Major Complication Of Diabetes Research Articles

Adropin Treatment Restores Cardiac Function and Metabolic Flexibility in Diabetic Cardiomyopathy

Background: Diabetic cardiomyopathy (DCM) is a major complication of diabetes, and has been recognized as a cause of heart failure independent of other common risk factors. Metabolic inflexibility is a hallmark feature, where increased free fatty acid availability and decreased myocardial glucose uptake lead to an over-reliance on fatty acid oxidation, reducing cardiac work effciency. Energetic ineffciency in diabetic hearts may have profound implications for cardiac function under conditions of increased workload, and therefore therapeutic approaches are warranted. Adropin is a liver- and brain-secreted peptide hormone shown to regulate fuel metabolism in the heart. Adropin levels are significantly reduced in obese and diabetic human subjects, and this decrease is linked to increased adiposity, insulin resistance, and impaired glucose tolerance. Our lab recently showed that acute adropin treatment restores glucose oxidation activity in the hearts of prediabetic obese mice. However, the effects of chronic adropin exposure in the heart remains unknown. Hypothesis: We hypothesize that adropin treatment will exhibit beneficial effects on cardiac fuel metabolism that may lead to long-term improvements in functional output. Methods: We used a preclinical model of DCM to investigate the effects of long-term adropin treatment on cardiac structural and metabolic remodeling. Mice were treated with adropin daily for four weeks, and subjected to echocardiography, glucose tolerance tests, histopathology, RNA-sequencing, and metabolomics. Results: We report that long-term adropin treatment restores normal cardiac structure and metabolic function in the diabetic heart, by inhibiting flux of non-oxidative glycolytic intermediates into the hexosamine biosynthetic pathway. Conclusions: Our findings highlight the therapeutic potential of adropin signaling to attenuate cardiac remodeling in DCM. The project described was supported by NIDDK 1F31DK134089 and NHLBI R01HL147861. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

USP7 Promotes Cardiometabolic Disorders and Mitochondrial Homeostasis Dysfunction in Diabetic Mice via stabilizing PGC1β

Diabetic cardiomyopathy (DCM) is a major complication of diabetes and is characterized by left ventricular dysfunction. Currently, there is a lack of effective treatments for DCM. Ubiquitin-specific protease 7 (USP7) plays a key role in various diseases. However, whether USP7 is involved in DCM has not been established. In this study, we demonstrated that USP7 was upregulated in diabetic mouse hearts and NMCMs co-treated with HG+PA or H9c2 cells treated with PA. Abnormalities in diabetic heart morphology and function were reversed by USP7 silencing through conditional gene knockout or chemical inhibition. Proteomic analysis coupled with biochemical validation confirmed that PCG1β was one of the direct protein substrates of USP7 and aggravated myocardial damage through coactivation of the PPARα signaling pathway. USP7 silencing restored the expression of fatty acid metabolism-related proteins and restored mitochondrial homeostasis by inhibiting mitochondrial fission and promoting fusion events. Similar effects were also observed in vitro. Our data demonstrated that USP7 promoted cardiometabolic metabolism disorders and mitochondrial homeostasis dysfunction via stabilizing PCG1β and suggested that silencing USP7 may be a therapeutic strategy for DCM.

Vacuolar H+-ATPase in Diabetes, Hypertension, and Atherosclerosis.

Vacuolar H+-ATPase (V-ATPase) is a multisubunit protein complex which, along with its accessory proteins, resides in almost every eukaryotic cell. It acts as a proton pump and as such is responsible for regulating pH in lysosomes, endosomes, and the extracellular space. Moreover, V-ATPase has been implicated in receptor-mediated signaling. Although numerous studies have explored the role of V-ATPase in cancer, osteoporosis, and neurodegenerative diseases, research on its involvement in vascular disease remains limited. Vascular diseases pose significant challenges to human health. This review aimed to shed light on the role of V-ATPase in hypertension and atherosclerosis. Furthermore, given that vascular complications are major complications of diabetes, this review also discusses the pathways through which V-ATPase may contribute to such complications. Beginning with an overview of the structure and function of V-ATPase in hypertension, atherosclerosis, and diabetes, this review ends by exploring the pharmacological potential of targeting V-ATPase.

Psychological factors and diabetic foot ulceration: a scoping review of the bi-directional relationship between diabetic foot ulcer healing and mental health factors

Introduction Diabetic foot ulceration (DFU) is a major complication of diabetes and is associated with high morbidity and mortality rates. Psychological factors are believed to play a role in wound healing, but it remains uncertain if psychological interventions can help individuals with an active DFU, or a history of DFUs, to achieve complete or improved wound healing or prevent recurrence. Objective The objective of the proposed scoping review is to investigate the emotional consequences/burden of living with DFU and to examine how psychosocial factors may impact progression and management of ulcerations. Methods This review will be conducted in accordance with the Joanna Briggs Institute methodology for scoping reviews and the Preferred Reporting Items for Systematic reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) will guide the reporting of results. Discussion While factors such as stress, depression, social support, and adherence to treatment have been identified as variables that may negatively affect DFU healing, there is a need for a greater understanding of how psychological and behavioural variables such as these may influence ulcer incidence, healing and recurrence in people with diabetes. This review will comprise of a broad and systematically mapped synthesis of the identified data. Findings will be used to provide a better understanding of the bi-directional relationship between DFU and psychological variables and will provide direction for the development or adaptation of a tailored psychological intervention that will aim to optimise wellbeing and improve outcomes for individuals with DFU.

Prediction and analysis of risk factors for diabetic retinopathy based on machine learning and interpretable models

ObjectiveDiabetic retinopathy is one of the major complications of diabetes. In this study, a diabetic retinopathy risk prediction model integrating machine learning models and SHAP was established to increase the accuracy of risk prediction for diabetic retinopathy, explain the rationality of the findings from model prediction and improve the reliability of prediction results. MethodsData were preprocessed for missing values and outliers, features selected through information gain, a diabetic retinopathy risk prediction model established using the CatBoost and the outputs of the mode interpreted using the SHAP model. ResultsOne thousand early warning data of diabetes complications derived from diabetes complication early warning dataset from the National Clinical Medical Sciences Data Center were used in this study. The CatBoost-based model for diabetic retinopathy prediction performed the best in the comparative model test. ALB_CR, HbA1c, UPR_24, NEPHROPATHY and SCR were positively correlated with diabetic retinopathy, while CP, HB, ALB, DBILI and CRP were negatively correlated with diabetic retinopathy. The relationships between HEIGHT, WEIGHT and ESR characteristics and diabetic retinopathy were not significant. ConclusionThe risk factors for diabetic retinopathy include poor renal function, elevated blood glucose level, liver disease, hematonosis and dysarteriotony, among others. Diabetic retinopathy can be prevented by monitoring and effectively controlling relevant indices. In this study, the influence relationships between the features were also analyzed to further explore the potential factors of diabetic retinopathy, which can provide new methods and new ideas for the early prevention and clinical diagnosis of subsequent diabetic retinopathy.

Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites.

Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes. This study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors. We used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2) and DR (defined as an Early Treatment Diabetic Retinopathy Study severity level ≥20). DKD and DR detection models were developed based on the variable selection results and externally validated on a sample of 5843 participants with diabetes from the UK biobank (2007-2010). Machine-learned model performance (area under the receiver operating characteristic curve [AUC] with 95% CI, sensitivity, and specificity) was compared to that of traditional LR adjusted for age, sex, diabetes duration, hemoglobin A1c, systolic blood pressure, and BMI. Singapore Epidemiology of Eye Diseases participants had a median age of 61.7 (IQR 53.5-69.4) years, with 49.1% (1361/2772) being women, 20.2% (555/2753) having DKD, and 25.4% (685/2693) having DR. UK biobank participants had a median age of 61.0 (IQR 55.0-65.0) years, with 35.8% (2090/5843) being women, 6.7% (374/5570) having DKD, and 6.1% (355/5843) having DR. The ML algorithms identified diabetes duration, insulin usage, age, and tyrosine as the most important factors of both DKD and DR. DKD was additionally associated with cardiovascular disease history, antihypertensive medication use, and 3 metabolites (lactate, citrate, and cholesterol esters to total lipids ratio in intermediate-density lipoprotein), while DR was additionally associated with hemoglobin A1c, blood glucose, pulse pressure, and alanine. Machine-learned models for DKD and DR detection outperformed traditional LR models in both internal (AUC 0.838 vs 0.743 for DKD and 0.790 vs 0.764 for DR) and external validation (AUC 0.791 vs 0.691 for DKD and 0.778 vs 0.760 for DR). This study highlighted diabetes duration, insulin usage, age, and circulating tyrosine as important factors in detecting DKD and DR. The integration of ML with biomedical big data enables biomarker discovery and improves disease detection beyond traditional risk factors.

The impact of inflammatory biomarkers on amputation rates in patients with diabetic foot ulcers.

Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, often leading to amputation. Understanding the relationship between haematological inflammatory markers and the incidence of amputation in DFU patients with infectious complications is crucial for improving management and outcomes. This retrospective study, conducted from May 2020 to October 2022, involved 109 patients with DFUs, categorised into amputation (AM) and non-amputation (NAM) groups. Patients were evaluated for various factors, including demographic data, DFU duration, and blood parameters such as haemoglobin A1c (HbA1c), haemoglobin (Hb), albumin (ALB), white blood cell count (WBC), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR). Statistical analyses were performed using independent sample t-tests, Mann-Whitney U test and logistic regression. The univariate analysis showed no significant difference in BMI, DM duration or DFU duration between groups. However, significant differences were noted in PCT, Hb, ESR, ALB, HbA1c and WBC levels, and in inflammatory ratios (NLR, PLR and LMR). Multivariate logistic regression identified CRP, NLR and PLR as independent risk factors for amputation. The study highlights CRP, PLR and NLR as key independent risk factors for amputation in patients with DFUs. These easily obtainable markers from routine blood tests can effectively aid in predicting the risk of osteomyelitis and amputation, enhancing clinical decision making and patient care strategies.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls.

Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD. We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis. The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p<0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered. We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

GSK3β: A ray of hope for the treatment of diabetic kidney disease.

Diabetic kidney disease (DKD), a major microvascular complication of diabetes, is characterized by its complex pathogenesis, high risk of chronic renal failure, and lack of effective diagnosis and treatment methods. GSK3β (glycogen synthase kinase 3β), a highly conserved threonine/serine kinase, was found to activate glycogen synthase. As a key molecule of the glucose metabolism pathway, GSK3β participates in a variety of cellular activities and plays a pivotal role in multiple diseases. However, these effects are not only mediated by affecting glucose metabolism. This review elaborates on the role of GSK3β in DKD and its damage mechanism in different intrinsic renal cells. GSK3β is also a biomarker indicating the progression of DKD. Finally, the protective effects of GSK3β inhibitors on DKD are also discussed.

TRPM2 knockdown attenuates myocardial apoptosis and promotes autophagy in HFD/STZ-induced diabetic mice via regulating the MEK/ERK and mTORC1 signaling pathway.

Diabetic cardiomyopathy (DCM) is a major complication of diabetes. Transient receptor potential melastatin 2 (TRPM2) activity increases in diabetic oxidative stress state, and it is involved in myocardial damage and repair. We explore the protective effect of TRPM2 knockdown on the progression of DCM. A type 2 diabetes animal model was established in C57BL/6N mice by long-term high-fat diet (HFD) feeding combined with a single injection of 100-mg/kg streptozotocin (STZ). Genetic knockdown of TRPM2 in heart was accomplished by the intravenous injection via the tail vein of adeno-associated virus type 9 carrying TRPM2 shRNA. Neonatal rat ventricular myocytes was exposed to 45mM of high-glucose (HG) stimulation for 72h in vitro to mimic the in vivo conditions. Western blot, real-time quantitative PCR (RT-qPCR), immunohistochemistry and fluorescence, electron, CCK-8, and flow cytometry were used to evaluate the phenotype of cardiac inflammation, fibrosis, apoptosis, and autophagy. Mice with HFD/STZ-induced diabetes exhibited systolic and diastolic dysfunction, as demonstrated by increased myocardial apoptosis and autophagy inhibition in the heart. Compared to control group, the protein expression of TRPM2, bax, cleaved caspase-3, and P62 was significantly elevated, and the protein expression of bcl-2 and LC3-II was significantly decreased in the myocardial tissues of the HFD/STZ-induced diabetes group. Knockdown of TRPM2 significantly reversed the HFD/STZ-induced myocardial apoptosis and autophagy inhibition. TRPM2 silencing attenuated HG-induced apoptosis and autophagy inhibition in primary cardiomyocytes via regulating the MEK/ERK mTORC1 signaling pathway. TRPM2 knockdown attenuates hyperglycemia-induced myocardial apoptosis and promotes autophagy in HFD/STZ-induced diabetic mice or HG-stimulated cardiomyocytes via regulating the MEK/ERK and mTORC1 signaling pathway.

Quantitative Proteomics Combined with Network Pharmacology Analysis Unveils the Biological Basis of Schisandrin B in Treating Diabetic Nephropathy.

Diabetic nephropathy (DN) is a major complication of diabetes. Schisandrin B (Sch) is a natural pharmaceutical monomer that was shown to prevent kidney damage caused by diabetes and restore its function. However, there is still a lack of comprehensive and systematic understanding of the mechanism of Sch treatment in DN. We aim to provide a systematic overview of the mechanisms of Sch in multiple pathways to treat DN in rats. Streptozocin was used to build a DN rat model, which was further treated with Sch. The possible mechanism of Sch protective effects against DN was predicted using network pharmacology and was verified by quantitative proteomics analysis. High dose Sch treatment significantly downregulated fasting blood glucose, creatinine, blood urea nitrogen, and urinary protein levels and reduced collagen deposition in the glomeruli and tubule-interstitium of DN rats. The activities of superoxide dismutase (SOD) and plasma glutathione peroxidase (GSH-Px) in the kidney of DN rats significantly increased with Sch treatment. In addition, the levels of IL-6, IL-1β, and TNF-α were significantly reduced in DN rats treated with Sch. 11 proteins that target both Sch and DN were enriched in pathways such as MAPK signaling, PI3K-Akt signaling, renal cell carcinoma, gap junction, endocrine resistance, and TNF signaling. Furthermore, quantitative proteomics showed that Xaf1 was downregulated in the model vs. control group and upregulated in the Sch-treated vs. model group. Five proteins, Crb3, Tspan4, Wdr45, Zfp512, and Tmigd1, were found to be upregulated in the model vs. control group and downregulated in the Sch vs. model group. Three intersected proteins between the network pharmacology prediction and proteomics results, Crb3, Xaf1, and Tspan4, were identified. Sch functions by relieving oxidative stress and the inflammatory response by regulating Crb3, Xaf1, and Tspan4 protein expression levels to treat DN disease.

MiR-17-5p-engineered sEVs Encapsulated in GelMA Hydrogel Facilitated Diabetic Wound Healing by Targeting PTEN and p21.

Delayed wound healing is a major complication of diabetes, and is associated with impaired cellular functions. Current treatments are unsatisfactory. Based on the previous reports on microRNA expression in small extracellular vesicles (sEVs), miR-17-5p-engineered sEVs (sEVs17-OE) and encapsulated them in gelatin methacryloyl (GelMA) hydrogel for diabetic wounds treatment are fabricated. SEVs17-OE are successfully fabricated with a 16-fold increase in miR-17-5p expression. SEVs17-OE inhibited senescence and promoted the proliferation, migration, and tube formation of high glucose-induced human umbilical vein endothelial cells (HG-HUVECs). Additionally, sEVs17-OE also performs a promotive effect on high glucose-induced human dermal fibroblasts (HG-HDFs). Mechanism analysis showed the expressions of p21 and phosphatase and tensin homolog (PTEN), as the target genes of miR-17-5p, are downregulated significantly by sEVs17-OE. Accordingly, the downstream genes and pathways of p21 and PTEN, are activated. Next, sEVs17-OE are loaded in GelMA hydrogel to fabricate a novel bioactive wound dressing and to evaluate their effects on diabetic wound healing. Gel-sEVs17-OE effectively accelerated wound healing by promoting angiogenesis and collagen deposition. The cellular mechanism may be associated with local cell proliferation. Therefore, a novel bioactive wound dressing by loading sEVs17-OE in GelMA hydrogel, offering an option for chronic wound management is successfully fabricated.

Research progress on the treatment of diabetic nephropathy with leech and its active ingredients.

Diabetic nephropathy (DN) is a major microvascular complication of diabetes and a common cause of chronic kidney disease. There is currently a lack of effective treatments for DN, and the prognosis for patients remains poor. Hirudin, one of the primary active components derived from leeches, demonstrates anti-coagulant, anti-fibrotic, anti-thrombotic, and anti-inflammatory properties, exhibiting significant protective effects on the kidneys. In recent years, there has been a surge of interest in studying the potential benefits of hirudin, especially in its role in the management of DN. This article delves into the mechanisms by which hirudin contributes to the treatment of DN and its clinical efficacy.

The relationship between diabetic retinopathy and diabetic nephropathy in type 2 diabetes.

Diabetic retinopathy (DR) and diabetic nephropathy (DN), are major microvascular complications of diabetes. DR is an important predictor of DN, but the relationship between the severity of DR and the pathological severity of diabetic glomerulopathy remains unclear. To investigate the relationship between severity of diabetic retinopathy (DR) and histological changes and clinical indicators of diabetic nephropathy (DN) in patients with type 2 diabetes mellitus (T2DM). Patients with T2DM (n=272) who underwent a renal biopsy were eligible. Severity of DR was classified as non-diabetic retinopathy, non-proliferative retinopathy, and proliferative retinopathy (PDR). Relationship between DN and DR and the diagnostic efficacy of DR for DN were explored. DN had a higher prevalence of DR (86.4%) and DR was more severe. The sensitivity and specificity of DR in DN were 86.4% and 78.8%, while PDR was 26.4% and 98.5%, respectively. In DN patients, the severity of glomerular lesions (p=0.001) and prevalence of KW nodules (p<0.001) significantly increased with increasing severity of DR. The presence of KW nodules, lower hemoglobin levels, and younger age were independent risk factors associated with more severe DR in patients with DN. DR was a good predictor of DN. In DN patients, the severity of DR was associated with glomerular injury, and presence of KW nodules, lower hemoglobin levels and younger age were independent risk factors associated with more severe DR. ClinicalTrails.gov, NCT03865914.

Development and deployment of a nationwide predictive model for chronic kidney disease progression in diabetic patients.

Chronic kidney disease (CKD) is a major complication of diabetes and a significant disease burden on the healthcare system. The aim of this work was to apply a predictive model to identify high-risk patients in the early stages of CKD as a means to provide early intervention to avert or delay kidney function deterioration. Using the data from the National Diabetes Database in Singapore, we applied a machine-learning algorithm to develop a predictive model for CKD progression in diabetic patients and to deploy the model nationwide. Our model was rigorously validated. It outperformed existing models and clinician predictions. The area under the receiver operating characteristic curve (AUC) of our model is 0.88, with the 95% confidence interval being 0.87 to 0.89. In recognition of its higher and consistent accuracy and clinical usefulness, our CKD model became the first clinical model deployed nationwide in Singapore and has been incorporated into a national program to engage patients in long-term care plans in battling chronic diseases. The risk score generated by the model stratifies patients into three risk levels, which are embedded into the Diabetes Patient Dashboard for clinicians and care managers who can then allocate healthcare resources accordingly. This project provided a successful example of how an artificial intelligence (AI)-based model can be adopted to support clinical decision-making nationwide.

Assessment of the radial peripapillary capillary plexus and retinal nerve fiber layer thickness in diabetic patients in comparison to normal age-matched individuals

Background Diabetic retinopathy (DR) is a major complication of diabetes, leading to vision impairment and blindness worldwide. As early detection is crucial, our study investigated the potential of radial peripapillary capillary plexus (RPCP) and retinal nerve fiber layer (RNFL) thickness as biomarkers for retinal assessment in diabetic patients. Methods We conducted a cross-sectional study involving 48 participants, categorized into three groups: healthy controls, diabetic patients without DR (No DR), and patients with mild to moderate nonproliferative DR (NPDR). Vascular density (VD) and RNFL thickness were evaluated using optical coherence tomography (OCT), and OCT-Angiography (OCT-A). Results The study showed a significant difference in VD among the three groups. The mean whole image VD% in the control group was 51.28%, while the No DR and NPDR groups had mean percentages of 49.27% and 49.46%, respectively (P=0.015). These differences were also significant for peripapillary VD (P=0.003), superior-hemi VD (P=0.035), and inferior-hemi VD percentage (P=0.002). Conversely, there were no significant differences in RNFL thickness among the groups (P=0.138). In the NPDR group, positive correlations were found between RNFL thickness and VD percentages, including superior-hemi RNFL thickness and superior-hemi VD% (r=0.724, P&lt;0.001), average whole RNFL thickness and whole image VD% (r=0.655, P&lt;0.001), and average whole RNFL thickness and peripapillary VD% (r=0.647, P&lt;0.001). Conclusion This research emphasizes the value of assessment of retinal VD thickness of the radial peripapillary plexus as an early indicator for preclinical diabetic retinal changes in diabetic patients.

Early Diagnosis of Risks and Management of Cardiometabolic Diseases: A Case Study

The case study presented underscores the importance of early identification of metabolic risks, effective management, and lifestyle modifications in preventing clinical complications associated with cardiometabolic diseases (CMDs). The individual in the study, a South Asian immigrant, experienced the development of essential hypertension in his mid-50s, leading to left ventricular hypertrophy (LVH) and mild diastolic dysfunction. However, through proactive measures such as early diagnosis of metabolic risks, robust management of cardiovascular disease (CVD), adherence to a heart-healthy diet, and lifestyle changes, he was able to avoid major clinical complications of diabetes and maintain overall well-being until the age of 87. The key takeaways from this case study align with broader public health initiatives aimed at addressing the global epidemic of metabolic diseases. The multifaceted and intricate nature of this problem requires a comprehensive approach that considers various factors contributing to the rising prevalence of these diseases. Primary prevention strategies, which focus on identifying and mitigating risk factors for CMDs before the onset of vascular disease, play a crucial role in curbing the epidemic. The success observed in this case study, highlights the potential impact of proactive management and lifestyle interventions, in preventing and mitigating the progression of cardiometabolic diseases. It emphasizes the need for increased awareness, early screening, and ongoing monitoring of individuals at risk. Additionally, promoting heart-healthy diets and encouraging lifestyle modifications, such as regular physical activity and stress reduction, are essential components of a holistic approach to cardiometabolic health. Despite the positive outcomes demonstrated in this case, the article acknowledges that the global response to preventing both communicable and non-communicable diseases has been tepid, with varying levels of enthusiasm for developing primary prevention strategies across different nations. Addressing this challenge requires coordinated efforts at the individual, community, and policy levels to promote a culture of preventive healthcare. In conclusion, the findings of this case study contribute to the growing body of evidence supporting the efficacy of early diagnosis of metabolic risks, effective management, and lifestyle modifications in preventing clinical complications associated with cardiometabolic diseases. The lessons learned from individual cases can inform broader public health initiatives and underscore the importance of a proactive and comprehensive approach to address the escalating prevalence of metabolic diseases globally

The cGAS-STING pathway: a therapeutic target in diabetes and its complications.

Diabetic wound healing (DWH) represents a major complication of diabetes where inflammation is a key impediment to proper healing. The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway has emerged as a central mediator of inflammatory responses to cell stress and damage. However, the contribution of cGAS-STING activation to impaired healing in DWH remains understudied. In this review, we examine the evidence that cGAS-STING-driven inflammation is a critical factor underlying defective DWH. We summarize studies revealing upregulation of the cGAS-STING pathway in diabetic wounds and discuss how this exacerbates inflammation and senescence and disrupts cellular metabolism to block healing. Partial pharmaceutical inhibition of cGAS-STING has shown promise in damping inflammation and improving DWH in preclinical models. We highlight key knowledge gaps regarding cGAS-STING in DWH, including its relationships with endoplasmic reticulum stress and metal-ion signaling. Elucidating these mechanisms may unveil new therapeutic targets within the cGAS-STING pathway to improve healing outcomes in DWH. This review synthesizes current understanding of how cGAS-STING activation contributes to DWH pathology and proposes future research directions to exploit modulation of this pathway for therapeutic benefit.

RTA 408 ameliorates diabetic cardiomyopathy by activating Nrf2 to regulate mitochondrial fission and fusion and inhibiting NF-κB-mediated inflammation.

Diabetic cardiomyopathy (dCM) is a major complication of diabetes; however, specific treatments for dCM are currently lacking. RTA 408, a semisynthetic triterpenoid, has shown therapeutic potential against various diseases by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway. We established in vitro and in vivo models using high glucose toxicity and db/db mice, respectively, to simulate dCM. Our results demonstrated that RTA 408 activated Nrf2 and alleviated various dCM-related cardiac dysfunctions, both in vivo and in vitro. Additionally, it was found that silencing the Nrf2 gene eliminated the cardioprotective effect of RTA 408. RTA 408 ameliorated oxidative stress in dCM mice and high glucose-exposed H9C2 cells by activating Nrf2, inhibiting mitochondrial fission, exerting anti-inflammatory effects through the Nrf2/NF-κB axis, and ultimately suppressing apoptosis, thereby providing cardiac protection against dCM. These findings provide valuable insights for potential dCM treatments.NEW & NOTEWORTHY We demonstrated first that the nuclear factor erythroid 2-related factor 2 (Nrf2) activator RTA 408 has a protective effect against diabetic cardiomyopathy. We found that RTA 408 could stimulate the nuclear entry of Nrf2 protein, regulate the mitochondrial fission-fusion balance, and redistribute p65, which significantly alleviated the oxidative stress level in cardiomyocytes, thereby reducing apoptosis and inflammation, and protecting the systolic and diastolic functions of the heart.

National technical guidelines for the prevention and treatment of diabetic kidney disease in primary care (2023)

Diabetic kidney disease (DKD) is one of the major chronic complications of diabetes and is associated with a heavy disease burden. Since the release of the National Guidelines for the Prevention and Control of Diabetes in Primary Care (2018), there has been continuous improvement in the basic public health services and basic medical services of the primary care setting and an expansion of the scope of work. Therefore, more detailed technical guidelines for the prevention and management of diabetes and its complications in primary care are needed. This guide aims to promote the standardization of DKD prevention and control in primary care, to assist primary care physicians with the prevention and control of DKD, and to ensure the comprehensive management of patients with DKD. The contents include the basic requirements for the management, overview, screening, diagnosis and staging, treatment, follow-up, and referral of patients with DKD.