Numerical simulation of water free-surface flows through a front-tracking lattice Boltzmann approach

Three-dimensional (3D) hydraulic modelling of rapidly varying surface flows is a challenging task for practical engineering applications. One example is represented by the fast-moving fronts originating from dam breaches that proceed downstream through artificial channels. In this work, a fully 3D lattice Boltzmann method (LBM) is tested. The numerical model is a front-tracking variant of the LBM, being the free surface tracked through the liquid volume fraction. Model performances are evaluated simulating the effect of dam-break flows on synthetic settings schematically represented by an artificial domain and comparing results with analytical data and experimental laboratory measurements. Obtained results are promising for the use of LBM for practical engineering applications

CFD modelling approach for dam break flow studies

Abstract. This paper presents numerical simulations of free surface flows induced by a dam break comparing the shallow water approach to fully three-dimensional simulations. The latter are based on the solution of the complete set of Reynolds-Averaged Navier-Stokes (RANS) equations coupled to the Volume of Fluid (VOF) method. The methods assessment and comparison are carried out on a dam break over a flat bed without friction, a dam break over a triangular bottom sill and a dam break flow over a 90° bend. Experimental and numerical literature data are compared to present results. The results demonstrate that the shallow water approach, even if able to sufficiently reproduce the main aspects of the fluid flows, loses some three-dimensional phenomena, due to the incorrect shallow water idealization that neglects the three-dimensional aspects related to the gravity force

Flattening mountains: Micro-fabrication of planar replicas for bullet lateral striae analysis

The application of replica molding has proven to be a valuable tool in the analysis of different forensic evidences in particular for its ability to extract the toolmarks from complex sample surfaces. A well known problem in the analysis of ballistic evidences is the accurate characterization of the lateral striae of real bullets seized on crime scenes after shots, due primarily to impact deformations and to unpredictable issues related to laboratory illumination setup. To overcome these problems a possible way is to confine over a flat surface all the features still preserving their three dimensionality. This can be achieved by a novel application of replica molding performed onto the relevant lateral portion of the bullet surface. A quasi-two-dimensional negative copy of the original tridimensional indented surface has been thus fabricated. It combines the real tridimensional topography of class characteristics (land and groove impressions) and of individual caracteristics (striae) impressed by rifled barrels on projectiles, moreover with the possibility of quantitative characterization of these features in a planar configuration, that will allow one-shot comparison of the "whole striae landscape" without the typical artifacts arising from the bullet shape and the illumination issue. A detailed analysis has been carried on at the morphological level by standard optical and scanning electron microscopy, while the 3D topography has been characterized by white light optical profilometry. A quantitative characterization of toolmarks of bullets derived from ammunitions shot by guns of large diffusion, as the Beretta 98 FS cal. 9×21mm, has been performed and will be presented ranging between the whole landscape and the sub-μm resolution. To investigate the real potentiality of this technique, the experiment has been extended to highly impact-deformed projectiles

Sensory inflow manipulation induces learning-like phenomena in motor behavior

© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Purpose: Perceptual and goal-directed behaviors may be improved by repetitive sensory stimulations without practice-based training. Focal muscle vibration (f-MV) modulating the spatiotemporal properties of proprioceptive inflow is well-suited to investigate the effectiveness of sensory stimulation in influencing motor outcomes. Thus, in this study, we verified whether optimized f-MV stimulation patterns might affect motor control of upper limb movements. Methods: To answer this question, we vibrated the slightly tonically contracted anterior deltoid (AD), posterior deltoid (PD), and pectoralis major muscles in different combinations in forty healthy subjects at a frequency of 100 Hz for 10 min in single or repetitive administrations. We evaluated the vibration effect immediately after f-MV application on upper limb targeted movements tasks, and one week later. We assessed target accuracy, movement mean and peak speed, and normalized Jerk using a 3D optoelectronic motion capture system. Besides, we evaluated AD and PD activity during the tasks using wireless electromyography. Results: We found that f-MV may induce increases (p \u3c 0.05) in movement accuracy, mean speed and smoothness, and changes (p \u3c 0.05) in the electromyographic activity. The main effects of f-MV occurred overtime after repetitive vibration of the AD and PD muscles. Conclusion: Thus, in healthy subjects, optimized f-MV stimulation patterns might over time affect the motor control of the upper limb movement. This finding implies that f-MV may improve the individual’s ability to produce expected motor outcomes and suggests that it may be used to boost motor skills and learning during training and to support functional recovery in rehabilitation

Information Storage Using Supramolecular Surface Patterns

Non

Diagnostic value of cerebrospinal fluid alpha-synuclein seed quantification in synucleinopathies

Several studies have confirmed α-synuclein real-time quaking-induced conversion (αSyn-RT-QuIC) assay to have high sensitivity and specificity for Parkinson's disease. However, whether the assay can be used as a robust, quantitative measure to monitor disease progression, stratify different synucleinopathies and predict disease conversion in patients with idiopathic REM sleep behaviour disorder remains undetermined. The aim of this study was to assess the diagnostic value of CSF aSyn-RT-QuIC quantitative parameters in regard to disease progression, stratification, and conversion in synucleinopathies. We performed αSyn-RT-QuIC in the CSF samples from 74 Parkinson's disease, 24 multiple system atrophy and 45 idiopathic REM sleep behaviour disorder patients alongside 55 healthy controls, analysing quantitative assay parameters in relation to clinical data. αSyn-RT-QuIC showed 89% sensitivity and 96% specificity for Parkinson's disease. There was no correlation between RT-QuIC quantitative parameters and Parkinson's disease clinical scores (e.g. UPDRS motor) but RT-QuIC positivity and some quantitative parameters (e.g. Vmax) differed across the different phenotype clusters. RT-QuIC parameters also added value alongside standard clinical data in diagnosing Parkinson's disease. The sensitivity in multiple system atrophy was 75%, and CSF samples showed longer T50 and lower Vmax compared to Parkinson's disease. All RT-QuIC parameters correlated with worse clinical progression of multiple system atrophy (e.g. change in UMSARS). The overall sensitivity in idiopathic REM sleep behaviour disorder was 64%. In three of the four longitudinally followed idiopathic REM sleep behaviour disorder cohorts, we found around 90% sensitivity, but in one sample (DeNoPa) diagnosing idiopathic REM sleep behaviour disorder earlier from the community cases, this was much lower 39%. During follow-up, 14 of 45 (31%) idiopathic REM sleep behaviour disorder patients converted to synucleinopathy with 9/14 (64%) of convertors showing baseline RT-QuIC positivity. In summary, our results showed that αSyn-RT-QuIC adds value in diagnosing Parkinson's disease and may provide a way to distinguish variations within Parkinson's disease phenotype. The quantitative parameters however did not correlate with disease severity in Parkinson's disease. The assay distinguished multiple system atrophy patients from Parkinson's disease patients and in contrast to Parkinson's disease, the quantitative parameters correlated with disease progression of multiple system atrophy. Our results also provided further evidence for αSyn-RT-QuIC having potential as an early biomarker detecting synucleinopathy in idiopathic REM sleep behaviour disorder patients prior to conversion. Further analysis of longitudinally followed idiopathic REM sleep behaviour disorder patients is needed to better understand the relationship between αSyn-RT-QuIC signature and the progression from prodromal to different synucleinopathies

Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects

Rapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention

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

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

: The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways