Elemental analysis of histological specimens: a method to unmask nano asbestos fibers
There is recent mounting evidence that nanoparticles may have enhanced toxicological potential in comparison to the same material in the bulk form. The aim of this study was to develop a new method for unmask asbestos nanofibers from Formalin-Fixed, Paraffin-Embedded tissue. There is an increasing amount of evidence that nanoparticles may enhance toxicological potential in comparison to the same material in the bulk form. The aim of this study was to develop a new method to unmask asbestos nanofibers from Formalin-Fixed Paraffin-Embedded (FFPE) tissue. For the first time, in this study we applied Energy Dispersive X-ray (EDX) microanalysis through transmission electron microscopy to demonstrate the presence of asbestos nanofibers in histological specimens of patients with possible occupational exposure to asbestos. The diagnostic protocol was applied to 10 randomly selected lung cancer patients with no history of previous asbestos exposure. We detected asbestos nanofibers in close contact with lung cancer cells in two lung cancer patients with previous possible occupational exposure to asbestos. We were also able to identify the specific asbestos iso-type, which in one of the cases was the same rare variety used in the workplace of the affected patient. By contrast, asbestos nanofibers were not detected in lung cancer patients with no history of occupational asbestos exposure. The proposed technique can represent a potential useful tool for linking the disease to previous workplace exposure in uncertain cases. Furthermore, Formalin-Fixed Paraffin-Embedded (FFPE) tissues stored in the pathology departments might be re-evaluated for possible etiological attribution to asbestos in the case of plausible exposure. Since diseases acquired through occupational exposure to asbestos are generally covered by workersâ€™ insurance in most countries, the application of the protocol used in this study may have also relevant social and economic implications.Â
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Copyright (c) 2016 M. Scimeca, A. Pietroiusti, F. Milano, L. Anemona, A. Orlandi, L.T. Marsella, E. Bonanno
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