Sélim Aït-Aïssa
email: selim.ait-aissa@ineris.fr.

Pascal Pandard

Hélène Magaud

André-Patrick Arrigo

Eric Thybaud

Jean-Marc Porcher

Evaluation of an in vitro hsp70 induction test for complex mixtures toxicity assessment: comparison with chemistry and ecotoxicity tests

Keywords: industrial wastes, heat shock protein, reporter gene, cellular stress, ecotoxicity tests, dose-response modelling, multivariate comparison

The aim of this study was to assess the potential of a human cell line containing the hsp70 promoter linked to the chloramphenicol acetyl transferase reporter gene, to evaluate toxic potential of complex mixtures. Cells were exposed to eluates of industrial wastes and the cellular responses were compared to the metal contents of the samples and to standardised aquatic (microalgae growth inhibition, daphnia immobilisation, bacterial luminescence inhibition, Ceriodaphnia dubia reproduction inhibition) and terrestrial (earthworms lethality, plant growth inhibition) tests. The hsp70 promoter was significantly induced by 11 out of 14 samples, with different dose-response patterns. Significant correlation of in vitro induction potency with aquatic ecotoxicity, especially with chronic tests, and with the metal contents of the samples were observed. Our study provides new information on the relevance of hsp70 gene induction as a criterion of toxicity and suggests its usefulness for the detection of toxicity associated to metallic pollution in complex mixtures.

INTRODUCTION

Hazard evaluation of environmental complex mixtures consists in the determination of their intrinsic toxicity towards living systems and thus requires information given by both chemical analysis and toxicity testing. It has now become evident that chemical analysis is not sufficient to achieve hazard assessment of environmental samples, since it is restricted to some specific classes of toxic compounds, for which analytical methods are available and toxicity is known. In addition, chemical analysis do not inform neither on the available fraction for living organisms nor on the potential joint effects of the different contaminants. Hence, a toxicological evaluation using bioassays has to be done in order to determine the actual hazardous properties of a given sample.

The potential of in vitro approach using cell tissues for assessing the harmful effects of chemicals on living systems has recently attracted much attention in ecotoxicology (reviewed by [START_REF] Walker | Alternative approaches and tests in ecotoxicology: a review of the present position and the prospects for change, taking into account ECVAM's Duties, topic selection and test criteria[END_REF][START_REF] Wells | Microscale testing in aquatic toxicology: advances, techniques, and practice[END_REF]. An emerging trend concerns the in vitro use of biochemical and molecular biomarkers for toxicity testing and the measurements of cellular responses related to the mechanisms of toxicity [START_REF] Bierkens | Comparative sensitivity of 20 bioassays for soil quality[END_REF][START_REF] Walker | Alternative approaches and tests in ecotoxicology: a review of the present position and the prospects for change, taking into account ECVAM's Duties, topic selection and test criteria[END_REF][START_REF] Wells | Microscale testing in aquatic toxicology: advances, techniques, and practice[END_REF]. In particular, cellular assays using reporter gene coupled to stress inducible gene promoters have gained acceptance as valuable tools for toxic potential evaluation. They are generally sensitive and specific, and their relative easy use and cost effectiveness allow their use in screening programs.

At present, the application of receptor-mediated gene responses to environmental mixtures has been well studied with regard to the detection and quantification of specific contaminants such as dioxin-like compounds [START_REF] Anderson | A biomarker, P450 RGS, for assessing the induction potential of environmental samples[END_REF][START_REF] Kerr | Evaluation of a reporter gene system biomarker for detecting contamination in tropical marine sediments[END_REF] or xenoestrogens [START_REF] Zacharewski | In vitro bioassays for assessing estrogenic substances[END_REF][START_REF] Balaguer | Reporter cell lines to study the estrogenic effects of xenoestrogens[END_REF]. The validity of the biological response has been achieved by correlating reporter gene induction with chemical analysis of the samples [START_REF] Anderson | A biomarker, P450 RGS, for assessing the induction potential of environmental samples[END_REF][START_REF] Vincent | Regulation of promoter-CAT stress gene in HepG2 cells by suspensions of particles from ambiant air[END_REF][START_REF] Kerr | Evaluation of a reporter gene system biomarker for detecting contamination in tropical marine sediments[END_REF]. Besides, the application of cellular damages-mediated reporter genes, such as those involved in response to heat shock, oxidative stress and/or DNA alteration, has been less extensively characterised for toxicity assessment of environmental mixtures, although several studies have reported their activation by environmentally realistic pollutant levels [START_REF] Fischbach | Induction of the human growth hormone gene placed under human hsp70 promoter control in mouse cells: a quantitative indicator of metal toxicity[END_REF][START_REF] Guven | Evaluation of a stress-inducible transgenic nematode strain for rapid aquatic toxicity testing[END_REF][START_REF] Van Dyk | Rapid and sensitive pollutant detection by induction of heat shock genebioluminescence gene fusions[END_REF][START_REF] Jones | Transgenic strains of the nematode C. elegans in biomonitoring and toxicology: effects of captan and related compounds on the stress response[END_REF] or environmental samples [START_REF] Vincent | Regulation of promoter-CAT stress gene in HepG2 cells by suspensions of particles from ambiant air[END_REF][START_REF] Power | Stress-inducible transgenic nematodes as biomonitors of soil and water pollution[END_REF][START_REF] Hamers | The application of reporter gene assays for the determination of the toxic potency of diffuse air pollution[END_REF].

These cellular responses are activated by stressors that alter vital cellular functions (i.e. proteins or DNA alteration), and are generally associated to early (cyto)toxic events [START_REF] Goering | Stress protein synthesis induced in rat liver by cadmium precedes hepatotoxicity[END_REF][START_REF] Neuhaus-Steinmetz | Heat shock protein induction by certain chemical stressors is correlated with their cytotoxicity, lipophilicity and protein-denaturating capacity[END_REF][START_REF] Aït-Aïssa | Activation of the hsp70 promoter by environmental inorganic and organic chemicals: relationships with cytotoxicity and lipophilicity[END_REF]. Thus, they may represent potential predictors of toxic effects at higher levels of biological organisation. However, to our knowledge, no study compared such in vitro stress gene induction assays with in vivo (eco)toxicity effects. Unlike several in vitro cytotoxicity tests using primary or continuous cell cultures which have been shown to correlate to in vivo chemicals toxicity or ecotoxicity assays [START_REF] Saito | Cytotoxicity of 109 chemicals to goldfish GFS cells and relationships with 1-octanol/water partition coefficients[END_REF][START_REF] Segner | Cytotoxicity of MEIC chemicals to rainbow trout R1 cell line and multivariate comparison with ecotoxicity tests[END_REF][START_REF] Gagné | Differences in the measurement of cytotoxicity of complex mixtures with rainbow trout hepatocytes and fibroblastes[END_REF], the predictive information provided by cellular reporter gene tests is left unexplored.

In this paper, we address the use of heat shock gene (hsp70) induction in response to exposure to complex mixtures in a stably transfected cellular model. The heat shock response is characterised by the induction of a set of stress proteins, namely called heat shock proteins (HSPs). Under physiological conditions, HSPs act as molecular chaperons and ensure cellular protein homeostasis and cell protection. After cellular aggression, the release of the heat shock transcription factor (HSF) from its binding to HSP70 in the cytoplasm, allows formation of an HSF homotrimer which migrates to the nucleus and binds the heat shock elements (HSE) in the promoter region of hsp genes, thus leading to the transcription activation of these genes. It is know admitted that the stressor-induced generation of misfolded proteins constitutes the trigger signal that up regulates the heat shock response [START_REF] Hightower | Heat shock, stress proteins, chaperones, and proteotoxicity[END_REF], and a number of environmental pollutants were shown to induce HSPs synthesis in many organisms or cell tissues [START_REF] Sanders | Stress proteins as biomarkers of contaminant exposure in archived environmental samples[END_REF], through different mechanisms of action involving cellular protein alterations [START_REF] Voellmy | Sensing stress and responding to stress[END_REF]. Due to their strong conservation through evolution, the wide diversity of their inducing agents and the relative sensitivity of their expression in comparison to conventional endpoints such as growth, survival or reproduction, the HSPs, and especially the major stress protein HSP70, have been proposed as sensitive markers of non-specific effects in environmental monitoring [START_REF] Sanders | Stress proteins in aquatic organisms: an environmental perspective[END_REF][START_REF] Ryan | Stress proteins as molecular biomarkers for environmental toxicology[END_REF][START_REF] Bierkens | Heat-shock proteins in ecotoxicological risk assessment[END_REF].

In a previous study, we used HeLa cells carrying the human hsp70 promoter linked to the chloramphenicol acetyl transferase (CAT) reporter gene [START_REF] Kretz-Remy | The kinetics of HIV-1 long terminal repeat transcriptional activation resemble those of hsp70 promoter in heat-shock treated HeLa cells[END_REF] to screen toxic chemicals [START_REF] Aït-Aïssa | Induction of the hsp70 gene promoter by various anticancer drugs[END_REF][START_REF] Aït-Aïssa | Activation of the hsp70 promoter by environmental inorganic and organic chemicals: relationships with cytotoxicity and lipophilicity[END_REF]. Heavy metals, pesticides, and chlorophenols induced the hsp70 promoter in this model, whereas some organic chemicals were found negative even at cytotoxic doses. The authors concluded that although HSP70 should not be considered as a universal marker of toxicity, it might be useful for the detection of toxic effects generated by many different types of chemical contaminants in complex samples. The aim of the present study was (i) to evaluate the applicability of the established hsp70-reporter gene model to reveal biological activity in complex mixtures, and (ii) to assess its toxicological significance by investigating how this cellular test compares to a battery of ecotoxicity tests and to chemical analyses. For this purpose, HeLa-CAT cells were exposed to fourteen eluates of industrial wastes and the cellular responses were compared to the metallic contents of the samples and to ecotoxicological effects, as measured by standardised aquatic and terrestrial tests performed in parallel on the wastes [START_REF] Pandard | Evaluation de l'écotoxicité des déchets[END_REF].

MATERIALS AND METHODS

Samples description, preparation and chemical analysis

The table 1 summarises the characteristics and the origins of the industrial wastes used in this study. Sampling, waste description and sample preparation have been detailed elsewhere [START_REF] Pandard | Evaluation de l'écotoxicité des déchets[END_REF]. Briefly, eluates of wastes were prepared by mixing the raw waste with distilled water with a liquid to solid (dry matter) ratio of ten, for 24 hrs under circular agitation at room temperature, according to the draft european standard (prEN12457-2). After settling, the supernatant was collected and filtered through a 100 µm size pore filter. The pH was then adjusted between 5.5 to 8.5 if pH value was out of this range. The samples were filtered again through a 0.45 µm filter and then used for toxicity testing and chemical analysis. All aquatic ecotoxicity tests were performed on the 0.45 µm filtered fraction except the Daphnia magna acute test (see below) which was performed on the 100 µm filtered fraction. For in vitro testing, a further filtration of the samples through 0.2 µm filters was performed in order to avoid any bacterial contamination of the cultures. For metal analysis, the 0.45 µm filtrates were analysed by inductively coupled plasma atomic emission spectroscopy (ICP/AES) according to standard procedures (NF EN ISO 11885, NF EN 1483 and NF T 90-043).

In vitro cellular stress test

HeLa-hsp70-CAT cells were routinely cultured in complete Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% heat inactivated foetal bovine serum (Gibco, France) and 1% antibiotics (Penicillin-Streptomycin) at 37°C in a humidified atmosphere containing 5% CO 2 .

Cellular test conditions were the same as those previously described for chemical compounds testing [START_REF] Aït-Aïssa | Activation of the hsp70 promoter by environmental inorganic and organic chemicals: relationships with cytotoxicity and lipophilicity[END_REF]. Briefly, subconfluent cells (about 80% confluency) grown in 24wells culture plates were washed twice with pre-warmed PBS and exposed in triplicates to various concentrations of the samples, ranging from 0.1 to 90% v/v. Just before exposure, nine volumes of sample were mixed with one volume of ten fold concentrated phosphate buffer saline (PBS), giving the upper range concentration (90 %), and thereafter serially diluted in serum-free culture medium. The former step allowed a salt correction of the sample as well as a pH stabilisation in physiological range values, thus preventing any osmotic or pH stress to the cells at the highest concentrations. Preliminary experiments showed that a 24 h exposure of cells in PBS did not neither modify the cell viability nor activate significantly the stress promoter. After a 16 hr exposure to wastes eluates, the cultures were washed once with pre-warmed complete medium and allowed to recover for 24 hours in complete medium before harvesting. Analysis of intracellular CAT content was performed with a CAT ELISA kit (Boeringher Mannheim) according to the manufacturer's instructions. Results are expressed as the ratio between the amount of CAT detected and the total cellular protein content as determined by a modification of the Lowry's method (BioRad DC Protein Assay kit). Cytotoxicity was evaluated by the total protein assay and was expressed as percentage of control cultures. Samples were stored at 4°C in the dark and tested for cellular stress 3 days maximum after preparation. This storage time did not influenced their toxic potential since we observed that a storage for two weeks did not diminish significantly their in vitro toxicity (not illustrated).

Ecotoxicological tests

The ecotoxicity tests (Table 2) were performed according to standard procedures. Aquatic tests were performed either on the 100µm (Daphnia magna test) or on the 0.45µm (C. dubia, P. subcapitata and V. fischeri tests) filtered fractions. For all three terrestrials tests, dilutions of raw wastes were carried out in artificial soil (20 % Kaolinite clay, 10% sphagnum peat finely ground, 70 % fine quartz sand with more than 50 % of particle size between 0.02 mm and 0.5 mm).

Analysis of hsp70 induction data

Hsp70 induction curves parameters, such as effective concentrations, maximal induction level and the rate of the induction, were calculated after modelling the observed in vitro patterns.

Because hsp70 induction profiles were often balanced by a cytotoxic effect, thus leading to biphasic induction curves, the measured effects were modelled as follows. Firstly, cytotoxicity data, expressed in % of control cultures, were fitted to a logistic model according to equation ( 1 The coordinate values of the maximum induction (Xmax, Ymax) were calculated from the first derivative of equation ( 2). The induction slope characteristics (maximal slope value at the inflection point of the increase and its corresponding concentration (EC slope )) were calculated from the second derivatives of equation ( 2). All the calculations were performed on Microsoft Excel spreadsheets by least squares minimisation.

Analysis of in vivo toxicity data

We aimed to use a single endpoint for each ecotoxicity test in order to reduce the number of variables to be further introduced in the multivariate analyses. The EC 20 (concentration leading to 20% of effect as compared to control) was chosen because it relies to a low effect and thus appeared more adapted than a EC 50 to compare sublethal cellular effects to in vivo acute and chronic effects. Dose-response curves from ecotoxicity tests were modelled using equation (1). The EC 20 s were calculated from the following equation :

(3)

B D D A EC EC 1 50 20 1 8 . 0
where A, B, EC 50 , D are calculated parameters resulting from equation 1.

Statistics

In vitro effects -Significant effects of wastes on either hsp70 induction or total protein content were tested by ANOVA. Homogeneity of variances was analysed with the Levene's test. When variances were found homogenous, significant effects of the tested concentrations on either hsp70-CAT induction or cytotoxicity were determined by a one-way ANOVA, followed by an unilateral Dunnett's test. When variances when not found homogenous, a non parametric Kruskall-Wallis test was performed. A value of p<0.05 was considered statistically significant.

Distribution of the chemical and toxicity data -The Lilliefors test, based on a modification of the

Kolmogorov-Smirnov test, revealed that none of the datasets were normally distributed.

Therefore, the data were log-transformed to conform to the normality assumption (Lilliefors test) and to the homogeneity of variance (Levene's test).

Principal component analysis (PCA) -The degree of similarities between all toxicity tests used

for the characterisation of the industrial wastes was explored by running a principal component analysis (PCA) on log-transformed data. The PCA was run from a data matrix which included the eight toxicity variables (four aquatic, three terrestrial and the hsp70 test) as the columns and the fourteen wastes as the lines. Chemical data were not included into the PCA due to missing values.

Correlation analysis -Correlation between stress promoter induction and either chemical analysis

or in vivo toxicity were determined with the Pearson correlation on log-transformed data.

Significance of the correlation was determined with a two-tailed Student's t test for significance.

All statistical calculations were carried out with SPSS 10.0 for Windows.

RESULTS

In vitro stress responses and calculation of induction potencies (PI)

The table 3 summarises the hsp70 activation and cytoxicity results. Eleven samples out of 14 induced significantly (p<0.05) the hsp70 promoter in a concentration-response relationship.

Different degrees of cellular stress response were noticed when considering the level of the CAT production and the effective concentrations. Some wastes, i.e. wastes 7, 8 or 11, induced a strong gene response at relatively low concentrations. Others, i.e. wastes 1, 2, 5 and 14 gave intermediate levels of response, while the last samples provoked low (wastes 3, 10, 12, 13) or no (wastes 4, 6, 9) activation of the promoter. On a first approach, these results show a good responsiveness of the cellular model for the detection of biological effects associated to complex mixtures, allowing a first ranking of the samples in three groups. In order to standardise the results, the measured effects were fitted to a double logistic model, as described in the Materials and Methods section. Examples of fits which illustrate different patterns of hsp70 induction by complex mixtures are given in the figure 1. As seen in this figure, this mathematical model allows a good fitting of the measured effects by non linear regression.

In order to rank the wastes with respect to their potency to induce the hsp70 promoter, we aimed to reduce the individual dose-response curves to simple descriptors which should reflect the induction potency (PI) of a given sample. Because the observed induction profiles varied in function of two parameters, i.e. the level of CAT production and the concentration of sample responsible for this induction, the PI is defined as the intensity of the reporter gene response per sample concentration unit. Hence, PI value could be represented either by the slope of the induction, which reflect the rate of gene induction with respect to the concentration, or, as previously described [START_REF] Aït-Aïssa | Activation of the hsp70 promoter by environmental inorganic and organic chemicals: relationships with cytotoxicity and lipophilicity[END_REF], by the ratio between the maximal induction value and the concentration leading this maximal induction (Ymax/Xmax). With our present set of data, a high correlation (r = 0.99, p<0.001) was obtained between the slope of the induction and the Ymax/Xmax values, suggesting that these two variables are equivalent. In further analysis, we used two parameters to describe the dose-response curves : the Ymax/Xmax variable as an index for hsp70 induction potency, and the EC slope endpoint (concentration responsible for median induction) in order to allow direct comparisons of effective concentrations measured in the different tests.

Comparison with metal contents

Values for selected metals are summarised in Table 4. Although only partial data were available, it appears clearly that metal contents presented a great diversity amongst the analysed samples.

High levels, i.e. above a milligram per litre, were found for zinc, cadmium, copper and lead in samples 5, 7, 8 and 11. Oppositely, very low to not detectable concentrations were found in wastes 3, 4, and 6. The total elemental contents of the other wastes (1, 2, 9, 14) were found in the 0.1-1 mg/l range. While it is interesting to note that wastes 5, 7, 8 and 11 came from metal industry, no clear evidence enabled us to rely the chemical characteristics of a given sample to its original industrial sector.

The hsp70 induction potencies of the samples were generally consistent with the chemical data.

The relationships between chemical data and in vitro data were analysed by linear regression, performed on log-transformed PI versus log(1+metal), with the metal contents expressed in µg.l -1 .

When considering individual elements, PI was significantly correlated to cadmium (r = 0.904; p<0.001), zinc (r = 0.869; p = 0.001) and lead (r = 0.915; p<0.001). This relationship was also true when considering the sum of cadmium, zinc and lead (r = 0.918 ; p < 0.001). Very similar results were obtained when comparing the EC slope factor to metal contents, significant correlation being observed with cadmium (r = -0.900; p<0.001), zinc (r = -0.812; p = 0.002) and lead (r = -0.879; p<0.001). No significant correlation was noticed with the other individual metals, nor with unspecific parameters such as total organic carbon or conductivity of the samples (not shown).

The relationships between hsp70 potencies and sum of cadmium, zinc and lead is illustrated in figure 2. These findings confirm the hypothesis that hsp70 induction is explained by the presence of metals in the samples.

Comparison with in vivo ecotoxicological effects

A battery of terrestrial and aquatic ecotoxicity bioassays has been performed on the raw wastes and on their corresponding eluates respectively. Because hsp70 induction relies to an effect at the subcellular level, we have chosen to compare it with a low effect endpoint, i.e. EC 20 , measured in all in vivo tests. The measured in vivo toxicity and the in vitro hsp70 induction are summarised in the Table 5.

The diversity of the in vivo wastes toxicity appears clearly in the Table 5. In order to explore the degree of similarities between the toxic responses given by the different tests, we ran a PCA normalised on the log-transformed data. In order to include all wastes into the calculation, we used 100% as EC 20 or EC slope values for the non toxic measurements. The locations of the samples and the tests on the first factorial plan resulting from the PCA are presented in Figure 3A and 3B, respectively. The PCA showed that 86 % of the overall variance is explained by the first two principal components. The first factor (F1) corresponds to 75 % of the overall variance and can be interpreted as a toxicity axis. For instance, wastes 8, 11 and 7 which are highly toxic for most of the organisms, are located at the left side of the figure, at the opposite of the non toxic wastes 4, 6 and 12 (Figure 3A). All the tests, including the hsp70 one, are able to distinguish between very toxic and non toxic samples since they present similar levels of correlation with the first component (Figure 3B). F1 is positively correlated with all ecotoxicity tests and with the EC slope and negatively correlated with PI. This last negative correlation can be explained by the difference of expression unit between PI and ecotoxicity tests, i.e. a toxic waste will have a low EC 20 and a high hsp70 induction potency. The second factor (F2) corresponds to 11 % of the global variance and distinguishes between terrestrial and aquatic tests (Figure 3B). This is likely due to differences in the samples tested in either aquatic or terrestrial tests, i.e. eluates or raw wastes respectively, thus leading to differences in bioavailable toxic compounds. For instance, the wastes 8, 10 and 5 were more toxic for the aquatic than the terrestrial organisms (Table 5). For these samples, the leaching step may have had a strong influence on the release of water soluble toxic compounds on the bioavailable fraction. Oppositely, waste 13 was more toxic in terrestrial than in aquatic tests. This waste came from petroleum industry and contained significant levels of polyaromatic hydrocarbon (PAHs) compounds, as confirmed by HPLC analysis (not shown). The presence of such hydrophobic toxicants in the raw waste explains why the water soluble fraction was less toxic than the solid phase, where PAHs were bioavailable for terrestrial organisms only.

Figure 3B shows that the hsp70 test was more closely related to aquatic than to terrestrial tests as EC slope is located in the aquatic tests group and PI is inversely correlated to this group on the second axis of the first factorial plan. This was confirmed by the univariate correlation analyses presented in Table 6. The Pearson correlation show that PI was highly correlated (p<0.01) with the two chronic tests P. subcapitata and C. dubia and with the acute test D. magna. Lower correlation, but still significant (p<0.05), were obtained with the bacterial V. fischeri test and with the three terrestrial tests. Correlation with the EC slope endpoint were very similar to those observed with PI, although the level of significance with acute tests were slightly higher with the EC slope .

Correlation analysis were performed from all toxicity measurements, including the arbitrary values of the non toxic results (i.e. EC 20 = 100 %). However, it is likely that the high observed correlation may be due to an artefact of our dataset introduced by extreme values, i.e. non toxic or highly toxic values. To verify this hypothesis, a second set of correlation analysis was run without introducing the in vitro and in vivo non toxic results into the analysis. The results presented in Table 7 show that correlation between PI or EC slope and aquatic tests (CER, ALG and DAP) were still highly significant, despite a lower number of samples were taken into account. The association between PI and these aquatic tests is illustrated in Figure 4. Oppositely, the correlation coefficients between PI and the bacterial and terrestrial tests were highly diminished, thus confirming that, with these last tests, an artefactual direction toward a region of non toxic values was established when all samples were introduced into the analysis. This was also true with the EC slope endpoint (Table 7), excepted with the acute test with earthworm for which a significant linear relationship was still noticed after excluding non toxic values.

DISCUSSION

Cellular stress responsive reporter gene systems have been proposed as useful tools for toxicity potential evaluation in biomonitoring. However, few studies have reported their application to complex mixtures, or have compared in vitro stress gene response with (eco)toxicity endpoints, measured at the cellular or multicellular levels. In the present study, we report the applicability of this cellular model for the determination of toxic potential of complex mixtures such as eluates of industrial wastes coming from different industrial sectors or processes. The relevance of the cellular stress response as a tool for toxicological diagnostic was assessed by comparing the in vitro results to (i) chemical analysis of the samples and (ii) in vivo ecotoxicological measurements from four aquatic and three terrestrial tests performed in parallel on the wastes [START_REF] Pandard | Evaluation de l'écotoxicité des déchets[END_REF].

In vitro results

For 11 out of 14 analysed samples, a significant induction of the promoter was observed in a dose-response relation, with various levels of gene response intensity and effective concentration.

The intensity of the response is an important parameter to be considered for the characterisation of hsp70 induction pattern. It strongly varies in function of the type of the inducing agent [START_REF] Fischbach | Induction of the human growth hormone gene placed under human hsp70 promoter control in mouse cells: a quantitative indicator of metal toxicity[END_REF][START_REF] Sacco | A transgenic mouse model for the detection of cellular stress induced by toxic inorganic compounds[END_REF][START_REF] Bourniasvardiabasis | Induction of lowmolecular-weight heat-shock proteins in Drosophila and human embryonic lineage cells after teratogen exposure[END_REF], and several studies showed that intracellular HSP accumulation can reach very high levels after severe treatment [START_REF] Dreano | High-level, heat-regulated synthesis of proteins in eukaryotic cells[END_REF][START_REF] Lindquist | The heat-shock proteins[END_REF][START_REF] Sanders | Stress proteins in aquatic organisms: an environmental perspective[END_REF].

By modelling the induction dose-response curves, we were able to calculate an index for hsp70 induction (PI) and thus to classify the samples with regard to their potency to activate the hsp70 response. In preliminary works, we have tested other non linear regression methods such as a combination of linear and logistic regression, Gaussian [START_REF] Kennedy | Chicken embryo hepatocyte bioassay for measuring cytochrome P4501A-based 2,3,7,8-tetrachlorodibenzo-p-dioxin equivalent concentrations in environmental samples[END_REF] or exponential [START_REF] Vincent | Regulation of promoter-CAT stress gene in HepG2 cells by suspensions of particles from ambiant air[END_REF] models, but graphical analysis showed that our model provided the best fit of our data. The model we retained allowed us to calculate both an induction potency (PI) index for a given waste and the concentration of eluate responsible for median hsp70 induction (EC slope ). The PI index combines both the magnitude of the gene response and the effective concentration of stressor. A similar index, which reflected the rate of change of marker protein with the log value of the concentration, was developed by [START_REF] Vincent | Regulation of promoter-CAT stress gene in HepG2 cells by suspensions of particles from ambiant air[END_REF] to describe induction potency of a given stressor. The authors used this parameter to compare stress gene response to chemical data in recombinant HepG2 cells exposed to air particles suspensions. This allowed them to identify substances well correlated to stress gene response. For instance, they identified amongst 21 analysed metals boron, titanium, copper and zinc as possibly associated with the cellular responses, while soluble copper emerged as the best explanatory variable for hsp70 and metallothionein promoters induction.

Hsp70 versus analytical data

Our results are in line with those previously reported by [START_REF] Vincent | Regulation of promoter-CAT stress gene in HepG2 cells by suspensions of particles from ambiant air[END_REF], since hsp70 induction in HeLa-CAT cells were consistent with the presence of metals in the samples (Figure 2). Heavy metals are well known as transcriptional activators of HSP70 in a plethora of living systems [START_REF] Fischbach | Induction of the human growth hormone gene placed under human hsp70 promoter control in mouse cells: a quantitative indicator of metal toxicity[END_REF][START_REF] Sanders | Stress proteins in aquatic organisms: an environmental perspective[END_REF][START_REF] Guven | Evaluation of a stress-inducible transgenic nematode strain for rapid aquatic toxicity testing[END_REF][START_REF] Ryan | Evaluation of heavy-metal ion toxicity in fish cells using a combined stress protein and cytotoxicity assay[END_REF].

Although partial chemical analysis were performed, the hsp70 response is explained, at least partly, by the contents in cadmium, zinc and lead (Figure 2). For instance, wastes 7, 8 and 11 were the most efficient hsp70 activators ; they also contained the highest amounts of metals, mainly cadmium, zinc, lead and copper. These metals, with zinc to a lesser extent, have been ranked amongst the most efficient chemicals able to induce the hsp70 promoter in different reporter gene systems [START_REF] Fischbach | Induction of the human growth hormone gene placed under human hsp70 promoter control in mouse cells: a quantitative indicator of metal toxicity[END_REF][START_REF] Guven | Evaluation of a stress-inducible transgenic nematode strain for rapid aquatic toxicity testing[END_REF][START_REF] Steiner | Analysis of hsp70 mRNA levels in HepG2 cells exposed to various metals differing in toxicity[END_REF]. On the opposite, metal contents in the wastes 4, 6 and 9, were very low to not detectable. In the same way, these samples were not effective to induce any significant stress response, even if a clear cytotoxic effect of the sample 9 was observed. The waste 5, which induced a moderate response of the hsp70 gene, did not fit well into the correlation (Figure 2). This sample had a relatively high zinc content but was less potent to induce the hsp70 promoter than wastes 1 and 14, which contained ten times less metals. This observation suggests that, although a significant linear correlation was noticed between PI and chemical analyses, induction of stress response by metals mixture may be the reflect of complex mechanistic events involving chemicals interactions and thus cannot be completely explained by simple linear relationships with individual or addition of metals species.

Metals ions are known to exert interactive effects when they are present in mixture [START_REF] Newman | Predicting relative toxicity and interactions of divalent metal ions: Microtox bioluminescence assay[END_REF], however it is not clear whether these effects are additive, antagonistic or synergistic. In vivo, this might depend on various conditions such as the nature of metal considered, the tested concentrations or the studied organisms [START_REF] Steiner | Analysis of hsp70 mRNA levels in HepG2 cells exposed to various metals differing in toxicity[END_REF][START_REF] Sharma | Combination toxicology copper, zinc, and cadmium in binary mixtures: concentration-dependent antagonistic, nonadditive, and synergistic effects on root growth in Silene vulgaris[END_REF][START_REF] Preston | Biosensing the acute toxicity of metal interactions: are they additive, synergistic, or antagonistic ?[END_REF]. In addition, only few data exist with in vitro systems. Recently, [START_REF] Tully | Effects of arsenic, cadmium, chromium, and lead on gene expression regulated by a battery of 13 different promoters in recombinant HepG2 cells[END_REF] reported the ability of toxic metals, alone or in combination, to induce 13 stress related promoters, including hsp70, in recombinant HepG2 cells. No synergistic activity was detected after exposure to an environmentally relevant mixture of cadmium, lead and chromium (III). By using the parental cell line HepG2, [START_REF] Steiner | Analysis of hsp70 mRNA levels in HepG2 cells exposed to various metals differing in toxicity[END_REF] showed different interactions between metals with regard to their abilities to stimulate hsp70 mRNA production. They observed antagonistic effects on hsp70 induction by paired combinations of metals such as cadmium/zinc or cadmium/manganese, and a potentiating effect, coupled to cytotoxicity, after a concomitant exposure to mercury and silver. Therefore, considering overall or individual metals of a complex mixture should be only partly explanatory for hsp70 induction since some are more effective than others to induce the stress response and interactions between elements may occur.

Nevertheless, integration of chemicals interactions in the biological response constitutes one major argument for the preferential use of bioassays rather than chemical analysis for the determination of toxic potential. Such argument is in line with the view that "stress protein accumulation may reflect the intregrated stress load on the organism regardless of the type or number of stressors involved" [START_REF] Sanders | Stress proteins in aquatic organisms: an environmental perspective[END_REF].

Comparison with in vivo ecotoxicity

One major aim of this study was to determine how comparable the hsp70 test and a set of ecotoxicity tests are. PCA showed that all the tests, including the in vitro one, were able to distinguish between highly toxic and non toxic samples (Figure 3). Furthermore, significant correlations were observed between PI and in vivo ecotoxicity of wastes (Table 6). When excluding non toxic results, PI was correlated to the C. dubia and P. subcapitata chronic tests (p<0.01), and to a lesser extent (p<0.05), to the D. magna acute test (Table 7, Figure 4). Similar relationships were observed between aquatic tests and EC slope factor, although some slight differences may be underlined. For instance, the PI descriptor, which relies to the intensity of the stress gene response, appeared more related to chronic tests than was EC slope . This suggests that the magnitude of such molecular effect may provide additional toxicological information than the knowledge of toxic concentration only. However, more data will be necessary to validate this hypothesis.

In general, our results show that, although a limited number of samples were analysed, a clear linear relationship between in vitro responses and in vivo aquatic toxicity was revealed for this set of samples. To our knowledge, this constitutes the first report on such in vitro/in vivo correlation using a cellular reporter gene test. Besides, similar relationships between in vitro cytotoxicity results and acute in vivo ecotoxicity tests results were often reported for a set of selected chemicals [START_REF] Saito | Cytotoxicity of 109 chemicals to goldfish GFS cells and relationships with 1-octanol/water partition coefficients[END_REF][START_REF] Segner | Cytotoxicity of MEIC chemicals to rainbow trout R1 cell line and multivariate comparison with ecotoxicity tests[END_REF] or environmental wastewaters [START_REF] Gagné | Differences in the measurement of cytotoxicity of complex mixtures with rainbow trout hepatocytes and fibroblastes[END_REF]. Such good correlations support the hypothesis of basal cytotoxicity, which stipulates that toxicity findings can be extrapolated between systems if chemical toxicity is caused by injury to basal structures and functions that are common to cells of all organisms and species [START_REF] Segner | Cytotoxicity of MEIC chemicals to rainbow trout R1 cell line and multivariate comparison with ecotoxicity tests[END_REF]. The heat shock response is induced in a protective way through non specific mechanisms of toxicity which involve the generation of abnormal proteins and alteration of cellular functions. As a consequence, maximum HSP induction is often related to early cytotoxic but reversible events [START_REF] Goering | Stress protein synthesis induced in rat liver by cadmium precedes hepatotoxicity[END_REF][START_REF] Neuhaus-Steinmetz | Heat shock protein induction by certain chemical stressors is correlated with their cytotoxicity, lipophilicity and protein-denaturating capacity[END_REF]. In our study, hsp70 induction was generally more sensitive than cytotoxicity (up to 25 fold for waste 1) and gave additional information on the molecular mechanisms of toxicity as well as on the extent of the cellular damages that occurred. Interestingly, our results suggest that hsp70 induction potency is more predictive of sublethal (i.e. chronic tests) than of acute in vivo effects.

The multivariate analysis revealed a low species specificity for this set of samples. This observation is unusual in ecotoxicology testing since the chosen test organisms are often phylogenetically far from each other. For these samples, the toxic mechanisms involved in the measured effects were not specific to the species. Nevertheless, this may be due to some inherent limitations of our dataset, i.e. a matrix of data of 14 samples to 9 variables is not propitious to obtain a good discrimination of the variability between tests. Therefore, it must be kept in mind that our positive results were obtained from a low number of samples, mainly contaminated by toxic metals. More data with other types of environmental mixtures (e.g. effluents, contaminated soils extracts, sediments, etc) will be necessary to improve the limit of the application of this in vitro test and to further validate its application in environmental toxicology. Finally, the use a battery of different molecular sublethal endpoints should allow the detection of a broader range of xenobiotics which act through various mechanisms of toxicity [START_REF] Blaise | Microscale testing in aquatic toxicology : Introduction, historical perspective, and context[END_REF] and would be more suitable for an exhaustive environmental screening.

CONCLUSION

In summary, this study reports for the first time the potential of a reporter gene test as a possible predictor of in vivo ecotoxicity of complex mixtures contaminated by metals. The significant correlation obtained between in vitro hsp70 promoter induction and chemical or ecotoxicological data suggest that the reporter gene response is a valuable quantitative tool for the assessment of toxic potential in environmental mixtures contaminated by metals. This point is particularly relevant when considering the reduced cost of the cellular test by comparison to a battery of in vivo ecotoxicity tests. However, our study should be considered as a first step in the application of such hsp70 reporter gene test and more data will be necessary to confirm our findings and validate its use in environmental biomonitoring.

  (cyto)toxicity, expressed in % of control, A = no effect value (set to 1), B = parameter representative of the slope of the viability fall, EC 50 = concentration leading to 50% (cyto)toxicity compared to control and D = maximal effect value (set to 0 for 100% toxicity). The resulting calculated parameters were then reported on a second model combining two logistic curves. The equation for the observed induction becomes: = level of CAT in control, B' = parameter representative of the slope of the induction curve in absence of cytotoxicity interference, C' = concentration leading to median induction (i.e. in absence of cytotoxicity interference) and D' = maximal induction level in absence of cytotoxicity.

Figure 1 :

 1 Figure 1 : Examples of modelled dose-response curves of hsp70 promoter induction and

Figure 2 :

 2 Figure 2 : Linear regression between hsp70 induction potency (PI) and metals contents (µg/l) of

Figure 3 :

 3 Figure 3 : Position of wastes (A) and toxicity tests (B) on the first factorial plane of the principal

Figure 4 :

 4 Figure 4 : Correlation between aquatic tests and hsp70 induction. PI was plotted vs (A) C. dubia,

  Figure1

Table 1 : Wastes description according to the European Waste Catalogue.

 1

	Waste	Waste description (industrial sector)
	number
	1	Sludge from on-site effluent treatment containing chromium (leather and fur
		industry)
	2	Sludge from on-site effluent treatment containing chromium (leather and fur
		industry)
	3	Waste from treatment of salt slags and black drosses (aluminium thermal
		metallurgy)
	4	sludge (iron and steel industry)
	5	Sludge from gas treatment (iron and steel industry)
	6	Waste from the processing of slag (iron and steel industry)
	7	Solid waste from gas treatment of electrical furnaces (iron and steel industry)
	8	Furnace dust (casting and ferrous pieces)
	9	Ball mill dust (aluminium metallurgy)
	10	De-inking sludge (paper recycling)
	11	Flue gas dust (second smelting, waste from aluminium metallurgy)
	12	Waste from paint powders (manufacture, formulation, supply and use of paints
		and varnishes)
	13	Tank bottom sludge (petroleum refining)
	14	Waste from dried paints (manufacture, formulation, supply and use of paints and
		varnishes)

Table 2 : Standardised ecotoxicity tests.

 2

	a test performed on Evian water without EDTA
	b 14 days after emergence of 50% of the seedlings in the control.

Table 4 : Metal contents (in mg.l -1 ) of the wastes eluates.

 4

	Metals

a : Metal contents of wastes 10, 12 and 13 are not available. -: not analysed.

Table 5 : Ecotoxicity and hsp70 induction potencies of the 14 wastes.

 5 : for non effective samples, a PI of 0.1 (i.e. 10 pg CAT/mg at the 100% concentration), corresponding to the control background, is given.

	Waste		In vivo toxicity (EC 20 in % sample) a			hsp70 induction
	No.	BAR	LET	EAR	ALG	DAP	VIB	CER	PI b	X slope
	1	4.3	2.0	4.2	1.1	9.2	0.6	1.0	6.83	8.5
	2	6.9	0.7	14.5	2.6	13.3	0.2	7.7	0.69	41.0
	3	58.0	4.4 c	17.5	23.9	NT	NT	50.5	0.44
	4	18.6	16.1	NT	NT	NT	NT	84.1	0.1 d	NI
	5	NT	NT	NT	2.2	69.1	36.6	0.3	2.02	85.9
	6	85	45.3	85.3	NT	NT	NT	48.9	0.1 d	NI
	7	1.8	1.3	1.6	0.6	5.1	17	0.006	158.81	3.9
	8	3.5	1.0	1.2	0.0004	0.1	0.02	0.004	3320.12	0.4
	9	16.9	6.3	3.3	3.3	5.3	8.7	0.2	0.1 d	NI
	10	NT	75	NT	63.6	37.0	5.4	11.7	0.40	28.2
	11	1.0	0.2	0.5	0.7	11.0	3.9	0.1	469.60	3.8
	12	47.5	22.6	NT	65.7	88.7	NT	>70	0.20	72.6
	13	1.5	0.68 c	1.0	35.5	5.4	3.3	0.6	0.24	7.4
	14	2.0	2.1	8.6	0.8	11.8	2.4	0.1	7.87	37.8
	a : NT, not toxic ; the test codes are given in the Table 2;
	b : hsp70 induction potency (PI) in pgCAT/mg protein/sample concentration unit;
	c : effect measured on emergence;

d

Table 6 : Pearson's correlation coefficients between hsp70 induction parameters and in vivo bioassays (EC 20 ) a .

 6 All data were included into the correlation. The test codes are given in the Table2. r = correlation coefficients ; p = signification level ; n = number of samples fitted into the correlation.

			CER	ALG	DAP	VIB	BAR	LET	EAR
	PI	r	-0.816	-0.868	-0.711	-0.597	-0.623	-0.574	-0.655
		p	0.000	0.000	0.004	0.024	0.011	0.032	0.011
		n	14	14	14	14	14	14	14
	EC slope	r	0.731	0.777	0.847	0.651	0.693	0.651	0.763
		p	0.003	0.001	0.000	0.012	0.006	0.012	0.002
		n	14	14	14	14	14	14	14
	a

Table 7 : Pearson's correlation coefficients between hsp70 induction parameters and in vivo bioassays (EC 20 ) a .

 7 Correlation were performed on the toxic data only. The test codes are given in the Table 2. r = correlation coefficients ; p = signification level ; n = number of samples fitted into the correlation.

			CER	ALG	DAP	VIB	BAR	LET	EAR
	PI	r	-0.864	-0.882	-0.730	-0.344	-0.563	-0.538	-0.612
		p	0.001	0.000	0.016	0.364	0.115	0.109	0.107
		n	10	11	10	9	9	10	8
	EC slope	r	0.759	0.765	0.910	0.545	0.628	0.517	0.818
		p	0.011	0.006	0.000	0.129	0.070	0.126	0.013
		n	10	11	10	9	9	10	8
	a

ACKNOWLEDGEMENTS

We wish to thank Dr C. Kretz-Rémy and cellular Stress Promoter Technology Corporation (TPSc Corp., Paris) for their scientific support. We are grateful to Dr E. Vindimian for his critical readings of the manuscript and modelling advising, and to the scientists of the Environmental Chemistry Unit at INERIS for the preparation of samples and the chemical analyses. Part of this study was supported by the french Ministère de l'Aménagement du Territoire et de l'Environnement and by the Budget Civil de la Recherche et du Développement (grant 97-028).

A-P. A. was supported by the Région Rhône-Aples.


Amin Kouniali

André Cicolella
email: andre.cicolella@ineris.fr

Norbert Gonzalez-Flesca

Roland Dujardin

Jean-François Gehanno

Frédéric Y Bois

ENVIRONMENTAL BENZENE EXPOSURE ASSESSMENT FOR PARENT-CHILD PAIRS IN ROUEN, FRANCE

Keywords: MA, trans,trans-muconic acid, HQ, hydroquinone, r, Pearson's correlation coefficient Benzene, Exposure, Children, trans,trans-muconic acid, Hydroquinone, Urine

There is a lack of data on children environmental benzene exposure. In this study we compared personal benzene exposure and inhalation uptake in a group of children to those of their parents. We also compared levels of urinary benzene metabolites, trans,trans-muconic acid (MA) and hydroquinone (HQ), for those two groups, and assess the correlation between personal benzene exposure and urinary MA and HQ concentrations.

The study was performed on twenty-one, 2-to 3-year-old children and their parents recruited on a voluntary basis among non smokers from the three largest day care centers of the town of Rouen in France. Average benzene concentrations were measured over 5 consecutive days with diffusive samplers. The following simultaneous measurements were carried out: personal exposure of the parents, concentrations inside and outside the day care centers and inside the volunteer's bedrooms. Morning and evening urine samples were collected during the same period.

Benzene personal exposure levels were 14.4 7.7 µg/m 3 and 11.09 6.15 µg/m 3 in parents and children respectively. Benzene inhalation uptake estimates were 2.51 1.23 µg/kg-day in the group of parents and 5.68 3.17 µg/kg-day in the group of children.

Detectable levels of MA and HQ were found in 85 % and 100 % of the samples respectively.

Intra-individual variation of urinary MA and HQ concentrations expressed as a coefficient of variation (CV) ranged from 63 to 232 % and from 13 to 144 %, respectively. Mean values of MA and HQ (in mg/g creatinine) were 1.6-and 1.8-fold higher in the group of children than in the group of parents (p = 0.008 and p < 0.0001 respectively).

Significant correlations between metabolites levels and benzene were not found.

Introduction

Environmental benzene exposure is potentially an important health concern. Benzene is an ubiquitary pollutant [START_REF] Wallace | The exposure of the general population to benzene[END_REF] and severe adverse health effects have occurred in occupationally exposed workers (US-EPA, 1997). It is clearly established and accepted that benzene exposure can cause acute non-lymphocytic leukemia and a variety of other bloodrelated disorders in humans (US-EPA, 1997).

The evaluation of risk posed by exposure to relatively low concentrations of benzene from occupational and environmental source is an active area of research. Benzene cancer risk assessments generally rely upon observations made in occupationally exposed population.

The effect of exposure to benzene could potentially be different in children. However, there are insufficient data on differences in metabolism between adults and children for benzene (US-EPA, 1998). Moreover, environmental benzene exposure data in children are very limited.

Children are likely to have higher benzene uptake per unit body weight than adults because of their heightened activity, as well as different ventilation volumes per time and ventilation frequency (US-EPA, 1997). Infants and children may be more vulnerable to leukemogenesis because their hematopoietic cell populations are differentiating and undergoing maturation (US-EPA, 1998). [START_REF] Weaver | Benzene exposure, assessed by urinary trans,trans-muconic acid, in urban children with elevated blood lead levels[END_REF] conducted a pilot study to evaluate the feasibility of using trans,trans-muconic acid (MA) as a biomarker for environmental benzene exposure in urban children. In a recent study conducted on 144 children living in Italy, [START_REF] Amodio-Cocchieri | Evaluation of benzene exposure in children living in Campania (Italy) by urinary trans,trans-muconic acid assay[END_REF] also used MA as a biomarker for environmental exposure. Measurements of benzene biomarkers, which can provide information on individual variation in absorption and metabolism and, thus susceptibility to adverse health effects, appear to be useful in the case of benzene.

Our study's aim was to investigate the possibility that children are more susceptible than adults to benzene exposure. To minimize the impact of genetic and lifestyle differences, we (A) compared the personal benzene exposure and inhalation uptake in a group of children to those of their parents after performing personal, indoor and outdoor measurements. We also (B) compared levels of urinary MA and hydroquinone (HQ), another benzene metabolite, for those two groups. Moreover, we (C) examined the correlation between personal benzene exposure and urinary MA and HQ concentrations.

Materials and methods

Study design

Study participants were recruited from the three largest public day care centers of the town of Rouen in France (each frequented by more than 60 children). A letter of solicitation had been sent by the director of each day care center to families meeting to certain criteria. The targeted population was non-smoking parents of "clean" children (needing no diapers), 2 to 3 years old. Father, mother or both were invited to participate with their children(s) in the study. Of the 50 families that were invited, 43 members of 20 families participated (individual written consents were collected) in the survey: twenty-one children (16 females and 5 males) and 22 non-smoking parents (17 mothers and 5 fathers). Their distribution within day care centers is given in the Table 1. Day care center B had 3 independent sections (sections 1, 2 and 3).

The measurement campaigns were conducted over the working week (Monday morning to Friday evening) (Table 1). Two urine samples were collected per day, one in the morning (between 7:00 and 10:00), the other in the evening (between 18:00 and 21:00). They were stored at -20°C until analysis.

In order to evaluate benzene exposure of the subjects, indoor measurements were carried out in parents and children's bedrooms and in the day care centers. Passive samplers used for indoor monitoring were attached to ad hoc supports, 1.5 m above the floor level. To measure background levels around the day care centers, outdoor monitoring was conducted in the front of the centers by placing samplers inside purpose-built aluminum shelters, attached at a height of 3 m. Each parent also carried one personal sampler within his/her breathing zone. This personal sampler was left open during the night in the bedroom according to a method previously described [START_REF] Gonzalez-Flesca | Benzene exposure assessment at indoor, outdoor and personal levels. The French contribution to the LIFE MACBETH programme[END_REF]. All of the parents worked indoors in an office. All sampling was carried out by passive means, which allows determination of an average concentration for the whole exposure period (from Monday morning to Friday evening).

Chemicals analysis 2.2.1. Benzene air concentrations

Benzene was sampled using Radiello Perkin Elmer (RPE) axial diffusive samplers assembled and validated at INERIS. Analyses were performed on an automatic thermal desorption apparatus (ATD400, Perkin Elmer) linked to Chrompack CP-9002 gas-chromatograph equipped with FID and a Chrompack Column (CP-Sil 5CB; 50 m 0.32 mm od; Film thickness 1.2 µm; Chrompack, The Netherlands). A full description and details of RPE validation is given elsewhere [START_REF] Bates | Ambient VOC monitoring by diffusive sampling. Compatibility of high uptake rate samplers with thermal desorption[END_REF].

MA concentrations in urine

A high-performance liquid chromatography (HPLC) method adapted from that of [START_REF] Ducos | Improvement in HPLC analysis of urinary trans,trans-muconic acid, a promising substitute for phenol in the assessment of benzene exposure[END_REF] and Lee et al. (1993a) was used. Two ml of urine sample were adjusted to pH 4.5-5.7 with concentrated HCL and then applied on a Bond Elut extraction cartridge filled with 500 mg of SAX sorbent (Varian, France) (preconditioned with 3 ml of acetonitrile and 3 ml of distilled water) at a flow rate of 0.5 ml/min using a Rapid-Trace automatic peristaltic pump from Zymarck (France). After the addition of urine, the cartridge was washed 3 times with 3 ml of 1 % acetic acid at 2 ml/min, 5 ml of distilled water at 20 ml/min, and 5 ml of acetonitrile at 20 ml/min. MA was finally eluated with 4 ml of 10 % acetic acid at 0.5 ml/min. Twenty microliters of this eluate was injected in the chromatograph for analysis (Varian 9012 equipped with an UV detector 9050). The HPLC column was a SAX C18 5 µm (25 cm 4.6 mm) analytical column. Chromatography was isocratic in a mobile phase consisting of glacial acetic acid, 1 M sodium acetate, and methanol (4.5/1.8/100 ml) q.s.f. 1000 ml of water at pH 3.0 at a flow rate of 1.5 ml/min. UV detection of MA was performed at a wavelength of 265 nm. All chemicals and water used were HPLC grade (Aldrich, France). MA stock, working standard solutions, and calibration curves were obtained according to [START_REF] Ducos | Improvement in HPLC analysis of urinary trans,trans-muconic acid, a promising substitute for phenol in the assessment of benzene exposure[END_REF]. The MA detection limit, obtained from spiked urine calibration curves, was 20 µg/l.

HQ concentrations in urine

Urinary HQ was measured according to the method described by Lee et al. (1993b) with minor modifications. Briefly, a 1 ml urine sample (previously adjusted to pH 4.5-5.3) was hydrolyzed with 0.1 ml of concentrated hydrochloric acid at 100°C for 120 min. Following cooling to room temperature, the sample was extracted with 2 ml of diethyl ether. Twenty microliters of the extract were then injected in the chromatograph (Varian 9012 equipped with a fluorometric detector 9070 and an ODS 5 µm n° 241 analytical column) with fluorimetric detection ( ex 304 nmem 338 nm). The HQ detection limit was 20 µg/l.

Creatinine concentrations in urine

Creatinine was measured using the Unimate Kit (Roche, France). Absorbance was measured in a Cobas spectrophotometer (Roche, France). The results were used to correct MA and HQ concentrations for urine dilution and expressed as micrograms of MA or HQ per gram of creatinine .

Computation of children personal exposure

As it was impractical to equip the children with passive samplers, we estimated the personal exposure of the children by computing the time-weighted average of the bedroom, day care center and outdoors benzene concentrations for each child. We assumed the average time spent at home, in the day care center, and outdoors to be 15, 8, and 1 hour respectively.. Calculations were therefore carried out as follows:

Personal exposure = (measured bedroom concentration x 15/24) + (mean concentration inside the day care center x 8/24) + (mean concentration outside of the day care center x 1/24).

Computation of subjects benzene inhalation uptake

We estimated personal benzene inhalation uptake for each subject as the product of average daily inhalation rate by personal benzene exposure. We assumed the daily inhalation rate for a male child (0.5 -< 3 years; mean body weight = 14 kg), a female child (0.5 -<3 years; mean body weight = 11 kg), a male adult (30 -< 60 years; mean body weight = 80 kg) and a female adult (30 -< 60 years; mean body weight = 68 kg) to be 0.52, 0.51, and 0.2, 0.16 m 3 /kg-day, respectively (US-EPA, 1997).

Statistical analysis

Descriptive statistics, mean differences, and regression lines were calculated using Statistica 5.5 software (Statsoft, Inc., 1997). All statistical tests and correlation analyses corrected the highly skewed distributions of the measured concentrations by natural logarithmic transformation. Values below the limit of detection (LD) were set at half its level for data analysis.

Mean differences between groups (Children vs. Parents) were evaluated using paired t-test.

Results

Objective A. Comparison of the personal benzene exposure and inhalation uptake

The box-plot in Figure 1 summarizes the distribution (min., lower quartile, median, upper quartile and maximum) of benzene concentrations in parents and children bedrooms, as well as of their personal exposures. There were no significant differences between the parent's and children's bedrooms concentrations (9.1 6.2 vs. 10.9 7.2; p = 0.16) whereas the personal exposure of the parents were higher than their bedroom concentrations (14.4 7.7 vs. 9.1 6.2; p < 0.002). The mean calculated personal exposure of the children was (11.09 6.15 µg/m 3 ) significantly lower than the parent's personal exposure (p = 0.04). Table 2 shows the mean indoor and outdoor concentrations of the day care centers. Despite a higher exposure of the parents, the mean of the estimated benzene inhalation uptake for children was higher than for parents: 5.68 3.17 µg/kg-day vs. 2.51 1.23 µg/kg-day (p < 0.0001).

Objective B. Comparison of urinary MA and HQ levels

The urinary MA and HQ concentrations, with and without creatinine adjustment, are shown in Table 3. The total number of urinary samples obtained from adults and children are, respectively, 200 on 220 foreseen (91%) and of 183 on 210 foreseen (87%). Quantifiable levels of MA were found in 315 of 380 samples (83 %). Quantifiable levels of HQ were found in all samples. A slight correlation was found between MA and HQ concentrations (r = 0.13, p = 0.012, n = 380). Concentrations of urinary MA analyzed during 5 days of sampling ranged for children and parents from 0.01 to 13.47 mg/g creatinine and from 0.004 to 9.04 mg/g creatinine, respectively. Concentrations of urinary HQ ranged for children and parents from 0.14 to 24.75 mg/g creatinine and from 0.01 to 21.72 mg/g creatinine respectively. Intraindividual variation of urinary MA concentrations expressed as a coefficient of variation (CV) ranged from 63 to 137 % for children and from 69 to 232 % for parents. Intra-individual variation of urinary HQ concentrations ranged, in children and adults, from 13 to 144 % and from 40 to 107 %, respectively. The differences in urinary MA and HQ levels between children and parents were examined. The geometric mean values of MA (mg/l), HQ (mg/l) and creatinine (g/l) in the group of parents were 1.7-, 1.5-, and 2.6-fold higher than the mean concentration of these compounds in the group of children. On the other hand, the mean values of MA and HQ normalized against creatinine (mg/g creatinine) were 1.6-and 1.8-fold higher in the group of children than in the group of parents. The differences in the mean concentrations of MA and HQ (mg/g creatinine) between children and parents were significant in all cases (Table 3). ANOVA analyses (un-paired) of the simultaneous impact of three factors: age, sex and time of examination, on MA concentrations in urine indicated no significant effect of these variables. HQ levels were only significantly influenced by age (p = 0.024) (Figure 2). The points in Figure 2 correspond to arithmetic means of log transformed values of HQ.

Objective C. Correlation between exposure and urinary metabolite levels

No statistically significant correlations were found between benzene exposure means and urinary metabolites levels. In the group of parents, benzene personal exposure was most correlated with Friday evening urinary MA and HQ concentrations, r = 0.54 (n=16) and r = 0.65 (n = 16), respectively. The lowest correlation was obtained for Monday evening, r = 0.05 (n=16) and r = 0.09 (n = 16), respectively. In the group of children, calculated benzene personal exposure was most correlated with the average urinary MA concentration, r = 0.51 (n = 21). Other r values with daily samples were between 0.03 and 0.38. Lower correlations were found between calculated benzene personal exposure and urinary HQ concentrations.

For the group of parents and children, uptake was similarly uncorrelated to MA and HQ levels (exposure and uptake are linearly related by the inhalation rate factor).

Discussion

Our atmospheric measurements show that the personal exposure of adults is generally higher (14.4 7.7 µg/m 3 ) than indoor and outdoor benzene levels (9.1 6.2 µg/m 3 ; 3.5 0.3 µg/m 3 ).

Since it was not possible to equip young children with personal samplers, we estimated their personal exposure on the basis of time-weighted average concentrations. This estimated exposure (11.09 6.15 µg/m 3 ) is significantly lower than the measured exposure of the parents. Children's exposure may be underestimated because microenvironments like inside cars, smoky places, etc, have relatively high benzene concentrations and could not be taken into account [START_REF] Gonzalez-Flesca | Benzene exposure assessment at indoor, outdoor and personal levels. The French contribution to the LIFE MACBETH programme[END_REF]. However, the children of our study are very young and their activity patterns are less varied than their parent's. [START_REF] Raaschou-Nielsen | Ambiant air levels and the exposure of children to Benzene, Toluene, and Xylenes in Denmark[END_REF] observed in 98 children aged between 4 and 12 years, equipped with personal monitors, a median personal exposure to the benzene of 5.4 µg/m 3 for 56 children living in an urban area and 4.5 µg/m 3 for 40 children living in a rural area. Indoor measurements show unusually high indoor concentrations of benzene in day care center B, section 1 (Table 2). In that area the level was 35.5 µg/m 3 versus a next highest level of only 11.1 µg/m 3 center B, section 2. This is probably due to repair and maintenance work (painting, new floor materials…) that took place within 2 months before our measurements. At the request of the day care center B, control measurements made one-year later showed benzene levels close to those of day care centers A and C.

Comparison with studies in children and adults not occupationally exposed shows that our MA results are generally higher than the means reported for adults [START_REF] Dor | Validity of biomarkers in enviromental health studies : The case of PAHs and benzene[END_REF][START_REF] Scherer | Analysis and evaluation of trans,trans-muconic acid as a biomarker for benzene exposure[END_REF] and children [START_REF] Amodio-Cocchieri | Evaluation of benzene exposure in children living in Campania (Italy) by urinary trans,trans-muconic acid assay[END_REF][START_REF] Weaver | Benzene exposure, assessed by urinary trans,trans-muconic acid, in urban children with elevated blood lead levels[END_REF]. Several reasons for these high values are possible. Misidentification of MA and HQ is unlikely since both retention time and UV absorbance by diode array detection were used for HPLC confirmation. However, ingestion of foods containing sorbic acid-based preservatives has the potential to increase MA excretion so significantly that MA may not be a sensitive biomarker for environmental benzene exposures. [START_REF] Weaver | Lack of specificity of trans,trans-muconic acid as a benzene biomarker after ingestion of sorbic acid-preserved foods[END_REF] found that ingestion of refrigerated flavored drinks and sweet snack foods resulted in the excretion of large amounts of MA in adults and children. An average MA peak of 0.45 mg/g creatinine was found in five adults after ingestion of a flavored drink and a mean of 0.67 mg/g creatinine was found in 6 adults after ingestion of a cupcake. Several other studies have addressed the potential effect of sorbic acid on MA specificity [START_REF] Ducos | Improvement in HPLC analysis of urinary trans,trans-muconic acid, a promising substitute for phenol in the assessment of benzene exposure[END_REF][START_REF] Pezzagno | The specificity of trans,trans-muconic acid as a biological indicator of low levels of environmental benzene[END_REF][START_REF] Pezzagno | Trans,trans-muconic acid, a biological indicator to low levels of environmental benzene: some aspects of its specificity[END_REF][START_REF] Renner | Determination of sorbic acid in urine by gas chromatography-mass spectrometry[END_REF][START_REF] Ruppert | Trans,trans-muconic acid as a biomarker of non-occupational environmental exposure to benzene[END_REF]. Ingestion of different amounts of sorbic acid (200-600 mg) can result in an increase of MA levels (in spot or 24h urine samples) from a baseline below the limit of detection to 90-fold greater MA level. Ingestion of preserved food varies from one country to another. Therefore, it is likely that sorbic acid ingestion is a factor in the variable correlation between MA and benzene exposure measurements reported in the literature. Some authors have found significant correlations between benzene in air and MA levels in 24 non-smoking bicyclists [START_REF] Bergamaschi | Biomarkers of dose and susceptibitity in cyclists exposed to monoaromatic hydrocarbons[END_REF]. Others, however, have not found significant correlations, at occupational exposure levels lower than 0.25 ppm [START_REF] Gobba | Inter-individual variability of benzene metabolism to trans,trans-muconic acid and its implications in the biological monitoring of occupational exposure[END_REF][START_REF] Ong | Biomarkers of exposure to low concentrations of benzene: a field assessment[END_REF]. In addition, several authors have reported the occasional observation of unexpectedly high MA levels in non-occupationally exposed control subjects [START_REF] Gobba | Inter-individual variability of benzene metabolism to trans,trans-muconic acid and its implications in the biological monitoring of occupational exposure[END_REF][START_REF] Isabell | Use of biomarkers in an indoor air study: Lack of correlation between aromatic VOCs with respective urinary biomarkers[END_REF][START_REF] Johnson | Perspectives on risk assessment impact of recent reports on benzene[END_REF][START_REF] Qu | Validation of biomarkers in humans exposed to benzene: urine metabolites[END_REF][START_REF] Weaver | Benzene exposure, assessed by urinary trans,trans-muconic acid, in urban children with elevated blood lead levels[END_REF]. The French mean daily intake of sorbic acid and its salts was estimated at 2.63 mg/kgday which corresponds to 184 mg/day ingestion for a 70 kg adult [START_REF] Verger | Estimation of the distribution of the maximum theoretical intake for ten additives in France[END_REF].

In our study, benzene personal exposures were not significantly correlated with urinary MA concentrations. This suggests that in the absence of a measure or control of sorbic acid intake, urinary MA is not a reliable biomarker for benzene exposure [START_REF] Sanguinetti | Failure of urinary trans,transmuconic acid as a biomarker for indoor environmental benzene exposure at ppb levels[END_REF].

Our HQ mean concentrations were also higher than the mean concentrations observed in occupationally exposed adults (Lee et al., 1993b;Ong, C. N. et al., 1994;Ong, C.N. et al., 1994;[START_REF] Rothman | Urinary excretion of phenol, catechol, hydroquinone, and muconic acid by workers occupationally exposed to benzene[END_REF]. Relatively few studies have been conducted to examine the relation between urinary HQ and benzene exposure since the common ingestion of dietary phenol contributes to the urinary excretion of HQ [START_REF] Decaprio | The toxicology of Hydroquinone -Relevance to occupational and environmental exposure[END_REF]. However, a better correlation between HQ and benzene exposure (< 0.25 ppm) than between MA and benzene exposure was observed in occupationally exposed subjects (r = 0.44, p < 0.01 and r = 0.14, p < 0.05, respectively) [START_REF] Ong | Biomarkers of exposure to low concentrations of benzene: a field assessment[END_REF]. The inter-individual variability of our HQ concentrations was lower than those of MA (from 13 to 144 % vs. 63 to 232 %, respectively). HQ levels were also significantly influenced by the age (Figure 2). In the absence of control or precise estimation of confounding factors (sorbic acid ingestion, intake of food-borne phenolic compounds…), MA and HQ do not appear to be specific marker of low benzene exposures.

Despite these concerns about the sensitivity of MA and HQ as environmental benzene biomarkers, our results show that the creatinine adjusted levels of MA and HQ were higher in the urine of children than in that of parents (Table 3). It is common practice to adjust the analytical values determined in spot samples of urine with creatinine concentration in order to correct for varying dilution of urine [START_REF] Araki | Filterable plasma concentration, glomerular filtration, tubular balance, and renal clearance of heavy metals and organic substances in metal workers[END_REF][START_REF] Greenberg | Urinary creatinine excretion is not stable: a new method for assessing urinary toxic substance concentrations[END_REF][START_REF] Ong | Biomarkers of exposure to low concentrations of benzene: a field assessment[END_REF]. Dilution of urine fluctuates considerably in a given subject during the day, especially after ingestion of liquids or sweating. [START_REF] Weaver | Benzene exposure, assessed by urinary trans,trans-muconic acid, in urban children with elevated blood lead levels[END_REF] observed that the creatinine urine levels were significantly lower in nondetectable MA urine samples. Creatinine adjustment therefore removes potentially significant source of bias and variation in urine concentration of MA and HQ. However, a strong correlation exists between creatinine elimination rate and body mass [START_REF] Boeniger | Interpretation of urine results used to assess chemical exposure with emphasis on creatinine adjustements: a review[END_REF]. Because of this, benzene metabolite concentrations in urine are higher in adults than in children when unadjusted for creatinine, while the inverse is found with creatinine-adjusted concentration. This apparent paradox is explained away when one realizes that concentration values expressed as mg/g of creatinine approximate values expressed as mg/kg of body mass which is a better measure of internal exposure. Therefore, adults in our study, because of their high total benzene uptake, excrete more benzene metabolites per unit time. However, internal exposure of the children to benzene or its metabolites, when assessed by unit of body mass, is higher than that of their parents. Children might metabolize a higher proportion of benzene to MA and HQ than adults. It is also possible as discussed by [START_REF] Gobba | Inter-individual variability of benzene metabolism to trans,trans-muconic acid and its implications in the biological monitoring of occupational exposure[END_REF] that there may exist in the general population "poor MA metabolizers" and "efficient MA metabolizers". In addition, children in our study have a higher benzene uptake per unit of body mass than adults. Benzene inhalation uptake per kg was twice higher in our group of children than in our group of parents. The mechanism(s) of leukemia induction by benzene are not yet fully understood. Unlike benzene exposure, administration of phenol, a major metabolite of benzene, to rats does not induce hematotoxicity (US-EPA 1998), whereas Witz et al. (1996) have demonstrated that trans, trans-muconaldehyde, a precursor of MA, is myelotoxic in mice. It has been hypothesized that combinations of hydroquinone and phenol, or muconaldehyde and hydroquinone, may be involved leukemogenesis [START_REF] Eastmond | An interaction of benzene metabolites reproduces the myelotoxicity observed with benzene exposure[END_REF]. This could apply to benzene induced leukemia but could also be the basis for a link between leukemia and dietary factors [START_REF] Mcdonald | Hypothesis: phenol and hydroquinone derived mainly from diet and gastrointestinal flora activity are causal factors in leukemia[END_REF]. We found that children excrete relatively higher levels of MA and HQ (when expressed in mg/g creatinine) than adults. Therefore, they may be at relatively higher risk of developing leukemia, independently of benzene exposure. b geometric mean and geometric standard deviation.

c 2-tail significance of differences between geometric means by paired Student's t-test on log-transformed data for 21 parents and their 21 children (for the male child with with 2 participating parents, only the father was kept for pairing).

d number of observations. e Not Detected.

Figure 1 .

 1 Figure 1. Box-plot showing the distribution of the parent's and children personal exposure as well as the bedroom's indoor concentrations (µg/m 3 ).

Figure 2 .

 2 Figure 2. Concentration of urinary HQ of children and parents on the time of sampling with

Table 1 :

 1 Characteristics of the study population.

	Day care	Location	Date of sampling	Number of	Number of	Number of parents*
	center			families	children
	A	Town center	25 -29/oct/99	9	10	10
	B section 1	Town center	29/nov -3/dec/99	2	2	2
	B section 2	Town center	29/nov -3/dec/99	2	2	2
	B section 3	Town center	29/nov -3/dec/99	2	2	2
	C	Out of town	22 -26/dec/99	5	5	6
	Total			20	21	22
	* Father, mother or both.

Table 2 .

 2 Mean benzene concentrations in the three day care centers (µg/m 3 ).

	Day care center		Indoor		Outdoor
		n	Mean SD	n	Mean SD
	A	8	10.5 1.9	6	5.0 2.1
	B section 1	4	35.5 13.5	2	7.6 0.3
	B section 2	4	11.1 6.9	2	7.6 0.3
	B section 3	4	9.1 5.0	2	7.6 0.3
	C	5	7.9 3.4	6	3.5 0.3
	n = number of observations.

Table 3 .

 3 Summary statistics for the urinary levels of MA, HQ and creatinine in a group of parents and their children.

	Variable		Parents (n = 22)			Children (n = 21)			p c
		Mean (SD) a GM (GSD) b	Min	Max d	Mean (SD) a GM (GSD) b	Min	Max Obs d
	MA (mg/ l)	0.78 (1.43)	0.22 (6.21)	ND e	14.01 199	0.42 (0.91)	0.13 (5.41)	ND e	9.79	183	< 0.001
	MA (mg/g creatinine)	0.73 (1.24)	0.21 (6.29) 0.004	9.04 199	0.85 (1.40)	0.31 (4.85)	0.01	13.47 181	0.008
	HQ (mg/l)	2.50 (2.42)	1.20 (2.77)	0.01	27.67 200	1.11 (0.99)	0.78 (2.44)	0.05	6.63	179	< 0.0001
	HQ (mg/g creatinine)	1.69 (2.20)	1.09 (2.60)	0.01	21.72 200	2.51 (2.43)	1.89 (2.10)	0.14	24.75 177	< 0.0001
	Creatinine (g/l)	1.24 (0.59)	1.09 (1.75)	0.20	2.74 200	0.49 (0.30)	0.41 (1.85)	0.05	2.31	183	< 0.0001

a arithmetic mean and arithmetic standard deviation.

ACKNOWLEDGMENTS

We would like to thank the children and parents who participated in this study. We are also grateful to the staff of the day care centers and the town council of Rouen for their support and assistance in this project. We wish to express our thanks to Mrs N. François, Mrs A. Frézier, Mrs C. Gillet, Mr D. Granier and Mr J-C Pinard for their analytical and technical assistance. This study was supported in part by the French PREDIT-PRIMEQUAL (Inter-ministerial land transport research and innovation program) (grant n° P20580) and the French Agency for Environment and Energy Management (ADEME) (grant n° BOU9930)