0.048). Binary logistic regression analysis indicated that TyG and indexed EAT volume were independently associated with high ECV value (TyG: OR 2.808, p = 0.002;indexed EAT volume: OR 1.038, p = 0.002), with results remaining stable after adjusting for confounding factors. Mediation analysis showed that even after adjusting for confounding factors, EAT continued to play a role in TyG-mediated ECV (indirect effect: 0.8844, [95% CI 0.4539-1.3666]).

CONCLUSIONS

IR in non-diabetic individuals at an early stage may change the physiological function of EAT and lead to the onset of myocardial fibrosis. Addressing IR early on could potentially improve the physiological function of EAT.

Validation of the Persian version of the summary of diabetes self-care activities scale (SDSCA) in pregnant women with gestational diabetes mellitus using a COSMIN methodology

BACKGROUND

Gestational diabetes mellitus (GDM) is a condition with significant prenatal and postnatal implications. This study aimed to validate the Summary of Diabetes Self-Care Activities (SDSCA) measure in Iranian women with GDM, focusing on its psychometric properties.

METHODS

The Persian version of the SDSCA was evaluated in 180 Iranian women with GDM. Following COSMIN guidelines, the instrument was translated into Persian, and its psychometric properties were assessed, including content validity, face validity, construct validity, internal consistency, test-retest reliability, measurement error, responsiveness, and interpretability. Floor and ceiling effects were also examined.

RESULTS

The validity assessments showed strong content validity, with a Content Validity Index (CVI) of 0.93 and a Content Validity Ratio (CVR) of 0.97. Face validity yielded an impact score of 4.38. Exploratory factor analysis (EFA) identified three factors-diet, exercise, and blood sugar testing-accounting for 57.4% of the variance. Confirmatory factor analysis (CFA) confirmed the model's excellent fit (CFI = 1.00, TLI = 0.99, NFI = 0.98, RFI = 0.96). The reliability analysis showed a Cronbach's alpha of 0.78 and a McDonald's omega of 0.91, with an intraclass correlation coefficient (ICC) of 0.92 (95% CI: 0.83-0.96). Ceiling effects were observed for blood sugar testing (26.7%), while floor effects were noted for exercise (6.7%) and blood sugar testing (6.1%). The Minimal Important Change (MIC) of 2.68 units exceeded the Smallest Detectable Change (SDC) of 1.11 units, indicating the tool's ability to detect clinically meaningful changes.

CONCLUSIONS

The Persian version of the SDSCA demonstrates strong psychometric properties, including both reliability and validity, making it a suitable tool for assessing self-care behaviors in Iranian women with GDM. Its use in future research can enhance understanding of self-management in this population.

A deep learning approach for blood glucose monitoring and hypoglycemia prediction in glycogen storage disease

Glycogen storage disease (GSD) is a group of rare inherited metabolic disorders characterized by abnormal glycogen storage and breakdown. These disorders are caused by mutations in G6PC1, which is essential for proper glucose storage and metabolism. With the advent of continuous glucose monitoring systems, development of algorithms to analyze and predict glucose levels has gained considerable attention, with the aim of preemptively managing fluctuations before they become problematic. However, there is a lack of research focusing specifically on patients with GSD. Therefore, this study aimed to forecast glucose levels in patients with GSD using state-of-the-art deep-learning (DL) algorithms. This retrospective study utilized blood glucose data from patients with GSD who were either hospitalized or managed at Yonsei University Wonju Severance Christian Hospital, Korea, between August 2020 and February 2024. In this study, three state-of-the-art DL models for time-series forecasting were employed: PatchTST, LTSF N-Linear, and TS Mixer. First, the models were used to predict the patients' Glucose levels for the next hour. Second, a binary classification task was performed to assess whether hypoglycemia could be predicted alongside direct glucose levels. Consequently, this is the first study to demonstrate the capability of forecasting glucose levels in patients with GSD using continuous glucose-monitoring data and DL models. Our model provides patients with GSD with a more accessible tool for managing glucose levels. This study has a broader effect, potentially serving as a foundation for improving the care of patients with rare diseases using DL-based solutions.

Leptin and Insulin in COPD: Unveiling the Metabolic-Inflammatory Axis-A Narrative Review

Chronic obstructive pulmonary disease (COPD) is a progressive and debilitating condition characterized by airflow limitations and systemic inflammation. The interaction between the metabolic and inflammatory pathways plays a key role in disease progression, with leptin and insulin emerging as pivotal metabolic regulators. Leptin, an adipokine that regulates energy homeostasis, and insulin, the primary regulator of glucose metabolism, are both altered in COPD patients. This narrative review provides an in-depth examination of the roles of leptin and insulin in COPD pathogenesis, focusing on the molecular mechanisms through which these metabolic regulators interact with inflammatory pathways and how their dysregulation contributes to a spectrum of extrapulmonary manifestations. These disturbances not only exacerbate COPD symptoms but also increase the risk of comorbidities such as metabolic syndrome, diabetes, cardiovascular disease, or muscle wasting. By exploring the underlying mechanisms of leptin and insulin dysregulation in COPD, this review underscores the significance of the metabolic-inflammatory axis, suggesting that restoring metabolic balance through leptin and insulin modulation could offer novel therapeutic strategies for improving clinical outcomes.

Predictive value of uric acid to albumin ratio for carotid atherosclerosis in type 2 diabetes mellitus: A retrospective study

BACKGROUND

This study aims to evaluate the correlation between the uric acid (UA) to albumin (ALB) ratio (UAR) and carotid atherosclerosis (CAS) in patients with type 2 diabetes mellitus (T2DM), as well as to assess the predictive value of UAR for CAS.

METHODS

A cross-sectional, single-center study was conducted, retrospectively analyzing hematological parameters from 259 T2DM patients with CAS (T2DM-CAS) and 131 T2DM patients without CAS (T2DM-WCAS). Carotid intima-media thickness (IMT) and carotid plaques (CAP) were measured using Doppler ultrasound.

RESULTS

The UAR level in the T2DM-CAS group was significantly higher than that in the T2DM-WCAS group (P <  0.001). Multivariate logistic regression analysis revealed that UAR is an independent risk factor for T2DM-CAS (P <  0.001). The area under the ROC curve (AUC) for UAR in predicting T2DM-CAS was 0.712, with a Youden index of 0.278.

CONCLUSION

High levels of UAR are closely associated with the occurrence of T2DM-CAS and may serve as a useful biomarker for predicting T2DM-CAS.

A Simple and Sensitive LC-MS/MS Method for Determination of Dapagliflozin and Its Major Metabolite in Human Plasma

Dapagliflozin (DAPA), an inhibitor of sodium-dependent glucose cotransporter-2, has been created to treat individuals with type 2 diabetes mellitus. A method was developed and validated using high-performance liquid chromatography coupled to tandem mass spectrometry to aid in studying the connection between clinical effectiveness and concentration of DAPA and its primary metabolite dapagliflozin 3-O-glucuronide (D3OG) in human plasma. The two analytes were separated using the Waters XSELECT HSS T3 (2.1 × 100 mm, 3.5 μm; Waters Co., Milford, USA) chromatographic column, with a mobile phase flow rate of 0.3 mL/min. The elution program was performed after protein precipitation with methanol, which only required a 5-min duration. The extraction recovery was from 99.8 to 109% for DAPA and from 101 to 103% for D3OG. Validation of the method for detecting DAPA within the range of 5-50 ng/mL and D3OG within the range of 50-500 ng/mL demonstrated satisfactory inter- and intra-day precision and accuracy. The method was successfully developed and validated, and it was used to measure the levels of DAPA and D3OG in plasma samples from patients with type 2 diabetes mellitus.

Associations of Skin Autofluorescence with Diabetic Kidney Disease in Type 2 Diabetes

Background: Diabetic kidney disease (DKD), a severe chronic complication of diabetes, significantly impacts the quality of life and life expectancy of affected individuals. Meanwhile, advanced glycation end products (AGEs) are believed to play a central role in the pathogenesis of DKD. Skin autofluorescence (SAF) is a well-validated, noninvasive technique for the estimation of AGE levels in the dermis. Aims: This study aims to evaluate the correlation between SAF and DKD prevalence, as well as the association between SAF and renal function parameters, in patients with Type 2 Diabetes Mellitus (T2DM). Methods: This cross-sectional analysis included 1259 hospitalized T2DM patients. SAF was measured using a spectroscopy device. Logistic regression analysis, p-trend analysis, and restricted cubic spline were performed with the prevalence of DKD as the dependent variable. Multiple linear regression analyses were conducted to investigate the associations of SAF with renal function parameters, specifically the estimated glomerular filtration rate (eGFR) and the log-transformed albumin-to-creatinine ratio (ln(ACR)). Results: The prevalence of DKD was strongly associated with SAF rather than with glycosylated hemoglobin (HbA1c). For each arbitrary unit (AU) increase in SAF, DKD incidence rose by 1.6%. A significant stepwise increase in the odds ratio (OR) of DKD was observed across SAF quartiles. A dose-response relationship existed between SAF and the OR value of DKD. Additionally, SAF showed a linear correlation with eGFR and ln(UACR). For each AU increase in SAF, eGFR decreased by 0.14 mL/min/1.73 m2, while UACR increased by 1.2%. Conclusions: Elevated SAF, rather than HbA1c, is independently associated with increased DKD prevalence and impaired renal function.

Elevated Triglyceride-Glucose Index as a Risk Stratification Marker for Diabetic Retinopathy in Type 2 Diabetes Mellitus: The Influence of Glycemic Control

Background

Diabetic retinopathy (DR) is a common microvascular complication observed in people with type 2 diabetes mellitus (T2DM). The triglyceride-glucose (TyG) index, an indicator of insulin resistance, has an uncertain role in glycemic management in T2DM patients at risk for DR. This study aimed to evaluate the association between the TyG index and DR risk across different glycemic control status.

Methods

A total of 4,372 T2DM in-patients from Beijing Tongren Hospital (2013-2024) were included in this study. The patients were categorized into four groups based on TyG index quartiles (Q1-Q4). Participants were stratified by TyG index quartiles (Q1-Q4) and glycemic control status (HbA1c <7%, 7-9%, and >9%). Restricted cubic spline (RCS) analysis, logistic regression, and subgroup analyses were employed to explore the associations among the TyG index, glycemic control and DR risk.

Results

Overall, there were positive association of the TyG index and DR risk. The highest TyG Q4 was significantly associated with an increased risk of DR (odds ratio [OR]: 1.289; 95% confidence interval [CI]: 1.008-1.648, P<0.05), compared with the lowest TyG Q1. Significant interaction was observed between the TyG index and glycemic control (P for interaction <0.05). Notably, the association was strongest in patients with HbA1c >9%.

Conclusion

The relationship between high TyG index and DR risk was more pronounced in patients with HbA1c >9% group, indicating that TyG index may serve as a useful tool for making risk stratification on glycemic control in T2DM patients.

White Matter Microstructural Alterations in Type 2 Diabetes: A Combined UK Biobank Study of Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging

Background and objectives: Type 2 diabetes mellitus (T2DM) affects brain white matter microstructure. While diffusion tensor imaging (DTI) has been used to study white matter abnormalities in T2DM, it lacks specificity for complex white matter tracts. Neurite orientation dispersion and density imaging (NODDI) offers a more specific approach to characterising white matter microstructures. This study aims to explore white matter alterations in T2DM using both DTI and NODDI and assess their association with disease duration and glycaemic control, as indicated by HbA1c levels. Methods and Materials: We analysed white matter microstructure in 48 tracts using data from the UK Biobank, involving 1023 T2DM participants (39% women, mean age 66) and 30,744 non-T2DM controls (53% women, mean age 64). Participants underwent 3.0T multiparametric brain imaging, including T1-weighted and diffusion imaging for DTI and NODDI. We performed region-of-interest analyses on fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI), intracellular volume fraction (ICVF), and isotropic water fraction (IsoVF) to assess white matter abnormalities. Results: We observed reduced FA and ICVF, and increased MD, AD, RD, ODI, and IsoVF in T2DM participants compared to controls (p < 0.05). These changes were associated with longer disease duration and higher HbA1c levels (0 < r ≤ 0.2, p < 0.05). NODDI identified microstructural changes in white matter that were proxies for reduced neurite density and disrupted fibre orientation, correlating with disease progression and poor glucose control. In conclusion, NODDI contributed to DTI in capturing white matter differences in participants with type 2 diabetes, suggesting the feasibility of NODDI in detecting white matter alterations in type 2 diabetes. Type 2 diabetes can cause white matter microstructural abnormalities that have associations with glucose control. Conclusions: The NODDI diffusion model allows the characterisation of white matter neuroaxonal pathology in type 2 diabetes, giving biophysical information for understanding the impact of type 2 diabetes on brain microstructure. Future research should focus on the longitudinal tracking of these microstructural changes to better understand their potential as early biomarkers for cognitive decline in T2DM.

Screening of common genomic biomarkers to explore common drugs for the treatment of pancreatic and kidney cancers with type-2 diabetes through bioinformatics analysis

Type 2 diabetes (T2D) is a crucial risk factor for both pancreatic cancer (PC) and kidney cancer (KC). However, effective common drugs for treating PC and/or KC patients who are also suffering from T2D are currently lacking, despite the probability of their co-occurrence. Taking disease-specific multiple drugs during the co-existence of multiple diseases may lead to adverse side effects or toxicity to the patients due to drug-drug interactions. This study aimed to identify T2D-, PC and KC-causing common genomic biomarkers (cGBs) highlighting their pathogenetic mechanisms to explore effective drugs as their common treatment. We analyzed transcriptomic profile datasets, applying weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis approaches to identify T2D-, PC-, and KC-causing cGBs. We then disclosed common pathogenetic mechanisms through gene ontology (GO) terms, KEGG pathways, regulatory networks, and DNA methylation of these cGBs. Initially, we identified 78 common differentially expressed genes (cDEGs) that could distinguish T2D, PC, and KC samples from controls based on their transcriptomic profiles. From these, six top-ranked cDEGs (TOP2A, BIRC5, RRM2, ALB, MUC1, and E2F7) were selected as cGBs and considered targets for exploring common drug molecules for each of three diseases. Functional enrichment analyses, including GO terms, KEGG pathways, and regulatory network analyses involving transcription factors (TFs) and microRNAs, along with DNA methylation and immune infiltration studies, revealed critical common molecular mechanisms linked to PC, KC, and T2D. Finally, we identified six top-ranked drug molecules (NVP.BHG712, Irinotecan, Olaparib, Imatinib, RG-4733, and Linsitinib) as potential common treatments for PC, KC and T2D during their co-existence, supported by the literature reviews. Thus, this bioinformatics study provides valuable insights and resources for developing a genome-guided common treatment strategy for PC and/or KC patients who are also suffering from T2D.

In silico exploration of the potential inhibitory activities of in-house and ZINC database lead compounds against alpha-glucosidase using structure-based virtual screening and molecular dynamics simulation approach

Inhibitors of α-glucosidase have been used to treat type-2 diabetes (T2DM) by preventing the breakdown of carbohydrates into glucose and prevent enhancing glucose conversion. Structure-based virtual screening (SBVS) was used to generate novel chemical scaffold-ligand α-glucosidase inhibitors. The databases were screened against the receptor α-glucosidase using SBVS and molecular dynamics simulation (MDS) techniques in this study. Based on molecular docking studies, three and two compounds of α-glucosidase inhibitors were chosen from a commercial database (ZINC) and an In-house database for this study respectively. The mode of binding interactions of the selected compounds later predicted their α-glucosidase inhibitory potential. Finally, one out of three lead compound from ZINC and one out of two lead compound from In-house database were shortlisted based on interactions. Furthermore, MDS and post-MDS strategies were used to refine and validate the shortlisted leads along with the reference acarbose/α-glucosidase. The Hits' ability to inhibit α-glucosidase was predicted by SBVS, indicating that these compounds have good inhibitory activities. The lead inhibitor's structure may serve as templates for the design of novel inhibitors, and in vitro testing to confirm their anti-diabetic potential is necessary. These insights can help rationally design new effective anti-diabetic drugs.

CDC WONDER: Trends in diabetes mellitus mortality in the United States from 1968 to 2021

This study analyzes U.S. diabetes mortality trends from 1968 to 2019 using CDC WONDER data. It reveals fluctuating age-adjusted mortality rates (AAMRs), with a decline halted between 2010-2019. Males saw rising AAMRs, while females experienced a decline. Racial disparities were evident, with higher AAMRs in the Black population.

From Metabolic Syndrome to Cardio-Kidney-Metabolic Syndrome in the SIMETAP Study: Prevalence Rates of Metabolic Syndrome and Its Independent Associations with Cardio-Renal-Metabolic Disorders Other than Its Defining Criteria

Background/Objectives: Metabolic syndrome (MetS) is a highly prevalent entity defined according to cardiometabolic criteria. Other disorders related to MetS could help assess the comprehensive risk of diabetes, cardiovascular disease, and chronic kidney disease (CKD). This study aimed to update the prevalence rates of MetS and to assess its relationship with other disorders and clinical conditions other than the criteria defining MetS. Methods: A cross-sectional observational study was conducted with a random population-based sample of 6588 study subjects between 18 and 102 years of age. Crude and sex- and age-adjusted prevalence rates of MetS were calculated, and their associations with comorbidities and clinical conditions other than their defining criteria were assessed by bivariate and multivariate analysis. Results: The adjusted prevalence rates were 36.0% for MetS (39.8% in men; 33.5% in women), 21.5% for premorbid Mets, and 14.5% for morbid MetS. Considering only clinical conditions other than the criteria defining MetS, the independent disorders associated with premorbid MetS were hypercholesterolemia, hypertension, high levels of lipid accumulation product, high triglyceride-glucose index (TyG), high visceral adiposity index, high fatty liver index, and high waist-to-height ratio (WtHR), highlighting excess adiposity (EA). The independent disorders associated with morbid MetS were hypercholesterolaemia, high-WtHR, EA, high-TyG index, heart failure, atrial fibrillation, CKD, and albuminuria, highlighting hypertension. Conclusions: One-fifth of the adult population has premorbid MetS, and almost one-sixth has morbid MetS. Almost two-fifths of people with MetS are at moderate, high, or very high risk of CKD, and four-fifths are at high or very high cardiovascular risk. In addition to the criteria defining MetS, other cardiovascular-renal-metabolic disorders show an independent association with MetS, highlighting EA for premorbid MetS and hypertension for morbid MetS.

The Application of Preventive Medicine in the Future Digital Health Era

A number of seismic shifts are expected to reshape the future of medicine. The global population is rapidly aging, significantly impacting the global disease burden. Medicine is undergoing a paradigm shift, defining and diagnosing diseases at earlier stages and shifting the health care focus from treating diseases to preventing them. The application and purview of digital medicine are expected to broaden significantly. Furthermore, the COVID-19 pandemic has further accelerated the shift toward predictive, preventive, personalized, and participatory (P4) medicine, and has identified health care accessibility, affordability, and patient empowerment as core values in the future digital health era. This "left shift" toward preventive care is anticipated to redefine health care, emphasizing health promotion over disease treatment. In the future, the traditional triad of preventive medicine-primary, secondary, and tertiary prevention-will be realized with technologies such as genomics, artificial intelligence, bioengineering and wearable devices, and telemedicine. Breast cancer and diabetes serve as case studies to demonstrate how these technologies such as personalized risk assessment, artificial intelligence-assisted and app-based technologies, have been developed and commercialized to provide personalized preventive care, identifying those at a higher risk and providing instructions and interventions for healthier lifestyles and improved quality of life. Overall, preventive medicine and the use of advanced technology will hold great potential for improving health care outcomes in the future.

Deciphering agronomic traits, biochemical components, and color in unique green-seeded fenugreek (Trigonella foenum-graecum L.) genotypes

Fenugreek is a high-value legume known for its potential to enhance human health and combat a variety of diseases and metabolic disorders. This versatile crop has demonstrated promising therapeutic effects in managing obesity, diabetes, cancer, and poor metabolism conditions that have become major global health concerns. Despite the availability of multiple pharmaceutical remedies for these ailments in the market, often times the heavy chemical doses are accompanied by side effects on human body. To investigate the agronomic traits, medicinal potential, and color of fenugreek seeds, this study was conducted and identified fenugreek genotypes with green seed color (GSF1 to GSF10), which can prevent the progression of aforementioned diseases without the hassle of side effects. Ten unique green-seeded fenugreek (GSF) genotypes were compared with five released varieties (yellow-seeded fenugreek; YSF1 to YSF5) as check. The genotypes were assessed during rabi season for 3 consecutive years (2021-22 to 2023-24) in semi-arid Eastern Plain Zone of Rajasthan, India. The findings exhibited that agronomically GSF performed well, almost at par with the YSF. Harvest index (23.21 ± 0.37%) is higher in GSF with very marginal differences in other agronomic traits. The medicinal potential of the GSF showed that GSF6 has nearly 1.5 to 2 times higher insulinotropic 4-hydroxyisoleucine (0.90%) levels compared to the YSF genotypes. This unique non-protein branched amino acid is found in fenugreek seeds. GSF1 has a high concentration of chlorophyll (0.45 mg/100 g), GSF10 has low diosgenin and high 4-OHIle (261.80 mg/100 g and 0.85%, respectively), and GSF9 has low total soluble sugars (TSS; 3.50%). Oil content, phenols, and proteins were found to be higher in GSF making it preferable over YSF. The study further revealed that darkness of green color in the seed is directly related to its chlorophyll content and is directly associated with higher content of 4-OHIle and lower TSS. Among the studied genotypes, harvest index is higher in green-seeded genotypes with maximum seed yield (2473.74 Kg/ha) in genotype GSF8. The superior genotypes GSF1, GSF6, GSF8, GSF9, and GSF10 developed in the study hold potential for future breeding initiatives, aimed at boosting medicinal value, nutritional quality, and productivity.

A Supramolecular Gel-Based Protocol for the Detection of α-Glycosidases for Screening Potential Drugs

α-Glycosidases are carbohydrate-digesting enzymes that catalyze the hydrolysis of α-1,4-glycopyranoside bonds from oligosaccharides and disaccharides. α-Glucosidase is an important biomarker for the diagnosis of type-II diabetes, Azoospermia and Pompe diseases. Additionally, the mutations in α-galactosidase lead to Fabry disease. Inhibitors targeting these enzymes are prescribed as anti-diabetic medications and as effective chaperones for Fabry disease. Comprehending the function - regulation of α-glycosidases requires accurate quantification methods. In this work, we highlight the design of a simple luminescent 'turn-on' assay for sensing these two α-glycosidases in a supramolecular TbCh hydrogel matrix using 1-α-glycosides as pro-sensitizers. The protocol offers a cost-effective method for selectively sensing α-glycosidases in the detection limit of the subnanomolar range. Importantly, the developed enzyme sensors functioned as a platform for rapid screening of drug molecules based on their inhibition potency. Therefore, the protocol is useful for facilitating the advancement of therapeutics and diagnostics targeting this important class of enzymes.

Pregestational Diabetes and Adverse Pregnancy Results: A Mendelian Randomization Study

BACKGROUND

Hyperglycemia in pregnancy is believed to be associated with negative pregnancy outcomes. However, establishing a causal connection between diabetes mellitus (DM) and adverse pregnancy results is challenging due to the limitations inherent in traditional observational studies.

METHODS

Our study used a two-sample Mendelian randomization (MR) technique to examine the possible influence of pregestational diabetes mellitus (PGDM) on adverse pregnancy outcomes. Summary-level data were obtained from genome-wide association studies (GWAS) of European ancestry and FinnGen biobank. The primary analysis employed the random-effects multiplicative inverse variance weighted (IVW) technique to appraise causal relationships between PGDM and adverse outcomes. Heterogeneity and pleiotropy were assessed using Cochran's Q statistic, Rucker's Q statistic, and the I² statistic. Sensitivity analyses were conducted using MR-Egger and weighted median methods. Additionally, outlier detection techniques, including MR-PRESSO and RadialMR, were applied.

RESULTS

The results from the IVW method indicated no significant causal association between PGDM and stillbirth (SB) (OR (SE)=0.99 (0.001); P value=0.992), miscarriage (MIS) (OR (SE)=0.97 (0.016); P value=0.125), and preterm birth (PTB) (OR (SE)=1.072 (0.028); P value=0.014). Pleiotropy and heterogeneity tests revealed no evidence of pleiotropy for SB, MIS, and PTB (MR-Egger intercept P value=0.296, 0.525, and 0.532, respectively), with no observed heterogeneity for SB, MIS, and PTB (Q- P values of IVW were 0.929, 0.999, and 0.069, and MR-Egger were 0.931, 0.999, and 0.065, respectively).

CONCLUSION

Our findings indicate that there is no direct causal link between PGDM and the likelihood of MIS, SB, and PTB.

Disease burden of cancers attributable to high fasting plasma glucose from 1990 to 2021 and projections until 2031 in China

BACKGROUND

High fasting plasma glucose (HFPG) has been indicated as one of the important risk factors for cancers. This study aimed to estimate the disease burden of cancers attributable to HFPG in China from 1990 to 2021 and predict the burden until 2031.

METHODS

The data of cancers attributable to HFPG were extracted from Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 project. A joinpoint regression model was conducted to estimate the temporal trends from 1990 to 2021. The effects of age, period, and cohort were estimated by an age-period-cohort (APC) model. Lastly, a Bayesian APC model was employed to predict the disease burden for the next decade.

RESULTS

From 1990-2021, cancer deaths attributable to HFPG in China increased by 232 % (95 % uncertainty interval [UI]: 156-330.77 %), and disability-adjusted life-years (DALYs) increased by 195.4 % (95 % UI: 127.38-289.7 %). In addition, the average annual percentage change (AAPC) for the age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR) were 0.6364 % (95 % confidence interval [CI]: 0.4234-0.8498 %) and 0.6263 % (95 % CI: 0.3024-0.9512 %), respectively. Among all cancer types, pancreatic cancer had the largest increase in disease burden. The risks of mortality and DALYs increased with age, while showing initial rapid increase with period growth followed by relative stabilization. The cohort effect indicates that males born later had higher risks of mortality and DALYs. Finally, despite a continuous decline in both ASMR and ASDR, the numbers of deaths and DALYs were projected to continue increasing in the next decade.

CONCLUSIONS

The disease burden of cancers attributable to HFPG significantly increased from 1990 to 2021 in China, and the numbers of deaths and DALYs would continuously increase in the next decade. Therefore, it is necessary to introduce targeted policies controlling the disease burden.

Impact of Blood Glucose Level on Hematological Indices in Patients with Type 2 Diabetes Mellitus

BACKGROUND

The severity and complications of type 2 diabetes mellitus (T2DM) are the most important preventable health burdens. This study was undertaken to assess the impact of hyperglycemia on hematological indices in patients with T2DM.

MATERIALS AND METHODS

This study was conducted on 300 patients with T2DM, which included group A having controlled diabetes [hemoglobin A1c (HbA1c) <7%] and group B having uncontrolled diabetes (HbA1c >7%). Information concerning medical history, physical examination, diabetic parameters, hematological indices, and laboratory findings was extracted for interpretation and association between both groups.

RESULTS

About 115 patients (38.33%) had HbA1c <7% and 185 patients (61.67%) had HbA1c >7%. Total leukocyte count (TLC), monocytes, basophils, red cell distribution width (RDW-CV), platelet distribution width (PDW), mean platelet volume (MPV), platelet large cell ratio (P-LCR), plateletcrit (PCT), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were significantly higher among patients with uncontrolled T2DM compared to those with controlled T2DM (p < 0.05), while red blood cells (RBC) count, hemoglobin, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) were significantly lower in the uncontrolled diabetic group compared to the controlled diabetic group (p < 0.05). HbA1c had a significant positive correlation coefficient with TLC, neutrophil count, basophil count, PDW, MPV, PCT, PLR, and NLR, while RBC count, hemoglobin, hematocrit (HCT), and MCV showed significant negative correlation coefficients (p < 0.05).

CONCLUSION

This study concluded that inflammation, tendency to coagulation, and thrombosis can be detected with easily accessible and inexpensive hematological indices. Therefore, hematological indices can be used as a direct measure to detect the severity of T2DM and its complications.

Targeted Therapies: The Role of Monoclonal Antibodies in Disease Management

Monoclonal antibodies (mAbs) are a key class of biotherapeutic medicines used to treat a wide range of diseases, such as cancer, infectious diseases, autoimmune disorders, cardiovascular diseases, and hemophilia. They can be engineered for greater effectiveness and specific applications while maintaining their structural elements for immune targeting. Traditional immunoglobulin treatments have limited therapeutic uses and various adverse effects. That makes mAbs show rapid growth in the pharmaceutical market, with over 250 mAbs in clinical studies. Although mAbs offer higher specificity, they are less effective against complex antigens. They have become essential in treating diseases with limited medical options, providing innovative solutions that improve patients' quality of life through increasing survival rates, shortening the length of stay in hospitals with an improved treatment outcome, and reducing side effects. This review outlines the mechanisms, applications, and advancements of mAbs, highlighting their transformative role in modern medicine and their potential to shape future therapeutic interventions.

Sucrose-preferring gut microbes prevent host obesity by producing exopolysaccharides

Commensal bacteria affect host health by producing various metabolites from dietary carbohydrates via bacterial glycometabolism; however, the underlying mechanism of action remains unclear. Here, we identified Streptococcus salivarius as a unique anti-obesity commensal bacterium. We found that S. salivarius may prevent host obesity caused by excess sucrose intake via the exopolysaccharide (EPS) -short-chain fatty acid (SCFA) -carbohydrate metabolic axis in male mice. Healthy human donor-derived S. salivarius produced high EPS levels from sucrose but not from other sugars. S. salivarius abundance was significantly decreased in human donors with obesity compared with that in healthy donors, and the EPS-SCFA bacterial carbohydrate metabolic process was attenuated. Our findings reveal an important mechanism by which host-commensal interactions in glycometabolism affect energy regulation, suggesting an approach for preventing lifestyle-related diseases via prebiotics and probiotics by targeting bacteria and EPS metabolites.

Generalized functional varying-index coefficient model for dynamic synergistic gene-environment interactions with binary longitudinal traits

The genetic basis of complex traits involves the function of many genes with small effects as well as complex gene-gene and gene-environment interactions. As one of the major players in complex diseases, the role of gene-environment interactions has been increasingly recognized. Motivated by epidemiology studies to evaluate the joint effect of environmental mixtures, we developed a functional varying-index coefficient model (FVICM) to assess the combined effect of environmental mixtures and their interactions with genes, under a longitudinal design with quantitative traits. Built upon the previous work, we extend the FVICM model to accommodate binary longitudinal traits through the development of a generalized functional varying-index coefficient model (gFVICM). This model examines how the genetic effects on a disease trait are nonlinearly influenced by a combination of environmental factors. We derive an estimation procedure for the varying-index coefficient functions using quadratic inference functions combined with penalized splines. A hypothesis testing procedure is proposed to evaluate the significance of the nonparametric index functions. Extensive Monte Carlo simulations are conducted to evaluate the performance of the method under finite samples. The utility of the method is further demonstrated through a case study with a pain sensitivity dataset. SNPs were found to have their effects on blood pressure nonlinearly influenced by a combination of environmental factors.

Hypomagnesemia in adults with type 2 diabetes mellitus in Riyadh, Saudi Arabia: A cross-sectional study

This study investigates the prevalence of hypomagnesemia in adults with type 2 diabetes mellitus (T2DM) in Riyadh, Saudi Arabia, and examines its association with various metabolic parameters. Conducted as a cross-sectional study at King Saud University, Riyadh, it included 294 Saudi adults aged 25 to 65 years, comprising 119 T2DM patients, 80 prediabetics, and 95 nondiabetic controls. Participants underwent physical examinations, and fasting blood samples were analyzed for glucose, glycated hemoglobin (HbA1c), lipid profile, and serum magnesium levels. Statistical analysis revealed that lower magnesium levels were significantly more prevalent in T2DM patients (1.65 ± 4.9 mg/L) compared to prediabetes (2.48 ± 5.2 mg/L) and controls (2.9 ± 5.4 mg/L; P < .001). T2DM patients with magnesium deficiency exhibited higher levels of fasting glucose (11.2 ± 3.9 mmol/L), HbA1c (8.6 ± 2.1 mmol/L), and triglycerides (2.1 ± 0.9 mmol/L), along with increased insulin resistance (Homeostatic Model Assessment of Insulin Resistance = 6.6) and decreased insulin sensitivity (Quantitative Insulin Sensitivity Check Index = 0.29). Magnesium levels correlated negatively with glucose (R = -0.58) and HbA1c (R = -0.61). The area under the curve for serum magnesium in predicting HbA1c > 5.7 was 0.88, and for HbA1c ≥ 6.5, it was 0.91, indicating high diagnostic accuracy. These findings suggest that magnesium deficiency significantly impacts the metabolic profile of T2DM patients in Riyadh. Therefore, routine monitoring of magnesium levels is crucial in diabetes management, and further research is needed to explore the benefits of magnesium supplementation in T2DM care.

Distinct effects of obesity and diabetes on the action potential waveform and inward currents in rat ventricular myocytes

Obesity is a significant global health challenge, increasing the risk of developing type 2 diabetes mellitus (T2DM) and cardiovascular disease. Research indicates that obese individuals, regardless of their diabetic status, have an increased risk of cardiovascular complications. Studies suggest that these patients experience impaired electrical conduction in the heart, although the underlying cause-whether due to obesity-induced fat toxicity or diabetes-related factors-remains uncertain. This study investigated ventricular action potential parameters, as well as sodium (INa) and calcium (ICa, L) currents, in Zucker fatty (ZF) rats and Zucker diabetic fatty (ZDF) rats, which serve as models for obesity and T2DM, respectively. Ventricular myocytes were isolated from 25- to 30-week-old Zucker rats. Resting and action potentials were recorded using a β-escin perforated patch clamp, while INa and ICa,L were assessed with whole-cell patch clamp methods. ZF rats exhibited higher excitability and faster upstroke velocity with greater INa density, whereas ZDF rats showed decreased INa and slower action potential upstroke. No differences in ICa,L density or voltage sensitivity were found among the groups. In summary, obesity, with or without accompanying T2DM, distinctly impacts the action potential waveform, INa density, and excitability of ventricular myocytes in this rat model of T2DM.

New semisynthetic α-glucosidase inhibitor from a doubly-chemically engineered extract

Chemically engineered extracts represent a promising source of new bioactive semi-synthetic molecules. Prepared through direct derivatization of natural extracts, they can include constituents enriched with elements and sub-structures that are less common in natural products compared to drugs. Fourteen such extracts were prepared through sequential reactions with hydrazine and a fluorinating reagent, and their α-glucosidase inhibition properties were compared. For the most bioactive mixture, a chemically modified propolis extract, enzyme inhibition increased 22 times due to the reaction sequence. Bio-guided fractionation led to the isolation of a new fluorinated pyrazole produced within the extract by chemical transformation of the flavonoid chrysin. The inhibitor results from the action of the two reagents used on four common functional groups present in natural products (carbonyl, phenol, aromatic carbon, and a double bond). The reactions led to the opening of a 6-member oxygenated heterocycle to produce a 5-member nitrogenated one, as well as the dehydroxylation and fluorination in two different positions of one of the aromatic rings of the natural starting material, all within a complex mixture of natural products. Overall, these transformations led to an approximately 20-fold increase in the α-glucosidase inhibition by the isolated inhibitor compared to its natural precursor.

Effects of Diabetes and Hyperlipidemia in Physiological Conditions - A Review

BACKGROUND

Diabetes mellitus (DM) is an autoimmune manifestation defined by persistent hyperglycemia and alterations in protein, fatty substances, and carbohydrate metabolism as an effect of problems with the secretion of insulin action or both. Manifestations include thirst, blurred eyesight, weight loss, and ketoacidosis, which can majorly lead to coma. There are different types of diabetes according to class or by cellular level. They are interrelated with hyperlipidemia as they are involved in the metabolism and regulation of physiological factors. Most parameters are seen at cellular or humoral levels, yet the underlying concern remains the same.

OBJECTIVE

To create a systematic correlation between the disease and locate the exact mechanism and receptors responsible for it. So, this article covers a proper way to resolve the conditions and their manifestation through literacy and diagrammatic.

CONCLUSION

Hence, this will be an insight for many scholars to understand the exact mechanism involved in the process.

Insights into the systemic risk factors associated with diabetic retinopathy in the Indian population: A comprehensive systematic review and meta-analysis

Diabetic retinopathy (DR) is a predominant cause of vision impairment globally. Understanding risk factors is crucial for effective planning. The aim of this study is to comprehensively investigate the risk factors in the Indian population contributing to the increased incidence of DR, which is a potentially sight-threatening complication among diabetic individuals. A comprehensive literature search was done on PubMed, Embase, and Google Scholar databases for epidemiological studies reporting risk factors in the adult Indian population in the English language. Joanna Briggs Institute's (JBI) critical appraisal tools were used to assess the quality of the included studies. Analysis was performed using R studio. I2 statistic was used for the assessment of heterogeneity. Results are expressed as odds ratio (OR) and standardized mean difference (SMD) along with a 95% confidence interval (CI). Overall, 20 studies enrolling 4,12,421 patients with 1,04,104 DR-positive and 3,08,317 DR-negative adults were analyzed. Being male (OR: 1.38, 95% CI: 1.11-1.72), intake of insulin (OR: 2.05, 95% CI: 1.02-4.14), higher HbA1c levels (MD: 0.50, 95% CI: 0.06-0.94), higher random (MD: 0.32, 95% CI: 0.10-0.55), and fasting blood glucose levels (MD: 0.51, 95% CI: 0.10-0.93) were found to be significantly associated with increased risks of DR among diabetic patients, while age, body mass index, hypertension, lipid profile, and smoking status did not indicate any association with DR. Good glycemic control remains the most important modifiable risk factor to reduce the risk of progression of DR and vision loss.

The Rise of Type 2 Diabetes in Children and Adolescents: An Emerging Pandemic

AIM

This review explores the increasing prevalence of Type 2 Diabetes Mellitus (T2DM) in children and adolescents, focusing on its etiology, risk factors, complications, and the importance of early detection and management. It also highlights the need for a multidisciplinary, family-centered approach in managing T2DM in pediatric populations, with an emphasis on nutrition, exercise, and lifestyle interventions.

MATERIALS AND METHODS

A literature review was conducted using PubMed, Google Scholar, and Scopus to incorporate studies from 2015 to 2024 on T2DM in youths/adolescents/children, focusing on epidemiology, risk factors, and prevention strategies. Studies on Type 1 Diabetes Mellitus (T1DM) or adult populations were excluded.

RESULTS

T2DM is a complex metabolic disorder with various societal, behavioral, environmental, and genetic risk factors. It accounts for one in three new childhood diabetes cases, with rising incidence among American Indian/Alaska Native, Black, and Hispanic/Latino children. The increase in T2DM incidence correlates with growing childhood obesity rates. Early onset significantly raises the risk of complications like retinopathy, nephropathy, neuropathy, cardiovascular diseases, nonalcoholic fatty liver disease, and obstructive sleep apnea. Early detection, screening, and treatment can prevent or delay these complications. A family-centered, multidisciplinary approach is essential for effective management, including lifestyle and behavioral support.

CONCLUSIONS

T2DM in children is a growing health concern with severe implications. Early detection and management, including nutrition and exercise counseling, are critical in reducing long-term complications. A multidisciplinary approach is vital for improving outcomes and minimizing morbidity and mortality.

Linarin Identified as a Bioactive Compound of Lycii Cortex Ameliorates Insulin Resistance and Inflammation Through the c-FOS/ARG2 Signaling Axis

Insulin resistance (IR) is a central pathophysiological process underlying numerous chronic metabolic disorders, including type 2 diabetes and obesity. Lycii Cortex, a widely used traditional Chinese herb, has demonstrated potential benefits in preventing and managing diabetes and IR. Whereas, the specific bioactive compounds responsible for these protective effects and their underlying mechanisms of action remain elusive. This study aimed to identify the bioactive components within Lycii Cortex that contribute to its anti-diabetic effects and to elucidate the molecular mechanisms underlying its beneficial actions on insulin resistance. Network pharmacology and molecular docking analyses were employed to identify the potential active compounds in Lycii Cortex and their corresponding target proteins. An in vitro model of IR was established using palmitic acid (PA)-treated HepG2 cells. Cell viability was assessed using the CCK-8 assay, while glucose uptake was evaluated by 2-NBDG staining and extracellular glucose measurement. To validate the in vitro findings, an in vivo model of obesity-induced IR was established using high-fat diet (HFD)-fed mice. The network pharmacology analysis preliminarily identified 13 candidate chemicals and 10 hub LyC and IR-related genes (LIRRGs). Molecular docking analysis demonstrates that Linarin as the potential active component exhibits the greatest potential to target c-FOS for preventing obesity-induced IR. Enrichment analysis suggested that Linarin-targeted pathways are correlated with inflammation. In vitro experimental validation demonstrated that Linarin was capable of protecting against PA-induced IR in HepG2 cells evidenced by improving glucose uptake ability and reducing extracellular glucose content. Additionally, we found that Linarin ablated PA-induced increase in the expression of c-FOS and inflammatory cytokines. Furthermore, in PA-treated cells, silencing c-FOS markedly improved glucose consumption, and reduced inflammation and Arginase 2 (ARG2) expression. Similarly, as exposure to PA, silencing ARG2 also ameliorated glucose uptake and inflammation, while not affecting c-FOS expression. In vivo experiments further showed that Linarin administration remarkably improved glucose tolerance and insulin sensitivity, and reduced the fat mass and body weight in HFD-induced obese mice. In this study, Linarin has been identified as the bioactive compound of Lycii Cortex to ameliorate obesity-related IR and inflammation through the c-FOS/ARG2 signaling cascade. These findings underscore the therapeutic potential of Linarin and provide valuable insights into developing novel intervention strategies for type 2 diabetes therapy.

Bioinformatics analysis of miRNAs germacrone protection on diabetic nephropathy

Diabetes nephropathy (DN) is a prevalent and severe microvascular diabetic complication. Despite the recent developments in germacrone-based therapies for DN, the underlying mechanisms of germacrone in DN remain poorly understood. This study used comprehensive bioinformatics analysis to identify critical microRNAs (miRNAs) and the potential underlying pathways related to germacrone activities. Additionally, we established a DN mice model, which was treated with germacrone, to investigate how it altered the miRNA transcriptome in mice kidneys. RNA sequencing was also performed on the DN mice model with and without germacrone pre-treatment. Based on our results, we found 23 miRNAs were differentially expressed in the DN group compared to the controls, and a total of 14 miRNAs were differentially expressed between the DN group and the germacrone-treated group. In addition, we identified three miRNAs (mmu-miR-542-5p, mmu-miR-149-5p and mmu-miR-196a-2-3p) that were upregulated with the DN group and downregulated in the germacrone-treated group. Bioinformatics analysis suggested that autophagy and apoptosis were related to the pathogenesis of DN and germacrone treatment. Subsequently, the expression level of mmu-miR-542-5p, mmu-miR-149-5p and mmu-miR-196a-2-3p were validated in a validation dataset. Altogether, these findings add important knowledge on the pathogenesis of DN and the impacts of germacrone.

Attenuation of Experimental Cholesterol Gallstone Formation by Manganese Chloride in Mice: Role of NF-κβ Pathways

Manganese (Mn), a trace element, has been documented to exert an important role in the metabolism of cholesterol. Cholesterol gallstone (CG) pathogenesis is directly linked to biliary cholesterol imbalance which could be due to diabetes complications or mismanagement. NF-κβ pathway, an inflammatory regulator, has been implicated in metabolic disease especially in the context of diabetes and gallstone formation. However, the management of cholesterol gallstones due to diabetes with trace elements is vague. This study investigates the probable role of manganese during CG formation due to diabetes complications. Eighty female Swiss mice were grouped: I (control), II (untreated CG), III and IV (normal mice treated 0.37 mg/kg and 0.74 mg/kg Mn, respectively), V and VI (CG treated 0.37 mg/kg and 0.74 mg/kg Mn, respectively), and VII and VIII (CG treated 75 mg/7 kg and 350 mg/kg aspirin, respectively). Experimental CG was induced with cholesterol-rich diets after alloxan-induced diabetes. On sacrifice, blood collected was evaluated for complete hematological analysis and biochemistry while the excised liver was assayed for biochemical variables. Results were subjected to one-way ANOVA values were expressed as Mean ± SEM and significant at p ≤ 0.05. Manganese treatment significantly increased packed cell volume, RBC count, and hemoglobin with decreased platelet and leukocyte counts, liver enzymes (AST, ALT, and ALP), BUN, and creatinine levels in CG groups compared with untreated CG. Blood glucose, plasma low-density lipoproteins, and liver malodialdehyde levels were significantly reduced while liver nitric-oxide, sulfhydryl, and glutathione levels increased significantly in manganese-treated groups compared with untreated CG. Manganese significantly increased fecal iron contents in normal mice by the 2nd week. Hepatocytes and gallbladder histology appear normal in manganese-treated groups. Liver NF-Kβ immunoreactivity was downregulated in manganese-treated CG groups. Manganese attenuated experimental hyperglycemia-induced cholesterol gallstone by ameliorating liver oxidative stress and NF-Kβ inflammatory pathway.

Evaluation of Hypoglycemic Polyphenolic Compounds in Blueberry Extract: Functional Effects and Mechanisms

Blueberries are rich in polyphenols, which exhibit significant anti-diabetic activity. In this study, polyphenolic compounds with potential hypoglycemic activity were identified from blueberry polyphenol extract (BPE). This research focused on assessing the hypoglycemic effects of BPE and its polyphenolic compounds (dihydroquercetin and gallic acid) on diabetic mice induced by streptozotocin (STZ) and high-fat diet (HFD), as well as the related fundamental mechanisms. The findings revealed that BPE treatment effectively reduced levels of fasting blood glucose (FBG) by decreasing hepatic oxidative stress, regulating lipid metabolism disorders and improving insulin resistance. Investigations into the insulin signaling pathway revealed that BPE can modulate the expression of Egfr, Insr, Irs-1, Pi3k and Akt, thereby influencing glucose metabolism. This study provides a research foundation for considering blueberry polyphenols as a nutritional dietary supplement for the prevention and intervention of diabetes.

Adipose tissue retains an epigenetic memory of obesity after weight loss

Reducing body weight to improve metabolic health and related comorbidities is a primary goal in treating obesity1,2. However, maintaining weight loss is a considerable challenge, especially as the body seems to retain an obesogenic memory that defends against body weight changes3,4. Overcoming this barrier for long-term treatment success is difficult because the molecular mechanisms underpinning this phenomenon remain largely unknown. Here, by using single-nucleus RNA sequencing, we show that both human and mouse adipose tissues retain cellular transcriptional changes after appreciable weight loss. Furthermore, we find persistent obesity-induced alterations in the epigenome of mouse adipocytes that negatively affect their function and response to metabolic stimuli. Mice carrying this obesogenic memory show accelerated rebound weight gain, and the epigenetic memory can explain future transcriptional deregulation in adipocytes in response to further high-fat diet feeding. In summary, our findings indicate the existence of an obesogenic memory, largely on the basis of stable epigenetic changes, in mouse adipocytes and probably other cell types. These changes seem to prime cells for pathological responses in an obesogenic environment, contributing to the problematic 'yo-yo' effect often seen with dieting. Targeting these changes in the future could improve long-term weight management and health outcomes.

The association between hypertension and different types of dietary carbohydrates

Background

Hypertension is the most prominent and well acknowledged chronic disease in developed countries and is a significant contributor to global mortality. The present study aimed to investigate the association between hypertension and different types of dietary carbohydrates.

Method

This cross-sectional study was conducted on 4184 people aged 35-70, including 1239 patients with hypertension and 2945 subjects with normal blood pressure (BP) in Sabzevar, Iran. The dietary intake data were collected through the administration of a semiquantitative Food Frequency Questionnaire. Utilizing Nutritionist IV software, dietary glucose, fructose, simple sugar, carbohydrate, and galactose consumption were evaluated.

Results

A direct association was found between dietary glucose and BP (odds ratio: 1.02; 95% CI: 1.01-1.05; P = 0.04). This association remained significant after adjusting for age. Further adjustments for education, marital status, job, physical activity, and BMI, and additional adjustments for energy intake did not change the results.

Conclusion

In summary, the present study identified a significant association between hypertension and dietary intake of glucose. Considering that carbohydrates are an essential part of the diet worldwide, these findings can be valuable in formulating dietary interventions for hypertensive patients.

Prognostic effectiveness of interactive vs. non-interactive mobile app interventions in type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Mobile app interventions are emerging as significant tools in managing the prognosis of type 2 diabetes, demonstrating progressively greater impacts. The effectiveness of these interventions needs further evidence-based support.

OBJECTIVE

This study conducted a systematic review and meta-analysis of randomized controlled trials to evaluate the effectiveness of mobile app interventions in improving prognosis for patients with type 2 diabetes.

METHODS

We searched PubMed, Cochrane, Embase, and Web of Science for relevant studies published from inception to 18 April 2024, adhering to the Cochrane Handbook guidelines. The quality of the included studies was assessed using the Cochrane risk of bias tool. Primary outcomes measured were changes in glycated hemoglobin (HbA1c) and diabetes self-management (DSM). Secondary outcomes included changes in diastolic blood pressure (DBP), systolic blood pressure (SBP), triglycerides(TG), total cholesterol(TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), lipid profiles, fasting plasma glucose (FPG), body mass index (BMI), and Steps outcomes. Subgroup analyses were performed for the primary outcomes and for high-density lipoprotein (HDL), low-density lipoprotein (LDL), diastolic blood pressure (DBP), and systolic blood pressure (SBP). Interventions with or without interactions were also used as a basis for subgrouping.

RESULTS

A total of 15 eligible articles involving 17 studies with 2,028 subjects (1,123 in the intervention group and 1,020 in the control group) were included in the synthesis. Interactive mobile app interventions significantly reduced HbA1c levels (SMD - 0.24; 95% CI, -0.33 to -0.15; P < 0.00001) and significantly improved diabetes self-care (SMD 0.71; 95% CI, 0.21 to 1.21; P = 0.005). Secondary outcomes, including FPG, LDL, DBP, and SBP, showed varying degrees of improvement. Subgroup analyses indicated that the intervention effect was more pronounced and less heterogeneous in the short-term (≤ 3 months) for younger Asian individuals (< 55 years) who used an interactive mobile app.

CONCLUSION

Interactive mobile app interventions effectively improve HbA1c levels and diabetes self-care competencies in patients with type 2 diabetes. These interventions offer supportive evidence for their clinical use in managing and prognosticating type 2 diabetes.

SYSTEMATIC REVIEW REGISTRATION

CRD42024550643.