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The aim of the study was to investigate the effect of various factors that modulate the metabolism of benzene, including smoking habits, metabolic genotype of GST and co-exposure to toluene, on the levels of three biomarkers, i.e. urinary benzene (UB), S-phenylmercapturic acid (SPMA) and t,t-muconic acid (t,t-MA), in 146 refinery workers exposed to low levels of air benzene (AB) in the range <1.5-529.2 μg/m 3 (mean value 32.6 μg/m 3 ). The study confirmed the validity of SPMA as a good biomarker of benzene exposure even at low levels of exposure. It was also confirmed that cigarette smoking is the main confounding factor when assessing biological monitoring data of occupational exposure to AB. Our data indicate that the GSTT1, but not the GSTM1 genotype, significantly increases the urinary levels of SPMA, even at low levels of exposure. It is not known, though, whether subjects with a GSTT1 "null" genotype may be more susceptible to the effects of benzene. Finally, environmental toluene appears to inhibit the metabolism of benzene to SPMA even at low concentrations, also resulting in an underestimation by SPMA levels of the actual exposure of workers to benzene., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objectives: The American Conference of Governmental Industrial Hygienists (ACGIH) has classified oak dust as a human carcinogen (A1), based on increased sinus and nasal cancer rates among exposed workers. The aims of this study were to investigate the use of gallic acid (GA) as a chemical marker of occupational exposure to oak dusts, to develop a high-performance liquid chromatography-diode array detector method to quantify GA and to apply the method in the analysis of oak dust samples collected in several factories., Methods: A high-performance liquid chromatography method was developed to detect GA in oak wood dust. The method was tested in the field, and GA was extracted from inhalable oak wood dust collected using the Institute of Occupational Medicine inhalable dust sampler in the air of five woodworking plants where only oak wood is used., Results: A total of 57 samples with dust concentrations in the range of 0.27-11.14 mg/m(3) were collected. Five of these samples exceeded the Italian threshold limit value of 5 mg/m(3), and 30 samples exceeded the ACGIH TLV of 1 mg/m(3). The GA concentrations were in the range 0.02-4.18 µg/m(3). The total oak dust sampled was correlated with the GA content with a correlation coefficient (r) of 0.95., Conclusions: The GA in the tannic extracts of oak wood may be considered a good marker for this type of wood, and its concentration in wood dust sampled in the work environment is useful in assessing the true exposure to carcinogenic oak dust.

A novel high-performance liquid chromatographic/ultraviolet method was developed to detect lapachol (LP) and deoxylapachol (DLP) in wood dust as chemical markers of teak wood (a suspected human carcinogen). The specificity of this analysis was determined by noting the absence of LP and DLP in 12 other specimens of different woods belonging to the angiosperm family. The consistency was examined by analyzing teak from three different sources, where the percentages (wt/wt) of the chemicals ranged from 0.006 to 0.261 for LP and from 0.038 to 0.497 for DLP, respectively. Although the LP and DLP components of teak varied according to source, a very high correlation coefficient (r (2) > 0.98 always) was found between the content of the two markers in the bulk specimens and in bulk dust derived from them. The method was then applied to teak dust collected on polyvinylchloride filters from aerosol in an exposure chamber in the range of mass loadings between 0.03 and 3.65 mg, which corresponds to a dust exposure between 0.124 and 8.703 mg m(-3) for a sampling time of 2h. A field test was also carried out in a small factory where teak was used. A good correlation was confirmed between LP and DLP versus the dust collected on the filter in both cases. LP and DLP can be markers to estimate the true quantities of teak dust inhaled in a workplace with mixed wood dust, provided the results are matched to the content of LP and DLP in the bulk wood. LP and DLP have also been proposed as the agents responsible for allergic reaction to teak dust. Therefore, it would be useful to evaluate the exposure to these two substances even without a relationship to teak dust exposure., (© The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

This study was aimed to identify useful biomarkers of exposure and effect in workers exposed to low levels of benzene, and to evaluate any correlations existing between these parameters. Benzene exposure was measured in 33 petrochemical industry operators (PIO), 28 service station attendants (SSA), 21 gasoline pump maintenance workers (GPMW) and 51 non-exposed controls by GC-FID analysis. Samples were collected with personal passive samplers (Radiello). End-shift urine samples were collected for t,t-muconic acid (t,t-MA) determination by HPLC and for S-phenylmercapturic acid (S-PMA) measurement by HPLC-MS/MS. The alkaline version of the comet assay and, in a subgroup of 19 SSA and 16 control subjects, chromosomal aberrations (CA) and glutathione (GSH) levels were measured in peripheral blood lymphocytes. Personal benzene exposure was significantly higher in PIO, SSA and GPMW as compared to controls. The urinary excretion of the two metabolites showed a significant increase in SSA (p=0.0258 and p=0.0001, for t,t-MA and S-PMA, respectively) and in PIO (p=0.0013 and p=0.0001, for t,t-MA and S-PMA, respectively) as compared with the control group, while no such increase was observed for GPMW, for whom occupational exposure was not continuous and occurred on specific working days only. Significant increases of DNA damage were found by the comet assay for tail moment (TM) and tail length (TL) in SSA (p<0.0001 and p=0.008, for TM and TL, respectively) and PIO (p<0.0001 and p<0.0001, for TM and TL, respectively) when compared with controls. The PIO group also displayed a significant increase in the number of cells with comet (p<0.0001). Smoking habits did not appear to interfere with these results in any of the groups. No difference was found in percentage of CA between exposed workers and controls. Significant correlations were found, in all groups, between benzene exposure and the more representative comet parameter TM (r=0.509, p=0.007; r=0.525, p=0.017 and r=0.420, p=0.046 in SSA, GPMW, and PIO, respectively). A trend of negative correlation was observed between DNA damage and either GSH or urine S-PMA for exposed workers. In summary, in present study urinary S-PMA and DNA damage by the comet assay were both sensitive to exposure to low levels of benzene, and GSH seems to play an important defence role against benzene-dependent DNA damage., (Copyright 2009 Elsevier Ireland Ltd. All rights reserved.)

A new gas chromatographic/mass spectrometric (GC/MS) method was developed to detect 2-methylanthraquinone (2-MeA) in wood dust. 2-MeA is present in teak wood (a suspected human carcinogen) but not in oak, beech, mahogany, birch, ash or pine. The method involved collection of workplace dust on filters and extraction of 2-MeA with methanol and GC/MS analysis. The method was tested on teak wood dust samples (n = 43) collected on polyvinylchloride membrane filters during various work operations in four small factories making furniture and fittings for leisure craft and boatyards (air teak wood dust concentration: range 0.32-14.32 mg m(-3)). A high correlation coefficient for the content of 2-MeA versus teak dust was obtained (logarithmic correlation: y = 1.5308x + 0.0998, r = 0.9215). Determination of airborne 2-MeA is a useful technique to confirm occupational exposure to teak wood dust.

There is conflicting evidence on the level of anesthetics that impairs neurobehavioral performance, leading to differences in exposure standards (25 or 50 ppm for N(2)O). Thirty-eight operating room nurses and 23 unexposed nurses were asked to provide information on confounding variables: age, gender, years of schooling, alcohol and coffee consumption, smoking, length of work, symptoms (Euroquest) and results of Block Design test. Afterward, all workers were repeatedly examined (on Monday and Friday of a working week, before and after workshift) for stress and arousal (Mood Scale) and complex reaction times (Color Word Vigilance, CWV), the latter being the outcome. Individual exposure was assessed through urinary end-shift concentrations of nitrous oxide (N(2)O) and isoflurane. According to the highest value of urinary excretion of N(2)O in the week, exposed workers were subdivided in three groups (<13; > or =13 and <27; and > or = 27 microg/l). The values of 13 and 27 microg/l correspond to environmental concentrations of 25 and 50 ppm, respectively. In order to take into account the pre-existing abilities of exposed and reference workers, and investigate the neurobehavioral changes over time, longitudinal data were analyzed by a two-stage regression model and analysis of variance for repeated measures (MANOVA). The former method, controlling for confounding factors and Monday morning CWV (which conveyed the pre-existing ability of the subjects), showed that, with respect to unexposed nurses, reaction times were significantly (p<0.020) higher only in workers with urinary N(2)O> or = 27 microg/l. Therefore, at MANOVA, all subjects were categorized in two classes (N(2)O urinary concentrations or = 27 microg/l), and CWV results were adjusted for the confounding variables and effects of stress and arousal, taken concurrently with CWV. CWV significantly (p<0.039) decreased over a working week (indicating a learning effect) in workers with urinary N(2)O<27 microg/l, while remained steady (indicating impairment of neurobehavioral performance) in those with urinary N(2)O> 27 microg/l.

The aim of this study was to assess gasoline filling-station attendants' exposure to benzene and to determine which biological exposure index (BEI), trans,trans-muconic acid (t,t-MA) or S-phenylmercapturic acid (S-PMA), shows better correlation with environmental exposure. Exposure to benzene was measured using passive samplers (Radiello) attached to the collar of the overalls of subjects (n=33) just before the work-shift (approximately 8h); analysis was performed by GC-FID. S-PMA and t,t-MA were determined, respectively, by an immunochemiluminescent assay based on specific monoclonal antibodies and by HPLC-UV at 264 nm. Both methods of biological monitoring were performed on beginning and end-shift urine samples, and expected t,t-MA and S-PMA values were calculated. Smoking habits and life-style were ascertained by means of a questionnaire. Both environmental and biological monitoring data showed that benzene exposure for gasoline filling-station attendants was low when compared with the respective ACGIH limit values (means-benzene: 0.044 mg/m(3); t,t-MA: 171 microg/g creatinine; S-PMA: 2.7 microg/g creatinine). No significant correlation was found between exposure to benzene and t,t-MA or S-PMA excretion data. The use of expected values was also experimented for S-PMA and t,t-MA. This consists of calculating, on the basis of the known half-life of the benzene metabolite, the concentration of that metabolite that a worker should present at the end of the work-shift, the difference between this value and the value actually found is a measure of benzene exposure during work. The use of expected values in biological monitoring did not improve correlations. At these low benzene levels, environmental monitoring seems to be the best method of evaluating individual exposure. However, biological monitoring remains useful, as a mean of assessing group exposure.