Simon Villain-Guillot

Alois Würger

Thermal di¤usion in a binary liquid due to recti…ed molecular ‡uctuations

The Soret motion in binary liquids is shown to arise to a large extent from recti…ed velocity ‡uctuations. From a hard-bead model with elastic collisions in a non-uniform temperature, we derive a net force on each molecule, which is proportional to the temperature gradient and depends on the ratio of the molecular masses and moments of inertia. Our …ndings agree with previous numerical simulations and provide an explanation for the thermal di¤usion isotope e¤ect observed for several liquids.

Non-equilibrium ‡uctuations may rectify the motion of a Brownian particle and give rise to directed di¤usion [1,2]. Noise-driven transport has been studied extensively in terms of ratchet models, where the broken symmetry is realized by a random force with zero mean and asymmetric spectrum, a saw-tooth like potential with a periodic time-dependent temperature pro…le, or non-uniform chemical reactions. Applications range from molecular motors to electron transport in quantum devices [2].

The thermal di¤usion or Soret e¤ect describes motion due to a temperature gradient [START_REF] De Groot | Non-equlibrium Thermodynamics[END_REF]. From kinetic theory it is known that in a gas mixture the lighter atoms move to the warm, the heavier ones to the cold [START_REF] Chapman | The Mathematical Theory of Non-uniform Gases[END_REF]. It has been realized early that this e¤ect can be used for isotope separation [START_REF] Furry | [END_REF]. In contrast to gases, thermally driven motion in molecular liquids is less well understood [START_REF] Köhler | Thermal Nonequilibrium Phenomena in Fluid Mixtures[END_REF]7], despite a variety of available approaches [8][9][10][11]. Part of the complexity is due to the presence of two basically di¤erent driving mechanisms: The …rst one results from solute-solvent interactions such as electric-double layer and dispersion forces [12][13][14][15], and is particularly relevant for charged colloidal suspensions [16][17][START_REF] Duhr | Proc. Natl. Acad. Sci[END_REF]. The second one, which we are interested in here, relies on the thermal ‡uctuations of solute and solvent molecules.

Since velocity ‡uctuations are inversely proportional to the mass, they are expected to be most relevant for light molecules or atoms. This is con…rmed by the isotope e¤ects observed in experiments on molecular liquids [START_REF] Rutherford | [END_REF][20][21][22] and by numerical simulations [23][24][25][26]. Thus Debuschewitz and Köhler reported that protonated benzene in cyclohexane migrates to higher temperatures, whereas deuterated benzene goes to the cold side [20]. Even more strikingly, the benzene isotopes 12 C 6 D 6 and 13 C 6 H 6 , which have equal mass but di¤erent moment of inertia, vary signi…cantly in their thermal di¤usion behavior, thus hinting at the role of rotational di¤usion.

In the present paper we study how velocity ‡uctuations and rotational di¤usion a¤ect the Soret e¤ect of a binary liquid. Thermal noise acts as a random force f and results in molecular Brownian motion. In thermal equilibrium the mean force is zero. In a non-equilibrium system, however, its average F = hf i does not necessarily T ∇ 1: Schematic view of a binary liquid of non-spherical molecules. The two species have equal volume but di¤erent mass and di¤erent moment of inertia. vanish and may result in a steady-state velocity

u = F ; (1)
where the Stokes friction coe¢ cient is given by the correlation hf (t)f (0)i. Our main purpose is to relate this drift term to the non-uniform temperature that appears in the molecular velocity distribution functions. The random force is described by the momentum p transferred from colliding neighbor molecules, f = P i p (t t i ).

Its average value reads

F = p ; (2)
where is the time separating two subsequent collisions. The conservation laws are evaluated explicitly for a hardbead model with elastic collisions, giving F as a function of the molecular masses and moments of inertia. The model is shown in Fig. 1, which in particular illustrates the importance of translation-rotation coupling for nonspherical molecules.

In the absence of an external potential, the weighted average of the forces F a and F b exerted on each component vanishes. For molecules of equal size this condition simpli…es to a F a + b F b = 0;

(3)

T 0 T L T R v 1 v 2 T 0 T L ω 1 ω 2 b v 1 b v 2 b T v 2 v 1 0 l FIG.
2: Schematic view of two-particle elastic collisions. The left panel shows a frontal impact with the second particle coming from the left (v2 > v1) or from the right (v2 < v1).

Because of the non-uniform temperature, the velocity distribution of each particle is with respect to a particular value, TL < T0 < TR. In terms of the constant gradient rT , the di¤erences read bT rT . The right panel shows the case of non-zero impact parameter b. The upper example illustrates an initial state with linear velocity and zero angular velocity (!i = 0), and the lower one the opposite case with …nite !i and zero vi. In both cases linear momentum p is transferred during the collision, according to Eq. ( 11). Only collisions from the left side are shown.

where the volume fractions satisfy a + b = 1. The momentum transfer p depends on the linear and angular velocities of both molecules. Elastic collisions of two rigid particles satisfy the conservation laws

E 0 1 + E 0 2 = E 1 + E 2 ; p 0 1 + p 0 2 = p 1 + p 2 ; (4)
0 1 + 0 2 = 1 + 2 ;
where p i = m i v i denotes the linear momentum, i the angular momentum, and

E i = p 2 i =2m i + 2 i =2I
i the kinetic energy with the moment of inertia I i . The primed quantities describe the state after the collision. In three dimensions there are seven independent equations for twelve unknown variables; an unambiguous …nal state is determined by …ve additional conditions for the collision.

Here we study a one-dimensional model where p and are taken as scalars. In a …rst approach we neglect the angular momentum and consider frontal collisions only, as illustrated in the left panel of Fig. 2. From the conservation laws for E and p, one readily obtains the momentum transfer p = p 0 1 p 1 in terms of the initial state,

p = 2 12 (v 2 v 1 ); (5)
with the reduced mass

1= 12 = 1=m 1 + 1=m 2 .
A net force arises from the fact that the thermal average in (2) has to be done with a particular temperature for each particle. The position of molecule 1 de…nes a reference temperature T 0 , whereas that of particle 2 may be lower or higher, depending on its relative position, as illustrated in the left panel of Fig. 2. As an important quantity, the collision rate 1= is a function of temperature and velocity. In order to keep the algebra as simple as possible, we adopt from the beginning the form

1= = jv 2 v 1 j=`; (6)
which is proportional to the relative velocity. The momentum transfer is positive for collisions from the left, that is for v 2 > v 1 ; inserting p and the rate in (2) one …nds

p L = 2 12 Z 1 1 dv 1 Z 1 v1 dv 2 ' 1 ' 2 (v 2 v 1 ) 2 `L ;
with the Maxwell velocity distribution function

'(v) = (2 hv 2 i) 1 2 e 1 2 v 2 =hv 2 i .
A similar expression of opposite sign arises from neighbor molecules coming from the right, where v 2 < v 1 . Because of the spatial variation of temperature and of the parameter `, these contributions do not completely cancel each other. Their di¤erence gives the net force on particle 1,

F 1 = 12 hv 2 1 i 0 + hv 2 2 i L `L hv 2 1 i 0 + hv 2 2 i R `R ; (7)
where 0; L; R indicate the molecular position. Now we determine the temperature dependence of the mean spacing `. We insert (7) with the mean velocity square hv 2 i i X = k B T X =m i in the constraint (3). Performing for both molecules 1 and 2 the average with respect to the species a and b, we obtain the condition

(T 0 + T L )=`L = (T 0 + T R )=`R; (8)
which means that `is determined by the mean temperature of the colliding molecules. This relation could be obtained equally well by requiring that the net force vanishes in a pure system, in other words, by putting F = 0 for an a-molecule in an a-environment.

The physical origin of the thermal force is best discussed in terms of the velocity ‡uctuations appearing in (7). Its positive and negative contributions arise from collisions with molecules at the left or at the right, with T L < T R . If particle 1 is much lighter than 2 (m 1 m 2 ), its mean square hv 2 1 i 0 = k B T 0 =m 1 dominates the numerators and, because of `L < `R, leads to a positive force to the hot side. In the opposite case m 1 m 2 , the numerators are proportional to T L and T R ; since `(T ) varies more weakly with T , the second term in (7) exceeds the …rst one, and the force takes a minus sign. Thus the temperature gradient acts like a recti…er on the molecular velocity ‡uctuations, which drives the heavier component to lower T , and the lighter one to the hot side.

Eq. ( 8) can be rewritten as `= `0(T + T 0 )=2T 0 , with constant `0. Replugging this expression in the force on an a-molecule, averaging the collision partner 2 with respect to composition, and expanding to linear order in the temperature variation, we …nd

F a = b b T `0 m b m a m b + m a k B rT: (9)
Here we have used T R=L = T 0 b T rT as de…ned in Fig. 2. The force on a molecule of the second species is obtained by exchanging the labels a and b; one readily veri…es the condition (3). It is noteworthy that F a vanishes in a pure a-system ( b = 0) and is maximum in a b-environment ( b = 1). Our expresson for F a compares favorably with early work for heavy Brownian particles, where F = k B rT [28]. This corresponds to our Eq. ( 9) for m a m b and b T = `0. The latter parameters are related to the molecular structure, which is hardly addressed in [28]. Now we take the angular momentum into account. Besides the three conservation laws (4), there is one condition relating the changes of momentum and angular momentum = 0 1 1 . In the one-dimensional model it takes the simple form

= b p; ( 10
)
where b is an impact parameter as illustrated in the right panel of Fig. 2. The four equations ( 4) and ( 10) determine the …nal state p 0 i ; 0 i in terms of the incoming quantities p i ; i , with the angular momentum i = I i ! i . In view of (2) we are mainly interested in the momentum transfer, and thus give its explicit expression

p = 2 1= 12 + b 2 =I 12 [v 2 v 1 + b(! 2 ! 1 )] ; (11)
with the reduced moment I 1 12 = I 1 1 +I 1 2 . For non-zero b both linear and angular velocities result in momentum transfer, as illustrated in the right panel of Fig. 2. In analogy to [START_REF] Köhler | Thermal Nonequilibrium Phenomena in Fluid Mixtures[END_REF], the collision rate reads 1= = jv 2 v 1 + b(! 2 ! 1 )j=`;

We consider separately collisions with non-zero velocities v i and angular velocities ! i . The …rst case is identical to the analysis between Eqs. ( 5) and ( 9), with the reduced mass replaced by the denominator in (11). Proceeding in the same way for the second case, where the center of mass of both moelcules is initially at rest (v i = 0), we merely have to replace the linear velocities v i with b! i . Inserting the mean square h! 2 i i = k B T =I i leads to a force similar to that of the …rst case, but with the moments of inertia instead of the masses.

Adding the contributions calculated independently for the cases ! i = 0 and v i = 0, we have

F a = b b T `0 k B rT; (12)
with the shorthand notation for the relative di¤erences of mass and inertia,

= m 1 a m 1 b + b 2 (I 1 a I 1 b ) m 1 a + m 1 b + b 2 (I 1 a + I 1 b ) : (13) -3 -2.5 -2 -1.5 -1
)

Ψ C6D6 -C6H12 C6HD5 -C6H12 C6H3D3 -C6H12 13 C 6 H 6 -C 6 H 12 C6H5D -C6H12 C6H6 -C6H12 C6D6 -C6D12 C 6 H 6 -C 6 D 12
FIG. 3: Isotope e¤ect on the Soret coe¢ cient ST of benzenecyclohexane mixtures. Black points are Debuschewitz and Köhler's experimental data at equal mole fractions [20]. The list of isotopes corresponds to the eight data points from the left to the right. The solid line is calcatuled from Eq. ( 14) with the ratio bT =`0 = 3:4 and the impact parameter b = 2:5 Å; the values of mi and Ii are taken from [20]. The vertical o¤-set S 0 T = 1:1 10 3 K 1 is indicated by the dashed line. With benzene as a-molecules, the …rst two data points correspond to > 0, and the remaining ones to negative .

For b = 0 we recover (9). In principle, this expression should be averaged over the parameters b, b T , `0. Moreover, in a general initial state both linear and angular velocities take non-zero values and should be considered simultaneously in (2). These modi…cations would encumber the algebra without signi…cantly modifying the net force.

Now we discuss the steady state resulting from the the drift velocity (1) and di¤usion with the Einstein co-e¢ cient D = k B T = . The current of the component a reads J a = Dr a + a u a and is opposite to that of b-molecules. The steady-state condition J a = 0 may be rewritten as [START_REF] De Groot | Non-equlibrium Thermodynamics[END_REF] r a + a b S T rT = 0;

where the Soret coe¢ cient S T describes the stationary non-uniform composition of the binary system. With this sign convention, a-molecules accumulate at lower temperature for S T > 0 and at higher T for S T < 0. From (1) and ( 12) one readily derives

S T = S 0 T + b T `0 T 0 ; (14)
where we have added a term S 0 T that accounts for molecular dispersion forces. Eqs. ( 12) and ( 14) consitute the main result of the present paper.

In Fig. 3 we plot data of Debuschewitz and Köhler for mixtures of benzene and cyclohexan• e [20]. Studying various isotopes that range from deuterated benzene and protonated cyclohexane (C 6 D 6 -C 6 H 12 ) to the opposite case C 6 H 6 -C 6 D 12 , these authors observed a strong mass e¤ect of the Soret coe¢ cient S T . Since the isotopes have very similar chemical properties and, in particular, the same van der Waals interaction potential, these data show unambiguously that thermal di¤usion varies with both molecular mass and moment of inertia. The dependence on the latter quantity is best displayed by comparing deuterated benzene C 6 D 6 and the protonated heavycarbon isotope 13 C 6 H 6 : These molecules have equal mass but di¤erent moment of inertia; their S T values di¤er by about 50 %.

The solid line in Fig. 3 is calculated from Eq. ( 14). With I i =m i 2:5 Å 2 for benzene and cyclohexane [20], the value for the impact parameter b = 2:5 Å implies that the angular velocity ‡uctuations k B T b 2 =I i are several times larger than the linear ones k B T =m i . Thus the quantity is determined by the moments of inertia rather than by the masses. In physical terms this means that the Soret e¤ect is mainly due to rotational di¤usion with the mean square angular velocity ! 2 i = k B T =I i . The vertical o¤set S 0 T describes thermally driven motion due to dispersion forces and thus is insensitive to a change of the molecular mass; its numerical value is taken from [20]. Thus the Soret coe¢ cient ( 14) consists of two terms, one of which depends on the composition and the other one on the molecular mass and inertia only [20,21]. This is con…rmed by several experiments that show that the mass and composition dependence of S T separates in additive contributions [20,21]. For components of comparable size, a linear variation of S 0 T with the volume fraction has been observed in accordance with simulations [27] and a simple mean-…eld model [15]. The Soret coe¢ cient (14) agrees with numerical simulations of Lennard-Jones and hard-bead systems. Several authors reported dependencies on mass and moment of inertia similar to (13) [23][24][25][26]. The ratio of the molecular mean distance b T and mean spacing `0 is related to the …lling factor; the linear variation of ( 14) compares favorably with simulation results at di¤erent densities [25]. The numerical value of b T =`0 used in Fig. 3 agrees with the molecular size b T 4 Å and the spacing between particles `0 1 Å.

The present one-dimensional hard-bead model considerably simpli…es the otherwise complex molecular collisions. The recti…cation of thermal ‡uctuations, as expressed by the mean-square velocities at di¤erent temperatures in Eq. (7), is insensitive to the model details and results in a net force proportional to rT with the coe¢ cient . The agreement of Eq. ( 14) with the isotope data and with numerical simulations [23][24][25][26] con-…rms that thermal di¤usion in binary liquids is to a large extent driven by recti…ed molecular ‡uctuations. Though similar e¤ects are expected to occur in macromolecular solutions [30], one should keep in mind that a polymer cannot be treated as a rigid body, thus requiring a re…ned picture for its collisions with solvent molecules.


Thorsten Schank
email: thorsten.schank@wiso.uni-erlangen.de

Claus Schnabel
email: claus.schnabel@wiso.uni-erlangen.de

Joachim Wagner
email: wagner@uni-lueneburg.de

Higher wages in exporting firms: self-selection, export effect, or both? First evidence from linked employer-employee data

Keywords: Exports, Wages, Exporter wage premium, Germany JEL Classifications F10, D21, J31

While it is a stylized fact that exporting firms pay higher wages than non-exporting firms, the direction of the link between exporting and wages is less clear. Using a rich set of German linked employer-employee panel data we follow over time plants that start to export. We show that the exporter wage premium does already exist in the years before firms start to export, and that it does not increase in the following years. Higher wages in exporting firms are thus due to self-selection of more productive, better paying firms into export markets; they are not caused by export activities.

large number of studies (surveyed in [START_REF] Schank | Do exporters really pay higher wages? First evidence from German linked employer-employee data[END_REF] with firm level data from many different countries. Some recent studies using linked employer-employee data have demonstrated that this positive link between export activities and the level of wages paid by a firm can even be found after controlling for observed and unobserved characteristics of both the employer and the employees. 1 An issue that, to the best of our knowledge, has not been investigated empirically with linked employer-employee data is the sequencing behind the correlation of export activities and higher wages at the firm level. Does exporting lead to a wage premium? Or did exporting firms pay a wage premium even before they started to export? Theoretical considerations point to possible links in both directions that are by no means mutually exclusive:

Hypothesis 1 (H1): The observed exporter wage premium reflects self-selection of more productive firms with higher wages into export markets. The recent literature on exporting by heterogeneous firms, pioneered by [START_REF] Melitz | The impact of trade on intra-industry reallocations and aggregate industry productivity[END_REF] and surveyed by [START_REF] Greenaway | Firm heterogeneity, exporting and foreign direct investment: A survey[END_REF], argues that only the more productive firms in an industry can bear the extra costs of entering foreign markets. In these models, exporters are more productive than non-exporters, and we observe self-selection of more productive firms into export activities, with the ex ante more productive firms becoming exporters. If wages are higher in more productive firms-due to higher profits and rent-sharing, or because higher (efficiency) wages cause higher productivity (see Akerlof and Yellen 1986) 2 -and if more productive firms selfselect into export markets, we expect that these future exporters already paid a wage premium to the workers ex ante, i.e. before they started to export.

1 See [START_REF] Munch | Human capital and wages in exporting firms[END_REF] for Denmark, [START_REF] Alcala | Firm characteristics, labor sorting, and wages[END_REF] for Spain, and [START_REF] Schank | Do exporters really pay higher wages? First evidence from German linked employer-employee data[END_REF] for Germany. Note, however, that [START_REF] Breau | Is there really an export wage premium? A case study of Los Angeles using matched employee-employer data[END_REF] find no wage difference between exporting and non-exporting plants after controlling for worker characteristics for the Los Angeles Consolidated Metropolitan Statistical Area. 2 [START_REF] Egger | Firm heterogeneity and the labour market effects of trade liberalization[END_REF] develop a model that incorporates workers' fair wage preferences into a general equilibrium framework a `la [START_REF] Melitz | The impact of trade on intra-industry reallocations and aggregate industry productivity[END_REF]. They modify the original [START_REF] Akerlof | The fair wage-effort hypothesis and unemployment[END_REF] fair-wage effort mechanism by introducing a rent-sharing motive as a determinant of workers' fair-wage preferences, assuming that the wage considered to be fair depends, among others, on the productivity level and thus on the performance of the firm. Identical workers then earn different wages in equilibrium, and higher wages are paid to employees working in more productive firms. They refer to [START_REF] Fehr | Fairness and retaliation: The economics of reciprocity[END_REF] who point out that the idea of gift exchange which is central to the fair-wage effort hypothesis implies exactly this. The theory of a positive correlation between productivity levels, profits and wages is well in line with empirical findings on rent-sharing in firms, as pointed out by [START_REF] Egger | Firm heterogeneity and the labour market effects of trade liberalization[END_REF]. A different approach of introducing efficiency wages into heterogeneous firms models of the [START_REF] Melitz | The impact of trade on intra-industry reallocations and aggregate industry productivity[END_REF] type is followed by [START_REF] Davis | Good Jobs, bad jobs, and trade liberalization[END_REF] who argue that heterogeneity in the ability of firms to monitor effort leads to different wages for identical workers in equilibrium, following the variant of the efficiency wage theory put forward by [START_REF] Shapiro | Equilibrium unemployment as a worker discipline device[END_REF]. If export starters are larger than non-exporters in the years before the start, and if monitoring costs are systematically higher in larger firms, this might lead to ex ante wage differentials for identical workers in future export starters and non-exporters. Furthermore, [START_REF] Amiti | Trade, firms, and wages: Theory and evidence[END_REF] introduce a fair-wage effort model into the Melitz framework and, in addition, provide some evidence for their theoretical hypotheses using Indonesian data. Also notable in this respect is a recent paper by [START_REF] Helpman | Understanding cross-country differences in exporter premia: Comparable evidence for 14 countries[END_REF] which produces wage differentiation across firms in a variant of the Melitz model in which labor market imperfections arise due to search frictions. This model generates a pure exporter wage premium even though productivity stays constant when a firm starts exporting. A similar result can be derived from a recent paper by [START_REF] Egger | Fairness, trade, inequality[END_REF].

Hypothesis 2 (H2): Exporting makes firms more productive and leads to higher wages. This hypothesis found in the literature on exports and productivity points to the role of learning-by-exporting (see [START_REF] Bernard | Exceptional exporter performance: Cause, effect, or both?[END_REF][START_REF] Bernard | Exports and success in German manufacturing[END_REF][START_REF] Baldwin | Export-market participation and productivity performance in Canadian manufacturing[END_REF]. Knowledge flows from international buyers and competitors help to improve the post-entry performance of export starters (see [START_REF] Crespi | Productivity, exporting, and the learning-by-exporting hypothesis: Direct evidence from UK firms[END_REF]. Furthermore, firms participating in international markets are exposed to more intense competition and must improve faster than firms which only sell their products domestically. Exporting thus makes firms more productive. If wages are higher in more productive firms due to higher profits and rentsharing, we may expect that exporting leads to higher wages. More specifically, this hypothesis predicts that after a firm has started to export, the wages of its employees increase stronger than the wages of employees who work in firms that continue to produce for the national market only, leading to an ex post exporter wage premium. 3Mainly due to a lack of suitable data at the level of individuals, these two hypotheses have not been convincingly investigated for wages. 4 Since empirical studies of exporter wage differentials must control for observed and unobserved characteristics of both employers and employees that might determine wages besides exporting, they have to use linked employer-employee (LEE) panel data. To investigate the relevance of both the self-selection hypothesis and the learning-byexporting hypothesis in explaining exporter wage differentials, LEE data are needed which cover a period that is long enough to follow cohorts of firms over a couple of years before and after they start to export, and which can be used to test for ex ante and ex post wage differentials. Apparently, such LEE data were not available until recently.

Using suitable LEE data for Germany, a leading actor on the world market for goods, this paper contributes to the literature by testing the two hypotheses mentioned above on the direction of the link between exporting and wages. 5 For the period 1994-2006, we show that the exporter wage premium does already exist in the years before firms start to export, and that it does not increase in the years after exporting started. According to our findings, higher wages in exporting firms are due to self-selection of more productive, better paying firms into export markets, but they are not caused by export activities.

The rest of the paper is organized as follows: Sect. 2 describes the LEE data. Section 3 presents the results of our empirical investigation, and Sect. 4 concludes.

The German linked employer-employee data

The data set used in the subsequent empirical analyses is the German LIAB, i.e. the linked employer-employee data set of the Institute for Employment Research (Institut fu ¨r Arbeitsmarkt-und Berufsforschung, IAB). The LIAB combines the Employment Statistics of the German Federal Employment Agency (Bundesagentur fu ¨r Arbeit) with plant level data from the IAB Establishment Panel. For detailed information on the LIAB, see [START_REF] Alda | The linked employer-employee dataset created from the IAB establishment panel and the process-produced data of the IAB (LIAB)[END_REF].

The employee side of our data set is the Employment Statistics, covering all employees and trainees subject to social security. They exclude, among others, the self-employed, family workers, a subgroup of civil servants (''Beamte''), students enrolled in higher education, and those in marginal employment. The employment statistics cover nearly 80% of all employed persons in western Germany and about 85% of employees in eastern Germany. They are collected by the social insurance institutions for their purposes according to a procedure introduced in 1973 and are made available to the Federal Employment Agency. Notifications are prescribed at the beginning and at the end of a person's employment in a plant. In addition, an annual report for each employee is compulsory at the end of a year. Misreporting is legally sanctioned. The employment statistics contain information on an employee's occupation, the occupational status, and gross earnings up to the contribution assessment ceiling,6 as well as on individual characteristics like sex, age, nationality, and qualification. Each personnel record also contains the establishment identifier, the industry, and the size of the plant.

The employer side of our data set is given by the IAB Establishment Panel, a random sample of establishments that is drawn from a stratified sample of the plants included in the Employment Statistics, where the strata are defined over industries and plant sizes (large plants are oversampled). In 1993, the panel started with 4,265 plants, covering 0.27% of all plants in western Germany (2 million) and 11 percent of total employment (29 million). In 1996, the establishment panel also started in eastern Germany with 4,313 establishments representing 1.1% of all plants (391,000) and 11% of total employment (6 million). The IAB Establishment Panel has been set up for the needs of the Federal Employment Agency to provide further information about the demand side of the labor market. Therefore, detailed information on the composition of the workforce and its development through time constitutes a major part of the questionnaire. Further questions include information on training and further education, wages, working time, business activities, establishment policies, and general information about the plant.

The LIAB is created by linking the Employment Statistics and the IAB Establishment Panel through a plant identifier which is available in both data sets. 7Because the Employment Statistics is spell-based (one record for each employment spell), the combined data is potentially complex. To simplify, we select all (fulltime) workers in the employment statistics who are employed by the surveyed plants on June 30th in a year. This yields an unbalanced annual panel of workers together with detailed information on the plants in which they work, which is unique for Germany. We are able to use the years 1994-2006, and we focus on the private sector. Finally, in order to avoid that the individual level estimates may be driven by a few very large plants we keep only plants which employ less than 1,000 workers in the first year they are observed.8

Empirical investigation

The core of our empirical strategy to test for the validity of the two hypotheses on export activities and higher wages consists in comparing over time wages in plants that start to export with wages in plants that continue to produce for the national market only. We start at a point in time when both groups of plants did not export, and end at a point in time when some of these firms have exported for a while. Using observation periods of 6 years, we define export starters as plants that do not export in the first 3 years (t = 1, 2, 3), but start to export in year t = 4 and continue to export in the years t = 5 and t = 6; non-exporters are plants that do not export in any of the years t = 1, …, 6.

Descriptive statistics

Using the LIAB data described in Sect. 2 above, the 6-year windows considered here are 1994-1999, 1995-2000,…, 2001-2006. Data for export starters and non-exporters were pooled over these eight cohorts, and wages and sales were deflated. Table 1 reports descriptive statistics for both groups of plants and each year t = 1, …, 6.

Since the design of our investigation requires establishments to be observed in six consecutive years and to show particular patterns of export behavior, the sample available for our empirical investigation reduces to 70 export starters and 3,517 nonexporters. A comparison of plants from both groups with regard to size (number of employees), labor productivity (sales per employee) and wages paid (average daily wage) reveals that export starters are on average larger, more productive, and better paying in each year. Compared to non-exporters, export starters have on average almost twice the number of employees, and pay wages that are more than 20% higher.

The descriptive statistics reported in Table 1 are in line with the first hypothesis (H1) according to which higher wages in exporting firms are due to self-selection of more productive and better paying firms into export markets-labor productivity and daily wages are higher in future export starters compared to non-exporters even in the years before the start (although the difference in average productivity is not statistically significant at any conventional level). In contrast, we find no evidence Sample is lower for sales per employee due to missing values. Export starters are plants which do not export in the first 3 years (t = 1, 2, 3), but export in the last 3 years (t = 4, 5, 6). Non-exporters do not export in any year. Wages and sales are deflated by the aggregate consumer price index. t = 1,…, 6 refers to a specific year in the 6-year window a plant is observed. Start (end) years for these windows vary across plants between 1994 (1999) and 2001 (2006) to support the second hypothesis (H2) which argues that exporting increases productivity and thus wages due to learning-by-exporting. Changes in labor productivity and in the daily wage between t = 3 and t = 6 do not differ in a statistically significant way between export starters and non-exporters.

Plant level regressions

While providing interesting information, the descriptive statistics reported in Table 1 cannot be considered as a basis for a convincing test of the two hypotheses H1 and H2. Since an exporter wage premium is a positive difference between the wages paid to employees in exporting and non-exporting firms after controlling for differences in other variables than exporting that determine wages, the rest of the empirical investigation is concerned with controlling for these influences on wages.

As a first step, we look at the difference in the plant average of daily wages between export starters and non-exporters over time, controlling for plant characteristics that can be expected to be related to the average wage level of a plant (including plant size, the presence or not of a works council, the use of new production technology, location in western or eastern Germany, various measures for the average qualification of the workforce, and dummies for industries, regions, and years). Results based on data for 3,587 plants are reported in column 1 of Table 2.

The coefficient of the exporter starter dummy variable captures any timeinvariant (unobserved) differences between export starters and non-exporters and reflects the selection effect into export activity. It shows that the average daily wage paid by export starters is 7.2% higher than in comparable non-exporting plants in t = 1, i.e. 3 years before exports start (see row 1 of Table 2). This difference is both statistically significant and of a relevant order of magnitude from an economic point of view.9 Results reported in column 3 of Table 2 show that the same holds for labor productivity. Controlling for all plant characteristics used in the wage regression, the estimated productivity premium for export starters 3 years before the start is 20.4%. The statistically insignificant coefficients of the interaction terms of the export starter dummy variable and the dummy variables for t = 2 to t = 6 show that neither the difference in the average wage nor the difference in the average productivity changes over the years t = 2 to t = 6.

These results are in line with our hypothesis H1-plants with higher wages (and a higher productivity) self-select into export markets. Contrary to this, hypothesis H2-that wages (and productivity) increase after starting to export due to learningby-exporting effects-is not supported. All point estimates of the interaction terms of the export starter dummy variable and the dummy variables for t = 4 to t = 6 are very small and statistically not significantly different from zero.10 These findings are consistent with the results from the descriptive statistics reported in Table 1.

Next, we apply an alternative approach to test for wage (and productivity) enhancing effects of starting to export. This is motivated by the problem that faster wage growth of plants which have just entered the export market (compared to plants that keep selling their products on the domestic market only) would not necessarily reflect a causal effect of exporting on wages. It could well be the case that better paying (and more productive) firms self-select into the export starting group, but would have experienced higher wage growth even without starting to export. However, we cannot observe the latter scenario (i.e. the wage developments of today's export starters if they had not started to export), which is the well-known problem of the missing counterfactual situation. 11This closely resembles a situation familiar from the evaluation of active labor market programs (or any other form of treatment of units): If participants, or treated units, are not selected randomly from a population but are selected or self-select according to certain criteria, the effect of a treatment cannot be evaluated by comparing the average performance of the treated and the non-treated. Since each unit (plant or person) either did participate or not, we lack the required information about its performance in the counterfactual situation. A way out is to construct a control group in such a way that every treated unit is matched to an untreated unit that was as similar as possible (ideally, identical) at the time before the treatment. Differences between the two groups (the treated, and the matched non-treated) after the treatment can then be attributed to the treatment (for a comprehensive discussion, see [START_REF] Heckman | The economics and econometrics of active labor market programs[END_REF]. The use of a matching approach to search for effects of starting to export on wages (and other dimensions of firm performance, including productivity) has been pioneered by [START_REF] Wagner | The causal effect of exports on firm size and labor productivity: First evidence from a matching approach[END_REF], and it has been used in a growing number of empirical studies (surveyed in Wagner 2007) ever since.

In the present study, export starters in year t = 4 were matched with ''statistical twins'' from the large group of non-exporters, based on characteristics of the plants in t = 1 (3 years before the starters begin to export). Matching was implemented by nearest neighbor propensity score matching. 12 The propensity score was estimated from a probit regression of a dummy variable indicating whether or not a plant is an export starter in year t = 4 on a set of variables (all measured at t = 1) that are considered as determinants of the probability to start to export and are related to the average wage paid in the firm. Details are given in Table 5 in the ''Appendix''. The balancing property (which requires an absence of statistically significant differences between the treatment group and the control group in the covariates after matching) is satisfied. The differences in the means of the variables used to compute the Regressions also include 37 sectoral dummies, 9 urbanisation dummies, 15 regional dummies, 12 year dummies as well as 5 dummies for the respective periods t.

|t|statistics in parentheses, based on robust standard errors adjusted for clustering at the plant level. ***,**,* denote significance at the level of 1, 5, and 10%, respectively.

Full sample refers to all observations with no missing values in the covariates. Matched sample refers to observations from plants which have been selected via nearest neighbor propensity score matching, where the propensity score has been obtained from a probit on export starting propensity score were never statistically significant between the starters and the matched non-exporters (see Table 6 in the ''Appendix''). The common support condition (which requires that the propensity score of a treated observation is neither higher than the maximum nor less than the minimum propensity score of the controls) was imposed by dropping export starters whose propensity score is higher than the maximum or lower than the minimum propensity score of the nonexporters. This matching approach leads to 59 (out of 70) export starters for which a nonexporting twin-plant could be found. These 59 pairs constitute our so-called matched sample made up of 118 plants. The plant level regressions of average daily wages and of sales per employee discussed above were repeated for data from this matched sample; results are reported in columns 2 and 4 of Table 2. By construction (due to the successful matching) neither wages nor productivity differ significantly between export starters and non-exporting plants in t = 1, and the same holds for the other years before the export start in t = 4.

In the matched sample, the estimated regression coefficients of the interaction terms of the export starter dummy variable with the dummy variables for the years t = 4, t = 5 and t = 6 turn out to be statistically insignificant at any conventional level in both the wage and the productivity regression. Therefore, in line with the findings from the descriptive statistics reported in Table 1 and from the regressions using the full sample of plants reported in columns 1 and 3 of Table 2, we find no evidence for hypothesis H2 which argues that exporting increases productivity and thus wages due to learning-by-exporting.

Individual level wage regressions

The plant level estimations presented in Sect. 3.2 may suffer from aggregation bias since individual heterogeneity which influences wages cannot be controlled for. Therefore, we replicate the empirical investigation for wages using data at the individual level, controlling for both observed employer and employee characteristics. 13 Like in the plant level analysis we consider two samples of plants-the full sample of all plants, and the matched sample made up of export starters and matched non-exporters.

Results for the full sample of 3,587 plants and all 242,879 employees, meaning a total of 819,076 observations, are reported in column 1 of Table 3. The estimated coefficient of the export starter dummy variable is positive and highly statistically significant. It is also large from an economic point of view, pointing to an export starter wage differential of 6.9% in t = 1 (i.e. 3 years before the start) which does not significantly change in the following 2 years (t = 2 and t = 3). These results are strongly in favor of hypothesis H1 according to which higher wages in exporting firms are due to self-selection of better paying firms into export markets. 14

Table 3

Individual level wage regressions (OLS); all employees; Germany (Dependent variable: logarithm of daily wage)

Explanatory variables

All employees

comprise stayers (workers which work for the respective plant in all 6 years of the data window) as well as employees which join/leave the plant during the observed 6 years. Regressions also include 37 sectoral dummies, 9 urbanisation dummies, 15 regional dummies, 11 year dummies as well as 5 dummies for the respective periods t. In contrast, hypothesis H2 (according to which wages and productivity increase after starting to export due to learning-by-exporting effects) is hardly supported by our data. In the full sample, only the interaction term for t = 6 is positive and (albeit weakly) significant, indicating that the wage change of export starters exceeds the wage change of non-exporters by 3%. However, turning to the results of the matched sample (column 3), we do not find any evidence in favor of a wage increase after starting to export because all interaction terms are insignificant.

In order to see whether the covariation between wages and exports differs when conditioning on plant productivity, we have repeated the regressions for the full and the matched sample with the logarithm of sales per employee included as an additional regressor (see columns 2 and 4 of Table 3). While this robustness check does not change the results in the matched sample, in the full sample the magnitude and statistical significance of the export starter dummy is reduced. This is further evidence that the observed export wage premium (largely) reflects self-selection of more productive firms into export markets (as proposed by hypothesis H1).

We also take into account that the selection effect only controls for time-invariant differences between export starters and non-exporters and their employees. Any changes in the workforce (due to hirings and separations) are by definition not absorbed by the selection effect. If quitters and joiners are non-random with respect to the introduction of the export activity, we may obtain a biased estimate of our hypothesis H2. We control for this by (additionally) looking only at wages of individuals who remain in the respective plant in all 6 years observed (stayers), the results of which are reported in Table 4.

The findings for stayers closely resemble those for all employees. We find an export starter wage premium of 5.9% (column 1). However, neither in the estimations based on all plants nor in the regressions including stayers in matched plants only the interaction terms of the export starter dummy and the dummy variables for the years t = 4, t = 5 and t = 6 are ever statistically significant. Higher wages in exporting plants thus do not seem to be induced by export activities. 15

Conclusions

Using a rich set of German linked employer-employee panel data, we have demonstrated that the exporter wage premium does already exist in the years before plants start to export, and that it does not increase in the years after exporting started. According to our results, higher wages in exporting plants that are found after controlling for observed and unobserved employer and employee characteristics are due to self-selection of more productive, better paying plants into export markets. This empirical finding is in accordance with the recent theoretical literature on exporting by heterogeneous firms (pioneered by [START_REF] Melitz | The impact of trade on intra-industry reallocations and aggregate industry productivity[END_REF] which postulates that only the more productive firms in an industry can bear the extra costs of entering foreign markets.

Our empirical results imply that the so-called exporter wage premium is labeled misleadingly since it may not be caused by export activities. At least in the case of Germany, one of the major exporting countries in the world, exporting does not seem to make firms more productive or lead to higher wages. One may, however, argue that it takes some time before the positive effects of exporting are fully realized, and that the period of 2 years after starting to export observed here is too short for investigating the presence or not of wage effects. Future research that can use data for a longer period will be able to provide empirical evidence on this. Furthermore, it would be interesting to see whether our finding can be replicated for other countries using linked employer-employee panel data. This sort of data provides information that should be tapped more intensively in order to gain additional insights in international firm activities.

  |t|-statistics in parentheses, based on robust standard errors adjusted for clustering at the plant level. ***,**,* denote significance at the level of 1, 5, and 10%, respectively. Full sample refers to all observations with no missing values in the covariates. Matched sample refers to observations of employees from plants which have been selected via nearest neighbor propensity score matching, where the propensity score has been obtained from a probit on export starting

Table 1

 1 Descriptive statistics for export starters and non-exporters, all plants

		Export starters	Non-exporters	Prob-value for
		(N = 70)	(N = 3,517)	H 0 : Diff. of
				means = 0
		Mean	Mean
	Plant size (number of persons)
	t = 1	108.31	60.08	0.01
	t = 2	107.90	59.36	0.00
	t = 3	106.93	58.47	0.00
	t = 4	108.04	57.95	0.00
	t = 5	110.33	56.79	0.00
	t = 6	110.52	55.63	0.00
	Yearly sales per employee (in thousands of €)
	t = 1	144.66	117.56	0.27
	t = 2	151.58	122.03	0.28
	t = 3	129.22	119.07	0.56
	t = 4	124.29	121.13	0.83
	t = 5	114.30	118.44	0.76
	t = 6	136.58	124.50	0.63
	Average daily wage (in €)
	t = 1	73.73	60.39	0.00
	t = 2	73.83	60.54	0.00
	t = 3	75.42	61.22	0.00
	t = 4	75.26	61.36	0.00
	t = 5	74.30	60.82	0.00
	t = 6	74.24	59.85	0.00
	Growth rates between t = 3 and t = 6, in %
	Plant size (number of persons)	23.48	-0.63	0.20
	Yearly sales per employee (in thousands of €)	-0.68	7.40	0.16
	Average daily wage (in €)	-1.77	-1.52	0.84

Table 2

 2 Plant level regressions of wages and labor productivity (OLS); Germany

Table 4

 4 Individual level wage regressions (OLS); stayers only; Germany (Dependent variable: logarithm of daily wage)Stayers are workers which work for the respective plant in all 6 years of the data window. Regressions also include 37 sectoral dummies, 9 urbanisation dummies, 15 regional dummies, 11 year dummies as well as 5 dummies for the respective periods t.|t|-statistics in parentheses, based on robust standard errors adjusted for clustering at the plant level. ***,**,* denote significance at the level of 1, 5, and 10%, respectively. Full sample refers to all observations with no missing values in the covariates.

		-0.036 (1.41)	-0.011 (0.96)	0.010 (0.77)	-0.002 (0.14)	-0.010 (0.56)	0.012 (0.66)	0.072 (4.09)***			0.124 (1.91)*	0.159 (2.31)**	0.120 (1.68)*	0.152 (2.14)**	0.203 (2.75)***	0.152 (1.86)*		0.036 (1.09)			0.006 (0.29)	-0.007 (0.42)	0.067 (2.91)***	0.001 (0.12)	-0.405 (6.26)***	0.031 (8.85)***
	Matched sample	-0.028 (1.03)	-0.006 (0.67)	0.006 (0.47)	0.004 (0.31)	-0.007 (0.41)	0.001 (0.07)				0.119 (1.60)*	0.171 (2.22)**	0.160 (2.02)**	0.177 (2.24)**	0.243 (2.91)***	0.139 (1.41)		0.046 (1.14)			-0.002 (0.10)	-0.011 (0.63)	0.091 (3.50)***	0.017 (1.37)	-0.259 (3.80)***	0.031 (8.70)***
		0.031 (1.26)	-0.011 (0.97)	0.026 (1.26)	0.024 (1.28)	0.019 (0.86)	0.040 (1.56)	0.084 (10.02)***			0.098 (7.69)***	0.134 (10.42)***	0.132 (8.92)***	0.153 (8.65)***	0.167 (9.12)***	0.173 (8.44)***	0.134 (2.63)***	0.062 (7.76)***			0.040 (3.21)***	0.019 (1.21)	0.035 (2.60)***	0.019 (2.99)***	-0.215 (5.28)***	0.019 (16.10)***
	Full sample	0.059 (2.05)**	0.001 (0.20)	0.003 (0.32)	0.006 (0.58)	0.012 (1.09)	0.017 (1.39)				0.103 (7.76)***	0.137 (10.33)***	0.135 (8.84)***	0.163 (8.90)***	0.178 (9.29)***	0.180 (8.12)***	0.126 (1.87)*	0.083 (6.06)***			0.036 (2.54)**	0.028 (1.75)*	0.056 (4.04)***	0.030 (4.39)***	-0.198 (4.26)***	0.020 (16.02)***
	Explanatory variables	Export starter (dummy: 1 = yes)	Dummy (t = 2) 9 export starter	Dummy (t = 3) 9 export starter	Dummy (t = 4) 9 export starter	Dummy (t = 5) 9 export starter	Dummy (t = 6) 9 export starter	Logarithm of sales per employee	Plant size dummies (number	of employees; reference: 1-9)	10-19	20-49	50-99	100-199	200-499	500-999	1,000 and more	Works council (dummy: 1 = yes)	Collective agreement (reference:	no collective agreement)	At sectoral level (dummy: 1 = yes)	At firm level (dummy: 1 = yes)	Plant belongs to a larger unit (dummy: 1 = yes)	New production technology (dummy: 1 = yes)	Eastern Germany (dummy: 1 = yes)	Age of employee (in years)

Table 6

 6 All covariates dated at t = 1. Regressions also include sectoral and year dummies. ***,**,* denote significance at the level of 1, 5, and 10%, respectively. Number of plants is lower than the respective figure reported in Table2or 3, since the latter also comprise plants which have missing values in the first year (and thus do not enter the probit regression), but with complete information in at least one of the other years Mean values of variables for export starters and non-exporters Information refers to the first year a plant is observed (t = 1), i.e. 3 years before the (potential) export start. Sample may be lower for some variables due to missing values b Numbers differ slightly from those reported in Table1(70 resp. 3,517) since the latter also include plants which have missing values in covariates in t = 1 c Two-sample t-test (with unequal variance) of the hypothesis that the difference in the mean is equal to zero Higher wages in exporting firms 321

	Table 5 continued
	Explanatory variables				Coefficient		Z-value
	Average age squared (divided by 100)			0.278		(1.50)
	Average tenure of employees (in years)			0.031		(0.45)
	Average tenure squared (divided by 100)		-0.337		(0.77)
	Proportion within total workforce of plant
	Female workers				0.500		(1.36)
	Workers with apprenticeship, no Abitur		-0.410		(1.49)
	Workers without apprenticeship, with Abitur		-0.801		(0.25)
	Workers with apprenticeship and Abitur		0.600		(0.72)
	Workers with technical college degree			-0.406		(0.41)
	Workers with university degree			0.508		(0.78)
	Master craftsman, foreman			-0.564		(0.36)
	Constant				-9.682		(.)
	Number of plants				2,329
	v 2 (52)				177.10		***
	Pseudo-R 2				0.310
	Variable a	All plants			Matched plants
		Export	Non-exporters	p-value c Export	Non-exporters	p-value c
		starters	(N = 3,413) b		starters	(N = 59)
		(N = 68) b			(N = 59)
	Logarithm of average	4.272	4.041	0.00	4.248	4.264	0.79
	wage
	Logarithm of total sales	12.243	11.818	0.00	12.251 12.467	0.21
	per employee
	Establishment size	105.60	60.03	0.00	106.70	92.42	0.57
	(number of employees)
	Works council (dummy:	0.471	0.214	0.00	0.441	0.458	0.86
	1 = yes)
	Collective agreement at	0.500	0.491	0.89	0.475	0.407	0.46
	the sectoral level
	(dummy: 1 = yes)
	Collective agreement at	0.103	0.098	0.90	0.119	0.169	0.44
	the firm level (dummy:
	1 = yes)
	Plant belongs to a larger	0.191	0.126	0.18	0.186	0.186	1.00
	unit (dummy: 1 = yes)

a

Note that profits play a role in both H1 and H2. Profits, however, cannot be directly controlled for in the empirical analysis here due to lack of information in the data. Using German firm level data[START_REF] Fryges | Exports and profitability-First evidence for German manufacturing firms[END_REF] find no evidence for self-selection of more profitable enterprises into exporting and a positive but small causal effect of exporting on profits.

In contrast to wages, there is ample empirical evidence on the relationship between productivity and exporting, showing substantial exporter productivity premia and many findings in favor of the selfselection hypothesis but much fewer results in favor of the learning-by-exporting hypothesis. See[START_REF] Wagner | Exports and productivity: A survey of the evidence from firm-level data[END_REF] for a survey, and International Study Group on Exports, Productivity (ISGEP) (2008) for recent comparable results for 14 countries.

 5 In contrast to[START_REF] Schank | Do exporters really pay higher wages? First evidence from German linked employer-employee data[END_REF], where the size of the exporter wage premium is estimated using similar data (albeit for a shorter time period), we focus on export starters and the evolution of this wage premium before and after exports start. This allows us to explicitly investigate the direction of the link between exporting and wages and test two alternative hypotheses.

For daily gross wages, the ceiling in 2000, for example, is at € 143.92 for western and at € 118.81 for eastern Germany. In our regression sample, 9.0 (4.5) percent of the wage observations in western (eastern) Germany are censored. In order to cope with a potential bias due to censoring, we also conducted analyses not reported here (but available on request) which show that restricting the sample to uncensored observations does not change our conclusions.

The LIAB data are confidential but not exclusive. They are available for non-commercial research by visiting the research data center of the German Federal Employment Agency at the IAB in Nuremberg, Germany. Researchers interested in replications or extensions of our work may contact the first author (email: thorsten.schank@wiso.uni-erlangen.de) for a copy of the Stata do-files used to produce the results reported here.

 8 This reduced our regression sample by 4 export starters and 72 non-exporters. When we kept all plants as a robustness check in the sample, the overall picture did not change substantially, but matching became more difficult (results are available upon request).

The control variables all have the expected signs, and most of them are statistically significant. Since the focus of this paper is on the exporter wage premium, we do not comment on the results for the control variables here and in other regressions. As a robustness check, we also included average investment per employee as a proxy for the capital stock per head (which reduced the regression sample due to missing information). While the estimated coefficient indicated a positive relationship with wages, the export dummy and the interaction terms of the export starter dummy and the year dummies remained literally unchanged.

While the insignificance of the interaction terms could be due to the small number of export starters, the very small point estimates found here and in the following regressions should not be a consequence of small sample size.

Although the regression results discussed above do not show a difference in wage growth between export starters and non-exporters, these estimates may be biased due to the self-selection of export starters.

Alternative matching procedures have also been carried out (using three and five nearest neighbors, kernel matching), but the (unreported) results were similar to those discussed in the next section.

Due to the lack of information for productivity at the individual level this replication is possible for the wage equations only.

As before, the control variables all have the expected signs, and most of them are statistically significant.

In a further regression for stayers, we conditioned on covariates fixed at t = 1 because one could argue that some observables might themselves respond to the start of the export activity. However, the results of this estimation did not alter our conclusions.

Acknowledgments We thank two anonymous referees and the participants of the 2008 Annual Congress of the Verein fu¨r Socialpolitik in Graz for their helpful comments.

Appendix

See Tables 5 and6.


Angela Mally

Wolfgang Dekant
email: dekant@toxi.uni-wuerzburg.de

Food Additives and Contaminants available evidence

Keywords: Ochratoxin A, carcinogenicity, DNA-adducts

The mycotoxin ochratoxin A (OTA) is a potent nephrotoxin and renal carcinogen in rodents.

However, the mechanism of OTA-induced tumour formation is unknown and conflicting results regarding the potential of OTA to react with DNA have been obtained. While experiments using radiolabelled ( 3 H or 14 C) OTA and liquid scintillation counting or accelerator mass spectrometry indicate lack of formation of covalent DNA-adducts, spots detected by 32 P-postlabelling have been attributed to treatment with OTA. However, these putative DNA-adducts have not been shown to contain OTA or part of the OTA molecule and so far no structural information has been provided. Consistent with the absence of DNAbinding of radiolabelled OTA, studies on biotransformation in vivo and in vitro indicate that OTA is poorly metabolized and does not form reactive intermediates capable of interacting with DNA. Recently however, the structures of a carbon-and an oxygen-bonded OTAdeoxyguanosine adduct which is formed by photoirradiation of OTA in the presence of deoxyguanosine have been reported and suggested to be involved in OTA carcinogenicity.

Introduction

Ochratoxin A (OTA) (N-{[(3R)-5-chloro-8-hydroxy-3-methyl-1-oxo-7-isochromanyl]-carbonyl}-3-phenyl-L-alanine) is a mycotoxin produced by Aspergillus and Penicillium species. OTA may contaminate a variety of food items such as cereals, coffee, wine etc., resulting in chronic human exposure. OTA is nephrotoxic and induces renal tumours in rodents, whereby it exhibits significant sex-and species differences [START_REF] Ntp | Toxicology and Carcinogenesis Studies of Ochratoxin A (CAS No. 303-47-9) in F344/N Rats (Gavage Studies)[END_REF]. Male rats are most susceptible to OTA carcinogenicity and repeated administration of low doses of OTA (up to 210 µg/kg b.w.) for two years results in high incidences of renal adenomas and carcinomas arising from the straight segment (S3) of the proximal tubule epithelium [START_REF] Ntp | Toxicology and Carcinogenesis Studies of Ochratoxin A (CAS No. 303-47-9) in F344/N Rats (Gavage Studies)[END_REF][START_REF] Boorman | Renal lesions induced by ochratoxin A exposure in the F344 rat[END_REF]. Interestingly, no increase in tumour incidence was observed following treatment with 21 µg/kg b.w, suggesting a non-linear dose-response for renal tumour formation by OTA [START_REF] Ntp | Toxicology and Carcinogenesis Studies of Ochratoxin A (CAS No. 303-47-9) in F344/N Rats (Gavage Studies)[END_REF]. Kidney tumours in OTA exposed rats develop with a relative rapid onset and are characterized by their malignant and aggressive behaviour [START_REF] Boorman | Renal lesions induced by ochratoxin A exposure in the F344 rat[END_REF]. In the NTP study, decreased survival rates in the mid-and high dose groups were associated with high incidences of metastasis. Histopathological changes induced by OTA in the kidney consist of disorganization of the S3 tubules, single cell death, karyomegaly, polyploidy and frequent mitosis [START_REF] Boorman | Renal lesions induced by ochratoxin A exposure in the F344 rat[END_REF][START_REF] Maaroufi | Karyomegaly of tubular cells as early stage marker of the nephrotoxicity induced by ochratoxin A in rats[END_REF][START_REF] Rasonyi | The role of alpha2u-globulin in ochratoxin A induced renal toxicity and tumors in F344 rats[END_REF]. These histopathological alterations together with the aggressive nature of the tumours are unique to OTA and suggest that the mechanism of OTA carcinogenicity is not merely based on sustained regenerative cell proliferation as a consequence of cytotoxicity, as frequently observed in response to non-genotoxic renal carcinogens such as chloroform and d-limonene [START_REF] Lock | Chemically induced renal tubule tumors in the laboratory rat and mouse: review of the NCI/NTP database and categorization of renal carcinogens based on mechanistic information[END_REF]. However, results of genotoxicity studies also do not suggest that OTA is mutagenic or a potent genotoxin. With respect to the potential of OTA to covalently bind to DNA, conflicting results have been obtained and the purpose of this manuscript is to present a review of the available literature.

Genotoxicity

Results from a range of studies assessing the mutagenicity and genotoxicity of OTA are summarized in Table 1. In most studies, OTA was found to be negative in the Ames-test even in the presence of metabolic activation systems. Increased mutation frequencies were only observed using modifications of the standard Ames-test with culture media from OTA-treated hepatocytes and in the presence of mouse, but not rat kidney microsomes [START_REF] Hennig | Mutagenicity and effects of ochratoxin A on the frequency of sister chromatid exchange after metabolic activation[END_REF][START_REF] Obrecht-Pflumio | Genotoxicity of ochratoxin A by Salmonella mutagenicity test after bioactivation by mouse kidney microsomes[END_REF]. Moreover, OTA was only found to be mutagenic in Salmonella typhimurium strain TA 100, but not in TA 1535, although mechanisms of mutagenicity are identical in both strains [START_REF] Obrecht-Pflumio | Genotoxicity of ochratoxin A by Salmonella mutagenicity test after bioactivation by mouse kidney microsomes[END_REF]. In the light of the large number of negative studies, these results are difficult to interpret since they provide no direct evidence for the mutagenicity of OTA and are not consistent with the known species differences in susceptibility to the carcinogenicity of OTA.

However, genotoxic effects such as DNA strand breaks, sister chromatid exchanges, chromosomal aberrations and induction of micronuclei have been observed in some mammalian cell systems in response to OTA exposure. However, in most cases, these effects occurred independently of metabolic activation (Table 1).

Biotransformation

Biotransformation of OTA to reactive intermediates with the potential to bind to DNA has been suggested to be involved in renal tumour formation by OTA. However, no metabolites indicative of reactive intermediate formation have been detected in rodent blood or urine after OTA-exposure. Results from several studies both in vivo and in vitro indicate that OTA is poorly metabolized both by cytochromes P450 and by peroxidases [START_REF] Gautier | Metabolism of ochratoxin A: absence of formation of genotoxic derivatives by human and rat enzymes[END_REF][START_REF] Zepnik | Ochratoxin A-induced tumor formation: is there a role of reactive ochratoxin A metabolites?[END_REF][START_REF] Gross-Steinmeyer | Metabolism and lack of DNA reactivity of the mycotoxin ochratoxin a in cultured rat and human primary hepatocytes[END_REF][START_REF] Zepnik | Toxicokinetics of the mycotoxin ochratoxin A in F 344 rats after oral administration[END_REF]. The major metabolite formed in vivo is ochratoxin α, which results from cleavage of the peptide bond (Zepnik et , 2003). In vitro, oxidative biotransformation by cytochromes P450 yields low amounts of hydroxylated derivatives, but their presence in urine could not be confirmed in recent studies despite the use of sensitive LC-MS/MS analysis [START_REF] Gautier | Metabolism of ochratoxin A: absence of formation of genotoxic derivatives by human and rat enzymes[END_REF][START_REF] Zepnik | Ochratoxin A-induced tumor formation: is there a role of reactive ochratoxin A metabolites?[END_REF][START_REF] Zepnik | Toxicokinetics of the mycotoxin ochratoxin A in F 344 rats after oral administration[END_REF]. However, two novel metabolites formed in rat hepatocytes in vitro and excreted in urine of OTA treated animals were recently identified as hexose-and pentoseconjugates [START_REF] Gross-Steinmeyer | Metabolism and lack of DNA reactivity of the mycotoxin ochratoxin a in cultured rat and human primary hepatocytes[END_REF][START_REF] Zepnik | Toxicokinetics of the mycotoxin ochratoxin A in F 344 rats after oral administration[END_REF]. The OTA metabolites identified are considered to be less toxic than OTA and it is unlikely that their mechanisms of formation involves electrophilic intermediates (Figure 1) [START_REF] Xiao | Toxicity of ochratoxin A, its opened lactone form and several of its analogs: structure-activity relationships[END_REF][START_REF] Gautier | Metabolism of ochratoxin A: absence of formation of genotoxic derivatives by human and rat enzymes[END_REF][START_REF] Zepnik | Ochratoxin A-induced tumor formation: is there a role of reactive ochratoxin A metabolites?[END_REF][START_REF] Gross-Steinmeyer | Metabolism and lack of DNA reactivity of the mycotoxin ochratoxin a in cultured rat and human primary hepatocytes[END_REF].

By electrochemical and photochemical oxidation of OTA, formation of a hydroquinone/quinone redox couple has recently been reported and speculated to be involved in OTA carcinogenicity [START_REF] Calcutt | Electrochemical oxidation of ochratoxin A: correlation with 4-chlorophenol[END_REF]. In addition to generation of reactive oxygen species due to redox cycling, the electrophilic quinone may potentially react with tissue nucleophiles to form covalently bound adducts or glutathione conjugates. However, experimental proof of this pathway has not been obtained. Several studies in vitro indicate that OTA does not form DNA adducts even in the presence of activation systems such as horseradish peroxidase which may catalyze formation of the hydroquinone derivative [START_REF] Gautier | Metabolism of ochratoxin A: absence of formation of genotoxic derivatives by human and rat enzymes[END_REF][START_REF] Mally | Functional, biochemical and pathological effects of repeated administration of ochratoxin A to rats. Chemical Research in Toxicology[END_REF]. Moreover, OTA-derived S-conjugates which may be directed to the kidney could not be detected [START_REF] Zepnik | Toxicokinetics of the mycotoxin ochratoxin A in F 344 rats after oral administration[END_REF][START_REF] Mally | Functional, biochemical and pathological effects of repeated administration of ochratoxin A to rats. Chemical Research in Toxicology[END_REF]Mally et al., 2005b). The involvement of a nephrotoxic S-conjugate in OTA toxicity and carcinogenicity is also not consistent with the potency of other hydroquinones activated by a glutathioneconjugation pathway, which usually require administration of much higher doses to induce nephrotoxicity [START_REF] English | Measurement of cell proliferation in the kidneys of Fischer 344 and Sprague-Dawley rats after gavage administration of hydroquinone[END_REF][START_REF] Monks | Glutathione Conjugation as a Mechanism for the Transport of Reactive Metabolites[END_REF][START_REF] Boatman | Differences in the nephrotoxicity of hydroquinone among Fischer 344 and Sprague-Dawley rats and B6C3F1 mice[END_REF] and/or renal tumours. Furthermore, it is well established that nephrotoxic hydroquinone S-conjugates promote tumour formation by inducing sustained regenerative cell proliferation in response to cytotoxicity and tissue necrosis, which is also not consistent with the histopathological [START_REF] Ntp | Toxicology and Carcinogenesis Studies of Ochratoxin A (CAS No. 303-47-9) in F344/N Rats (Gavage Studies)[END_REF][START_REF] Boorman | Renal lesions induced by ochratoxin A exposure in the F344 rat[END_REF][START_REF] English | Measurement of cell proliferation in the kidneys of Fischer 344 and Sprague-Dawley rats after gavage administration of hydroquinone[END_REF][START_REF] Nakagawa | Effect of hexachloro-1,3-butadiene on renal carcinogenesis in male rats pretreated with N-ethyl-N-hydroxyethylnitrosamine[END_REF][START_REF] Lock | Chemically induced renal tubule tumors in the laboratory rat and mouse: review of the NCI/NTP database and categorization of renal carcinogens based on mechanistic information[END_REF].

DNA binding using radiolabelled compound

The use of radiolabelled compounds combined with liquid scintillation counting or accelerator mass spectrometry (AMS) allows the unambiguous determination as to whether or not the compound of interest covalently binds to DNA. Both decay counting and AMS can produce false positive results if insufficiently pure DNA is used (i.e. contamination with proteins or RNA which often bind reactive intermediates with higher yields) or if parts of the molecule containing radiolabel are metabolically incorporated into DNA. In contrast, negative results by both methods clearly indicate lack of DNA binding.

In three independent studies, binding of OTA to rat kidney DNA could not be demonstrated after administration of 3 H or 14 C-labelled OTA to rodents using liquid scintillation counting ( 3 H) or AMS ( 14 C) as analytical procedures [START_REF] Schlatter | Carcinogenicity and kinetic aspects of ochratoxin A[END_REF][START_REF] Gautier | Metabolism of ochratoxin A: absence of formation of genotoxic derivatives by human and rat enzymes[END_REF][START_REF] Mally | Functional, biochemical and pathological effects of repeated administration of ochratoxin A to rats. Chemical Research in Toxicology[END_REF]. Similarly, adduct formation was not observed by scintillation counting in DNA extracted from rat and human hepatocytes treated with 3 H-OTA in vitro [START_REF] Gross-Steinmeyer | Metabolism and lack of DNA reactivity of the mycotoxin ochratoxin a in cultured rat and human primary hepatocytes[END_REF]. Conditions and results of these studies are summarized in Table 2. Limits of detection in all studies were well below those required to detect "adducts" present in concentrations indicated by 32 P-postlabelling and doses of OTA administered were similar to those used in the 32 P-postlabelling experiments. Thus, studies using radiolabelled OTA have been sufficiently sensitive to detect DNA-modifications as indicated by postlabelling containing the OTA-molecule if present.

DNA adduct formation analyzed by 32 P-postlabelling

The 32 P-postlabelling assay is a highly sensitive method for the detection of DNA modifications in response to carcinogen treatment. The postlabelling procedure involves enzymic labelling of the 3´-monophosphates using [γ-32 P]-ATP followed by separation using two-dimensional thin layer chromatography. Adducts "spots" are then detected and quantified by autoradiography. The advantages of 32 P-postlabelling over other methods such as scintillation counting or AMS are the requirement of only small sample sizes (1-10 µg of DNA), the ability to assess DNA adduct formation when radioactive compound is not available, and the potential to detect DNA base modifications that do not contain parts of the compound of interest, such as oxidative lesions or I-compounds [START_REF] Randerath | I-compounds--endogenous DNA markers of nutritional status, ageing, tumour promotion and carcinogenesis[END_REF].

However, thin layer chromatography does not offer high resolution and is often difficult to reproduce. Moreover, labelling of hydroxylated compounds still present in the incubation mixtures and the presence of endogenous DNA base modifications may lead to false positive results, particularly in the absence of reference compounds [START_REF] Masento | Enzyme-mediated phosphorylation of polycyclic hydrocarbon metabolites: detection of non-adduct compounds in the 32P-postlabelling assay[END_REF][START_REF] Scates | Appearance of artefacts when using 32 Ppostlabelling to investigate DNA adduct formation by bile acids in vitro: lack of evidence for covalent binding[END_REF]. Incomplete DNA digestion, which can occur in the presence of bulky DNA adducts, may also produce false negative results. Most importantly, postlabelling does not provide structural information and it is not possible to determine if the "adduct" spots observed actually contain covalently bound compound. In this respect, low "adduct" levels of classic non-genotoxic carcinogens, which may alter concentrations of endogenous DNA base modifications but which do not bind to DNA, have been reported and raised concerns that the postlabelling procedure may be too sensitive [START_REF] Liehr | 32P-postlabelling in studies of hormonal carcinogenesis[END_REF][START_REF] Randerath | I-compounds--endogenous DNA markers of nutritional status, ageing, tumour promotion and carcinogenesis[END_REF].

Using this method, DNA adducts ascribed to OTA have been reported by one laboratory in a wide range of tissues from rodents (summarized in Table 3), pigs after OTA-exposures and from humans presumably exposed to OTA, as well as in various cell lines in response to OTA treatment [START_REF] Pfohl-Leszkowicz | Ochratoxin A-related DNA adducts in urinary tract tumours of Bulgarian subjects[END_REF][START_REF] Grosse | Formation of ochratoxin A metabolites and DNA-adducts in monkey kidney cells[END_REF][START_REF] El Adlouni | Phenobarbital increases DNA adduct and metabolites formed by ochratoxin A: role of CYP 2C9 and microsomal glutathione-S-transferase[END_REF][START_REF] Arlt | Analyses of DNA adducts formed by ochratoxin A and aristolochic acid in patients with Chinese herbs nephropathy[END_REF][START_REF] Faucet | Evidence for covalent DNA adduction by ochratoxin A following chronic exposure to rat and subacute exposure to pig[END_REF]. In some tissue samples, up to 24 adducts spots were detected.

These unusually large numbers of adducts were often reported to be tissue, sex-or species specific and occurred with variable kinetics (some "adducts" disappeared rapidly, others ). However, "adduct" maps were not consistent over a range of studies and a clear dose-response for the formation of these adducts could not be established. Large numbers of OTA-derived "adducts" have also been reported to be present in mice, which are far less susceptible to OTA carcinogenicity, or in liver DNA of rodents treated with OTA. However, the liver is not a target organ for tumorigenicity or toxicity of OTA [START_REF] Boorman | Renal lesions induced by ochratoxin A exposure in the F344 rat[END_REF], further questioning the relevance of the observed "adducts" for OTA carcinogenicity.

Frequently, background adduct levels in DNA extracted from control animals were not assessed or were reported to be below the limit of detection. This is in contrast to a large number of studies assessing "endogenous" DNA base modifications (modifications present in control animals) which demonstrate the presence of a number of "spots" in DNA from control animals (Vulimiri et al., 1998;Gupta et al., 1999;[START_REF] Gupta | Background DNA damage for endogenous and unavoidable exogenous carcinogens: a basis for spontaneous cancer incidence?[END_REF][START_REF] Zhou | Acute elevation by shortterm dietary restriction or food deprivation of type I I-compound levels in rat liver DNA[END_REF].

Most importantly, however, "adduct spots" attributed to OTA treatment were never shown to contain parts of the OTA molecule, suggesting that these DNA modifications -if presentmay be due to oxidative stress or modulation of endogenous DNA base modifications.

Recently, the structures of a photochemically generated carbon-and oxygen-bonded C8-OTA-dGMP adduct have been reported. It has been suggested that these compounds represent the DNA-adducts presumably formed from OTA in vivo (Figure 2) [START_REF] Dai | Ochratoxin a forms a carbon-bonded c8deoxyguanosine nucleoside adduct: implications for c8 reactivity by a phenolic radical[END_REF][START_REF] Faucet | Evidence for covalent DNA adduction by ochratoxin A following chronic exposure to rat and subacute exposure to pig[END_REF]. In a recent paper., synthetic standards of these compounds were reported to comigrate with two of the adduct "spots" found in kidney from OTA treated rats [START_REF] Faucet | Evidence for covalent DNA adduction by ochratoxin A following chronic exposure to rat and subacute exposure to pig[END_REF]. This observation has been claimed as evidence for covalent DNA binding of OTA.

However, two other laboratories were independently unable to confirm the presence of OTA related "spots" suggestive of DNA-modifications using 32 P-postlabelling [START_REF] Mally | Functional, biochemical and pathological effects of repeated administration of ochratoxin A to rats. Chemical Research in Toxicology[END_REF]Mally et al., 2005a). In these studies, rats were repeatedly given by gavage high doses (up to 2 mg/kg b.w.) of OTA (5 days/week for two weeks), which correspond to approximately ten times the top dose used in the NTP bioassay resulting in a renal tumour incidence of 74%. This dosing regimen resulted in high plasma and tissue concentrations and OTA-specific histopathological changes in the kidney of treated animals (Mally et al., 2005b). OTA-dGMP adduct standards obtained by photoirradiation of OTA in the presence of dGMP as well as positive controls (aristolochic acid) were included. In these studies, "spots" were detected in OTA-treated animals, but the same "spot" patterns were also present in controls and total "adduct" levels were not increased in response to OTA exposure. Furthermore, formation of the postulated carbon-bonded C8-OTA-dG adduct in response to OTA treatment could not be confirmed using either 32 P-postlabelling or LC-MS/MS [START_REF] Mally | Functional, biochemical and pathological effects of repeated administration of ochratoxin A to rats. Chemical Research in Toxicology[END_REF]Mally et al., 2005a). However, DNA strand breakage was evident in target and non-target tissues as assessed by the Comet Assay. These effects were further enhanced in the presence of formamidopyrimidine glycosylase, which is known to convert oxidative lesions into DNA strand breaks, suggesting that the observed DNA damage may be a result of oxidative stress rather than formation of covalent DNA-adducts (Mally et al., 2005a).

In the context of substantial evidence arguing against metabolic activation and covalent binding to DNA, the results of the study by [START_REF] Faucet | Evidence for covalent DNA adduction by ochratoxin A following chronic exposure to rat and subacute exposure to pig[END_REF] should be interpreted carefully. In this study, only one chromatographic system was applied, which is not very selective and does not offer a high resolution for lipophilic compounds. As previously reported, up to 19 adduct spots were detected in kidney DNA of rats administered OTA for two years (0.4 mg/kg b.w., 3 times per week) and all of these migrated to the upper right-hand corner of the plates [START_REF] Pfohl-Leszkowicz | Sex-and strain-specific expression of cytochrome P450s in ochratoxin A-induced genotoxicity and carcinogenicity in rats[END_REF]. It is therefore not surprising that the synthetic standard which also migrates to this region co-eluted with one of these spots.

Clearly, confirmation of the presence of the postulated OTA-DNA adducts requires further qualifiers such as mass-or UV-spectra or at least co-chromatography in at least two chromatographic systems with high resolution and different selectivities. A clear and reproducible separation is also required. Therefore, it is highly questionable if co- 9 chromatography in one system with poor resolution and low specificity, even in the absence of conflicting data, provides sufficient "evidence" for adduct formation.

Conclusions

By a weight of evidence approach, the lack of mutagenicity and only weak genotoxicity of OTA, the lack of formation of reactive metabolites and absence of DNA-binding of radiolabelled OTA in several independent studies, and the inconsistencies and difficulties in reproducing results obtained by 32 P-postlabelling, do not support the conclusion that covalent DNA adduct formation is important in the mechanism of OTA carcinogenicity. [START_REF] Hennig | Mutagenicity and effects of ochratoxin A on the frequency of sister chromatid exchange after metabolic activation[END_REF] SOS DNA Reparatur negative [START_REF] Sakai | Genotoxicity of fungi evaluated by SOS microplate assay[END_REF] SOS Chromotest E. coli PQ 35, 37 negative [START_REF] Krivobok | Study of the genotoxic potential of 17 mycotoxins with the SOS Chromotest[END_REF] E. coli PQ 35, 37 positive (at cytotoxic concentrations) [START_REF] Malaveille | Genotoxicity of ochratoxin A and structurally related compounds in Escherichia coli strains: studies on their mode of action[END_REF] Mutagenicity in mammalian cells L5178Y TK+/-mouse lymphoma cells negative [START_REF] Bendele | Evaluation of ochratoxin A for mutagenicity in a battery of bacterial and mammalian cell assays[END_REF] HPRT negative [START_REF] Umeda | Mutagenicity and inducibility of DNA singlestrand breaks and chromosome aberrations by various mycotoxins. Gann 68: 619-625. DNA adducts (I-compounds) in pig liver. Modulation by high cholesterol/high fat diet[END_REF] lacZ`-mutations (NIH/3T3 mouse fibroblasts expressing human CYP450 positive (de [START_REF] De Groene | Development of human cytochrome P450-expressing cell lines: application in mutagenicity testing of ochratoxin A[END_REF] DNA repair rat and mouse hepatocytes positive (weak effects only at cytotoxic concentrations) [START_REF] Mori | Genotoxicity of a variety of mycotoxins in the hepatocyte primary culture/DNA repair test using rat and mouse hepatocytes[END_REF] rat hepatocytes negative [START_REF] Bendele | Evaluation of ochratoxin A for mutagenicity in a battery of bacterial and mammalian cell assays[END_REF] rat hepatocytes positive [START_REF] Dorrenhaus | Effects of ochratoxin A on DNA repair in cultures of rat hepatocytes and porcine urinary bladder epithelial cells[END_REF])

DNA strand breaks

Chinese hamster ovary cells rat fibroblasts positive [START_REF] Stetina | Induction of DNA single-strand breaks and DNA synthesis inhibition by patulin, ochratoxin A, citrinin, and aflatoxin B1 in cell lines CHO and AWRF[END_REF] mouse splenocytes positive [START_REF] Creppy | Genotoxicity of ochratoxin A in mice: DNA single-strand break evaluation in spleen, liver and kidney[END_REF] MDCK kidney epithelial cells positive [START_REF] Lebrun | Detection of ochratoxin A-induced DNA damage in MDCK cells by alkaline single cell gel electrophoresis (comet assay)[END_REF]) HepG2 cells positive [START_REF] Ehrlich | Genotoxic effects of ochratoxin A in human-derived hepatoma (HepG2) cells[END_REF] Micronuclei-Test Syrian embryo fibroblasts positive [START_REF] Dopp | Induction of genotoxic effects and modulation of the intracellular calcium level in syrian hamster embryo (SHE) fibroblasts caused by ochratoxin A[END_REF] HepG2 cells positive [START_REF] Ehrlich | Genotoxic effects of ochratoxin A in human-derived hepatoma (HepG2) cells[END_REF] Sister Chromatid Exchange Chinese hamster ovary cells negative [START_REF] Ntp | Toxicology and Carcinogenesis Studies of Ochratoxin A (CAS No. 303-47-9) in F344/N Rats (Gavage Studies)[END_REF] porcine urinary bladder epithelial cells positive [START_REF] Follmann | Sister chromatid exchange frequency in cultured isolated porcine urinary bladder epithelial cells (PUBEC) treated with ochratoxin A and alpha[END_REF] human lymphocytes positive (?) [START_REF] Hennig | Mutagenicity and effects of ochratoxin A on the frequency of sister chromatid exchange after metabolic activation[END_REF] human lymphocytes negative [START_REF] Cooray | Effects of some mycotoxins on mitogen-induced blastogenesis and SCE frequency in human lymphocytes[END_REF])

  treatment with OTA (NTP

  hydrolysis of DNA from tissues, enrichment of the adduct fraction,

  Fig. 1Biotransformation of Ochratoxin A

Table 1

 1 Mutagenicity and genotoxicity of ochratoxin A in vitro

	Test system	Results	Reference
		(positive / negative)
	Ames Test	negative	(Wehner et al., 1978)
	S. typhimurium TA 98, 100, 1535,
	1537, 1538
	S. typhimurium TA 102	negative	(Wurgler et al., 1991)
	S. typhimurium TA 98, 100, 1535,
	1537, 1538	negative	(Bendele et al., 1985)
	S. typhimurium TA 98, 100, 1535,	negative	(Follmann and Lucas,
	1538, 102,104		2003)
	S. typhimurium TA 97, 98,100, 1535	negative	(NTP, 1989)
	S. typhimurium TA 100, 2638	negative	(Zepnik et al., 2001)
	S. typhimurium TA 98, 1535, 1538	positive	(Obrecht-Pflumio et al.,
		(in the presence of mouse,	1999)
		but not rat kidney
		microsomes)
	S. typhimurium TA 100, 1535, 1538	positive
		(hepatocyte culture medium)

Table 2

 2 Results from DNA binding studies using radiolabelled ochratoxin A

	Treatment conditions	Results	Limit of detection	Reference
	Male rat, single oral dose	No adducts detected,	2.7 / 10 9 DNA bases	(Gautier et al., 2001)
	of 1 mg/kg b.w., 24 h	3 H
	Rats, single oral dose of	No adducts detected,	1.3 / 10 10 DNA bases (Schlatter et al., 1996)
	210 µg/kg, 24 h	3 H
	Rats, single oral dose of	No adducts detected,	< 3 / 10 9 DNA bases	(Mally et al., 2004)
	500 µg/kg, 48h	14 C
	Human and rat	No adducts detected,	2 / 10 9 DNA bases	(Gross-Steinmeyer et
	hepatocytes	3 H		al., 2002)

Table 3

 3 Results from a range of in vivo studies using 32 P-postlabelling to assess DNA adduct formation by ochratoxin A.

	Species/Strain	Dosing regimen	DNA adducts in kidney	Comments / Conclusions	Reference
	Γ Swiss mice	2.5 mg/kg b.w. by gavage
		sacrifice 24-72h after single dose

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants

Acknowledgements

Parts of the authors work were supported by the Fifth RTD Framework Programme of the European Union, Project No.: QLK1-2001-01614, by the Institute for Scientific Information on Coffee (ISIC) in Vevey, Switzerland and the Physiological Effects of Coffee Committee (PEC) in Paris, France and by the Deutsche Forschungsgemeinschaft, Bonn. http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk Food Additives and Contaminants

maximum adduct levels after 72h 40 / 10 9 nucleotides, no background 9 adduct spots in liver maximum adduct levels after 72h 7 / 10 9 nucleotides [START_REF] Pfohl-Leszkowicz | DNA adduct formation in mice treated with ochratoxin A[END_REF] Γ Swiss mice 2.5 mg/kg b.w. by gavage sacrifice 8-384h after single dose 24 adduct spots maximum adduct levels after 48h (Mally et al., 2005a)