[Patterns of experienced and anticipated discrimination in patients with schizophremia. Italian results from the INDIGO international multisite project]

To describe patterns of experienced and anticipated discrimination in a sample of schizophrenic patients recruited in Italy in the context of the International Study of Discrimination and Stigma Outcomes (INDIGO)

Visual field loss and vision-related quality of life in the Italian Primary Open Angle Glaucoma Study

The aim of this study was to examine the relationship between visual field (VF) loss, vision-related quality of life (QoL) and glaucoma-related symptoms in a large cohort of primary open angle glaucoma (POAG) patients. POAG patients with or without VF defects or "glaucoma suspect" patients were considered eligible. QoL was assessed using the validated versions of the 25-item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) and glaucoma-related symptoms were assessed using the Glaucoma Symptom Scale (GSS). Patients were classified as having VF damage in one eye (VFD-1), both eyes (VFD-2), or neither eye (VFD-0). 3227 patients were enrolled and 2940 were eligible for the analysis. 13.4% of patients were classified in the VFD-0, 23.7% in the VFD-1, and 62.9% in the VFD-2 group. GSS visual symptoms domain (Func-4) and GSS non-visual symptoms domain (Symp-6) scores were similar for the VFD-0 and VFD-1 groups (p = 0.133 and p = 0.834 for Func-4 and Symp-6, respectively). VFD-0 group had higher scores than VFD-2 both in Func-4 (p < 0.001) and Symp-6 domains (p = 0.035). Regarding the NEI-VFQ-25, our data demonstrated that bilateral VF defects are associated with vision-related QoL deterioration, irrespective of visual acuity

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

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CFD study on electrolyte distribution in redox flow batteries

The most important component in a redox flow battery (RFB) cell is the MEA (membrane electrode assembly), a sandwich consisting of two catalyzed electrodes with an interposed polymeric membrane. In order to allow electrolyte flow toward the electroactive sites, the electrodes have a porous structure that can be obtained with carbon base materials such as carbon felts. The RFB cell is closed by two plates containing the distribution flow channels. Considering that a uniform electrolyte distribution in the reaction region is a prerequisite for high-efficiency operation, the flow pattern is an important parameter to be investigated for the optimization of the cell. In the present work, the effect of different channels patterns on the electrolyte distribution and on the pressure drop is numerically investigated. Three-dimensional simulations have been carried out with ANSYS Fluent code and four different layouts have been considered. Calculations have been performed both in the distribution channels and in the felt porous region