It has been suggested that the threshold limit value (TLV) for the time-weighted average (TWA), of benzene be lowered because of its possible leukemogenic effect at low exposure concentrations. This requires the development of new methods of biological monitoring. In this cross-sectional study the diagnostic power of blood and breath benzene and of urinary phenol, catechol, hydroquinone, S-phenylmercapturic acid, and muconic acid were compared in a population of 410 male workers exposed to benzene in garages, in two coke plants, and in a by-product plant. Benzene exposure was assessed by personal air sampling (charcoal tube and passive dosimeter). In all, 95% of the workers were exposed to less than 0.5 ppm benzene. According to the multiple regression equation, the muconic acid and S-phenylmercapturic acid concentrations detected in nonsmokers exposed to 0.5 ppm benzene were 0.3 mg/g and 6 micrograms/g, respectively (range 0.2-0.6 mg/g and 1.2-8.5 micrograms/g, respectively). With muconic acid very few false-positive test results were found, and this determination remained reliable even around a cutoff level of 0.1 ppm benzene. Moreover, the diagnostic power of this test proved to be good even when diluted or concentrated urine samples were not excluded. S-Phenylmercapturic acid (S-PMA) also performed fairly well. Blood and breath benzene as well as urinary phenol (PH) and hydroquinone (HQ) were clearly less suitable biomarkers than muconic acid (MA). Catechol (CA) was not associated with occupational benzene exposure. According to the results of biological monitoring, the skin resorption of benzene from gasoline or other fuels seems negligible. Correlation, multiple regression, and likelihood ratios consistently showed that MA and S-PMA concentrations were fairly good indicators of benzene exposure in the 0.1- to 1-ppm range, even in a population comprising both smokers and nonsmokers. PH, HQ, CA, and blood and breath benzene were less suitable, if at all, in the same exposure range.

Accurate measurement of the mechanical properties of ultra-thin films with thicknesses typically below 100 nm is a challenging issue with an interest in many fields involving coating technologies, microelectronics, and MEMS. A bilayer curvature based method is developed for the simultaneous determination of the elastic mismatch strain and Young's modulus of ultra-thin films. The idea is to deposit the film or coating on very thin cantilevers in order to amplify the curvature compared to a traditional "Stoney" wafer curvature test, hence the terminology "micro-Stoney." The data reduction is based on the comparison of the curvatures obtained for different supporting layer thicknesses. The elastic mismatch strain and Young's modulus are obtained from curvature measurements of cantilevers before and after the film deposition. The data reduction scheme relies on both analytical and finite element calculations, depending on the magnitude of the curvature. The experimental validation has been performed on ultra-thin low pressure chemical vapor deposited silicon nitride films with thickness ranging between 54 and 133 nm deposited on silicon cantilevers. The technique is sensitive to the cantilever geometry, in particular, to the thickness ratio and width/thickness ratio. Therefore, the precision in the determination of the latter quantities determines the accuracy on the extracted elastic mismatch strain and elastic modulus. The method can be potentially applied to films as thin as a few nanometers.

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The hypothesis of Renz and Kalf could not be confirmed. Although the low level exposure of the study population and methodological factors are possible explanations, it cannot be excluded that the hypothesis of Renz and Kalf is not generalizable to benzene-exposed humans. Presently, one cannot advise the measurement of IL-1 alpha production for biological effect monitoring of workers exposed to low concentrations of benzene.

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