Search results for "CoV"

showing 10 items of 9749 documents

Clinical Characteristics and Outcomes of Patients with COVID-19 Infection: The Results of the SARS-RAS Study of the Italian Society of Hypertension

2021

: The COVID-19 infection has rapidly spread around the world and a second wave is sweeping in many countries. Different clinical and epidemiological aspects characterize the disease and their understanding is necessary to better face the management of the pandemic in progress. The Italian society of arterial hypertension with the SARS-RAS study has contributed significantly to the knowledge of the interaction between inhibition of the renin-angiotensin system and COVID-19 infection. Furthermore, the study results help to understand some of the main aspects related to mortality and morbidity deriving from the infection through a multicentre analysis throughout the national territory.

0301 basic medicineSettore MED/09 - Medicina InternaCross-sectional studyDiseaseComorbiditySeverity of Illness IndexComorbiditiesRenin-Angiotensin System0302 clinical medicineRisk FactorsSex-differences.EpidemiologyPandemicFrailtySars-Cov2Treatment OutcomeItalyAnti-hypertensive therapy; comorbidities; frailty; Sars-Cov2; sex-differencesHypertensionComorbiditiePosition PaperRisk assessmentCardiology and Cardiovascular Medicinemedicine.medical_specialtySex-differenceRisk Assessment03 medical and health sciencesPharmacotherapySex FactorsSeverity of illnessmedicineAnti-hypertensive therapy Sars-Cov2 Frailty Comorbidities Sex-differencesInternal MedicineHumansArterial PressureAnti-hypertensive therapy Comorbidities Frailty Sars-Cov2 Sex-differencesIntensive care medicineAnti-hypertensive therapyAntihypertensive AgentsAnti-hypertensive therapy; Comorbidities; Frailty; Sars-Cov2; Sex-differences; Antihypertensive Agents; Arterial Pressure; COVID-19; Comorbidity; Cross-Sectional Studies; Frailty; Humans; Hypertension; Italy; Renin-Angiotensin System; Risk Assessment; Risk Factors; Severity of Illness Index; Sex Factors; Treatment OutcomeSettore MED/14 - Nefrologiabusiness.industryCOVID-19medicine.diseaseComorbiditySex-differences030104 developmental biologyCross-Sectional Studiesbusiness030217 neurology & neurosurgery
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Antibodies Responses to SARS-CoV-2 in a Large Cohort of Vaccinated Subjects and Seropositive Patients

2021

COVID-19 is a current global threat, and the characterization of antibody response is vitally important to update vaccine development and strategies. In this study we assessed SARS-CoV-2 antibody concentrations in SARS-CoV-2 positive patients (N = 272) and subjects vaccinated with the BNT162b2 m-RNA COVID-19 vaccine (N = 1256). For each participant, socio-demographic data, COVID-19 vaccination records, serological analyses, and SARS-CoV-2 infection status were collected. IgG antibodies against S1/S2 antigens of SARS-CoV-2 were detected. Almost all vaccinated subjects (99.8%) showed a seropositivity to anti-SARS-COV-2 IgG and more than 80% of vaccinated subjects had IgG concentrations &gt

0301 basic medicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)virusesImmunologyArticleSerologyPersistence (computer science)03 medical and health sciences0302 clinical medicineAntigenDrug DiscoveryMedicinePharmacology (medical)030212 general & internal medicineskin and connective tissue diseasesPharmacologyantibody concentrations.biologybusiness.industryImmunogenicitySARS-CoV-2 infectionfungiRantibody concentrationsrespiratory tract diseasesVaccinationbody regions030104 developmental biologyInfectious DiseasesImmunizationImmunologybiology.proteinMedicineAntibodybusinessCOVID-19 vaccineVaccines
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Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.

2021

Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2′-o-ribose methyltransferase). Supported by…

0301 basic medicineSimeprevirArtificial intelligencevirusesMERS Middle East Respiratory SyndromeHealth InformaticsBiologyMachine learningcomputer.software_genremedicine.disease_causeAntiviral AgentsArticleWHO World Health OrganizationAUC area under the curve03 medical and health sciences0302 clinical medicinessRNA single-stranded RNA virusmedicineChemotherapyHumansSARS severe acute respiratory syndromeCOVID-19 coronavirus disease 2019CoronavirusNatural productsVirtual screeningACE2 angiotensin converting enzyme 2Drug discoverybusiness.industrySARS-CoV-2COVID-19LBE lowest binding energyFDA Food and Drug AdministrationROC receiver operating characteristicComputer Science ApplicationsHIV human immunodeficiency virusMolecular Docking SimulationDrug repositioning030104 developmental biologyDrug developmentSevere acute respiratory syndrome-related coronavirusParitaprevirInfectious diseasesRespiratory virusArtificial intelligenceSupervised Machine Learningbusinesscomputer030217 neurology & neurosurgeryComputers in biology and medicine
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P/CAF-mediated spermidine acetylation regulates histone acetyltransferase activity

2016

Histones and polyamines are important determinants of the chromatin structure. Histones form the core of nucleosome particles and their modification by acetylation of N-terminal tails is involved in chromatin structural changes and transcriptional regulation. Polyamines, including spermidine, are also targets of both cytoplasmic and nuclear acetylation, which in turn alters their affinity for DNA and nucleosomes. Previous studies report the interplay between polyamines metabolism and levels of histone acetylation, but the molecular basis of this effect is still unclear. In this work, we have analyzed the in vitro effect of spermidine on histone H3 acetylation catalyzed by P/CAF, a highly co…

0301 basic medicineSpermidine acetylationSpermidineSAP30BiologyHistones03 medical and health sciences0302 clinical medicineHistone H1Drug DiscoveryHistone H2AAnimalsHistone acetyltransferase activityp300-CBP Transcription FactorsHistone octamerHistone H3 acetylationHistone AcetyltransferasesPolytene ChromosomesPharmacologyAcetylationGeneral MedicineHistone acetyltransferaseEnzyme ActivationKineticsDrosophila melanogaster030104 developmental biologyBiochemistry030220 oncology & carcinogenesisbiology.proteinJournal of Enzyme Inhibition and Medicinal Chemistry
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Targeting Bacterial Sortase A with Covalent Inhibitors: 27 New Starting Points for Structure-Based Hit-to-Lead Optimization.

2019

Because of its essential role as a bacterial virulence factor, enzyme sortase A (SrtA) has become an attractive target for the development of new antivirulence drugs against Gram-positive infections. Here we describe 27 compounds identified as covalent inhibitors of

0301 basic medicineStaphylococcus aureusMagnetic Resonance SpectroscopyAntivirulenceVirulence Factors030106 microbiologySmall Molecule Libraries03 medical and health sciencesMiceBacterial ProteinsCatalytic DomainDrug DiscoveryAnimalschemistry.chemical_classificationBinding SitesChemistryHit to leadFibroblastsAminoacyltransferasesAnti-Bacterial AgentsMolecular Docking SimulationCysteine Endopeptidases030104 developmental biologyInfectious DiseasesEnzymeBiochemistryCovalent bondSortase ABacterial virulenceNIH 3T3 CellsStructure basedACS infectious diseases
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Synthesis and biofilm formation reduction of pyrazole-4-carboxamide derivatives in some Staphylococcus aureus strains

2016

The ability of several N-phenyl-1H-pyrazole-4-carboxamide derivatives and other pyrazoles opportunely modified at the positions 3, 4 and 5, to reduce the formation of the biofilm in some Staphylococcus aureus strains (ATCC 29213, ATCC 25923 and ATCC 6538) were investigated. All the tested compounds were able, although to a different extent, to reduce the biofilm formation of the three bacterial strains considered. Among these, the 1-(2,5-dichlorophenyl)-5-methyl-N-phenyl-1H-pyrazole-4-carboxamide 14 resulted as the best inhibitor of biofilm formation showing an IC50 ranging from 2.3 to 32 μM, against all the three strains of S. aureus. Compound 14 also shows a good protective effect in vivo…

0301 basic medicineStaphylococcus aureusmedicine.drug_class030106 microbiologyCarboxamideMothsN-phenyl-1H-pyrazole-4-carboxamidePyrazoleSettore BIO/19 - Microbiologia Generalemedicine.disease_cause01 natural sciencesMicrobiologyStructure-Activity Relationship03 medical and health scienceschemistry.chemical_compoundDrug DiscoveryInhibition of biofilm formationmedicineAnimalsIC50PharmacologyWaxVirulencebiology010405 organic chemistryDrug Discovery3003 Pharmaceutical ScienceAnti-virulenceOrganic ChemistryBiofilmS. aureuGeneral MedicineStaphylococcal Infectionsbiology.organism_classificationSettore CHIM/08 - Chimica FarmaceuticaAnti-Bacterial Agents0104 chemical sciencesGalleria mellonellaHydrazinesSettore AGR/11 - Entomologia Generale E ApplicatachemistryStaphylococcus aureusBiofilmsLarvavisual_artWax moth larva modelvisual_art.visual_art_mediumPyrazolesLead compoundEuropean Journal of Medicinal Chemistry
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Stagewise pseudo-value regression for time-varying effects on the cumulative incidence

2015

In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event s…

0301 basic medicineStatistics and ProbabilityCarcinoma HepatocellularTime FactorsEpidemiologyComputer scienceFeature selectionBiostatistics01 natural sciences010104 statistics & probability03 medical and health sciencesRisk FactorsStatisticsCovariateEconometricsHumansComputer SimulationCumulative incidenceRegistries0101 mathematicsEvent (probability theory)Models StatisticalIncidenceLiver NeoplasmsAbsolute risk reductionRegression analysisRegression030104 developmental biologyRegression AnalysisJackknife resamplingAlgorithmsStatistics in Medicine
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Prioritizing covariates in the planning of future studies in the meta-analytic framework

2016

Science can be seen as a sequential process where each new study augments evidence to the existing knowledge. To have the best prospects to make an impact in this process, a new study should be designed optimally taking into account the previous studies and other prior information. We propose a formal approach for the covariate prioritization, i.e., the decision about the covariates to be measured in a new study. The decision criteria can be based on conditional power, change of the p-value, change in lower confidence limit, Kullback-Leibler divergence, Bayes factors, Bayesian false discovery rate or difference between prior and posterior expectation. The criteria can be also used for decis…

0301 basic medicineStatistics and ProbabilityFalse discovery rateComputer scienceBayesian probabilityBayes factorGeneral MedicineMultiple-criteria decision analysis01 natural sciencesConfidence interval010104 statistics & probability03 medical and health sciences030104 developmental biologySample size determinationCovariateEconometrics0101 mathematicsStatistics Probability and UncertaintyDivergence (statistics)Biometrical Journal
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Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI-TOF mass spectrometry.

2017

International audience; Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology and use this approach for protein quantification by a classical signal processing algori…

0301 basic medicineStatistics and ProbabilityMALDI-TOFexperimental designBiometryprotein quantificationQuantitative proteomicsVariance component analysis[ CHIM ] Chemical Sciences01 natural sciencesSignaltechnological variability010104 statistics & probability03 medical and health sciencesstatistical analysis[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[CHIM.ANAL]Chemical Sciences/Analytical chemistryComponent (UML)[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]biomarker discoverysum of squares type0101 mathematicsBiomarker discoverysignal processingMathematicsSignal processingAnalysis of Variance[ PHYS ] Physics [physics]Noise (signal processing)ProteinsGeneral MedicineVariance (accounting)[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]030104 developmental biologySpectrometry Mass Matrix-Assisted Laser Desorption-IonizationLinear Modelsvariance components[ CHIM.ANAL ] Chemical Sciences/Analytical chemistryStatistics Probability and UncertaintyBiological systemAlgorithmsBiomarkersBiometrical journal. Biometrische Zeitschrift
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A heuristic, iterative algorithm for change-point detection in abrupt change models

2017

Change-point detection in abrupt change models is a very challenging research topic in many fields of both methodological and applied Statistics. Due to strong irregularities, discontinuity and non-smootheness, likelihood based procedures are awkward; for instance, usual optimization methods do not work, and grid search algorithms represent the most used approach for estimation. In this paper a heuristic, iterative algorithm for approximate maximum likelihood estimation is introduced for change-point detection in piecewise constant regression models. The algorithm is based on iterative fitting of simple linear models, and appears to extend easily to more general frameworks, such as models i…

0301 basic medicineStatistics and ProbabilityMathematical optimizationIterative methodHeuristic (computer science)Linear model01 natural sciencesPiecewise constant model Approximate maximum likelihood Model linearization Grid search limitations010104 statistics & probability03 medical and health sciencesComputational MathematicsDiscontinuity (linguistics)030104 developmental biologyHyperparameter optimizationCovariatePiecewise0101 mathematicsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaChange detectionMathematics
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