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Imaging Approaches to Assessments of Toxicological Oxidative Stress Using Genetically-encoded Fluorogenic Sensors
Published on: February 7, 2018
Chemometrics models for assessment of oxidative stress risk in chrome-electroplating workers
Rezvan Zendehdel1, Seyed Vahid Shetab-Boushehri, Mansoor R Azari
1Department of Occupational Hygiene, School of Public Health, Shahid Beheshti University of Medical Sciences , Tehran , Iran .
Abstract:
Oxidative stress is the main cause of hexavalant chromium-induced damage in chrome electroplating workers. The main goal of this study is toxicity analysis and the possibility of toxicity risk categorizing in the chrome electroplating workers based on oxidative stress parameters as prognostic variables. We assessed blood chromium levels and biomarkers of oxidative stress such as lipid peroxidation, thiol (SH) groups and antioxidant capacity of plasma. Data were subjected to principle component analysis (PCA) and artificial neuronal network (ANN) to obtain oxidative stress pattern for chrome electroplating workers. Blood chromium levels increased from 4.42 ppb to 10.6 ppb. Induction of oxidative stress was observed by increased in lipid peroxidation (22.38 ± 10.47 μM versus 14.74 ± 4.82 μM, p < 0.0008), decreased plasma antioxidant capacity (3.17 ± 1.35 μM versus 7.74 ± 4.45 μM, p < 0.0001) and plasma total thiol (SH groups) (0.21 ± 0.07 μM versus 0.45 ± 0.41 μM, p < 0.0042) in comparison to controls. Based on the oxidative parameters, two groups were identified by PCA methods. One category is workers with the risk of oxidative stress and second group is subjects with probable risk of oxidative stress induction. ANN methods can predict oxidative-risk category for assessment of toxicity induction in chrome electroplaters. The result showed multivariate modeling can be interpreted as the induced biochemical toxicity in the workers exposed to hexavalent chromium. Different occupation groups were assessed on the basis of risk level of oxidative stress which could further justify proceeding engineering control measures.

