The rapid scientific interest in gut microbiota (GM) has coincided with a global increase in the prevalence of infectious and non-infectivous liver diseases. GM, which is also called “the new virtual metabolic organ”, makes axis with a number of extraintestinal organs, such as kidneys, brain, cardiovascular, and the bone system. The gut-liver axis has attracted greater attention in recent years. GM communication is bi-directional and involves endocrine and immunological mechanisms. In this way, gut-dysbiosis and composition of “ancient” microbiota could be linked to pathogenesis of numerous chronic liver diseases such as chronic hepatitis B (CHB), chronic hepatitis C (CHC), alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), development of liver cirrhosis, and hepatocellular carcinoma (HCC). In this paper, we discuss the current evidence supporting a GM role in the management of different chronic liver diseases and potential new therapeutic GM targets, like fecal transplantation, antibiotics, probiotics, prebiotics, and symbiotics. We conclude that population-level shifts in GM could play a regulatory role in the gut-liver axis and, consequently, etiopathogenesis of chronic liver diseases. This could have a positive impact on future therapeutic strategies.

Hospital-acquired infections (HAIs) are a global public health concern. As the COVID-19 pandemic continues, its contribution to mortality and antimicrobial resistance (AMR) grows, particularly in intensive care units (ICUs). A two-year retrospective study from April 2019–April 2021 was conducted in an adult ICU at the Hospital for Infectious and Tropical Diseases, Belgrade, Serbia to assess causative agents of HAIs and AMR rates, with the COVID-19 pandemic ensuing halfway through the study. Resistance rates >80% were observed for the majority of tested antimicrobials. In COVID-19 patients, Acinetobacter spp. was the dominant cause of HAIs and more frequently isolated than in non-COVID-19 patients. (67 vs. 18, p = 0.001). Also, resistance was higher for imipenem (56.8% vs. 24.5%, p < 0.001), meropenem (61.1% vs. 24.3%, p < 0.001) and ciprofloxacin (59.5% vs. 36.9%, p = 0.04). AMR rates were aggregated with findings from our previous study to identify resistance trends and establish empiric treatment recommendations. The increased presence of Acinetobacter spp. and a positive trend in Klebsiella spp. resistance to fluoroquinolones (R2 = 0.980, p = 0.01) and carbapenems (R2 = 0.963, p = 0.02) could have contributed to alarming resistance rates across bloodstream infections (BSIs), pneumonia (PN), and urinary tract infections (UTIs). Exceptions were vancomycin (16.0%) and linezolid (2.6%) in BSIs; tigecycline (14.3%) and colistin (0%) in PNs; and colistin (12.0%) and linezolid (0%) in UTIs. COVID-19 has changed the landscape of HAIs in our ICUs. Approval of new drugs and rigorous surveillance is urgently needed.

Changes in gut microbiota influence both the gut and liver, which are strictly connected by the so-called “gut–liver axis”. The gut microbiota acts as a major determinant of this relationship in the onset and clinical course of liver diseases. According to the results of several studies, gut dysbiosis is linked to viral hepatitis, mainly hepatitis C virus and hepatitis B virus infection. Gut bacteria-derived metabolites and cellular components are key molecules that affect liver function and modulate the pathology of viral hepatitis. Recent studies showed that the gut microbiota produces various molecules, such as peptidoglycans, lipopolysaccharides, DNA, lipoteichoic acid, indole-derivatives, bile acids, and trimethylamine, which are translocated to the liver and interact with liver immune cells causing pathological effects. Therefore, the existence of crosstalk between the gut microbiota and the liver and its implications on host health and pathologic status are essential factors impacting the etiology and therapeutic approach. Concrete mechanisms behind the pathogenic role of gut-derived components on the pathogenesis of viral hepatitis remain unclear and not understood. In this review, we discuss the current findings of research on the bidirectional relationship of the components of gut microbiota and the progression of liver diseases and viral hepatitis and vice versa . Moreover, this paper highlights the current therapeutic and preventive strategies, such as fecal transplantation, used to restore the gut microbiota composition and so improve host health.

Purpose The purpose of this study is to determine heart rate (HR) recovery after maximal test in elite athletes who compete in high dynamic, high static, and in mixed sport disciplines; to assess differences in HR recovery between these groups of athletes; and to measure the association of HR index (HRI) with heart adaptation variables to determine whether these values were correlated with the type of exercise. Methods One hundred and ninety-four elite athletes were divided into three groups according to the predominant type of exercise performed: endurance (n = 40), strength-sprinter (n = 36), and ball-game players (n = 118). They performed maximal cardiopulmonary exercise testing on a treadmill and were subjected to echocardiography. The rate of decline (HR recovery) was calculated as the difference between maximum and recovery HRs (HRrec1 and HRrec3). The HRI was calculated as HRmax – 1-min post-exercise HR (HRrec1). Results The most significant correlation of HRI was with posterior wall diameter and left ventricular (LV) mass index (r = 0.43 and r = 0.51; p = 0.012 and p = 0.003, respectively). LV mass index [Beta (B) = 0.354, p = 0.001] was an independent predictor of HRI and HRrec1. HRI may be an effective tool for discrimination of physiological and “gray zone” LV hypertrophy, with area under the curve of 0.545 (95% CI = 0.421–0.669, p = 0.0432). HRI displayed a sensitivity of 50% and specificity of 52.2% at the optimal cut-off value of 23.5. Conclusion HR recovery pattern, especially HRI, may offer a timely and efficient tool to identify athletes with autonomous nervous system adaptive changes.