Artificial intelligence powered glucose monitoring and controlling system: Pumping module

Double Diabetes: A Converging Metabolic and Autoimmune Disorder Redefining the Classification and Management of Diabetes

This review explores the pathophysiology, clinical implications, and management of double diabetes. The increasing prevalence of obesity, sedentary lifestyles, and genetic predisposition has blurred the difference between type 1 and type 2 diabetes, leading to diagnostic and therapeutic challenges. Double diabetes presents with overlapping symptoms from both diabetes types, making accurate diagnosis crucial. Biomarkers, such as C-peptide levels, autoantibody testing, and insulin resistance markers, help differentiate double diabetes from classic diabetes subtypes. Early intervention is necessary because of the condition's elevated risk of microvascular and macrovascular consequences, such as retinopathy, nephropathy, and cardiovascular disease. Effective management integrates pharmacological and lifestyle approaches. Metformin, sodium-glucose cotransporter 2 (SGLT2) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, and insulin therapy adjustments all boost glycemic control and metabolic results. Additionally, structured exercise, dietary modifications, and weight management are essential for reducing insulin resistance and preserving beta-cell activity. The potential of precision medicine, artificial intelligence (AI)-driven healthcare, and continuous glucose monitoring (CGM) offers promising advancements for personalized treatment strategies. Future research should focus on targeted immunotherapies, genetic profiling, and refined clinical guidelines to improve early detection and individualized treatment, with long-term outcomes. The review emphasizes the need for a multidisciplinary approach in managing double diabetes, ensuring early diagnosis, optimized treatment, and improved metabolic health to mitigate long-term complications.

The role of pharmacy in promoting public health: Pharmacy and public health in 2050

From 2000 to 2025, the profession of pharmacy expanded into vaccinations, point-of-care testing, and chronic disease prevention and management. In the next 25 years, pharmacy will continue to advance in new ways. This paper focuses on expanded roles of community and ambulatory care pharmacy to more directly improve public health. Built around the ten essential services of public health, this paper calls upon the profession of pharmacy to stretch beyond traditional roles to assume roles that would strengthen the public health workforce and make seminal contributions to improved population health. Barriers to be overcome in pursuit of that future are also addressed. The paper will conclude with a public health-focused call to pharmacy.

Need for an Artificial Intelligence-based Diabetes Care Management System in India and the United States

Objective

Diabetes mellitus is an important chronic disease that is prevalent around the world. Different countries and diverse cultures use varying approaches to dealing with this chronic condition. Also, with the advancement of computation and automated decision-making, many tools and technologies are now available to patients suffering from this disease. In this work, the investigators attempt to analyze approaches taken towards managing this illness in India and the United States.

Methods

In this work, the investigators have used available literature and data to compare the use of artificial intelligence in diabetes management.

Findings

The article provides key insights to comparison of diabetes management in terms of the nature of the healthcare system, availability, electronic health records, cultural factors, data privacy, affordability, and other important variables. Interestingly, variables such as quality of electronic health records, and cultural factors are key impediments in implementing an efficiency-driven management system for dealing with this chronic disease.

Conclusion

The article adds to the body of knowledge associated with the management of this disease, establishing a critical need for using artificial intelligence in diabetes care management.