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Challenges in the Statistical Analysis of Biomarker Data
Published in Anthony P. DeCaprio, Toxicologic Biomarkers, 2006
Stephen W. Looney, Joseph L. Hagan
Bartczak et al. (66) compared a high-pressure liquid chromatography-based assay with a gas chromatography-based assay for urinary muconic acid, both of which have been used as biomarkers of exposure to benzene. They used Pearson’s correlation coefficient r and the slope of the fitted regression line in their assessment of the agreement between the two methods (p. 255). However, at least as far back as 1973, it was recognized that r is not appropriate for assessing agreement in what are typically called “method comparison studies,” i.e., studies in which neither method of measurement can be considered to be the gold standard (67). In fact, Westgard and Hunt go so far as to state that “the correlation coefficient … is of no practical use in the statistical analysis of comparison data” (67). The use of linear regression coefficients is also inappropriate for assessing agreement between continuous biomarkers, as discussed by several authors (68).
Benzene Metabolism (Toxicokinetics and the Molecular Aspects of Benzene Toxicity)
Published in Muzaffer Aksoy, Benzene Carcinogenicity, 2017
Keith R. Cooper, Robert Snyder
It has been known for over 100 years that benzene is converted to phenol30 and to catechol and hydroquinone.31 The first detailed studies of the metabolism of benzene in vivo were reported by Porteous and Williams,32,33 and with the advent of 14C-benzene, these studies were extended by Parke and Williams.12 Rabbits were given 14C-benzene (0.3 to 0.5 ml/kg) by oral gavage, and radioactivity was determined in expired air, tissues, and urine. The major hydroxylation product was phenol which, along with some catechol and hydroquinone, is found for the most part in urine conjugated with ethereal sulfate or glucuronic acid. Unconjugated phenol has been found in mouse and rat urine after benzene administration.13,34,35 Parke and Williams12 also reported on the occurrence of phenylmercapturic acid and trans, trans-muconic acid. The occurrence of labeled carbon dioxide and trans, transmuconic acid in the expired air would indicate that an opening of the ring occurred. Based on the administered dose, 43% was detected as benzene in the expired air, 1.5% as expired CO2, and 35% was recovered as metabolites in the urine. Between 5 to 10% was present in the feces or body tissues. Hydrolysis of the urinary metabolies resulted in 23% as phenol, 4.8% hydroquinone. and 2.2% as catechol. Extensions of this work in recent years have concentrated on metabolism in various species, on the mechanism of metabolism using in vitro techniques, and on attempting to relate benzene metabolism to its toxicity.36-38
Urinary levels of the acrolein conjugates of carnosine are associated with inhaled toxicants
Published in Inhalation Toxicology, 2020
Timothy E. O’Toole, Xiaohong Li, Daniel W. Riggs, David J. Hoetker, Ray Yeager, Pawel Lorkiewicz, Shahid P. Baba, Nigel G. F. Cooper, Aruni Bhatnagar
The direct inhalation of reactive aldehydes (e.g., contained in cigarette smoke), or of air-borne toxins which promote oxidative stress and lipid peroxidation in vivo, and the systemic delivery of these reactive products, are believed to underlie the pathologies associated with PM2.5 and cigarette smoke exposure. The endogenous histidyl-di-peptide carnosine neutralizes oxidized lipids and, in this way, may protect against the deleterious effects of inhaled toxins. In this study we show that urinary levels of carnosine-propanol are inversely associated with current smoking but positively associated with never smoking (Table 2). Levels of this carnosine conjugate demonstrated a similar, inverse association with contemporaneous levels of ambient PM2.5, but we found no association with other determinants or indicators of pollution exposure such as distance to major roadways, traffic level, or levels of the benzene metabolite, muconic acid (Table 2).
The shape of low-concentration dose–response functions for benzene: implications for human health risk assessment
Published in Critical Reviews in Toxicology, 2021
Louis A. Cox, Hans B. Ketelslegers, R. Jeffrey Lewis
Figure 2 shows the compartmental structure of a recent benzene PBPK model for humans (Knutsen et al. 2013). Figure 3 compares model predictions to observations of metabolites in data not used in building the model. (The scales in Figure 3 are logarithmic, so predictions and data are compared across estimated exposure concentrations that differ by several orders of magnitude.) Estimated rates of human conversion of benzene to muconic acid (MA) and phenylmercapturic acid (PMA), phenol (PH), catechol (CA), hydroquinone (HQ), and benzenetriol (BT) in the model were validated using urinary benzene metabolite data from Chinese benzene workers. Although there is substantial interindividual variability, as reflected in the large vertical scatter in Figure 3, the PBPK model predictions pass through the observed data clouds, and in this sense roughly describe the data. Other PBPK models for benzene have been developed over the past 30 years and at least partially validated by comparing their predictions to observations in data sets not used in developing them, although most do not show bone marrow as a separate compartment. Similar to Figure 3, these PBPK models predict linear or sublinear (upward-curving, as detoxifying pathways begin to saturate) production of metabolites as a function of air benzene concentrations, for air benzene concentrations below about 10 ppm. We defer to the references for details of these PBPK models, but note that the approximate linearity of metabolite production as exposure concentration approaches zero is a property of a broad class of classical (compartmental) pharmacokinetic and PBPK models at low doses (Cox 1995). Saturation of metabolite production begins at air benzene concentrations between about 10 ppm and about 100 ppm.
Females with impaired ovarian function could be vulnerable to environmental pollutants: identification via next-generation sequencing of the vaginal microbiome
Published in Journal of Obstetrics and Gynaecology, 2022
Seongmin Kim, Se Hee Lee, Kyung Jin Min, Sanghoon Lee, Jin Hwa Hong, Jae Yun Song, Jae Kwan Lee, Nak Woo Lee, Eunil Lee
The following compounds were analysed using a high-performance liquid chromatography-triple tandem mass detector (HPLC-MS/MS, 6410B, Agilent, Santa Clara, CA): phthalate metabolites (mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP)), environmental phenols (bisphenol A (BPA), methyl paraben (MP), ethyl paraben (EP), propyl paraben (PP) and 2,4-dichlorophenol (24DCP)), volatile organic compounds (VOCs: trans,trans-muconic acid (ttMA), benzyl mercapturic acid (BMA), phenyl glyoxylic acid (PGA) and o,m,p-methyl hippuric acid (MHA), mandelic acid (MA)).