Bi-Directional Interactions between Glucose-Lowering Medications and Gut Microbiome in Patients with Type 2 Diabetes Mellitus: A Systematic Review.

Background: Although common drugs for treating type 2 diabetes (T2D) are widely used, their therapeutic effects vary greatly. The interaction between the gut microbiome and glucose-lowering drugs is one of the main contributors to the variability in T2D progression and response to therapy. On the one hand, glucose-lowering drugs can alter gut microbiome components. On the other hand, specific gut microbiota can influence glycemic control as the therapeutic effects of these drugs. Therefore, this systematic review assesses the bi-directional relationships between common glucose-lowering drugs and gut microbiome profiles. Methods: A systematic search of Embase, Web of Science, PubMed, and Google Scholar databases was performed. Observational studies and randomised controlled trials (RCTs), published from inception to July 2023, comprising T2D patients and investigating bi-directional interactions between glucose-lowering drugs and gut microbiome, were included. Results: Summarised findings indicated that glucose-lowering drugs could increase metabolic-healthy promoting taxa (e.g., Bifidobacterium) and decrease harmful taxa (e.g., Bacteroides and Intestinibacter). Our findings also showed a significantly different abundance of gut microbiome taxa (e.g., Enterococcus faecium (i.e., E. faecium)) in T2D patients with poor compared to optimal glycemic control. Conclusions: This review provides evidence for glucose-lowering drug and gut microbiome interactions, highlighting the potential of gut microbiome modulators as co-adjuvants for T2D treatment.

Computing the electrical activity of the heart with a dynamic inverse monodomain operator.

The inverse problem in electrocardiography is to reconstruct the voltage in the surface of the heart, using a high density electrocardiogram. This problem is usually solved using regularization techniques, which tend to give the minimum energy response in a static scheme. In our work, we propose to calculate a dynamic inverse solution using the Monodomain as a model of electrical heart activity, thus constraining the family of solutions to one that satisfies the model.