Bacterial metabolites of human gut microbiota correlating with depression

Depression is a global threat to mental health that affects around 264 million people worldwide. Despite the considerable evolution in our understanding of the pathophysiology of depression, no reliable biomarkers that have contributed to objective diagnoses and clinical therapy currently exist. The discovery of the microbiota-gut-brain axis induced scientists to study the role of gut microbiota (GM) in the pathogenesis of depression. Over the last decade, many of studies were conducted in this field. The productions of metabolites and compounds with neuroactive and immunomodulatory properties among mechanisms such as the mediating effects of the GM on the brain, have been identified. This comprehensive review was focused on low molecular weight compounds implicated in depression as potential products of the GM. The other possible mechanisms of GM involvement in depression were presented, as well as changes in the composition of the microbiota of patients with depression. In conclusion, the therapeutic potential of functional foods and psychobiotics in relieving depression were considered. The described biomarkers associated with GM could potentially enhance the diagnostic criteria for depressive disorders in clinical practice and represent a potential future diagnostic tool based on metagenomic technologies for assessing the development of depressive disorders. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Modeling of the atomic ordering processes in Fe3Al intermetallics by the monte carlo simulation method combined with electronic theory of alloys

The evolution of atomic ordering processes in Fe3Al has been modeled by the Monte Carlo (MC) simulation method combined with the electronic theory of alloys in pseudopotential approximation. The magnitude of atomic ordering energies of atomic pairs in the Fe3Al system has been calculated by means of electronic theory in pseudopotential approximation up to sixth coordination spheres and subsequently used as input data for MC simulation for more detailed analysis for the first time. The Bragg–Williams long-range order (LRO) and Cowley–Warren short-range order (SRO) parameters have been calculated from the equilibrium configurations attained at the end of MC simulation for each predefined temperature and Al concentration levels, which reveal the evolution of the system from DO3 → B2 → disordered state as temperature increases. The variation of ordering parameters with temperature has identified the transition temperature from DO3 → B2 type superlattice, and from B2 → disordered (a) solid solution at about 540 °C and .900 °C, respectively, showing good qualitative agreement with experimental results. The results of the present study imply that combination of electronic theory of alloys in pseudopotential approximation with MC simulation can be successfully applied for qualitative or semiquantitative analysis of energetical and structural characteristics of atomic ordering processes in Fe3Al intermetallics