In the intestine, gut distension and nutrients are detected by mechanoreceptors and chemoreceptors, respectively. The activation of these receptors sends an afferent nervous message to the hypothalamus in the brain. In turn, the hypothalamus controls the glucose entry in tissues, and thus glycemia.
The discovery of intestinal actors, such as enterosynes, able to modulate the ENS-induced duodenal contraction is an innovative approach. Among all the intestinal factors, the understanding of the role of gut microbes in controlling glycaemia remains a major target. For instance, we researched and demonstrated how the modulation of gut microbiota by prebiotics could permit the identification of novel enterosynes.
Targeting the enteric nervous system that controls gut motility is now considered as an innovative therapeutic way in T2D to limit intestinal glucose absorption and restore the gut‐brain axis to improve insulin sensitivity. So far, little is known about the role of glucose on duodenal contraction in fasted and fed states in normal and diabetic conditions.
Currently, the gut is considered a primary site for the development of pathologies that modify brain functions such as neurodegenerative (Parkinson’s, Alzheimer’s, etc.) and metabolic (type 2 diabetes, obesity, etc.) disorders. Deciphering the mode of interaction between microbiota and the brain is a real original option to prevent (and maybe treat in the future) the establishment of gut-brain disfunctions and associated pathologies.
The Amazonian forests are home to a shrub, the camu-camu, whose fruit could be of great help in the fight against obesity and metabolic diseases. This is described in our latest study published with the A-Mansia R&D team in the journal Metabolites.
The enteric nervous system (ENS) plays a key role in controlling the gut-brain axis under normal and pathological conditions, such as type 2 diabetes. The discovery of intestinal actors, such as enterosynes, able to modulate the ENS-induced duodenal contraction is considered a pioneering approach.