Oxidative Stress and Low-Grade Inflammation in Polycystic Ovary Syndrome: Controversies and New Insights

The pathophysiology of Polycystic Ovary Syndrome (PCOS) is quite complex and different mechanisms could contribute to hyperandrogenism and anovulation, which are the main features of the syndrome. Obesity and insulin-resistance are claimed as the principal factors contributing to the clinical presentation; in normal weight PCOS either, increased visceral adipose tissue has been described. However, their role is still debated, as debated are the biochemical markers linked to obesity per se. Oxidative stress (OS) and low-grade inflammation (LGI) have recently been a matter of researcher attention; they can influence each other in a reciprocal vicious cycle. In this review, we summarize the main mechanism of radical generation and the link with LGI. Furthermore, we discuss papers in favor or against the role of obesity as the first pathogenetic factor, and show how OS itself, on the contrary, can induce obesity and insulin resistance; in particular, the role of GH-IGF-1 axis is highlighted. Finally, the possible consequences on vitamin D synthesis and activation on the immune system are briefly discussed. This review intends to underline the key role of oxidative stress and low-grade inflammation in the physiopathology of PCOS, they can cause or worsen obesity, insulin-resistance, vitamin D deficiency, and immune dyscrasia, suggesting an inverse interaction to what is usually considered.     

Regulatory Noncoding and Predicted Pathogenic Coding Variants of CCR5 Predispose to Severe COVID-19

Genome-wide association studies (GWAS) found locus 3p21.31 associated with severe COVID-19. CCR5 resides at the same locus and, given its known biological role in other infection diseases, we investigated if common noncoding and rare coding variants, affecting CCR5, can predispose to severe COVID-19. We combined single nucleotide polymorphisms (SNPs) that met the suggestive significance level (P ≤ 1 × 10⁻⁵) at the 3p21.31 locus in public GWAS datasets (6406 COVID-19 hospitalized patients and 902,088 controls) with gene expression data from 208 lung tissues, Hi-C, and Chip-seq data. Through whole exome sequencing (WES), we explored rare coding variants in 147 severe COVID-19 patients. We identified three SNPs (rs9845542, rs12639314, and rs35951367) associated with severe COVID-19 whose risk alleles correlated with low CCR5 expression in lung tissues. The rs35951367 resided in a CTFC binding site that interacts with CCR5 gene in lung tissues and was confirmed to be associated with severe COVID-19 in two independent datasets. We also identified a rare coding variant (rs34418657) associated with the risk of developing severe COVID-19. Our results suggest a biological role of CCR5 in the progression of COVID-19 as common and rare genetic variants can increase the risk of developing severe COVID-19 by affecting the functions of CCR5.     

Modeling and biological investigations of an unusual behavior of novel synthesized acridine-based polyamine ligands in the binding of double helix and G-quadruplex DNA

Three novel 2,7-substituted acridine derivatives were designed and synthesized to investigate the effect of this functionalization on their interaction with double-stranded and G-quadruplex DNA. Detailed investigations of their ability to bind both forms of DNA were carried out by using spectrophotometric, electrophoretic, and computational approaches. The ligands in this study are characterized by an open-chain (L1) or a macrocyclic (L2, L3) framework. The aliphatic amine groups in the macrocycles are joined by ethylene (L2) or propylene chains (L3). L1 behaved similarly to the lead compound m-AMSA, efficiently intercalating into dsDNA, but stabilizing G-quadruplex structures poorly, probably due to the modest stabilization effect exerted by its protonated polyamine chains. L2 and L3, containing small polyamine macrocyclic frameworks, are known to adopt a rather bent and rigid conformation; thus they are generally expected to be sterically impeded from recognizing dsDNA according to an intercalative binding mode. This was confirmed to be true for L3. Nevertheless, we show that L2 can give rise to efficient π-π and H-bonding interactions with dsDNA. Additionally, stacking interactions allowed L2 to stabilize the G-quadruplex structure: using the human telomeric sequence, we observed the preferential induction of tetrameric G-quadruplex forms. Thus, the presence of short ethylene spacers seems to be essential for obtaining a correct match between the binding sites of L2 and the nucleobases on both DNA forms investigated. Furthermore, current modeling methodologies, including docking and MD simulations and free energy calculations, provide structural evidence of an interaction mode for L2 that is different from that of L3; this could explain the unusual stabilizing ability of the ligands (L2>L3>L1) toward G-quadruplex that was observed in this study.     

Scouring at Bed Sills as a Response to Flash Floods

The temporal development of clear-water local scour depth at bed sills in uniform gravel beds is considered. Experiments are presented on the development of scour holes under unsteady hydraulic conditions, with the triangular-shaped hydrographs tested being of different durations and different rates of flow variation. Based on the experimental results and a theoretical framework, a method is given for the definition and prediction of the scouring process under unsteady flows in terms of a dimensionless temporal parameter. A “flash flood” is here defined as an event for which the scour doesn’t attain its potential magnitude, i.e., the equilibrium value for the peak hydrograph flow rate. This flood nature is dependent on both the characteristics of the flood event itself and the characteristics of the stream. A quantitative measure of what constitutes a flash flood is given in terms of the identified temporal parameter. Results show that the ratio between the final scour depth and the potential scour depth at a bed sill for a given hydrograph can be estimated as a function of the identified temporal parameter.     

A speed sensorless control based on a MRAS applied to a double fed induction machine drive

This paper proposes a new MRAS method to estimate the mechanical quantities in a double fed induction machine. In the traditional formulation the integral term, introduced by the PI MRAS regulator, is canceled in the transfer function between the estimated and the real speed. As a novelty, an additional term depending on the reference rotor flux through a constant gain g is introduced in the adjustable model of the MRAS. This innovation restores the integral term in the transfer function. As a consequence, during the closed loop operation, the estimated speed does not exhibit anymore a steady state error. The influence of the inverter non-linearities and of the non-linear rotor brush resistance on the speed estimation is also discussed. Some experimental tests validate the proposed method.     

Nuclear reactor dynamics on-line estimation by Locally Recurrent Neural Networks

In this paper, the Causal Recursive Back-Propagation (CRBP) algorithm is employed to train on-line an Infinite Impulse Response–Locally Recurrent Neural Network (IIR–LRNN) for modelling the dynamics of a next-generation nuclear reactor. The results demonstrate the advantages of the on-line training over the batch-mode learning in the reconstruction of complex nonlinear dynamic relationships.