Search results for "cover"
showing 10 items of 5959 documents
Discovering discriminative graph patterns from gene expression data
2016
We consider the problem of mining gene expression data in order to single out interesting features characterizing healthy/unhealthy samples of an input dataset. We present an approach based on a network model of the input gene expression data, where there is a labelled graph for each sample. To the best of our knowledge, this is the first attempt to build a different graph for each sample and, then, to have a database of graphs for representing a sample set. Our main goal is that of singling out interesting differences between healthy and unhealthy samples, through the extraction of "discriminative patterns" among graphs belonging to the two different sample sets. Differently from the other…
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 >
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…
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…
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
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…
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…
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…
Metal Ions and Metal Complexes in Alzheimer's Disease.
2015
Background: Alzheimer’s disease (AD) is the most common form of dementia that seriously affects daily life. Even if AD pathogenesis is still subject of debate, it is generally accepted that cerebral cortex plaques formed by aggregated amyloid-β (Aβ) peptides can be considered a characteristic pathological hallmark. It is well known that metal ions play an important role in the aggregation process of Aβ. Methods: This review focuses on the anti-Aβ aggregation activity of chelating ligands as well as on the use of metal complexes as diagnostic probes and as potential drugs. Conclusion: While chelating agents, such as curcumin or flavonoid derivatives, are currently used to capture metal ions …
Fluorinated Chaperone−β-Cyclodextrin Formulations for β-Glucocerebrosidase Activity Enhancement in Neuronopathic Gaucher Disease
2017
Amphiphilic glycomimetics encompassing a rigid, undistortable nor-tropane skeleton based on 1,6-anhydro-L-idonojirimycin and a polyfluorinated antenna, when formulated as the corresponding inclusion complexes with β-cyclodextrin (βCD), have been shown to behave as pharmacological chaperones (PCs) that efficiently rescue lysosomal β- glucocerebrosidase mutants associated to the neuronopathic variants of Gaucher disease (GD), including the highly refractory L444P/L444P and L444P/P415R single nucleotide polymorphs, in patient fibroblasts. The body of work here presented includes the design criteria for the PC prototype, the synthesis of a series of candidates, the characterization of the PC:βC…