Magnesium orotate has been cited in the medical literature for the past three years as a possible adjuvant in some pediatric and adult gastroenterological disorders associated with dysbiosis. Studies also focus on the possibility of adding magnesium orotate in psychiatric disorders’ treatment, such as major depression and anxiety. The most relevant element in these studies is the efficiency of magnesium orotate therapy in cases with both gastroenterological and psychiatric symptoms. This article proposes a literature review, focused on the studies published in the last three years, targeting magnesium orotate treatment and probiotic supplementation in patients with both digestive and psychiatric symptoms. Moreover, this review will compare the efficiency of magnesium orotate and probiotics within both the pediatric and adult communities, focusing on the possibility of gut–brain axis modulation and its involvement in the clinical evolution of these patients.

The altered magnesium status in inflammatory bowel disease (IBD) patients may have a significant clinical imprint considering its role in cell signaling and genomic stability, as well as its involvement in IBD patients’ fatigue. Our study pioneers the investigation of magnesium hair concentration patterns in an adult population of IBD patients. The hair magnesium concentration in IBD patients is compared to healthy controls in order to identify correlations between the magnesium status and relevant parameters related to disease activity, psychological status, and sleep quality. We report a significantly lower hair magnesium concentration within the IBD group compared to healthy controls (95%CI: 0.006–0.062; p = 0.017) and lower levels in CD compared to UC (95%CI: −0.061–−0.002; p = 0.038). We identified a borderline statistical significance between the hair magnesium concentration and UC disease activity (95%CI; −0.679–0.008; p = 0.055) and a significantly lower magnesium concentration in patients who reported increased sleep latency (95%CI −0.65–−0.102; p = 0.011) or decreased sleep duration (95%CI −0.613–−0.041; p = 0.028). Our results advance several hypotheses with substantial clinical impact to be confirmed in future studies. Magnesium levels appear to be modified in IBD patients, which suggests it either plays a primary role in disease pathophysiology or a is result of the disease’s evolution. Magnesium could be used in predictive models for clinical/subclinical disease activity. Moreover, magnesium supplementation may improve IBD evolution and sleep quality for patients with a deficit of this mineral. However, confirmatory evidence-based studies are needed to generate specific dosing, time of supplementation, and optimum monitoring of magnesium status in IBD patients.

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.

Irritable bowel syndrome (IBS) has a global prevalence of around 4.1% and is associated with a low quality of life and increased healthcare costs. Current guidelines recommend that IBS is diagnosed using the symptom-based Rome IV criteria. Despite this, when patients seek medical attention, they are usually over-investigated. This issue might be resolved by novel technologies in medicine, such as the use of Artificial Intelligence (AI). In this context, this paper aims to review AI applications in IBS. AI in colonoscopy proved to be useful in organic lesion detection and diagnosis and in objectively assessing the quality of the procedure. Only a recently published study talked about the potential of AI-colonoscopy in IBS. AI was also used to study biofilm characteristics in the large bowel and establish a potential relationship with IBS. Moreover, an AI algorithm was developed in order to correlate specific bowel sounds with IBS. In addition to that, AI-based smartphone applications have been developed to facilitate the monitoring of IBS symptoms. From a therapeutic standpoint, an AI system was created to recommend specific diets based on an individual’s microbiota. In conclusion, future IBS diagnosis and treatment may benefit from AI.

The assessment of fibrosis in chronic liver diseases using non-invasive methods is an important topic in hepatology. The aim of this study is to identify patients with non-alcoholic fatty liver disease (NAFLD) and advanced liver fibrosis by establishing correlations between biological/ultrasound markers and non-invasively measured liver stiffness. This study enrolled 116 patients with non-alcoholic fatty liver disease, which were evaluated clinically, biologically, and by ultrasound. Liver fibrosis was quantified by measuring liver stiffness by shear wave elastography (SWE). Multiple correlation analysis of predictors of liver fibrosis identified a number of clinical, biological, and ultrasound parameters (BMI, blood glucose, albumin, platelet count, portal vein diameter, bipolar spleen diameter) that are associated with advanced liver fibrosis in patients with non-alcoholic fatty liver disease. The correlations between the degree of liver fibrosis and the risk values of some serological and ultrasound markers obtained in our study could be useful in clinical practice for the identification of advanced fibrosis in patients with NAFLD.

The progression of liver fibrosis and the presence of portal hypertension are two key points in the follow-up and severity assessment of patients with chronic liver disease. Objective evaluation of such aspects has proven to be difficult due to the lack of reproducible and standardized non-invasive methods. Therefore, the aim of this study was to evaluate whether spleen stiffness (SS) can rule out the presence of high-risk varices (HRVs) in patients with non-alcoholic fatty liver disease (NAFLD). We designed a prospective follow-up of a cohort of 48 consecutive patients diagnosed with compensated advanced chronic liver disease (cACLD) due to NAFLD, between January 2020 and January 2021. After clinical evaluation, laboratory testing, ultrasonography (US), and shear-wave elastography (2D-SWE.GE) of both the liver and the spleen, patients were endoscopically screened for esophageal varices, gastric varices, and portal hypertensive gastropathy. Correlations and predictors were assessed. After univariate, multivariate, and predictive analyses, SS could be referred to as an independent predictor for high-risk varices (AUROC 0.987, p < 0.001, OR 4.985, 95% CI: 1.57–15.73, p = 0.006), with a calculated cutoff value of 17.95 kPa. These results are consistent with those of other, similar studies using both 2D-SWE.GE and a similar module (2D-SWE.SSI) in patients with metabolic liver disease. When confirmed by subsequent larger studies, SS could potentially become a useful non-invasive tool in the assessment of clinically significant portal hypertension in patients with advanced fatty liver disease.