M
Maurizio Guida
Researcher at University of Salerno
Publications - 171
Citations - 3647
Maurizio Guida is an academic researcher from University of Salerno. The author has contributed to research in topics: Medicine & Pregnancy. The author has an hindex of 30, co-authored 142 publications receiving 2975 citations. Previous affiliations of Maurizio Guida include National Research Council.
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A crash-prediction model for multilane roads
TL;DR: The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options.
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Neuro-toxic and Reproductive Effects of BPA
Antonietta Santoro,Rosanna Chianese,Jacopo Troisi,Sean Richards,Stefania Lucia Nori,Silvia Fasano,Maurizio Guida,Elizabeth Plunk,Andrea Viggiano,Riccardo Pierantoni,Rosaria Meccariello +10 more
TL;DR: This review critically analyzes recent findings on the neuro-toxic and reproductive effects of BPA with focus on neuronal differentiation, synaptic plasticity, glia and microglia activity, cognitive functions, and the central and local control of reproduction.
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A miRNA signature in leukocytes from sporadic amyotrophic lateral sclerosis.
TL;DR: It is suggested that miRNAs profiles found in the peripheral blood leukocytes from sALS patients can be relevant to understand the pathogenesis of sALS and/or used as biomarkers of the disease.
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Bisphenol A in Reproduction: Epigenetic Effects.
Rosanna Chianese,Jacopo Troisi,Sean M. Richards,Marika Scafuro,Silvia Fasano,Maurizio Guida,Riccardo Pierantoni,Rosaria Meccariello +7 more
TL;DR: The environmental exposure to BPA - especially in fetal and neonatal period - deserves attention to preserve the reproductive ability in both sexes and to reduce the epigenetic risk for the offspring.
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A mixed-Weibull regression model for the analysis of automotive warranty data
TL;DR: A mixed-Weibull distribution, where the pdf of each subpopulation depends on the covariates through the scale parameter, is used to analyze the component lifetime and the adequacy of the proposed model to fit the observed data has been assessed.