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Your search keyword '"Adami G"' showing total 24 results
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24 results on '"Adami G"'

23. In vitro transdermal absorption of Al2O3 nanoparticles

Author

Francesca Larese Filon, Marcella Mauro, Giovanni Maina, Elena Baracchini, Gianpiero Adami, Matteo Crosera, Massimo Bovenzi, Mauro, M., Crosera, M., Bovenzi, M., Adami, G., Maina, G., Baracchini, E., and Larese Filon, F.

Subjects
Franz cell, 0301 basic medicine, Antiperspirants, Aluminium nanoparticles, Franz cells, In vitro, Transdermal absorption, Population, Human skin, Toxicology, Dermal exposure, 03 medical and health sciences, 0302 clinical medicine, education, education.field_of_study, Chromatography, integumentary system, Chemistry, General Medicine, Permeation, Aluminium nanoparticle, 030104 developmental biology, 030220 oncology & carcinogenesis, Al2o3 nanoparticles
Abstract

Dermal exposure to Aluminium nanoparticles (AlNPs) can occur in occupationally- and non occupationally exposed- population, due to the use of Al salts-based antiperspirants. No AlNPs transdermal permeation data exists. Our study investigated in vitro the permeation of 30–60 nm Al2O3NPs dispersed in synthetic sweat (20 g/L) using excised human skin on Franz cells. Experiments were performed using intact (experiment 1) and needle-abraded skin (experiment 2). After 24 h traces of Al were detectable in receiving solution of exposed cells (35.0 ± 6.0 ng/cm2 for intact and 88.5 ± 34.2 ng/cm2 for damaged skin, mean and SD) and in blank cells (36.3 ± 7.0 ng/cm2), without statistical significance (p = 0.08, Mann-Whitney test). The average amount of Al into intact and damaged skin samples was 3.96 ± 0.20 μg/cm2 for intact and 4.36 ± 0.47 μg/cm2 for damaged skin (p = 0.08). Al content was similar in epidermal and dermal layers of intact and damaged skin (1.95 ± 0.13 μg/cm2 and 2.31 ± 0.12 μg/cm2 epidermal, 2.01 ± 0.25 μg/cm2 and 2.05 ± 0.35 μg/cm2 dermal). Al is a trace element in human body and the amount found in receiving solutions could be due as background impurity. This data suggest a reassuring transdermal permeation profile for Al2O3NPs.

Published
2019

24. Characterization of variability of air particulate matter size profiles recorded by optical particle counters near a complex emissive source by use of Self-Organizing Map algorithm

Author

Sergio Cozzutto, Sabina Licen, Gianpiero Adami, G. Barbieri, Matteo Crosera, Pierluigi Barbieri, Licen, S., Cozzutto, S., Barbieri, G., Crosera, M., Adami, G., and Barbieri, P.

Subjects
Self-organizing map, Self-Organizing Map, 01 natural sciences, Analytical Chemistry, 03 medical and health sciences, Pattern recognition, Cluster (physics), Cluster analysis, Spectroscopy, 030304 developmental biology, Remote sensing, Ambient air, Optical particle counter, Particulate matter, 0303 health sciences, Process Chemistry and Technology, 010401 analytical chemistry, Particulates, 0104 chemical sciences, Computer Science Applications, Visualization, Outlier, Environmental science, Graph (abstract data type), Particle counter, Software
Abstract

In the present study we propose the application of a procedure of data analysis based on the Self-Organizing Map algorithm and k-means clustering in series (1st level and 2nd level abstraction respectively) as a strategy to identify recurrent ambient air particulate matter (PM) size profiles starting from the elaboration of high frequency data recorded by an Optical Particle Counter (OPC). We tested the strategy on data deriving from a three months survey at a residential site in proximity to an integral cycle steel plant in Trieste (NE Italy). We were able to identify four clusters representing recurrent PM class profiles whose meaning has been interpreted and confirmed by correlation to “external data”, i.e. data not used to build the model, registered by other devices (meteorological and pollutant monitoring stations). The four clusters were found to be related to two different plant type of emissions (sources) and to two different site background profiles, respectively. The powerful visualization features of SOM map allowed to describe and characterize the variability of size distribution of PM in a concise form. The clustered SOM being built for one measuring station, proved to be helpful for the analysis of OPC data collected at another location close to the industrial plant. Moreover, occasional episodes of Saharan dusts could be identified as outliers with respect to local particulate and discussed in terms of size distribution. Eventually, by means of an animated graph, we propose a method to visualize the PM experimental data evolution during the day using the PM cluster profiles as a legend.

Published
2019

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