The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) in healthcare is transforming chronic disease management and pandemic response, particularly for vulnerable populations such as the elderly and those with multiple chronic conditions. This review systematically examines the current applications of AI and IoT technologies in managing chronic diseases like diabetes, cardiovascular disease, and chronic obstructive pulmonary disease (COPD), alongside their role in enhancing healthcare response during the COVID-19 pandemic. Key findings demonstrate significant improvements in patient outcomes, including enhanced glycemic control in diabetes management, early detection of cardiovascular anomalies, and a reduction in hospital admissions for chronic disease patients through AI-enabled remote monitoring. Despite these advancements, challenges remain, including data security, algorithmic bias, and the high cost of implementing AI and IoT systems. This review explores future directions for overcoming these obstacles, emphasizing the potential of multi-dimensional data integration, real-time predictive analytics, and personalized AI models to further revolutionize healthcare. Additionally, the accompanying Graphic Abstract visually illustrates how AI-driven insights, generated from IoT-enabled devices, are transforming healthcare delivery by facilitating real-time monitoring, personalized interventions, and proactive patient care. The article concludes with recommendations for addressing the technological, ethical, and regulatory challenges that must be overcome to fully realize the potential of AI and IoT in healthcare.

Stem cells can be used to treat diabetic mellitus and complications. ω3-docosahexaenoic acid (DHA) derived lipid mediators are inflammation-resolving and protective. This study found novel DHA-derived 7S,14R-dihydroxy-4Z,8E,10Z,12E,16Z,19Z-docosahexaenoic acid (7S,14R-diHDHA), a maresin-1 stereoisomer biosynthesized by leukocytes and related enzymes. Moreover, 7S,14R-diHDHA can enhance mesenchymal stem cell (MSC) functions in the amelioration of diabetic mellitus and retinal pericyte loss in diabetic db/db mice. MSCs treated with 7S,14R-diHDHA were delivered into db/db mice i.v. every 5 days for 35 days. Blood glucose levels in diabetic mice were lowered by 7S,14R-diHDHA-treated MSCs compared to control and untreated MSC groups, accompanied by improved glucose tolerance and higher blood insulin levels. 7S,14R-diHDHA-treated MSCs increased insulin+ β-cell ratio and decreased glucogan+ α-cell ratio in islets, as well as reduced macrophages in pancreas. 7S,14R-diHDHA induced MSC functions in promoting MIN6 β-cell viability and insulin secretion. 7S,14R-diHDHA induced MSC paracrine functions by increasing the generation of hepatocyte growth factor and vascular endothelial growth factor. Furthermore, 7S,14R-diHDHA enhanced MSC functions to ameliorate diabetes-caused pericyte loss in diabetic retinopathy by increasing their density in retina in db/db mice. Our findings provide a novel strategy for improving therapy for diabetes and diabetic retinopathy using 7S,14R-diHDHA-primed MSCs.

Background: Cardiovascular comparisons between glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and Sodium-glucose co-transporter-2 (SGLT-2) inhibitors in type 2 diabetes(T2D) remain an area of interest. Thus, the purpose of this meta-analysis is to compare the impact of these two drug classes on major CV outcomes, such as heart failure hospitalization(HHF), major adverse cardiovascular events (MACE), CV mortality, myocardial infarction, stroke, and all-cause mortality, with an emphasis on heart failure hospitalizations. Methods: PubMed (including MEDLINE), Google Scholar, Cochrane Central Library, PLOSONE, and Science Direct databases were searched for studies that compared GLP-1 RAs and SGLT-2 inhibitors in patients with type 2 diabetes. Six cohort studies were selected for the analysis. Odds ratios (OR) with 95% CI were calculated and a random-effects model was used to estimate the hazard ratios (HR) of the studies. The quality of the studies was evaluated using the Newcastle-Ottawa Scale (NOS), and publication bias was assessed using funnel plots and Egger’s test. Results: Pooled analysis demonstrated a significant reduction in heart failure hospitalizations with SGLT-2 inhibitors compared to GLP-1 RAs (HR: 0.78 [0.62–0.98], I² = 87%, p < 0.01). Cardiovascular mortality was also significantly reduced by SGLT-2 inhibitors (HR: 0.74 [0.31–1.67], I² = 87%, p < 0.01), and a modest reduction was observed for all-cause mortality (HR: 0.85 [0.44–1.64], I² = 17%, p = 0.27). While SGLT-2 inhibitors appeared to slightly reduce the risk of myocardial infarction (HR: 0.83 [0.74–0.92], I² = 0%, p = 0.85), no significant difference was observed for MACE (HR: 0.91 [0.82–1.01], I² = 0%, p = 0.70) or stroke (HR: 0.88 [0.77–1.00], I² = 0%, p = 0.85). Conclusions: Compared to GLP-1 receptor agonists, SGLT-2 inhibitors were more effective in lowering heart failure hospitalizations and cardiovascular mortality in patients with type 2 diabetes. It was also found that all-cause mortality and myocardial infarction were moderately reduced using oral agents. However, the differences were not significant for MACE or stroke. These results imply that SGLT-2 inhibitors may potentially provide better cardiovascular benefits, especially with respect to heart failure and cardiovascular mortality, than GLP-1 RA. Further research should be conducted to determine the effects of the long-term use of these therapies on stroke and other cardiovascular events.

Glycosylation, a prevalent post-translational modification, plays a pivotal role in regulating intricate cellular processes by covalently attaching glycans to macromolecules. Dysregulated glycosylation is linked to a spectrum of diseases, encompassing cancer, neurodegenerative disorders, congenital disorders, infections, and inflammation. This review delves into the intricate interplay between glycosylation and protein conformation, with a specific focus on the profound impact of N-glycans on the selection of distinct protein conformations, characterized by distinct interactomes – namely protein assemblies - under normal and pathological conditions across various diseases. We begin by examining the spike protein of the SARS virus, illustrating how N-glycans regulate the infectivity of pathogenic agents. Subsequently, we utilize the prion protein and the chaperone glucose-regulated protein 94 as examples, exploring instances where N-glycosylation transforms physiological protein structures into disease-associated forms. Unraveling these connections provides valuable insights into potential therapeutic avenues and a deeper comprehension of the molecular intricacies that underlie disease conditions. This exploration of glycosylation's influence on protein conformation effectively bridges the gap between the glycome and disease, offering a comprehensive perspective on the therapeutic implications of targeting conformational mutants and their pathologic assemblies in various diseases. The goal is to unravel the nuances of these post-translational modifications, shedding light on how they contribute to the intricate interplay between protein conformation, assembly and disease.

Abstract: This review addresses the complexities of type 1 diabetes (T1D)and its associated complications, with a par-ticular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of the review is devoted to technological advances in diabetes management, particu-larly the use of Hybrid Closed Loop systems (HCLS) and to the potential of open-source HCLS systems, which could be easily adapted to different patiens’needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.