In recent years, the worldwide epidemic of metabolic diseases, namely obesity, metabolic syndrome, diabetes and metabolic-associated fatty liver disease (MAFLD) has been strongly associated with constant exposure to endocrine-disruptive chemicals (EDCs), in particular, the ones able to disrupt various metabolic pathways. EDCs have a negative impact on several human tissues/systems, including metabolically active organs, such as the liver and pancreas. Among their deleterious effects, EDCs induce mitochondrial dysfunction and oxidative stress, which are also the major pathophysiological mechanisms underlying metabolic diseases. In this narrative review, we delve into the current literature on EDC toxicity effects on the liver and pancreatic tissues in terms of impaired mitochondrial function and redox homeostasis.

Sodium–glucose cotransporter 2 inhibitors (SGLT2i), a novel class of glucose-lowering drugs, have revolutionized the management of heart failure with reduced and preserved ejection fraction, regardless of the presence of diabetes, and are currently incorporated in the heart failure guidelines. While these drugs have consistently demonstrated their ability to decrease heart failure hospitalizations in several landmark clinical trials, their cardioprotective effects are far from having been completely elucidated. In the past decade, a growing body of experimental research has sought to address the molecular and cellular mechanisms of SGLT2i in order to provide a better understanding of the off-target acute and chronic cardiac benefits, beyond the on-target renal effect responsible for blood glucose reduction. The present narrative review addresses the direct cardioprotective effects of SGLT2i, delving into the off-target mechanisms of the drugs currently approved for heart failure therapy, and provides insights into future perspectives.

Introduction: Diabetes mellitus (DM) has a millennia-long history, with early references dating back to ancient Egypt and India. However, it was not until the 20th century that the connection between diabetes and insulin was fully understood. The sequencing of insulin in the 1950s initiated the convergence of biotechnology and diabetes management, leading to the development of recombinant human insulin in 1982. This marked the start of peptide-based therapies in DM. Recombinant peptides for DM treatment: Numerous recombinant peptides have been developed since, starting with modified insulin molecules, with the aim of bettering DM management through fine-tuning the glycemic response to insulin. Peptide-based therapies in DM have expanded substantially beyond insulin to include agonists of Glucagon-like peptide-1 receptor and Glucose-dependent insulinotropic polypeptide receptor, glucagon receptor antagonists, and even peptides exerting multiple receptor agonist effects, for better metabolic control. Insulin pumps, continuous glucose monitoring, and automated insulin delivery systems: The development of modern delivery systems combined with real-time glucose monitoring has significantly advanced diabetes care. Insulin pumps evolved from early large devices to modern sensor-augmented pumps with automated shutoff features and hybrid closed-loop systems, requiring minimal user input. The second-generation systems have demonstrated superior outcomes, proving highly effective in diabetes management. Islet cell transplantation, organoids, and biological pancreas augmentation represent innovative approaches to diabetes management. Islet cell transplantation aims to restore insulin production by transplanting donor beta cells, though challenges persist regarding graft survival and the need for immunosuppression. Organoids are a promising platform for generating insulin-producing cells, although far from clinical use. Biological pancreas augmentation relies on therapies that promote beta-cell (re)generation, reduce stress, and induce immune tolerance. Further biotechnology-driven perspectives in DM will include metabolic control via biotechnology-enabled tools such as custom-designed insulin hybrid molecules, machine-learning algorithms to control peptide release, and engineering cells for optimal peptide production and secretion.