Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive endoscopy included. The detection rate of preneoplastic lesions (i.e., polyps) during colonoscopy may be increased with artificial intelligence assistance. It has also proven useful in detecting signs of ulcerative colitis activity. In upper digestive endoscopy, deep learning models may prove to be useful in the diagnosis and management of upper digestive tract diseases, such as gastroesophageal reflux disease, Barrett’s esophagus, and gastric cancer. As is the case with all new medical devices, there are challenges in the implementation in daily medical practice. The regulatory, economic, organizational culture, and language barriers between humans and machines are a few of them. Even so, many devices have been approved for use by their respective regulators. Future studies are currently striving to develop deep learning models that can replicate a growing amount of human brain activity. In conclusion, artificial intelligence may become an indispensable tool in digestive endoscopy.
Globally, metabolic diseases such as obesity, type 2 diabetes mellitus and non-alcoholic fatty liver disease pose a major public health threat. Many studies have confirmed the causal relationship between risk factors and the etiopathogenesis of these diseases. Despite this, traditional therapeutic management methods such as physical education and diet have proven insufficient. Recently, researchers have focused on other potential pathways for explaining the pathophysiological variability of metabolic diseases, such as the involvement of the intestinal microbiota. An understanding of the relationship between the microbiome and metabolic diseases is a first step towards developing future therapeutic strategies. Currently, much attention is given to the use of biotics family members such as prebiotics (lactolose, soy oligosaccharides, galactooligosaccharides, xylooligosaccharides or inulin) and probiotics (genera Lactobacillus, Bifidobacterium, Lactococcus, Streptococcus or Enterococcus). They can be used both separately and together as synbiotics. Due to their direct influence on the composition of the intestinal microbiota, they have shown favorable results in the evolution of metabolic diseases. The expansion of the research area in the biotics family has led to the discovery of new members, like postbiotics. In the age of personalized medicine, their use as therapeutic options is of great interest to our study.
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