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(1) Background: The oxidized guanine derivatives excreted into urine, products of DNA and RNA oxidation and repair, are used as biomarkers of oxidative damage in humans. This study aims to evaluate oxidative damage in gasoline pump attendants occupationally exposed to benzene. Benzene is contained in the gasoline but it is also produced from traffic and from smoking. (2) Methods: Twenty-nine gasoline pump attendants from two major cities of Saudi Arabia and 102 from Italy were studied for urinary 8-oxo-7,8-dihydroguanine (8-oxoGua), 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodGuo), 8-oxo-7,8-dihydroguanosine (8-oxoGuo), and S-phenyl-mercapturic acid (SPMA) for benzene exposure and urinary cotinine for smoking status assessment by liquid chromatography-tandem mass spectrometry. Airborne benzene was also assessed in the Italian group by gas-chromatography with flame ionization detector (GC-FID). (3) Results: The results suggest that high levels of benzene exposure can cause an accumulation of SPMA and bring about the formation of the oxidation biomarkers studied to saturation. At low exposure levels, SPMA and oxidation biomarker levels were correlated among them and were associated with the smoking habit. (4) Conclusions: The study confirms the association between benzene exposure and the excretion of nucleic acid oxidation biomarkers and enhances the importance of measuring the smoking habit, as it can significantly influence oxidative damage, especially when the exposure levels are low.

This study investigated the effect of polymorphic genes GSTT1, GSTM1, GSTA1, EHPX1, NQO1, CYP2E1, CYP1A and MPO on the urinary concentrations and ratio (R) of the benzene metabolites trans,trans-muconic acid (t,t-MA) and S-phenyl mercapturic acid (S-PMA) in 301 oil refinery workers. The metabolites' concentrations are lower and R is higher (100.66) in non-smokers (n=184) than in smokers (n=117, R=36.54). Non-smokers have lower S-PMA and a higher R in GSTT1 null genotypes than in positive, and a higher S-PMA and a lower R in GSTA1 wild type genotypes. In smokers the GSTT1 null genotype effect on both S-PMA and R is confirmed, and is also shown in GSTM1 null, but not in GSTA1 wild type genotypes. GSTT1 null polymorphism reduces the conjugation rate of benzene epoxide with GSH, and to a lesser extent also GSTTA1 mutant, GSTM1 null and NQO1 mutant genotypes. The activity of one GST is compensated by another in GSTM1 and GSTA1 defective subjects, but not in GSTT1 null genotypes, whose average S-PMA excretion is about 50% with respect to the positive ones, for the same benzene exposure. R showed to be a more sensitive marker for these effects than the metabolite levels., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

This paper aims to examine some methods to measure human exposure to benzene, both in life and occupational environments, through environmental and biological monitoring, examining the critical issues and optimal conditions of use. The overall performance of environmental monitoring, from the analytical point of view, strongly depend on the choice of an appropriate method of sampling and analysis. Urinary SPMA and t, t-MA are the biomarkers listed by ACGIH to evaluate occupational exposure: most of the recent studies use HPLC with tandem mass spectrometry, but since t, t-MA is present in the urine in larger quantities it is also determinable with UV detectors. The urinary benzene is an index not officially included in the list of the ACGIH BEIs, but it is useful to assess exposure and benzene at low concentrations, that most frequently are found today in the occupational and life environments.

The identification of reliable biomarkers is critical for the assessment of occupational exposure of benzene: S-phenylmercapturic acid (SPMA) and trans,trans-muconic acid (t,t-MA) are the most currently used. t,t-MA is an open-ring metabolite, but it is also a metabolite of the food preservative sorbic acid, while SPMA is formed by conjugation with glutathione, and several studies suggested that the genetic polymorphism of glutathione S-transferases modulates its production. This study compared the ability of these metabolites to assess the benzene exposure in a big group of petrochemical workers. Furthermore, investigated how genetic polymorphism of glutathione S-transferase theta 1 (GSTT1), glutathione S-transferase mu 1 (GSTM1), glutathione S-transferase pi 1 (GSTP1) and smoking habits, may influence their excretion. Results showed that occupational exposure to benzene was negligible compared to that from smoking and confirmed the modulating effect of the genetic polymorphism of GSTT1 on the urinary excretion of SPMA, but not of t, t-MA, even at very low levels of benzene exposure. The same effect was found for GSTM1, but only for smokers. The t,t-MA/SPMA ratio was not a constant value and resulted to be higher than the corresponding Biological Exposure Index (BEI) ratio, which is currently equal to 20. Higher values of metabolite have been associated with the GSTT1 or GSTM1 null genotype and these are responsible for increase health risk. We suggest that this ratio could be used as a marker of individual susceptibility for subjects with benzene exposure., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

The present study compared three methods for the determination of S-phenylmercapturic acid (S-PMA), a metabolite of benzene, in human urine: a HPLC/MS/MS technique with two different sample treatments (strong and partial hydrolysis) and a commercial assay based on anti-S-PMA monoclonal antibodies with chemiluminescence detection. Biological monitoring was done on 126 volunteers and the results were compared for the three methods and also with benzene exposure levels (range <3.0-592.5 μg/m(3)). The correlation between environmental monitoring data and S-PMA levels in non-smokers (n=73) was highly significant (p<0.0001, Student's t-test) for both HPLC/MS/MS methods (r=0.65 both for strong acidic hydrolysis of the urine and hydrolysis at pH 2) but not for the immunoassay, which overestimated the S-PMA levels by about 8 μg/g creatinine (creat.). Therefore the immunoassay is only useful as a semiquantitative screening test, but quantitative results need to be confirmed by a more accurate method like HPLC/MS/MS. The HPLC/MS/MS procedure with strong acid hydrolysis led to a recovery of S-PMA about double that using pH 2 hydrolysis, giving more accurate results. The difference between the results with the two methods makes it difficult to compare the strong acidic hydrolysis data with the ACGIH BEI value of 25 μg/g creat. since the BEI(®) documentation is based on data collected in pH conditions that were not always controlled, which may underestimate the true S-PMA concentration. Besides, as levels of benzene exposure were high, smoking was not considered a confounding factor. The BEI for S-PMA in end of shift urine samples could be reconsidered when sufficient data are available from studies where the analyses are carried out in comparable conditions of hydrolysis and monitoring only non-smoking subjects., (Copyright © 2009 Elsevier B.V. All rights reserved.)

The present work was aimed to study in petrochemical industry operators the correlation, if any, between environmental exposure to low levels of benzene and two biological exposure indexes in end-shift urine, i.e. trans, trans-muconic acid (t,t-MA) and S-phenylmercapturic acid (SPMA). Exposure to benzene was assessed in 133 male subjects employed in outdoor operations in a petrochemical plant, using personal passive-diffusive air samplers worn at the breathing zone; adsorbed benzene was determined by GC-FID analysis. S-PMA was determined by a new HPLCMS/MS method, after (quantitative) acidic hydrolysis of the cysteine conjugate precursor. t,t-MA was measured by an HPLC-UV method. Smoking habits were assessed by means of a self-administered questionnaire. Both environmental and biological monitoring data showed that benzene exposure of petrochemical industry operators was low (mean values were 0.014ppm, 101mug/g creat, and 2.8mug/g creat, for benzene, t,t-MA, and S-PMA, respectively) if compared with the ACGIH limits. Cigarette smoking was confirmed to be a strong confounding factor for the urinary excretion of both metabolites: statistically significant increases of t,t-MA and S-PMA levels were recorded in smokers when compared to non-smokers (p<0.0001). The best correlation found was that between exposure to benzene and S-PMA levels, particularly in non-smokers. This was partly due to the hydrolysis of the S-PMA precursor N-acetyl-S-(1,2-dihydro-2-hydroxyphenyl)-l-cysteine, a crucial step of the new analytical method used, which indeed reduced the variability of the results by means of an improved standardization of this critical preanalytical factor. A weaker correlation was found between exposure to benzene and t,t-MA, possibly explained by the fact that the latter is also a metabolite of sorbic acid, a common diet component. In summary, even at such low levels of exposure, urinary metabolites proved to be a useful tool for assessing individual occupational exposure to benzene, S-PMA appearing to be a more specific biomarker than t,t-MA, particularly in non-smokers., (Copyright 2009 Elsevier Ireland Ltd. All rights reserved.)

Urinary trans,trans-muconic acid (t,t-MA), a biomarker of benzene exposure, is usually determined by HPLC methods with detection by either UV or, more recently, electrospray tandem mass spectrometry. However, not all these methods have been fully validated for quantitative analysis. This paper presents an HPLC/MS/MS method for reliable quantitative determination of t,t-MA that uses a commercial deuterium-labeled isotope as internal standard; the matrix effect has been evaluated and LOD is 0.22 microg/L. We used this method to test 200 urine samples, 175 of them collected at end-of-shift from workers in an oil refinery.

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.

Background: The objective of this study is to evaluate the effects of traffic on human health comparing biomonitoring data measured during the COVID-19 lockdown, when restrictions led to a 40% reduction in airborne benzene in Rome and a 36% reduction in road traffic, to the same parameters measured in 2021. Methods: Biomonitoring was performed on 49 volunteers, determining the urinary metabolites of the most abundant traffic pollutants, such as benzene and PAHs, and oxidative stress biomarkers by HPLC/MS-MS, 28 elements by ICP/MS and metabolic phenotypes by NMR. Results: Means of s-phenylmercaputric acid (SPMA), metabolites of naphthalene and nitropyrene in 2020 are 20% lower than in 2021, while 1-OH-pyrene was 30% lower. A reduction of 40% for 8-oxo-7,8-dihydroguanosine (8-oxoGuo) and 8-oxo-7,8-dihydro-2-deoxyguanosine (8-oxodGuo) and 60% for 8-oxo-7,8-dihydroguanine (8-oxoGua) were found in 2020 compared to 2021. The concentrations of B, Co, Cu and Sb in 2021 are significantly higher than in the 2020. NMR untargeted metabolomic analysis identified 35 urinary metabolites. Results show in 2021 a decrease in succinic acid, a product of the Krebs cycle promoting inflammation. Conclusions: Urban pollution due to traffic is partly responsible for oxidative stress of nucleic acids, but other factors also have a role, enhancing the importance of communication about a healthy lifestyle in the prevention of cancer diseases. [ABSTRACT FROM AUTHOR]

The article discusses a study related to measuring human exposure to benzene through environmental and biological monitoring by analyzing critical issues and optimal conditions of use. Topics discussed include using HPLC with tandem mass spectrometry, urinary benzene is used to assess exposure and benzene at low concentrations, and environmental monitoring depends on the choice of appropriate method of sampling and analysis.

Urban air contains benzene and polycyclic aromatic hydrocarbons (PAHs) which have carcinogenic properties. The objective of this paper is to study the correlation of exposure biomarkers with biomarkers of nucleic acid oxidation also considering smoking. In 322 subjects, seven urinary dose biomarkers were analyzed for benzene, pyrene, nitropyrene, benzo[a]pyrene, and naphthalene exposure, and four effect biomarkers for nucleic acid and protein oxidative stress. Chemometrics was applied in order to investigate the existence of a synergistic effect for the exposure to the mixture and the contribution of active smoking. There is a significant difference between nicotine, benzene and PAH exposure biomarker concentrations of smokers and non-smokers, but the difference is not statistically significant for oxidative stress biomarkers. The PAH biomarkers are those which best correlate with all the oxidative stress biomarkers. Results suggest that 8-Oxo-7,8-dihydroguanine and protein nitro-oxidation 3-nitrotyrosine are the most sensitive biomarkers for the exposure to the urban pollutant mixtures and that a synergic effect of the mixtures exists. All the oxidative stress biomarkers studied drive the increase in the oxidative stress biomarkers in the subjects having higher exposures. Chemometrics proved to be a powerful method for the interpretation of human biomonitoring data. [ABSTRACT FROM AUTHOR]

Background: Benzene is an important component of cigarette smoke and car exhaust. Products containing benzene in concentrations greater than 0.1% are prohibited in Europe, but 1% of benzene is still allowed in gasoline. The purpose of the study was to assess the levels of urine benzene biomarkers in a sample of the general population not occupationally exposed to benzene, resident in the period 2013–2014 in Central Italy, compared to other groups. Methods: The urinary levels of the benzene metabolites S-phenyl-mercapturic acid (SPMA) and cotinine (nicotine metabolite) were determined by means of HPLC with mass spectrometric detection in 1076 subjects. Results: The median SPMA value in smokers was 1.132 µg/g of creatinine while in non-smokers it was 0.097 µg/g of creatinine, and the 95th percentile results were seven times higher. Conclusion: The main source of benzene exposure in the studied population was active smoking, however, non-smokers were also exposed to airborne benzene concentrations. The concentration ranges found in this study can be used as a background reference for occupational exposure assessment to benzene by means of SPMA biomonitoring. [ABSTRACT FROM AUTHOR]