91 research outputs found

    Closing the loop of SIEM analysis to Secure Critical Infrastructures

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    Critical Infrastructure Protection is one of the main challenges of last years. Security Information and Event Management (SIEM) systems are widely used for coping with this challenge. However, they currently present several limitations that have to be overcome. In this paper we propose an enhanced SIEM system in which we have introduced novel components to i) enable multiple layer data analysis; ii) resolve conflicts among security policies, and discover unauthorized data paths in such a way to be able to reconfigure network devices. Furthermore, the system is enriched by a Resilient Event Storage that ensures integrity and unforgeability of events stored.Comment: EDCC-2014, BIG4CIP-2014, Security Information and Event Management, Decision Support System, Hydroelectric Da

    Evidence of Polygenic Adaptation to High Altitude from Tibetan and Sherpa Genomes

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    Although Tibetans and Sherpa present several physiological adjustments evolved to cope with selective pressures imposed by the high-altitude environment, especially hypobaric hypoxia, few selective sweeps at a limited number of hypoxia related genes were confirmed by multiple genomic studies. Nevertheless, variants at these loci were found to be associated only with downregulation of the erythropoietic cascade, which represents an indirect aspect of the considered adaptive phenotype. Accordingly, the genetic basis of Tibetan/Sherpa adaptive traits remains to be fully elucidated, in part due to limitations of selection scans implemented so far and mostly relying on the hard sweep model.In order to overcome this issue, we used whole-genome sequence data and several selection statistics as input for gene network analyses aimed at testing for the occurrence of polygenic adaptation in these high-altitude Himalayan populations. Being able to detect also subtle genomic signatures ascribable to weak positive selection at multiple genes of the same functional subnetwork, this approach allowed us to infer adaptive evolution at loci individually showing small effect sizes, but belonging to highly interconnected biological pathways overall involved in angiogenetic processes.Therefore, these findings pinpointed a series of selective events neglected so far, which likely contributed to the augmented tissue blood perfusion observed in Tibetans and Sherpa, thus uncovering the genetic determinants of a key biological mechanism that underlies their adaptation to high altitude

    Complex interplay between neutral and adaptive evolution shaped differential genomic background and disease susceptibility along the Italian peninsula

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    The Italian peninsula has long represented a natural hub for human migrations across the Mediterranean area, being involved in several prehistoric and historical population movements. Coupled with a patchy environmental landscape entailing different ecological/cultural selective pressures, this might have produced peculiar patterns of population structure and local adaptations responsible for heterogeneous genomic background of present-day Italians. To disentangle this complex scenario, genome-wide data from 780 Italian individuals were generated and set into the context of European/Mediterranean genomic diversity by comparison with genotypes from 50 populations. To maximize possibility of pinpointing functional genomic regions that have played adaptive roles during Italian natural history, our survey included also ∼250,000 exomic markers and ∼20,000 coding/regulatory variants with well-established clinical relevance. This enabled fine-grained dissection of Italian population structure through the identification of clusters of genetically homogeneous provinces and of genomic regions underlying their local adaptations. Description of such patterns disclosed crucial implications for understanding differential susceptibility to some inflammatory/autoimmune disorders, coronary artery disease and type 2 diabetes of diverse Italian subpopulations, suggesting the evolutionary causes that made some of them particularly exposed to the metabolic and immune challenges imposed by dietary and lifestyle shifts that involved western societies in the last centuries

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

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    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

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    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

    Role of prenatal magnetic resonance imaging in fetuses with isolated mild or moderate ventriculomegaly in the era of neurosonography: international multicenter study

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    Objectives To assess the role of fetal magnetic resonance imaging (MRI) in detecting associated anomalies in fetuses presenting with mild or moderate isolated ventriculomegaly (VM) undergoing multiplanar ultrasound evaluation of the fetal brain. Methods This was a multicenter, retrospective, cohort study involving 15 referral fetal medicine centers in Italy, the UK and Spain. Inclusion criteria were fetuses affected by isolated mild (ventricular atrial diameter, 10.0–11.9 mm) or moderate (ventricular atrial diameter, 12.0–14.9 mm) VM on ultrasound, defined as VM with normal karyotype and no other additional central nervous system (CNS) or extra‐CNS anomalies on ultrasound, undergoing detailed assessment of the fetal brain using a multiplanar approach as suggested by the International Society of Ultrasound in Obstetrics and Gynecology guidelines for the fetal neurosonogram, followed by fetal MRI. The primary outcome of the study was to report the incidence of additional CNS anomalies detected exclusively on prenatal MRI and missed on ultrasound, while the secondary aim was to estimate the incidence of additional anomalies detected exclusively after birth and missed on prenatal imaging (ultrasound and MRI). Subgroup analysis according to gestational age at MRI (< 24 vs ≥ 24 weeks), laterality of VM (unilateral vs bilateral) and severity of dilatation (mild vs moderate VM) were also performed. Results Five hundred and fifty‐six fetuses with a prenatal diagnosis of isolated mild or moderate VM on ultrasound were included in the analysis. Additional structural anomalies were detected on prenatal MRI and missed on ultrasound in 5.4% (95% CI, 3.8–7.6%) of cases. When considering the type of anomaly, supratentorial intracranial hemorrhage was detected on MRI in 26.7% of fetuses, while polymicrogyria and lissencephaly were detected in 20.0% and 13.3% of cases, respectively. Hypoplasia of the corpus callosum was detected on MRI in 6.7% of cases, while dysgenesis was detected in 3.3%. Fetuses with an associated anomaly detected only on MRI were more likely to have moderate than mild VM (60.0% vs 17.7%; P < 0.001), while there was no significant difference in the proportion of cases with bilateral VM between the two groups (P = 0.2). Logistic regression analysis showed that lower maternal body mass index (adjusted odds ratio (aOR), 0.85 (95% CI, 0.7–0.99); P = 0.030), the presence of moderate VM (aOR, 5.8 (95% CI, 2.6–13.4); P < 0.001) and gestational age at MRI ≥ 24 weeks (aOR, 4.1 (95% CI, 1.1–15.3); P = 0.038) were associated independently with the probability of detecting an associated anomaly on MRI. Associated anomalies were detected exclusively at birth and missed on prenatal imaging in 3.8% of cases. Conclusions The incidence of an associated fetal anomaly missed on ultrasound and detected only on fetal MRI in fetuses with isolated mild or moderate VM undergoing neurosonography is lower than that reported previously. The large majority of these anomalies are difficult to detect on ultrasound. The findings from this study support the practice of MRI assessment in every fetus with a prenatal diagnosis of VM, although parents can be reassured of the low risk of an associated anomaly when VM is isolated on neurosonography

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

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    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

    Genetic mechanisms of critical illness in COVID-19.

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    Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

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

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