Glycemic homeostasis is an essential mechanism for the proper working of an organism. However, balance in blood lipid and protein levels also plays an important role. The discovery of the hormone insulin and the description of its function for glycemic control made fundamental scientific progress in this field. However, since then our view of the problem has been deeply influenced only in terms of glucose and insulin (in an insulin-centric and glucose-centric way). Based on recent scientific discoveries, a fine and sophisticated network of hormonal and metabolic interactions, involving almost every apparatus and tissue of the human body, has been theorized. Efficient metabolic homeostasis is founded on these intricate interactions. Although it is still not fully defined, this complex network can undergo alterations that lead to metabolic disorders such as diabetes mellitus (DM). The endocrine pancreas plays a crucial role in the metabolic balance of an organism, but insulin is just one of the elements involved and each single pancreatic islet hormone is worthy of our concern. Moreover, pancreatic hormones need to be considered in a general view, concerning both their systemic function as direct mediators and as hormones, which, in turn, are regulated by other hormones or other substances. This more complex scenario should be taken into account for a better understanding of the pathophysiology and the therapeutic algorithms of DM. As a consequence, improvements in modern medicine could help to contemplate this new perspective. This review is focused on some aspects of gut-pancreas interaction, aiming to integrate this synergy into a wider context involving other organs and tissues.

This commentary is the product of a concerted effort to understand the needs, barriers, and gaps in the field of speech and language biomarkers for Alzheimer’s disease (AD). It distills interviews, surveys, and extensive correspondence with global leaders in the areas of dementia research, clinical trials, linguistics, and data analytics into an idealized clinical-study design for the harmonized collection of voice recordings. The ultimate goal of the effort is to democratize the ongoing speech and language analytics efforts by making such rich datasets available to the wider research ecosystem.