The burden and risks of emerging complications of diabetes mellitus

Exploring the effect and mechanism of action of Jinlida granules (JLD) in the treatment of diabetes-associated cognitive impairment based on network pharmacology with experimental validation

OBJECTIVES

To explore the effect and the probable mechanisms of JLD in the treatment of type 2 diabetes mellitus (T2DM) - associated cognitive impairment (TDACI).

METHODS

The effect of JLD in combating TDACI was assessed in T2DM model mice by conducting Morris water maze (MWM) behaviour testing. Active components and their putative targets, as well as TDACI-related targets, were collected from public databases. Protein-protein interactions (PPIs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and molecular docking were then utilized to explore potential molecular network mechanisms. Finally, the main targets were verified in animal model experiments.

RESULTS

MWM test showed that JLD improved aspects of behaviour in T2DM model mice. JLD improved glucose intolerance, tissue insulin sensitivity, lipid metabolism and enhanced synapse-associated protein expression in hippocampus tissue. Network pharmacology revealed 185 active components, 337 targets of JLD, and 7998 TDACI related targets were obtained . PPI network analyses revealed 39 core targets. GO and KEGG analyses suggested that JLD might improve TDACI by regulating gene expression, apoptotic processes and inflammatory responses mainly via PI3K-AKT and AGE-RAGE signaling pathways. Molecular docking revealed strong binding of the main components to core targets. JLD reduced hippocampus tissue expression of the inflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin-6 (IL6), core targets of treatment of TDACI.

CONCLUSIONS

The findings suggested that JLD has the potential to improve TDACI through multiple components, multiple targets and multiple pathways. JLD may be a promising treatment for diabetic cognitive impairment.

Bioactive hydrogel formulations for regeneration of pathological bone defects

Bone defects caused by osteoporosis, infection, diabetes, post-tumor resection, and nonunion often cause severe pain and markedly increase morbidity and mortality, which remain a significant challenge for orthopedic surgeons. The precise local treatments for these pathological complications are essential to avoid poor or failed bone repair. Hydrogel formulations serve as injectable innovative platforms that overcome microenvironmental obstacles and as delivery systems for controlled release of various bioactive substances to bone defects in a targeted manner. Additionally, hydrogel formulations can be tailored for specific mechanical strengths and degradation profiles by adjusting their physical and chemical properties, which are crucial for prolonged drug retention and effective bone repair. This review summarizes recent advances in bioactive hydrogel formulations as three-dimensional scaffolds that support cell proliferation and differentiation. It also highlights their role as smart drug-delivery systems with capable of continuously releasing antibacterial agents, anti-inflammatory drugs, chemotherapeutic agents, and osteogenesis-related factors to enhance bone regeneration in pathological areas. Furthermore, the limitations of hydrogel formulations in pathological bone repair are discussed, and future development directions are proposed, which is expected to pave the way for the repair of pathological bone defects.

Multi-tissue metabolomics reveal mtDNA- and diet-specific metabolite profiles in a mouse model of cardiometabolic disease

RATIONALE

Excess consumption of sugar- and fat-rich foods has heightened the prevalence of cardiometabolic disease, which remains a driver of cardiovascular disease- and type II diabetes-related mortality globally. Skeletal muscle insulin resistance is an early feature of cardiometabolic disease and is a precursor to diabetes. Insulin resistance risk varies with self-reported race, whereby African-Americans have a greater risk of diabetes development relative to their White counterparts. Self-reported race is strongly associated with mitochondrial DNA (mtDNA) haplogroups, and previous reports have noted marked differences in bioenergetic and metabolic parameters in cells belonging to distinct mtDNA haplogroups, but the mechanism of these associations remains unknown. Additionally, distinguishing nuclear DNA (nDNA) and mtDNA contributions to cardiometabolic disease remains challenging in humans. The Mitochondrial-Nuclear eXchange (MNX) mouse model enables in vivo preclinical investigation of the role of mtDNA in cardiometabolic disease development, and has been implemented in studies of insulin resistance, fatty liver disease, and obesity in previous reports.

METHODS

Six-week-old male C57nDNA:C57mtDNA and C3HnDNA:C3HmtDNA wild-type mice, and C57nDNA:C3HmtDNA and C3HnDNA:C57mtDNA MNX mice, were fed sucrose-matched high-fat (45% kcal fat) or control diet (10% kcal fat) until 12 weeks of age (n = 5/group). Mice were weighed weekly and total body fat was collected at euthanasia. Gastrocnemius skeletal muscle and plasma metabolomes were characterized using untargeted dual-chromatography mass spectrometry; both hydrophilic interaction liquid chromatography (HILIC) and C18 columns were used, in positive- and negative-ion modes, respectively.

RESULTS

Comparative analyses between nDNA-matched wild-type and MNX strains demonstrated significantly increased body fat percentage in mice possessing C57mtDNA regardless of nDNA background. High-fat diet in mice possessing C57mtDNA was associated with differential abundance of phosphatidylcholines, lysophosphatidylcholines, phosphatidylethanolamines, and glucose. Conversely, high-fat diet in mice possessing C3HmtDNA was associated with differential abundance of phosphatidylcholines, cardiolipins, and alanine. Glycerophospholipid metabolism and beta-alanine signaling pathways were enriched in skeletal muscle and plasma, indicating mtDNA-directed priming of mitochondria towards oxidative stress and increased fatty acid oxidation in C57nDNA:C57mtDNA wild-type and C3HnDNA:C57mtDNA MNX mice, relative to their nDNA-matched counterparts. In mtDNA-matched mice, C57mtDNA was associated with metabolite co-expression related to the pentose phosphate pathway and sugar-related metabolism; C3HmtDNA was associated with branched chain amino acid metabolite co-expression.

CONCLUSIONS

These results reveal novel nDNA-mtDNA interactions that drive significant changes in metabolite levels. Alterations to key metabolites involved in mitochondrial bioenergetic dysfunction and electron transport chain activity are implicated in elevated beta-oxidation during high-fat diet feeding; abnormally elevated rates of beta-oxidation may be a key driver of insulin resistance. The results reported here support the hypothesis that mtDNA influences cardiometabolic disease-susceptibility by modulating mitochondrial function and metabolic pathways.

Wearable multiple sensing platform for enhanced biomolecules monitoring in food

Monitoring of biomolecules in food plays a crucial role in safeguarding human health. Prevalent biomolecule monitoring systems are constructed predominantly from rigid materials and have inherent limitations in detection capabilities. Wearable sensors have increasingly captured attention, significantly propelling the evolution of biomolecular detection process. However, most studies concentrate on the single sensing core that catalyze individual biomolecule, primarily for healthcare applications. This study introduces multiple biomolecules sensing platform based on a single-sensor core of hollow Prussian blue (h-PB), enabling efficient food detection. By utilizing varied potentials and leveraging excellent conductivity of MXene, this platform selectively and effectively tracks biomolecules including hydrogen peroxide, ascorbic acid, and glucose. Notably, the origin of electrochemical activity in this sensing system is demonstrated. This research provides a novel pathway for multi-sensing platforms design, leveraging a single catalytic core as active layer, thereby offering a promising trajectory for wearable electronics endowed with enhanced sensing capabilities.

Effect of long-term Mediterranean versus low-fat diet on neutrophil count, and type 2 diabetes mellitus remission in patients with coronary heart disease: results from the CORDIOPREV study

BACKGROUND

Recent evidence links diet and physical activity with type 2 diabetes mellitus (T2DM) remission, but emerging findings suggest that immune system dysregulation may play a crucial role. This study aimed to investigate the associations between neutrophils and T2DM remission.

METHODS

We conducted a comprehensive analysis of newly-diagnosed T2DM patients (N = 183) from the CORDIOPREV study, without glucose-lowering treatment, and were randomized to follow either a Mediterranean or low-fat diet. Patients were classified into two groups: Responders, who achieved T2DM remission (n = 73), and Non-Responders, who did not achieve remission during the 5-year dietary intervention (n = 110). Neutrophil count and their related-ratio (NER, NBR, NLR and NHR, normalized with erythrocytes, basophils, lymphocytes, and HDL respectively) were measured at the baseline and 5 years of follow-up.

RESULTS

The lowest baseline tertile of neutrophil count was associated with an increased likelihood of T2DM remission among patients following a Mediterranean diet (but not for low-fat diet) when compared with the highest tertile [adjusted HR of 4.23 (95% CI: 1.53-11.69)], in which similar results were observed for NER and NHR. When considering clinical and neutrophil variables, the predictive capacity of this model yielded an AUC of 0.783 (95% CI: 0.680-0.822). Furthermore, after 5-years, Responders exhibited lower neutrophil count compared to Non-responders (p = 0.006) and a significant decrease in neutrophil count (p = 0.001) compared to baseline. This decrease in neutrophil count in Responders who consumed a Mediterranean diet exhibited a significant increase in Insulin Sensitivity and Disposition Index (p = 0.011 and p = 0.018) after the follow-up period.

CONCLUSION

These findings suggest that neutrophil count can help in identifying patients that are more likely to achieve T2DM remission following a Mediterranean diet, suggesting a role on insulin sensitivity and β-cell function. Further research holds promise for providing valuable insights into the pathophysiology of T2DM.

CLINICAL TRIAL REGISTRATION

ID: NCT00924937; URL Clinical trial: https://clinicaltrials.gov/study/NCT00924937?cond=NCT00924937&rank=1 .

Loneliness and social isolation as risk factors for type 2 diabetes onset: A systematic review and meta-analysis

AIMS

This study sought to analyze the association of social isolation and loneliness with the risk of type 2 diabetes onset.

METHODS

Two authors systematically searched PubMed, EMBASE, and Web of Science databases for studies published until February 2025, assessing the risk of incidence of type 2 diabetes in individuals who are socially isolated or lonely. To quantify the risk of incident diabetes, hazard ratios (HR) for loneliness and social isolation were pooled using a random-effects inverse-variance model with empirical Bayes estimation.

RESULTS

Nine prospective cohort studies were included, comprising 1,112,887 individuals (60.5 % female, mean age = 57.1 years), with 50,961 new cases of type 2 diabetes over a mean follow-up of 10.7 years. Loneliness was associated with a 32% increased risk of type 2 diabetes (HR = 1.32 [95 % confidence interval [CI]:1.11-1.57]). Social isolation was linked to a 20% higher risk (HR = 1.20 [95 %CI:1.01-1.43]). The included studies showed fair-to-good methodological quality (mean score: 10.11/14) based on the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.

CONCLUSIONS

Social isolation and loneliness are significant risk factors for type 2 diabetes. Addressing social connectedness could be a valuable strategy for diabetes prevention, emphasizing the need to incorporate psychosocial factors into public health initiatives.

Design, synthesis, and investigation of novel 5-arylpyrazole-glucose hybrids as α-glucosidase inhibitors

Considering the global incidence of diabetes, developing new compounds to lower blood sugar levels has become increasingly crucial. As a result, there has been a growing focus on the synthesis of α-glucosidase inhibitors in recent years. This study investigated design, synthesis, and effects of novel 5-aryl pyrazole-glucose hybrids as α-glucosidase inhibitors. Thirteen derivatives from this class of compounds were synthesized, demonstrating superior in vitro inhibitory effects (IC50 values ranging from 0.5 to 438.6 µM, compared to acarbose at 750.0 µM). Among them, compound 8g (IC50 = 0.5 µM) was selected for further investigations and the kinetic studies revealed that it is a competitive inhibitor (Ki = 0.46 µM). Fluorescence assays indicated changes in the fluorescence intensity, while thermodynamic analyses suggested that compound 8g promoted a transition of the enzyme into an unfolded state. Furthermore, in vivo studies demonstrated that 8g effectively reduced blood sugar levels in rats at doses comparable to acarbose. Molecular docking studies revealed that this compound interacted with the enzyme's active site, and molecular dynamics simulations showed that pharmacophores engaged in various interactions with the enzyme.

Exploring patterns of multimorbidity in South Korea using exploratory factor analysis and non negative matrix factorization

The increasing prevalence of multimorbidity and the co-occurrence of multiple chronic diseases presents a measurable challenge to public health, impacting healthcare strategies and planning. This study aimed to explore disease patterns and temporal clustering using data from South Korea's National Health Insurance Service, spanning 2002-2019. The dataset included approximately 1 million individuals, focusing on those with at least two chronic diseases while excluding individuals who died within five years of follow-up. We analyzed 126 non-communicable diseases, considering only those with a prevalence above 1%, and applied a wash-out period to determine incidence. Exploratory factor analysis (EFA) and non-negative matrix factorization (NMF) were used to identify disease clustering over time. Participants were divided into four groups: men and women in their 50 s and 60 s. EFA identified five patterns in men in their 50 s and seven in their 60 s, while four patterns emerged in women in their 50 s and five in their 60 s. NMF identified 10 clusters for men in their 50 s, 15 in their 60 s, and 16 clusters for women in both age groups. Our study confirms established comorbidity patterns and reveals previously unrecognized clusters, providing data-driven insights into multimorbidity mechanisms and supporting evidence-based healthcare strategies.

User-Centered Prototype Design of a Health Care Robot for Treating Type 2 Diabetes in the Community Pharmacy: Development and Usability Study

Background

Technology can be an effective tool for providing health services and disease self-management, especially in diabetes care. Technology tools for disease self-management include health-related applications for computers and smartphones as well as the use of robots. To provide a more effective continuity of care and to better understand and facilitate disease management in middle-aged and older adult patients with diabetes, robots can be used to improve the quality of care and supplement community health resources, such as community pharmacies.

Objective

The aim of this study was to develop a health care robot prototype that can be integrated into current community pharmacies.

Methods

Three user-centered approaches were used: (1) review of the literature on technology use among older adults, 2) reference to the seven key diabetes self-care behaviors by the American Association of Diabetes Educators (AADE), and (3) meeting with health care providers in the community. Field investigations and interviews were conducted at community pharmacies and diabetes health education centers to determine the appearance, interface, content, and function of the robot.

Results

The results show that diabetes health care prototype robots can be established through user-centered design. The following important features were revealed: (1) perceived ease of use is considered a friendly operating interface; therefore, we used less than 3 buttons in an interface; (2) minimization of the interface between blue and yellow, which is unfriendly to older adults; (3) the health education mode was the most preferred mode with sound, image, and video presentation; (4) the most predilected functions are health education resources and health records, and that patient data can be easily collected through health education games and dialogue with robots; and (5) touching the screen is the most preferred operation mode.

Conclusions

An evidence-based health care robot can be developed through user-centered design, an approach in which a model that connects medical needs to people with health conditions can be built, thereby facilitating the sustainable development of technology in the diabetes care field.

Pragmatic, multicentre, randomised controlled trial of a Hospital-Community-Home Tiered Transitional Care (HCH-TTC) programme for individuals with type 2 diabetes: a study protocol

INTRODUCTION

Type 2 Diabetes Mellitus (T2DM) and its complications significantly increase the risk of premature mortality and disability among patients, placing a considerable burden on socioeconomic development. Evidence has shows that effective transitional care can improve health outcomes for patients with T2DM. However, T2DM transitional care faces challenges including service discontinuity, communication breakdowns and a lack of personalised design, leading to potential issues of undertreatment and overtreatment, increasing the risk of improper blood sugar management. To address these challenges, our research team developed the Hospital-Community-Home Tiered Transitional Care (HCH-TTC) programme for patients with T2DM, aiming to evaluate its effectiveness and feasibility through a randomised controlled trial (RCT).

METHOD AND ANALYSIS

The multicentre, pragmatic, double-blind RCT will enrol 180 patients with T2DM from the Jinqiao Medical Union in Pudong New Area, Shanghai, China. Participants will be randomly assigned to either the experimental group or the control group. The experimental group will participate in a 6-month HCH-TTC programme, which provides personalised transitional care strategies tailored to patients' evolving health conditions and nursing needs. This tiered management approach includes follow-up, health education, personalised guidance and health monitoring, with variations in intensity, frequency and type based on individual requirements. The control group will receive Hospital-Community-Home Routine Transitional Care programme, consisting of routine follow-up, health education and health monitoring during the same period. Data collection will be conducted at baseline, 1 month postintervention, 3 months and 6 months. The primary outcomes are glycated haemoglobin (HbA1c). Secondary outcomes include fasting plasma glucose (FPG), 2-hour postprandial blood glucose (2hPPG), diabetes knowledge level, diabetes self-management ability, diabetes treatment adherence, nursing service satisfaction, diabetes complications rate and unplanned readmission rate. Statistical analysis will employ independent sample t-tests and repeated measures analysis of variance.

ETHICS AND DISSEMINATION

The Gongli Hospital Ethics Committee (GLYY1s2021-010) approved the study. Results will be disseminated through publication in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

Chinese Clinical Trial Registry ChiCTR2200063322.

Distinct Roles of Common Genetic Variants and Their Contributions to Diabetes: MODY and Uncontrolled T2DM

Type 2 diabetes mellitus (T2DM) encompasses a range of clinical manifestations, with uncontrolled diabetes leading to progressive or irreversible damage to various organs. Numerous genes associated with monogenic diabetes, exhibiting classical patterns of inheritance (autosomal dominant or recessive), have been identified. Additionally, genes involved in complex diabetes, which interact with environmental factors to trigger the disease, have also been discovered. These genetic findings have raised hopes that genetic testing could enhance diagnostics, disease surveillance, treatment selection, and family counseling. However, the accurate interpretation of genetic data remains a significant challenge, as variants may not always be definitively classified as either benign or pathogenic. Research to date, however, indicates that periodic reevaluation of genetic variants in diabetes has led to more consistent findings, with biases being steadily eliminated. This has improved the interpretation of variants across diverse ethnicities. Clinical studies suggest that genetic risk information may motivate patients to adopt behaviors that promote the prevention or management of T2DM. Given that the clinical features of certain monogenic diabetes types overlap with T2DM, and considering the significant role of genetic variants in diabetes, healthcare providers caring for prediabetic patients should consider genetic testing as part of the diagnostic process. This review summarizes current knowledge of the most common genetic variants associated with T2DM, explores novel therapeutic targets, and discusses recent advancements in the pharmaceutical management of uncontrolled T2DM.

Astragalus Polysaccharides Ameliorate Diabetic Bladder Dysfunction via Normalization of Neuromuscular Conduction

Neuromuscular conduction dysfunction-induced underactive bladder (UAB) is a major urological complication associated with diabetes mellitus (DM), and there remain deficiencies in reliable pharmacological treatment options. Astragalus polysaccharides (APS), as an edible active substance in Astragalus membranaceus, have a therapeutic effect on diabetes and its complications. We investigated the effects and mechanism of APS in high-fat-diet-induced (HFD) diabetic UAB mice. APS significantly reduced fasting plasma glucose, insulin, and HOMA-IR index. Furthermore, APS treatment significantly decreased maximum bladder capacity, residual volume, bladder compliance, contraction intervals, empty and full resting pressure, and increased voiding volume and voided efficiency. In addition, APS ameliorated the hyporesponsiveness of purinergic and cholinergic-mediated neuromuscular contraction of the detrusor and improved the dysregulation of inhibitory and excitatory neurotransmission by downregulating the levels of nNOS and VIP, and upregulating ChAT and SP in HFD mice. This study revealed that APS ameliorates diabetic UAB via the normalization of neuromuscular conduction.

Cross-Linking-Enabled Core-shell Nanostructure Based on Conductive Polymer Hydrogels/Carbon Nanotubes for Salivary Glucose Biosensor

Due to the 3-fold increase in the number of people with diabetes, there is an urgent need for noninvasive, user-friendly glucose monitoring technologies. However, current noninvasive methods are limited by low accuracy and susceptibility to interference. In this work, we develop a noninvasive salivary glucose biosensor using a core-shell nanostructure of conductive polymer hydrogels/carbon nanotubes (CNTs) on carbon paper. With the electrostatic interaction between the functional groups on CNTs and pyrrole monomer, the cross-linked polypyrrole (PPy) hydrogel can form in situ on the CNTs surface. The 3D interconnected networks of core-shell PPy/CNTs feature high surface area, porosity, and flexibility, facilitating efficient electron and ion transport, thereby leading to a superior glucose sensing sensitivity of 119.74 μA mM-1 cm-2 in the region of 50-700 μM. Additionally, this biosensor exhibited an ultralow Michaelis-Menten constant of 0.33 mM and high specificity toward glucose, even in the presence of various interferences, demonstrating a high affinity for the enzyme toward PPy/CNTs. This facile, controlled synthesis of core-shell PPy/CNTs offers a promising avenue for constructing enzymatic biosensors for accurate and regular monitoring of blood glucose via saliva tests.

Puerarin Targets HIF-1α to Modulate Hypoxia-Related Sphingolipid Metabolism in Diabetic Hepatopathy via the SPTLC2/Ceramide Pathway

Background and Objectives: Diabetic hepatopathy, characterized by hepatic hypoxia and metabolic dysregulation, has a rising global incidence and prevalence, with limited effective treatments. Hepatic hypoxia activates hypoxia-inducible factor-1 alpha (HIF-1α), regulating sphingolipid metabolism and elevating ceramide, a key factor in insulin resistance. Puerarin (Pue), a flavonoid derived from Pueraria lobata, exhibits therapeutic effects in diabetes, but its effects on hypoxia-related hepatic metabolism are unclear. This study investigates Pue's mechanisms in modulating hepatic metabolism, focusing on HIF-1α and sphingolipid metabolism. Methods: Using bioinformatics and molecular docking, HIF-1α was identified as a key target in diabetic liver disease, confirmed via drug affinity responsive target stability. In vitro experiments utilized insulin-resistant HepG2 cells to assess glucose intake and HIF-1α expression. In vivo, type 2 diabetes mellitus (T2DM) was induced in mice using a high-fat diet and streptozotocin injections. Pue administration was evaluated for its effects on fasting blood glucose, oral glucose tolerance, and hepatoprotective effects. Liver metabolomics and qPCR/Western blot analyses were conducted to assess metabolic pathways. Results: Pue increased glucose uptake in HepG2 cells and bound HIF-1α. Pue reduced HIF-1α expression in HepG2 cells, an effect attenuated by the HIF-1α stabilizer DMOG. Pue improved fasting blood glucose, oral glucose tolerance, and hepatoprotective effects in T2DM mice, which DMOG reversed. Metabolomics revealed that Pue modulates sphingolipid metabolism, decreasing ceramide content. qPCR and Western blot results confirmed that Pue dramatically decreases HIF-1α and SPTLC2 expression. Conclusions: Pue improves diabetic hepatopathy by reducing ceramide expression through the HIF-1α/SPTLC2 pathway, offering a novel therapeutic strategy for diabetes management.

MUTATE: a human genetic atlas of multiorgan artificial intelligence endophenotypes using genome-wide association summary statistics

Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide intermediate phenotypes (i.e. endophenotypes) that bridge the genetics and clinical manifestations of human disease. However, the genetic architecture of these AI endophenotypes remains largely unexplored in the context of human multiorgan system diseases. Using publicly available genome-wide association study summary statistics from the UK Biobank (UKBB), FinnGen, and the Psychiatric Genomics Consortium, we comprehensively depicted the genetic architecture of 2024 multiorgan AI endophenotypes (MAEs). We comparatively assessed the single-nucleotide polymorphism-based heritability, polygenicity, and natural selection signatures of 2024 MAEs using methods commonly used in the field. Genetic correlation and Mendelian randomization analyses reveal both within-organ relationships and cross-organ interconnections. Bi-directional causal relationships were established between chronic human diseases and MAEs across multiple organ systems, including Alzheimer's disease for the brain, diabetes for the metabolic system, asthma for the pulmonary system, and hypertension for the cardiovascular system. Finally, we derived polygenic risk scores for the 2024 MAEs for individuals not used to calculate MAEs and returned these to the UKBB. Our findings underscore the promise of the MAEs as new instruments to ameliorate overall human health. All results are encapsulated into the MUlTiorgan AI endophenoTypE genetic atlas and are publicly available at https://labs-laboratory.com/mutate.

Expression of MMP-14 and CD147 in Gingival Tissue of Patients With and Without Diabetes Mellitus Type II

Background: Diabetes mellitus (DM) is a major risk factor for the development of periodontal disease and aggravates the severity of periodontal conditions. Matrix metalloproteinases (MMPs) are known to degrade periodontal ligament attachment and bone matrix proteins. Increased expression of CD147 is associated with increased synthesis of several MMPs, being a modulator of MMP expression, including that of MMP-14. The purpose of this study was to quantify and compare the expressions of MMP-14 and CD147 in gingival tissues of patients with and without type 2 diabetes mellitus. Material and Methods: In this histological study, we included 33 subjects with periodontal disease: 16 patients with type 2 DM (test group) and 17 systemically healthy patients (control group). Tissue fragments were processed using an immunohistochemistry technique to determine immunoreactivity (IR) intensity of MMP-14 and CD147. Results: In the group of diabetes patients with periodontitis, 56.2% showed weak positive expressions (+), while 43.8% had intensely positive expressions (+++) of MMP-14. Statistically significant differences between test and control groups (p = 0.004, p = 0.883, and p = 0.002) were found for the membranous IR intensity of MMP-14. In the group of diabetes patients with periodontitis, 56.2% had moderate positive expressions (++) of CD 147, while 43.8% showed intensely positive expressions (+++). Statistically significant differences between the test and control groups were found (p = 0.001, p = 0.002, and p = 0.003) for the membranous IR intensity of CD147. Conclusions: The significantly higher membranous IR intensity for MMP-14 and CD 147 demonstrates the role of these biomarkers in the development of periodontal pathology in diabetes patients. It can be assumed that MMP-14 and CD147 could be further investigated as potential predictive biomarkers.

Alleviation of hyperglycaemia and oxidative stress by fruit extracts of different cultivars of the cornelian cherry (Cornus mas L. and Cornus mas × Cornus officinalis) in rats with diabetes mellitus

The development of new cornelian cherry cultivars with stronger antidiabetic properties than those of previously studied Cornus mas L. extracts is essential. Accordingly, the aim of the present study was to assess the biological effects of fruit extracts derived from the 'Uholok' and 'Koralovyi' cultivars of C. mas and mix of two hybrids of C. mas × C. officinalis ('Jerzy' and 'Tomasz' cultivars) in rats with streptozotocin-induced diabetes mellitus. The quantitative and qualitative identification of bioactive substances in cornelian cherry fruits was conducted using HPLC-PDA. Fruit extracts from different cultivars were administered orally to rats with diabetes for 14 days at a dose of 20 mg per kg b.w. This resulted in a notable decrease in glucose-related parameters in the blood, proving the extracts' effectiveness as inhibitors of α-glucosidase activity. The fruit extract from the hybrids showed the most pronounced effect among the studied extracts with regard to these indicators. In addition, the fruit extracts demonstrated a positive corrective impact on the metabolites of glycolysis (pyruvate and L-lactate) and lactate dehydrogenase activity. The extracts produced antioxidant effect in diabetic rats by reducing oxidative stress biomarkers in plasma. Extracts from fruits of the 'Uholok' and 'Koralovyi' cultivars exhibited a higher efficiency than the extracts from C. mas 'Yantarnyi' and 'Flava' cultivars. The biological effects of the fruit extract from the 'Uholok' cultivar are comparable to those of the 'Podolski' cultivar. These findings contribute to the understanding of the antidiabetic effect of the studied extracts and indicate their potential application as promising drugs.

Diabetes mellitus, vaginal microbiome and sexual function: Outcomes in postmenopausal women

Diabetes mellitus is a chronic disease and a public health challenge worldwide, associated with numerous complications, including genitourinary infections and sexual dysfunction in women, particularly in menopause. The vaginal microbiome, which comprises beneficial and pathogenic bacteria, their genomes, and the surrounding environment, plays a crucial role in maintaining genitourinary health. Chronic hyperglycemia disrupts immune functions, exacerbates oxidative stress, and alters the vaginal microbiome, increasing the risk of genitourinary infections. Recent advances in microbial analysis, including 16S rRNA sequencing, have provided insights into the complex composition of the vaginal microbiome and its dysbiosis in diabetes mellitus. Some glucose-lowering drugs, such as sodium-glucose cotransporter 2 inhibitors, may increase the risk of genitourinary infections. Additionally, psychological distress, hormonal imbalances, and diabetes-related genitourinary symptoms contribute to sexual dysfunction in diabetic women. Healthcare for diabetic women requires a multidisciplinary approach, including not only glycemic control but also vaginal and sexual health assessment. A holistic approach is essential to advance personalized strategies, including medications and psychological support.

Design and synthesis of N-(3-cyanothiophen-2-yl)-2-phenoxyacetamide-based α-glucosidase inhibitors

This study investigates the design and synthesis of a series of novel selective α-glucosidase inhibitors based on N-(3-cyanothiophen-2-yl)-2-phenoxyacetamide framework, employing a bioisosterism strategy. Among the nineteen newly synthesized analogs, compound 4d9 demonstrated the highest α-glucosidase inhibitory potency (IC50 = 2.11 μM) when compared to the established inhibitors Acarbose (IC50 = 327.0 μM) and HXH8r (IC50 = 15.32 μM), while exhibiting a remarkable 17.48-fold selectivity for α-glucosidase over α-amylase. Kinetic studies revealed that compound 4d9 acts as a non-competitive inhibitor, and its binding interactions were further investigated using molecular docking analysis. Additionally, compound 4d9 showed noncytotoxic effects on human normal hepatocyte (LO2) cells and demonstrated improved metabolic stability in rat plasma. These findings position compound 4d9 as a promising candidate for the development of therapeutics targeting type 2 diabetes.

Educational Needs and Priorities of People with Diabetes and Healthcare Providers in South Korea: A Mixed-Methods Study

Introduction: Effective self-care for managing diabetes requires culturally sensitive and patient-centered education. This study explored the educational needs and priorities of people with diabetes (PWD) and healthcare providers (HCPs). Method: A mixed-methods approach was employed with participants from a university-affiliated hospital in South Korea. Descriptive and content analyses were used for the questionnaire and interview data. Results: Both PWD (n=33) and HCPs (n=42) ranked diabetes-related side-effect management and medication purpose as the most important aspects of diabetes education. PWD had higher educational needs regarding diagnosed diseases and lifestyle modifications than HCPs. Three themes were revealed: incorporating lifestyle changes and medication taking, collaborating with HCPs and caregivers and providing care to meet person-centered mental health needs, and enhancing education on disease and complications. Discussion: Culturally sensitive and patient-centered education programs that recognize communal values, reflect individual preferences and needs, and promote lifestyle changes by leveraging technologies for Korean PWD are crucial.

Prediabetes and sleep patterns: Linking poor sleep to adverse outcomes through metabolic syndrome

AIMS

Evaluate how sleep patterns are associated with the risk of adverse health outcomes in individuals with prediabetes, and explore the potential mediating role of metabolic syndrome in these associations.

METHODS

We assessed 44,938 adults with prediabetes from the UK Biobank. Sleep health was evaluated using sleep pattern, comprised of five sleep factors. Mediation analysis was performed to explore the potential mediating role of metabolic syndrome.

RESULTS

Unhealthy sleep patterns were linked to a higher risk of adverse outcomes. Compared to those with a healthy sleep pattern, individuals with an intermediate sleep pattern had a higher propensity to develop adverse outcomes (HRs ranging from 1.07 to 1.31). Respectively, those with a poor sleep pattern also had an increased risk for these outcomes (HRs ranging from 1.21 to 1.92). For each poor sleep factor increase, the risk of these adverse outcomes increased by 4% to 23%. Metabolic syndrome may partially mediate, with mediation proportions ranging from 0.94% to 9.61%.

CONCLUSIONS

In adults with prediabetes, both poor and intermediate sleep patterns are associated with an increased risk of adverse outcomes. Metabolic syndrome partially mediates the relationship between sleep patterns and adverse outcomes.

On-demand release of insulin using glucose-responsive chitosan-based three-compartment microspheres

Various injectable glucose-responsive insulin release systems, including microspheres, have been developed to achieve insulin release for over a day. However, a major challenge is on-demand release insulin, which is closely related to the degradation rate of the delivery vehicle. Herein, chitosan-based three-compartment microspheres (TCMs) were fabricated using gas-shearing microfluidics. Glucose reacts with glucose oxidase (GOD) to generate gluconic acid, and chitosan degrades under acidic conditions to release insulin. The chitosan concentration in each compartment is adjusted to have gradient pH response ranges. Low, medium and high concentrations of insulin are encapsulated in low, medium and high concentration chitosan compartments respectively. The number of compartments involved in insulin release increases from one to three as blood glucose rises. Compared with single one-compartment microspheres (OCMs), TCMs maintain structural integrity and drug action for a longer duration. In vitro experiments have proven the on-demand release of insulin and excellent biocompatibility of TCMs. In chemically induced type 2 diabetes cell models, TCMs demonstrated long-term regulation of blood glucose levels for 20 to 35 h. This work presents a novel concept of constructing three compartments in microspheres to release insulin on-demand, and is highly attractive for research on insulin analogs and other related application.

Prevalence of Diagnosed Diabetes Among U.S. Adults Aged ≥18 Years With Disabilities, 2021-2022

OBJECTIVE

To compare the prevalence of diagnosed diabetes among U.S. adults with and without disabilities, overall and by subgroups.

RESEARCH DESIGN AND METHODS

We used data on adults aged ≥18 years from the cross-sectional 2021-2022 National Health Interview Survey to report the prevalence of diagnosed diabetes by functional disability status and for each disability type (hearing, seeing, mobility, cognition, self-care, and communication) separately. With use of the Washington Group Short Set on Functioning indicator, disability was defined according to the categories of milder (reporting some difficulty), moderate (reporting a lot of difficulty), and severe (cannot do at all) by disability type. Crude prevalence and age-standardized prevalence of diabetes were also calculated for adults with any difficulty with any disability by age, sex, race/ethnicity, education, insurance, and poverty-to-income ratio.

RESULTS

Diabetes prevalence increased with number of disability types, was lower among adults with no disability (5.8%) than among those with milder (9.5%) or moderate to more severe (18.3%) disability, and was 4.0-10.3 percentage points higher among those with moderate to more severe disability than among those with milder disability for vision, hearing, mobility, and cognitive disabilities. Diabetes prevalence was similar for adults with milder and moderate to more severe self-care and communication disabilities.

CONCLUSIONS

Prevalence of diabetes was higher among adults with any functional disability than without and increased with increasing number of disability types. Adults with multiple disability types, or those who have difficulty with self-care or communication or other moderate to more severe disabilities, may benefit from diabetes prevention programs.

Structural alteration of hippocampal subfields in type 2 diabetes mellitus patients with dyslipidemia

OBJECTIVE

To explore alterations in hippocampal subfield volumes in type 2 diabetes mellitus (T2DM) patients with dyslipidemia using hippocampal subfield segmentation.

METHODS

A total of 99 T2DM patients were prospectively recruited and divided into two groups based on the presence or absence of dyslipidemia: the T2DM dyslipidemia group and the T2DM normal lipidemia group. Additionally, 57 healthy volunteers were recruited as the healthy control (HC) group. General clinical data and cognitive psychological scale scores were collected. Subgroup analyses of T2DM patients were conducted based on the presence or absence of mild cognitive impairment (MCI). Hippocampal subfield volumes were analyzed using a general linear model with post-hoc Bonferroni correction. Significant differential hippocampal subfields were further analyzed in subgroups using the general linear model with post-hoc Bonferroni tests. Partial correlation analyses were performed to assess correlations between subfield-specific volumes and lipid and glucose metabolism indicators, as well as cognitive psychological scale scores. P-values from partial correlation analyses were corrected using the false discovery rate (FDR).

RESULTS

Volumes of the bilateral hippocampal tail, left presubiculum_body, and right subiculum_body were significantly reduced in the T2DM dyslipidemia group compared to both the HC group and the T2DM normal lipidemia group. Post-hoc analyses revealed that the T2DM dyslipidemia group had the smallest hippocampal subfield volumes. Further subgroup analysis showed that T2DM dyslipidemia patients with MCI exhibited the most pronounced volume reductions in the bilateral hippocampal tail and right subiculum_body. After FDR correction, partial correlation analysis indicated that, in the T2DM dyslipidemia group, the left hippocampal tail volume was positively correlated with the Montreal Cognitive Assessment score. In the T2DM dyslipidemia without MCI group, the volume of the right subiculum_body was negatively correlated with fasting insulin levels and the insulin resistance index, but positively correlated with total cholesterol and low-density lipoprotein cholesterol levels. In T2DM patients with normal lipidemia without MCI, the volume of the right subiculum_body was positively correlated with TC levels.

CONCLUSION

T2DM patients with dyslipidemia, especially those with MCI, exhibit significant atrophy in hippocampal subfield volumes, with correlations observed between lipid levels and hippocampal subfield volume changes. These findings suggest that lipid alterations may play an essential role in hippocampal structural abnormalities and cognitive impairment in T2DM patients. This study provides new insights into the neuropathophysiological mechanisms underlying brain alterations and cognitive decline in T2DM.

Lactobacillus casei Zhang prevents hippocampal atrophy and cognitive impairment in rats with type 2 diabetes by regulating blood glucose levels

PURPOSE

Lactobacillus casei Zhang (LCZ) has health benefits, such as the ability to improve blood glucose levels in individuals with type 2 diabetes mellitus (T2DM). However, little is known about the effects of LCZ on brain structural plasticity and cognitive function in T2DM. The aims of this study were to determine whether LCZ can prevent and alleviate brain damage and memory impairment in T2DM, and to understand the mechanisms underlying the effects of LCZ in T2DM.

METHODS

Forty-one male Sprague-Dawley rats were divided into the saline control (CON, n = 14), T2DM (n = 14) and T2DM + LCZ (n = 13) groups. Magnetic resonance imaging (MRI) was used to evaluate alterations in brain structure among these three groups. The novel object recognition and Y-maze tests were conductedto assess cognitive function. Histological and immunohistochemical analysis, including Nissl staining, Golgi-Cox staining and glial fibrillary acidic protein immunostaining, were performed to explore the pathophysiological mechanisms underlying brain structural changes.

RESULTS

T2DM rats presented hyperglycemia, cognitive decline, hippocampal atrophy, and damage to hippocampal neurons and astrocytes. Compared with those in the T2DM groups, rats in the T2DM + LCZ group presented lower blood glucose levels, better cognitive function, a larger hippocampal volume, and more normal hippocampal neurons and astrocytes. There was no significant difference in these metrics between rats in the T2DM + LCZ and CON groups.

CONCLUSION

Hyperglycemia-induced damage to hippocampal neurons and astrocytes may lead to hippocampal atrophy and cognitive dysfunction in T2DM. LCZ can effectively prevent this damage by regulating blood glucose levels, preventing brain atrophy and cognitive impairment in T2DM rats. These findings provide a scientific basis for the clinical application of LCZ.

Elevated risk of infection in individuals with hyperinsulinaemic type 2 diabetes: a Danish 12 year cohort study

AIMS/HYPOTHESIS

A better understanding of the mechanisms underlying an elevated infection risk in individuals with type 2 diabetes is needed to guide risk stratification and prevention. We investigated the risk of infection in subgroups of individuals with type 2 diabetes according to indices of insulin sensitivity and beta cell function.

METHODS

We classified 7265 individuals with recently diagnosed type 2 diabetes (median duration 1.4 years, IQR 0.5-2.9 years) into hyperinsulinaemic (high beta cell function [HOMA 2-beta-cell function, HOMA2-B], low insulin sensitivity [HOMA 2-insulin sensitivity, HOMA2-S]), classical (low HOMA2-B, low HOMA2-S) and insulinopenic (low HOMA2-B, high HOMA2-S) type 2 diabetes. Individuals were followed until first hospital-treated infection or first prescription for an anti-infective agent (community-treated infection). We used Cox regression analysis to estimate HRs adjusted for age, sex, index year, diabetes duration and treatment, lifestyle behaviours and comorbidities.

RESULTS

Among study participants, 28% had hyperinsulinaemic, 63% had classical and 9% had insulinopenic type 2 diabetes. The 10 year risks of hospital-treated infections were 42.3%, 36.8% and 31.0% in the three subgroups, respectively. Compared with the insulinopenic subgroup, adjusted HRs for hospital-treated infections were elevated for hyperinsulinaemic (1.38 [95% CI 1.16, 1.65]) and classical type 2 diabetes (1.20 [95% CI 1.02, 1.42]). The 10 year risks of community-treated infections were high in all three subgroups at 91.6%, 90.1% and 88.3%, respectively, corresponding to adjusted HRs of 1.20 (95% CI 1.08, 1.33) for the hyperinsulinaemic and 1.10 (95% CI 1.00, 1.21) for the classical subgroup. Infection risk in the hyperinsulinaemic subgroup decreased substantially when further adjusted for abdominal obesity, metabolic derangements and low-grade inflammation.

CONCLUSIONS/INTERPRETATION

The risk of severe infections is clearly elevated in individuals with type 2 diabetes characterised by a higher degree of insulin resistance/hyperinsulinaemia.

Comparative effectiveness of SGLT2 inhibitors and GLP-1 receptor agonists in preventing Alzheimer's disease, vascular dementia, and other dementia types among patients with type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus (T2DM) is associated with an elevated risk of dementia, including Alzheimer's disease (AD) and vascular dementia (VaD). While sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists have shown neuroprotective potential, comparative data on their efficacy in dementia prevention remain scarce.

METHODS

- We conducted a retrospective cohort study using the TriNetX database, including 307,103 SGLT2 inhibitor users and 348,686 GLP-1 receptor agonist users with T2DM. Propensity score matching yielded 221,883 pairs with balanced baseline characteristics. The primary outcome was overall dementia incidence, with secondary outcomes including AD, VaD, and all-cause mortality. Hazard ratios (HRs) were calculated using Cox proportional hazards models.

RESULTS

SGLT2 inhibitors were associated with a significantly lower incidence of overall dementia compared to GLP-1 receptor agonists (2.7 % vs. 3.6 %; HR, 0.92; 95 % CI, 0.89-0.95). The risk of VaD (HR, 0.89; 95 % CI, 0.84-0.95) and AD (HR, 0.90; 95 % CI, 0.86-0.94) was also reduced with SGLT2 inhibitors. All-cause mortality was lower in the SGLT2 group (3.6 % vs. 4.6 %; HR, 0.95; 95 % CI, 0.92-0.98). No significant difference was observed in other dementia subtypes (HR, 0.96; 95 % CI, 0.91-1.01).

CONCLUSIONS

In this large, real-world cohort, SGLT2 inhibitors demonstrated superior efficacy over GLP-1 receptor agonists in reducing the risks of overall dementia, VaD, and AD among patients with T2DM. These findings support the preferential use of SGLT2 inhibitors in mitigating dementia risk in this population, though randomized controlled trials are warranted for confirmation.

Facilitation of diabetic wound healing by far upstream element binding protein 1 through augmentation of dermal fibroblast activity

AIMS

Diabetes mellitus (DM) often leads to wound healing complications, partly attributed to the accumulation of advanced glycosylation end products (AGEs) that impair fibroblast function. Far Upstream Element Binding Protein 1 (FUBP1) regulates cell proliferation, migration, and collagen synthesis. However, the impact of FUBP1 on diabetic wound healing remains unknown. This study is designed to explore the function and mechanisms of FUBP1 in diabetic wound healing.

METHODS

Eighteen Sprague-Dawley rats (weighing 220-240 g) were randomly assigned to three groups (n = 6): a control group (NC) of healthy rats, a model group (DM) of untreated diabetic rats, and a treatment group (DM + FUBP1) of diabetic rats accepting FUBP1 treatment. A 10 mm diameter circular full-thickness skin defect was created on the back of each rat. On days 1 and 7, rats in the treatment group received local injections of 5 µg FUBP1 protein at the wound site, whereas the control group and model group were administered saline. Wound healing was documented on days 0, 3, 7, 10, and 14, with tissue samples from the wound areas collected on day 14 for histological analysis, including H&E staining, Masson's trichrome staining, and immunohistochemistry. Western blot analysis was utilized to assess the expression of GSK-3β, Wnt3a, and β-catenin. In vitro, the effects of various concentrations of AGEs on cell viability and FUBP1 expression were examined in human dermal fibroblasts (HDF). Cells were genetically modified to overexpress FUBP1 using lentiviral vectors and were cultured for 48 h in media with or without AGEs. The impacts on fibroblast proliferation, migration, and Wnt/β-catenin signaling were evaluated using CCK-8, scratch assays, and Western blot analysis.

RESULTS

Animal investigation revealed that from day 7 onwards, the wound healing rate of the treatment group was higher than that of the model group but lower than the control group. On day 14, the wound healing rates were as follows: control group (0.97 ± 0.01), model group (0.84 ± 0.03), and treatment group (0.93 ± 0.01). These differences were statistically significant. Histological analysis indicates that FUBP1 promotes granulation tissue formation, re-epithelialization, and collagen deposition in treatment group. Additionally, FUBP1 protein expression decreased in dermal fibroblasts when exposed to AGEs. Overexpression of FUBP1 significantly enhanced fibroblast proliferation and migration, activating the Wnt/β-catenin pathway and mitigating the inhibitory effects of AGEs.

CONCLUSIONS

Our results suggest that FUBP1 can be a promising therapeutic target for diabetic wound healing, potentially counteracting the detrimental effects of AGEs on dermal fibroblasts through the Wnt/β-catenin pathway.

Diabetes-Driven Atherosclerosis: Updated Mechanistic Insights and Novel Therapeutic Strategies

The global rise in diabetes prevalence has significantly contributed to the increasing burden of atherosclerotic cardiovascular disease (ASCVD), a leading cause of morbidity and mortality in this population. Diabetes accelerates atherosclerosis through mechanisms such as hyperglycemia, oxidative stress, chronic inflammation, and epigenetic dysregulation, leading to unstable plaques and an elevated risk of cardiovascular events. Despite advancements in controlling traditional risk factors like dyslipidemia and hypertension, a considerable residual cardiovascular risk persists, highlighting the need for innovative therapeutic approaches. Emerging treatments, including sodium-glucose cotransporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, epigenetic modulators, and RNA-based therapies, are showing promise in addressing the unique challenges of diabetes-associated ASCVD. Precision medicine strategies, such as nanoparticle-based drug delivery and cell-specific therapies, offer further potential for mitigating cardiovascular complications. Advances in multiomics and systems biology continue to deepen our understanding of the molecular mechanisms driving diabetes-associated atherosclerosis. This review synthesizes recent advances in understanding the pathophysiology and treatment of diabetes-related atherosclerosis, offering a roadmap for future research and precision medicine approaches to mitigate cardiovascular risk in this growing population.

Explainable machine learning for health disparities: type 2 diabetes in the All of Us research program

Type 2 diabetes (T2D) is a disease with high morbidity and mortality and a disproportionate impact on minority groups. Machine learning (ML) is increasingly used to characterize T2D risk factors; however, it has not been used to study T2D health disparities. Our objective was to use explainable ML methods to discover and characterize T2D health disparity risk factors. We applied SHapley Additive exPlanations (SHAP), a new class of explainable ML methods that provide interpretability to ML classifiers, to this end. ML classifiers were used to model T2D risk within and between self-identified race and ethnicity (SIRE) groups, and SHAP values were calculated to quantify the effect of T2D risk factors. We then stratified SHAP values by SIRE to quantify the effect of T2D risk factors on prevalence differences between groups. We found that ML classifiers (random forest, lightGBM, and XGBoost) accurately modeled T2D risk and recaptured the observed prevalence differences between SIRE groups. SHAP analysis showed the top seven most important T2D risk factors for all SIRE groups were the same, with the order of importance for features differing between groups. SHAP values stratified by SIRE showed that income, waist circumference, and education best explain the higher prevalence of T2D in the Black or African American group, compared to the White group, whereas income, education and triglycerides best explain the higher prevalence of T2D in the Hispanic or Latino group. This study demonstrates that explainable ML can be used to elucidate health disparity risk factors and quantify their group-specific effects.

Dipeptidyl Peptidase 4 Inhibitors vs Metformin for New-onset Dementia: A Propensity Score-matched Cohort Study

BACKGROUND

Hypoglycemic pharmacotherapy interventions for alleviating the risk of dementia remain controversial, particularly regarding dipeptidyl peptidase 4 (DPP4) inhibitors vs metformin. Our objective was to investigate whether the initiation of DPP4 inhibitors, as opposed to metformin, was linked to a reduced risk of dementia.

METHODS

We included individuals with type 2 diabetes over 40 years old who were new users of DPP4 inhibitors or metformin in the Chinese Renal Disease Data System database between 2009 and 2020. The study employed Kaplan-Meier and Cox regression for survival analysis and the Fine and Gray model for the competing risk of death.

RESULTS

Following a 1:1 propensity score matching, the analysis included 3626 DPP4 inhibitor new users and an equal number of metformin new users. After adjusting for potential confounders, the utilization of DPP4 inhibitors was associated with a decreased risk of all-cause dementia compared to metformin [hazard ratio (HR) 0.63, 95% confidence interval (CI) 0.45-0.89]. Subgroup analysis revealed that the utilization of DPP4 inhibitors was associated with a reduced incidence of dementia in individuals who initiated drug therapy at the age of 60 years or older (HR 0.69, 95% CI 0.48-0.98), those without baseline macrovascular complications (HR 0.62, 95% CI 0.41-0.96), and those without baseline microvascular complications (HR 0.67, 95% CI 0.47-0.98).

CONCLUSION

In this real-world study, we found that DPP4 inhibitors presented an association with a lower risk of dementia in individuals with type 2 diabetes than metformin, particularly in older people and those without diabetes-related comorbidities.

Multiple long-term conditions as the next transition in the global diabetes epidemic

Several transitions, or new patterns and dynamics in the contributors and health outcomes, have altered the character and burden of the multi-decade, worldwide growth in prevalence of type 2 diabetes (T2DM). These changes have led to different needs for prevention and care. These dynamics have been driven by diverse demographic, socio-economic, behavioural, and health system response factors. In this Perspective, we describe these transitions and how their attributes have set the stage for multimorbidity, or multiple long-term conditions (MLTCs), to be the next major challenge in the diabetes epidemic. We also describe how the timing and character of these stages differ in high-, middle-, and low-income countries. These challenges call for innovation and a stronger focus on MLTCs across the spectrum of cause, effectiveness, and implementation studies to guide prevention and treatment priorities.

Clonal hematopoiesis of indeterminate potential, health indicators, and risk of cardiovascular diseases among patients with diabetes: a prospective cohort study

BACKGROUND

Clonal hematopoiesis of indeterminate potential (CHIP) was associated with diabetes and cardiovascular diseases (CVD). However, the effect of CHIP on CVD have not been evaluated among patients with diabetes, and whether maintaining the healthy indictors could mitigate the adverse influence was also unclear.

METHODS

A total of 22,239 adults from the UK Biobank with diabetes and available whole-exome sequence data, and free of CVD were included. Multivariable-adjusted Cox regressions were used to explore the associations of any CHIP (variant allele fraction ≥ 2%), large CHIP (variant allele fraction ≥ 10%), and the top 10 commonly mutated driver genes for CHIP and with risk of CVD. The joint associations between health indicators (body mass index [BMI], HbA1c, blood pressure [BP], and low-density lipoprotein cholesterol [LDL]) and CHIP were further investigated.

RESULTS

Over a median follow-up of 13.2 years, 5366 participants with diabetes developed CVD events. The hazard ratios (HRs) (95% confidence intervals [CIs]) of any CHIP and large CHIP were (1.21, 1.08-1.36) and (1.25, 1.09-1.43) for incident CVD, respectively. Significant associations between any CHIP and coronary heart disease (HR, 95%CI: 1.18, 1.03-1.36) and heart failure (1.73, 1.46-2.06) were observed, but not for stroke (1.14, 0.89-1.48). Gene-specific analyses suggested that the greatest association were for SF3B1 (HR, 95%CI: 2.50, 1.25-5.01) and TET2 (HR, 95%CI: 1.36, 1.07-1.77) with risk of CVD. There was no significant interaction between the four health indicators and CHIP in relation to incident CVD. Compared to patients without CHIP, those with any CHIP and ideal health indicators still exhibited significantly or nonsignificantly higher HRs (BMI: 1.18, 0.82-1.68; HbA1c: 1.12, 0.96-1.30; BP: 1.24, 1.03-1.49; LDL: 1.29, 1.09-1.53). Similar results were demonstrated using large CHIP.

CONCLUSIONS

CHIP is independently associated with an increased risk of CVD in patients with diabetes, regardless of health indicator levels. Diabetic patients with CHIP but ideal health indicators still exhibited higher CVD risk compared with diabetic patients without CHIP.

Therapeutic Potential of Medicinal Plants and Their Phytoconstituents in Diabetes, Cancer, Infections, Cardiovascular Diseases, Inflammation and Gastrointestinal Disorders

Conditions like diabetes mellitus (DM), cancer, infections, inflammation, cardiovascular diseases (CVDs), and gastrointestinal (GI) disorders continue to have a major global impact on mortality and morbidity. Medicinal plants have been used since ancient times in ethnomedicine (e.g., Ayurveda, Unani, Traditional Chinese Medicine, and European Traditional Medicine) for the treatment of a wide range of disorders. Plants are a rich source of diverse phytoconstituents with antidiabetic, anticancer, antimicrobial, antihypertensive, antioxidant, antihyperlipidemic, cardioprotective, immunomodulatory, and/or anti-inflammatory activities. This review focuses on the 35 plants most commonly reported for the treatment of these major disorders, with a particular emphasis on their traditional uses, phytoconstituent contents, pharmacological properties, and modes of action. Active phytomolecules with therapeutic potential include cucurbitane triterpenoids, diosgenin, and limonoids (azadiradione and gedunin), which exhibit antidiabetic properties, with cucurbitane triterpenoids specifically activating Glucose Transporter Type 4 (GLUT4) translocation. Capsaicin and curcumin demonstrate anticancer activity by deactivating NF-κB and arresting the cell cycle in the G2 phase. Antimicrobial activities have been observed for piperine, reserpine, berberine, dictamnine, chelerythrine, and allitridin, with the latter two triggering bacterial cell lysis. Quercetin, catechin, and genistein exhibit anti-inflammatory properties, with genistein specifically suppressing CD8+ cytotoxic T cell function. Ginsenoside Rg1 and ginsenoside Rg3 demonstrate potential for treating cardiovascular diseases, with ginsenoside Rg1 activating PPARα promoter, and the PI3K/Akt pathway. In contrast, ternatin, tannins, and quercitrin exhibit potential in gastrointestinal disorders, with quercitrin regulating arachidonic acid metabolism by suppressing cyclooxygenase (COX) and lipoxygenase activity. Further studies are warranted to fully investigate the clinical therapeutic benefits of these plants and their phytoconstituents, as well as to elucidate their underlying molecular mechanisms of action.

Advances in Oral Biomacromolecule Therapies for Metabolic Diseases

Metabolic diseases like obesity and diabetes are on the rise, and therapies with biomacromolecules (such as proteins, peptides, antibodies, and oligonucleotides) play a crucial role in their treatment. However, these drugs are traditionally injected. For patients with chronic diseases (e.g., metabolic diseases), long-term injections are accompanied by inconvenience and low compliance. Oral administration is preferred, but the delivery of biomacromolecules is challenging due to gastrointestinal barriers. In this article, we introduce the available biomacromolecule drugs for the treatment of metabolic diseases. The gastrointestinal barriers to oral drug delivery and strategies to overcome these barriers are also explored. We then discuss strategies for alleviating metabolic defects, including glucose metabolism, lipid metabolism, and energy metabolism, with oral biomacromolecules such as insulin, glucagon-like peptide-1 receptor agonists, proprotein convertase subtilisin/kexin type 9 inhibitors, fibroblast growth factor 21 analogues, and peptide YY analogues.

A Randomized Controlled Trial of a Combined Physical Activity and Attitude Education Intervention on Weight Stigma and Health Outcomes

BACKGROUND

Weight stigma is prevalent among adolescents and can negatively impact physical and mental health. This study examined the effects of a combined physical activity and attitude education intervention on weight stigma and related outcomes among high school students.

METHODS

A randomized controlled trial was conducted with 524 high school students. The intervention group received a 3-month program combining physical activity education and anti-stigma attitude training. Outcomes measured included the use of weight loss medication, physical activity levels, weight loss, and depressive symptoms.

RESULTS

The intervention group showed significant decreases in weight loss medication use and depressive symptoms, and increases in physical activity levels compared to the control group. No significant differences were observed in weight loss between groups. Gender differences were noted, with girls showing greater improvements in physical activity.

IMPLICATIONS

Findings support integrating weight stigma reduction strategies into school health programs. Schools should adopt attitude modification approaches, promote inclusive physical activities, and foster social support to address weight stigma and associated depression symptoms.

CONCLUSIONS

Combining physical activity and attitude education can effectively reduce weight stigma and improve health behaviors among high school students. Future research should explore long-term effects and tailored approaches for different student populations.

Patient perspectives on continuous glucose monitoring system (CGMS) for diabetes in Malaysia: a vital voice in health technology assessment (HTA) informing decision-making

OBJECTIVE

To integrate patient perspectives into Health Technology Assessment (HTA) by exploring the perceived benefits, barriers, and expectations of diabetes patients and their caregivers in Malaysia regarding the use of CGMS.

METHODS

This qualitative study employed focus group discussions (FGDs) with 30 participants, including adults, adolescents, and caregivers managing insulin-requiring diabetes, conducted between May and September 2023 in Kuala Lumpur and Putrajaya, Malaysia. Participants were recruited through purposive sampling. Data were collected using semi-structured interviews and analyzed thematically to capture insights into CGMS benefits, barriers, and expectations.

RESULTS

Participants highlighted CGMS as a transformative tool, offering real-time data, improving glycemic control, and enhancing quality of life by reducing anxiety and the burden of frequent glucose checks. Despite these benefits, significant barriers were identified, including high costs, limited access, technical issues, and social stigma, particularly among adolescents. There was a strong call for government subsidies, better technical support, and healthcare provider training to optimize CGMS use. Patient perspectives were integrated into the HTA alongside systematic reviews and economic evaluations, directly informing policy recommendations, including prioritizing CGMS for high-risk T1DM patients and exploring subsidy frameworks to improve affordability.

CONCLUSIONS

Patient perspectives serve as a vital voice in HTA, offering real-world insights that enhance the understanding of CGMS in diabetes management. Addressing financial, technical, and social barriers is crucial to improving CGMS accessibility and usability. By embedding patient perspectives into HTA and strengthening partnerships across healthcare systems, patient perspectives become instrumental in shaping patient-centered policies and informing equitable decision-making on CGMS utilization in Malaysia.

Targeting aldose reductase using natural African compounds as promising agents for managing diabetic complications

Background

Diabetes remains a leading cause of morbidity and mortality due to various complications induced by hyperglycemia. Inhibiting Aldose Reductase (AR), an enzyme that converts glucose to sorbitol, has been studied to prevent long-term diabetic consequences. Unfortunately, drugs targeting AR have demonstrated toxicity, adverse reactions, and a lack of specificity. This study aims to explore African indigenous compounds with high specificity as potential AR inhibitors for pharmacological intervention.

Methodology

A total of 7,344 compounds from the AfroDB, EANPDB, and NANPDB databases were obtained and pre-filtered using the Lipinski rule of five to generate a compound library for virtual screening against the Aldose Reductase. The top 20 compounds with the highest binding affinity were selected. Subsequently, in silico analyses such as protein-ligand interaction, physicochemical and pharmacokinetic profiling (ADMET), and molecular dynamics simulation coupled with binding free energy calculations were performed to identify lead compounds with high binding affinity and low toxicity.

Results

Five natural compounds, namely, (+)-pipoxide, Zinc000095485961, Naamidine A, (-)-pipoxide, and 1,6-di-o-p-hydroxybenzoyl-beta-d-glucopyranoside, were identified as potential inhibitors of aldose reductase. Molecular docking results showed that these compounds exhibited binding energies ranging from -12.3 to -10.7 kcal/mol, which were better than the standard inhibitors (zopolrestat, epalrestat, IDD594, tolrestat, and sorbinil) used in this study. The ADMET and protein-ligand interaction results revealed that these compounds interacted with key inhibiting residues through hydrogen and hydrophobic interactions and demonstrated favorable pharmacological and low toxicity profiles. Prediction of biological activity highlighted Zinc000095485961 and 1,6-di-o-p-hydroxybenzoyl-beta-d-glucopyranoside as having significant inhibitory activity against aldose reductase. Molecular dynamics simulations and MM-PBSA analysis confirmed that the compounds bound to AR exhibited high stability and less conformational change to the AR-inhibitor complex.

Conclusion

This study highlighted the potential inhibitory activity of 5 compounds that belong to the African region: (+)-Pipoxide, Zinc000095485961, Naamidine A, (-)-Pipoxide, and 1,6-di-o-p-hydroxybenzoyl-beta-d-glucopyranoside. These molecules inhibiting the aldose reductase, the key enzyme of the polyol pathway, can be developed as therapeutic agents to manage diabetic complications. However, we recommend in vitro and in vivo studies to confirm our findings.

Are Trends in Economic Modeling of Pediatric Diabetes Mellitus up to Date with the Clinical Practice Guidelines and the Latest Scientific Findings?

Background: Modeling techniques in the field of pediatrics present unique challenges beyond traditional model limitations, and sometimes difficulties in faithfully simulating the condition's evolution over time. Objective: This study aimed to identify whether economic modeling approaches in diabetes in pediatric patients align with the recommendations of clinical practice guidelines and the latest scientific evidence. Methods: A literature review was performed in March 2023 to identify modeling-based economic evaluations in diabetes in pediatric patients. Data were extracted and synthesized from eligible studies. Clinical practice guidelines for diabetes were gathered to compare their alignment with modeling strategies. Two endocrinology specialists provided insights on the latest findings in diabetes that are not yet included in the guidelines. A multidisciplinary group of experts agreed on the relevant themes to conduct the comparative analysis: parameter informing on glycemic control, diabetic ketoacidosis/hypoglycemia, C-peptide as prognostic biomarker, metabolic memory, age at diagnosis, socioeconomic status, pediatric-specific sources of risk equations, and pediatric-specific sources of utilities/disutilities. Results: Nineteen modeling-based studies (7 de novo, 12 predesigned models) and 34 guidelines were selected. Hemoglobin A1c was the main parameter to model the glycemic control; however, guidelines recommend the usage of complementary measures (eg, time in range) which are not included in economic models. Eight models included diabetic ketoacidosis (42.1%), 16 included hypoglycemia (84.2%), 2 included C-peptide (1 of those as prognostic factor) (10.5%) and 1 included legacy effect (5.3%). Neither guidelines nor models included recent findings, such as age at diagnosis or socioeconomic status, as prognostic factors. The lack of pediatric-specific sources for risk equations and utility/disutility values were additional limitations. Discussion: Economic models designed for assessing interventions in diabetes in pediatric patients should be based on pediatric-specific data and include novel adjuvant glucose-monitoring metrics and latest evidence on prognostic factors (C-peptide, legacy effect, age at diagnosis, socioeconomic status) to provide a more faithful reflection of the disease. Conclusions: Economic models represent useful tools to inform decision making. However, further research assessing the gaps is needed to enhance evidence-based health economic modeling that best represents reality.

Unveiling the Multitarget Potential of a Rare Caffeoyl Ester from Artemisia capillaris for Diabetes Mellitus: An Integrated In Vitro and In Silico Study

As a part of our ongoing search for bioactive constituents of Artemisia capillaris, we isolated 4-O-caffeoyl-2-C-methyl-d-threonic acid (PPT-14). This is a rare caffeic acid ester derivative that is reported here for the first time in the Artemisia species, which is the third occurrence in any plant species worldwide. In this study, we evaluated the anti-diabetic potential of PPT-14 using in vitro and in silico approaches. PPT-14 demonstrated significant inhibitory activity against two crucial enzymes linked to diabetes progression and complications: protein tyrosine phosphatase 1B (PTP1B) and aldose reductase (AR). These had IC50 values of 64.92 and 19.50 µM, respectively. Additionally, PPT-14 exhibited free radical scavenging activity with 2,2-diphenyl-2-picrylhydrazyl (IC50 14.46 µM). Molecular docking and 200 ns molecular dynamics simulations confirmed that there were stable binding interactions with the key residues of PTP1B and AR, highlighting strong affinity and dynamic stability. Pharmacokinetic analyses revealed favorable water solubility, adherence to Lipinski's Rule of Five, and minimal interactions with cytochrome P450 enzymes, indicating the drug-like potential of PPT-14. Toxicity studies confirmed its safety profile, showing no genotoxicity, hepatotoxicity, or significant toxicity risks, with an acceptable oral LD50 value of 2.984 mol/kg. These findings suggest that PPT-14 could be a promising multitarget lead compound for ameliorating diabetes and its associated complications.

Association of intrinsic capacity with incident type 2 diabetes mellitus in older Chinese: Guangzhou Biobank Cohort Study

BACKGROUND

The World Health Organization introduced intrinsic capacity (IC) as a metric for healthy aging. However, we found no report on the association between IC and type 2 diabetes mellitus (T2DM). We investigated the association between IC and incident T2DM in older Chinese from the Guangzhou Biobank Cohort Study.

METHODS

IC was assessed across five domains equally: locomotion, vitality, cognition, psychological and sensory. Composite IC scores (0-10) were classified into three groups: poor (0-5.9), fair (6.0-8.9), and high (9.0-10), with higher scores representing greater IC. Multivariable linear regression and cox regression was used to analyze the association between IC with glycemia and T2DM, respectively.

RESULTS

Of 3582 participants with a mean age of 59.1 years (standard deviation (SD)=7.13) without baseline diabetes, during an average follow-up of 3.3 years (SD=0.86), 497 (13.87%) developed T2DM. After adjustments for potential confounders, those with baseline poor IC, versus high, had higher fasting glucose, 2-hour post-load glucose and glycosylated hemoglobin A1c at follow-up, and a higher risk of incident T2DM (HR (95%CI): 1.80 (1.20, 2.72)). Among IC domains, only vitality impairment was associated with an increased risk of T2DM (P for trend < 0.001).

CONCLUSION

We first reported the prospective associations of poor IC and vitality with higher glycemia and incident T2DM risk. Enhancing muscle strength to improve functional ability may be a possible intervention for reducing future risk of T2DM in older populations.

Machine learning-driven Raman spectroscopy: A novel approach to lipid profiling in diabetic kidney disease

Diabetes mellitus is a chronic metabolic disease that increasingly affects people every year. It is known that with its progression and poor management, metabolic changes can lead to organ dysfunctions, including kidneys. The study aimed to combine Raman spectroscopy and biochemical lipid profiling, complemented by machine learning (ML) techniques to evaluate chemical composition changes in kidneys induced by Type 2 Diabetes mellitus (T2DM). Raman spectroscopy identified significant differences in lipid content and specific molecular vibrations, with the 1777 cm-1 band emerging as a potential spectroscopic marker for diabetic kidney damage. The integration of ML algorithms improved the analysis, providing high accuracy, selectivity, and specificity in detecting these changes. Moreover, lipids metabolic profiling revealed distinct variations in the concentration of 11 phosphatydylocholines and 9 acyl-alkylphosphatidylcholines glycerophospholipids. Importantly, the correlation between Raman data and lipids metabolic profiling differed for control and T2DM groups. This study underscores the combined power of Raman spectroscopy and ML in offering a low-cost, fast, precise, and comprehensive approach to diagnosing and monitoring diabetic nephropathy, paving the way for improved clinical interventions. However, taking into account small number of data related to ethical committee approvals, the study should be verified on a larger number of cases.

Preparation, identification and α-glucosidase inhibitory activity of a high-methoxyl HG-type pectin from Liangping pomelo (Citrus maxima cv. Liangpin Yu) peel

BACKGROUND

The peel from Liangping pomelo (Citrus maxima cv. Liangpin Yu) is generally discarded as waste during post-harvest handling and process, resulting in environmental pollution and waste. Pectin is the major component in pomelo peels and yields significant economic advantages. Thus, developing pomelo peel pectin (PPs) might be a feasible strategy to reduce environmental pollution caused by pomelo peel.

RESULTS

The optimized PPs yield was 156.5 ± 2.5 g kg-1 under the inoculum size of 100 mg g-1, liquid-solid ratio of 31 mL g-1, fermentation time of 64 h, and fermentation temperature of 39 °C. PPs-6Aa, a pectin fraction from PPs purified with DEAE-52 cellulose, Sephadex G-100 and Sephadex G-75 column chromatography, showed higher α-glucosidase inhibitory activity, with an IC50 of 0.12 ± 0.03 mg mL-1. It was a high-methoxyl HG-type pectin of 42.8 kDa, and its repeat unit was →4)-α-GalpA-6-OMe-(1→4)-α-GalpA-6-OMe-(1→. Additionally, its α-glucosidase inhibitory activity might be related to hydrogen bonds formed with Lys-156, Glu-277, His-280, Asp-307, Arg-315, Asn-350, Asp-352 and Glu-411, and to hydrophobic interactions formed with Ser-157, Tyr-158, Asp-233, Gln-239, Ser-240, Phe-303, Thr-306, Leu-313, Phe-314, Gln-353 and Arg-442.

CONCLUSION

These findings provide structural and bioactivity information on pectin from Liangping pomelo peel, which could be beneficial for the development of functional foods and pharmaceuticals. © 2024 Society of Chemical Industry.

The impact of diabetes on Sepsis-induced cardiomyopathy

PURPOSE

This study investigated the association between diabetes and Sepsis-induced cardiomyopathy (SIC), focusing on how changes in inflammatory response and cardiac function influence SIC prognosis. The aim is to provide clinicians with more accurate treatment and management strategies, ultimately enhancing patient outcomes and quality of life.

METHODS

This retrospective cohort study analyzed 258 Sepsis-induced cardiomyopathy (SIC) patients, stratified by diabetes status and HbA1C levels. Data were collected from electronic medical records. Statistical tests included the Kolmogorov-Smirnov, t-test, Mann-Whitney U, Kruskal-Wallis, chi-square, and Spearman correlation. Univariate and multivariate logistic regression assessed diabetes' impact on SIC severity. Model fit was evaluated with the Hosmer-Lemeshow and negative log-likelihood ratio tests. A nomogram was constructed and validated using ROC curves, calibration curves, and decision curve analysis. Subgroup and interaction analyses were performed (P < 0.05).

RESULTS

Diabetes worsened inflammation and immune responses in SIC, significantly affecting markers like LVEF, TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA scores (P < 0.05). Grouping by HbA1C levels revealed no significant differences in LVEF (P = 0.078), Alb (P = 0.105), or L/A (P = 0.211), but differences were found for TnI, CK-MB, BNP, NLR, IL-6, PCT, CRP, APACHE II, and SOFA (P < 0.05). HbA1C strongly correlated with CRP (rs = 0.8664). BNP (OR 1.001) and HbA1C (OR 1.302) were significant risk factors for SIC, with the nomogram showing good predictive performance (AUC 0.693). No significant interaction between HbA1C and BNP on SIC severity was observed (P = 0.791).

CONCLUSION

Diabetes exacerbates inflammatory and immune responses in Sepsis-induced cardiomyopathy patients, leading to worsened cardiac function.

Prediction model for type 2 diabetes mellitus and its association with mortality using machine learning in three independent cohorts from South Korea, Japan, and the UK: a model development and validation study

Background

Type 2 diabetes mellitus (T2DM) is a significant global public health concern that has steadily increased over the past few decades. Thus, this study aimed to predict the incidence of T2DM within 5 years and the risk of mortality following the onset of T2DM. Data from three independent cohorts worldwide were used.

Methods

We utilized data from three independent, large-scale, general population-based, and worldwide cohort studies. The Korean cohort (NHIS-NSC cohort; discovery cohort; n = 973,303), conducted between 1 January, 2002 and 31 December, 2013, was used for training and internal validation, whereas the Japanese cohort (JMDC cohort; validation cohort A; n = 12,143,715) and UK cohort (UK Biobank; validation cohort B; n = 416,656) were used for external validation. We employed various machine learning (ML)-based models, using 18 features, to predict the incidence of T2DM within five years of regular health checkups and calculated the Shapley Additive Explanation (SHAP) values. To ensure the robustness of our ML-based prediction model, we investigated the potential association between the model probability divided into tertiles and the risk of mortality following the onset of T2DM.

Findings

In the discovery cohort, the ensemble model using voting with logistic regression and adaptive boosting achieved a balanced accuracy of 72.6% and an area under the receiver operating characteristics curve (AUROC) of 0.792. The SHAP value analysis of our proposed model revealed that age was the most important predictor of incident T2DM, followed by fasting blood glucose, hemoglobin, γ-glutamyl transferase level, and body mass index. The model probability is associated with an increased risk of mortality (T1: adjusted hazard ratio, 2.82 [95% CI, 2.01-3.94]; T2: 3.89 [2.74-5.53]; and T3: 7.73 [5.37-11.12]). Similar patterns and trends were observed in the validation cohorts (T1: 1.74 [1.49-2.03], T2: 1.97 [1.69-2.30], and T3: 3.31 [2.82-3.38] in validation cohort A; T1: 1.33 [1.03-1.71], T2: 1.54 [1.21-1.96], and T3: 1.73 [1.36-2.20] in validation cohort B).

Interpretation

This study derived and validated an ML-based model to predict the incidence of T2DM within 5 years across three countries (South Korea, Japan, and the UK), showing that the model probability is associated with an increased risk of mortality.

Funding

Institute of Information & Communications Technology Planning & Evaluation, South Korea.

Comparison of the incidence of post-endoscopic retrograde cholangiopancreatography pancreatitis in patients with and without diabetes: a meta-analysis

BACKGROUND

Pancreatitis is a common complication for patients receiving endoscopic retrograde cholangiopancreatography (ERCP). The objective of the meta-analysis was to compare the incidence of post-ERCP pancreatitis (PEP) in individuals with and without pre-existing diabetes.

METHODS

A comprehensive review of the existing literature was carried out in PubMed, Embase, and Web of Science to identify applicable observational studies. The data were combined using a random-effects model while accounting for potential heterogeneity.

RESULTS

A total of 16 datasets from 14 observational studies involving 158,847 patients who received ERCP were included. Among them, 26,823 (16.9%) had pre-existing diabetes, and 24,654 (15.5%) had developed PEP. The pooled results showed that, compared to patients without diabetes, those with pre-existing diabetes had a lower incidence of PEP (odds ratio: 0.77, 95% confidence interval: 0.63 to 0.94, p = 0.01; I2 = 52%). A sensitivity analysis conducted by excluding one dataset at a time showed similar results (OR 0.74 to 0.81, p all < 0.05). Further subgroup and meta-regression analyses indicated that the link between diabetes and a decreased likelihood of PEP was not notably influenced by study factors such as country, average age, male representation, diabetes prevalence, incidence of PEP among the patients studied, diagnostic methods for PEP, or study quality scores.

CONCLUSIONS

Integrated evidence from observational studies currently indicate that diabetes could potentially act as a protective element against PEP. However, it is important to confirm these findings through extensive prospective studies that account for various influencing factors.

Update on Menopause Hormone Therapy; Current Indications and Unanswered Questions

OBJECTIVE

To provide clinicians involved in managing menopause with a summary of current evidence surrounding menopause hormone therapy (MHT).

DESIGN

The authors evaluate and synthesize existing pooled evidence relating to MHT's clinical indications, efficacy, and safety and explore the limitations of existing data.

PATIENTS

The review focuses on MHT-related outcomes in women with natural-timed menopause captured within observational studies, RCTs, and pooled data from pivotal meta-analyses and reviews.

MEASUREMENTS

Available published data are scrutinized. Available evidence and notably lacking data from women not adequately represented in published MHT trials, such as those with socioeconomic adversity, significant comorbidities, and minority ethnic backgrounds, are highlighted and deliberated.

RESULTS

The impact of MHT differs significantly between demographics. Current consensus recommendations for MHT emphasize the importance of tailoring type, route, dose, and duration of therapy to individual needs and risk/benefit ratio through shared decision-making. MHT impact can change over time. Current MHT data support its benefits for treating menopause symptoms and a potential window of opportunity in midlife to benefit skeletal health. Limitations of current evidence highlight menopause health inequalities and underscores the need for further research.

CONCLUSIONS

This review recommends tailored use of MHT for well-defined indications, recognizing its value for menopause symptom relief and skeletal benefits for many midlife women. MHT may be used as long as benefits outweigh risks, through shared decision-making. There is insufficient clinical evidence to support the long-term use of MHT in some contemporary cohorts of women accessing MHT in clinical practice.

A Narrative Review: Relationship Between Glycemic Variability and Emerging Complications of Diabetes Mellitus

A growing body of evidence emphasizes the role of glycemic variability (GV) in the development of conventional diabetes-related complications. Furthermore, advancements in diabetes management and increased life expectancy have led to the emergence of new complications, such as cancer, liver disease, fractures, infections, and cognitive dysfunction. GV is considered to exacerbate oxidative stress and inflammation, acting as a major mechanism underlying these complications. However, few reviews have synthesized the association between GV and these emerging complications or examined their underlying mechanisms. Hence, this narrative review provides a comprehensive discussion of the burden, risks, and mechanisms of GV in these complications, offering further evidence supporting GV as a potential therapeutic target for diabetes management.

Immunomodulation effects of collagen hydrogel encapsulating extracellular vesicles derived from calcium silicate stimulated-adipose mesenchymal stem cells for diabetic healing

Diabetic wounds are characterized by chronic inflammation, reduced angiogenesis, and insufficient collagen deposition, leading to impaired healing. Extracellular vesicles (EVs) derived from adipose-derived mesenchymal stem cells (ADSC) offer a promising cell-free therapeutic strategy, yet their efficacy and immunomodulation can be enhanced through bioactivation. In this study, we developed calcium silicate (CS)-stimulated ADSC-derived EVs (CSEV) incorporated into collagen hydrogels to create a sustained-release system for promoting diabetic wound healing. CSEV exhibited enhanced protein content, surface marker expression, and bioactive cargo enriched with pro-angiogenic and anti-inflammatory factors. In vitro, CSEV-loaded collagen significantly reduced reactive oxygen species production, promoted cell proliferation and migration compared to standard EV-loaded collagen. Cytokine profiling revealed the upregulation of anti-inflammatory cytokines and extracellular matrix components, highlighting their immunomodulatory and regenerative potential. In vivo, histological evaluation of diabetic rabbit models treated with CSEV-loaded collagen revealed superior reepithelialization and organized collagen deposition, indicating accelerated wound closure. These findings underscore the potential of CSEV-loaded collagen hydrogels as an innovative and effective therapeutic platform for enhancing diabetic wound healing by simultaneously addressing inflammation and tissue regeneration.

Diabetes Mellitus Impairs Blood-Brain Barrier Integrality and Microglial Reactivity

Diabetes mellitus (DM), a chronic metabolic disorder that adversely affects the blood-brain barrier (BBB) and microglial function in the central nervous system (CNS), contributing to neuronal damage and neurodegenerative diseases. However, the underlying molecular mechanisms linking diabetes to BBB dysfunction and microglial dysregulation remain poorly understood. Here, we assessed the impacts of diabetes on BBB and microglial reactivity and investigated its mechanisms. We found diabetes severely disrupted the BBB integrity and microglial response to vascular injury. We also revealed a potential relationship between BBB disruption and impaired microglial function, whereby increasing BBB permeability led to a downregulation of microglial P2RY12 expression, thereby impairing microglial protection against cerebrovascular injury. Understanding these mechanisms may contribute to the developing of therapeutic strategies for diabetes-related neurological complications.