Introduction: The growing prevalence of Type 2 Diabetes (T2D) places a significant burden on health care systems in Low- and Middle-Income Countries (LMICs) due to resource limitations. Better understanding of health care team perspectives regarding the barriers and facilitators in these settings will help develop sustainable, evidence-informed improvements that are necessary to meet the increasing need for diabetes care. Methods: This study explored the perceptions of providers, support staff, and administration of a regional diabetes clinic in the Dominican Republic that sees approximately 70 patients per week. Semi-structured interviews were conducted with all eleven clinic employees. Inductive thematic analysis was conducted to determine emergent themes. Results: Five interrelated themes emerged: 1) Moral orientation towards patient care; 2) Resource scarcity; 3) Time and educational constraints; 4) Outdated equipment and systems; 5) Limitations in infrastructure accessibility. Participants consistently stated that they see their job as more of a calling and must take on additional responsibilities to help provide the quality care the patients require. Constrained clinic resources and infrastructure led to significant inefficiencies, and the lack of a diabetes educator limited medical provider capacity. Discussion: These findings suggest that healthcare team resilience helps sustain diabetes care under resource constraints, but reliance on individual adaptations may threaten long-term sustainability in the absence of system-level investment. Conclusion: Targeted, low-cost improvements, low-burden programming, and structured patient education may strengthen long-term diabetes care delivery in LMIC clinics.
Introduction/Objective: Diabetes mellitus is characterized by persistent hyperglycemia and progressive β-cell dysfunction. GLP-1 receptor agonists improve glycemic control and weight management, with cardiovascular and renal benefits reported in some patients, while DPP-4 inhibitors generally have more modest effects. Limitations such as peptide instability, administration challenges, tolerability, cost, and long-term treatment burden have encouraged the development of advanced drug-delivery and regenerative strategies. Methods: This narrative review evaluates the molecular mechanisms of GLP-1 and DPP-4 signaling and the therapeutic potential of emerging approaches for diabetes management. The literature was reviewed with particular emphasis on nanotechnology-based drug-delivery systems, geneand mRNA-based therapies, and cell-based strategies for incretin therapy, β-cell preservation, and regeneration. Evidence regarding therapeutic efficacy, delivery-system characteristics, development status, advantages and limitations, and barriers to clinical translation was critically examined to provide an integrated overview of current advances and future opportunities. Results: GLP-1 signaling and DPP-4 inhibition improve glucose-dependent insulin secretion while supporting β-cell survival and function. Nanotechnology-based delivery systems show potential to improve peptide stability, bioavailability, controlled release, and tissue targeting, although most approaches remain at the preclinical stage. Gene, mRNA, and cell-based approaches have shown β-cell regeneration or preservation in animal models; however, clinically meaningful endogenous β-cell regeneration has not yet been established in humans. Key barriers to clinical translation include long-term biosafety, immunogenicity, manufacturing scalability and reproducibility, regulatory requirements, cost, and clinical implementation. Discussion: Combining cutting-edge delivery technologies with well-established incretin pharmacology may help overcome some of the drawbacks of conventional treatments. However, nano-delivery, gene, mRNA, and regeneration techniques are still in preclinical or early research stages; they should be clearly distinguished from clinically proven treatments. To determine their longterm efficacy, safety, and clinical value, more validation in well-organized clinical trials is needed. Conclusion: GLP-1 receptor agonists and DPP-4 inhibitors remain established components of incretin- based therapy, while advanced nanotechnology-based delivery systems offer promising opportunities but are largely supported by preclinical evidence. Future research should highlight the combination of precision medicine, pharmacogenomics, artificial intelligence-assisted treatment, and optimized drug-delivery systems to improve therapeutic efficacy and patient-specific outcomes. Smart glucose-responsive nanocarriers may further allow controlled, targeted, and adaptive drug release, supporting the development of more precise incretin-based therapies.
Gliflozin derivatives, a class of Sodium-Glucose Cotransporter (SGLT) inhibitors, have emerged as effective antidiabetic agents offering notable cardiovascular and renal protection. This class of compounds inhibits glucose reabsorption in the kidneys, thereby improving overall glycaemic control. This review provides a comprehensive overview of gliflozin derivatives, emphasizing their chemical characterization, safety, therapeutic efficacy, pharmacokinetic analysis, and potential future applications, focusing on clinical trials and new developments released between 2010 and 2026. Gliflozin derivatives slow the progression of chronic kidney disease and reduce the risk of heart failure. Some preliminary experimental evidence has reported the antibacterial activity of canagliflozin against MRSA. The Gliflozin derivatives dapagliflozin (IC50 =1.1nM), ertugliflozin (IC50 =0.9nM), sotagliflozin (IC50 =1.8nM), and bexagliflozin (IC50 =2.3nM), which has core motif, 1-chloro-2-(4-alkoxy benzyl) benzene as an aglycon unit and a glycon unit bind with SGLT2 receptor and lowered the HbA1c by 1.2%, 1.7%, 0.41% and 0.80%, respectively. Its selectivity, pharmacokinetics, and toxicity profiles are also optimal. Recent studies have demonstrated their involvement in conditions other than diabetes, including obesity, non-alcoholic fatty liver disease, Cardioprotective, Nephroprotective, Anti-inflammatory, and antihypertensive effects. Gliflozin derivatives represent a paradigm shift in the management of diabetes and have broad therapeutic potential. Future studies should emphasize creative structural changes to increase safety and efficacy.
Diabetes mellitus is one of the world’s leading health problems, and standard approaches to therapy do not take into consideration the impact of circadian misalignment on metabolic health. Chronobiological processes are involved in regulating glucose homeostasis, insulin release, hepatic glucose production, lipids, and energy metabolism; hence, disruptions such as those caused by non-rhythmic sleep patterns, shifts at work, irregular meal times, and light exposure could cause insulin resistance and even type 2 diabetes. The current critical review discusses the light-melatonin interaction and personalized chronobiological medicine. Instead of giving a descriptive account of particular treatments, the paper introduces the integrative importance of chronobiology for the management of diabetes by considering data about chrononutrition, time-restricted feeding, chronopharmacology, chrono-exercise, and an approach to chronometabolism based on the integration of the timing of meals, drugs, exercise, sleep, and light exposure with chronotype, metabolic phenotype, and the feasibility of the therapy. Circadian timing can be a promising adjuvant in the treatment of diabetes; however, the available evidence does not suggest an ideal time for intervention. Further studies should focus on measuring time, well-powered randomized controlled trials, long-term outcomes, and individualization of chronotherapy.
Abstract: Diabetes mellitus is a global health issue with escalating metabolic dysfunction, clinical heterogeneity, and rising microvascular and macrovascular consequences. Traditional diabetes diagnosis, risk assessment, treatment selection, and complication surveillance rely on periodic clinical measures and population-level risk models, which may not fully capture dynamic, individualized disease pathways. Precision diabetes treatment is being transformed by Artificial intelligence (AI), including machine learning (ML), deep learning (DL), and multimodal data analytics. This review critically examines AI-driven approaches to diabetes management, including early disease prediction, diagnostic support, glycemic monitoring, treatment-response prediction, and the prevention and detection of diabetes-associated complications. The US Food and Drug Administration (USFDA) has sanctioned multiple AI/ML-based medical devices for automated retinal screening, clinical diagnostic assistance, and patient self-management applications. For clinically meaningful patterns and disease progression prediction, AI-enabled analysis of continuous glucose monitoring data, retinal images, electronic health records, wearable device signals, laboratory parameters, and multi-omics datasets is prioritized. The use of AI for detecting diabetic retinopathy, kidney disease, cardiovascular disease, neuropathy, and foot disorders is also highlighted.Data quality, algorithmic bias, interpretability, privacy, cybersecurity, model drift, regulatory monitoring, clinical validation, and equitable access prevent widespread application despite promising results. This study offers a thorough and critical assessment of the developing roles of AI, specifically ML and DL, in the prediction, diagnosis, and management of diabetes and its related complications. Real-world validation, standardized evaluation frameworks, trustworthy AI, and effective human- AI collaboration will drive advancement. AI could transform diabetes management into predictive, tailored, continuous, and complication-preventive care.
