Antonio Gallo
email: antonio.gallo@unicatt.it

Francesco Masoero

Terenzio Bertuzzi

Gianfranco Piva

Amedeo Pietri

Effect of the inclusion of adsorbents on aflatoxin B1 quantification in animal feedstuffs

Keywords: Chromatography -HPLC, Extraction Additives/Contaminants: Aflatoxins Food Types: Animal feedingstuffs, Milk aflatoxin B 1, analysis, feedstuffs, adsorbents, solvents 30

at two different levels of inclusion (10 and 20 g kg -1 ). After solvent extraction and immunoaffinity 16 column clean-up, all samples were analysed for AFB 1 by HPLC with fluorescence detection. For each 17 contamination level (HC and LC), the data obtained were analysed using a factorial arrangement in a 18 completely randomized design. Means were compared to the correspondent controls using the 19 Dunnett's test. No statistical difference was found in AFB 1 levels of feedstuffs not containing ADSs, 20 when extracted with AC or MeOH, even if numerically higher values were obtained with AC. A dose-21 dependent effect (P < 0.01) of ADSs inclusion was observed on AFB 1 recoveries, that were lower 22 when the higher ADS level (20 g kg -1 ) was included in the HC and LC feedstuffs. Higher AFB 1 23 recoveries were obtained using AC compared to MeOH, both in HC (75.0 vs. 12.0%, respectively) and 24 in LC (84.0 vs. 22.8%, respectively) ADSs containing feedstuffs. However, when activated carbon and 25 the sodium bentonite were included in feeds, lower AFB 1 concentrations with respect to control values 26

Introduction 31

Crops such as corn, cotton and peanuts and their industrial by-products are frequently contaminated 32 by aflatoxins (AFs), hepatocarcinogenic molecules (IARC, 2002) produced primarily by Aspergillus 33 flavus and A. parasiticus, either in field or during transport or storage [START_REF] Scheidegger | Unlocking the secrets behind secondary metabolism: a review of 363 Aspergillus flavus from pathogenicity to functional genomics[END_REF]. 34

Aflatoxin B 1 (AFB 1 ), the most toxic and carcinogenic aflatoxins (AFs) (Roebuck and Maxuitenko, 35 1994), once ingested by mammals is absorbed in the gastro-intestinal tract and appears rapidly in blood 36 [START_REF] Gallo | Aflatoxins absorption in the gastro-intestinal tract and in the 312 vaginal mucosa in lactating dairy cows[END_REF] and in milk (Veldman et al., 1992a;[START_REF] Masoero | Carryover of aflatoxin from feed to milk in 336 dairy cows with low or high somatic cell counts[END_REF] as aflatoxin M 1 (AFM 1 ), 37 the principal AFB 1 hydroxylated metabolite. The AFB 1 carry over (CO) rate into milk as AFM 1 has 38 been determined to range from 1% to 3% in lactating dairy cows and to be principally affected by milk 39 yield [START_REF] Diaz | Aflatoxin binders II: Reduction of aflatoxin M1 in milk by sequestering agents of cows 300 consuming aflatoxin in feed[END_REF][START_REF] Van Eijkeren | A simple steady-state model for carry-over of 379 aflatoxins from feed to cow's milk[END_REF][START_REF] Masoero | Carryover of aflatoxin from feed to milk in 336 dairy cows with low or high somatic cell counts[END_REF], with a reported maximum 40 value of about 6% (Veldman et al., 1992a). 41

The limits for AFB 1 fixed by the European Commision (EC) in animal feeds and complete 42 feedingstuffs for dairy animals are 20 and 5 µg kg -1 , respectively (European Commission, 2003). In 43 milk, the EC set the AFM 1 maximum permitted level at 0.050 µg kg -1 (European Commission, 2006), 44 while in the USA the maximum AFM 1 concentration is regulated by the Food and Drug Administration 45 (FDA) at 0.500 µg kg -1 [START_REF] Berg | How to establish international limits for mycotoxins in food and feed?[END_REF]. 46

Various equations to predict the AFM 1 level in milk (ng kg -1 ) from AFB 1 intake (µg per cow per 47 day) have been proposed (Veldman et al., 1992a;[START_REF] Pettersson | Carry-over of aflatoxin from dairy cattle feed to milk. 341 Healthy animals, safe foods, healthy man[END_REF][START_REF] Van Eijkeren | A simple steady-state model for carry-over of 379 aflatoxins from feed to cow's milk[END_REF]. In 48 dairy farms, the precise AFB 1 determination in animal feeds is useful to predict the AFM 1 49 concentration in milk and to avoid contamination levels exceeding the legal limits. 50 [START_REF] Trucksess | Recent methods of analysis for aflatoxins in foods and feeds[END_REF][START_REF] Stroka | 372 chromatography using post-column bromination for determination of aflatoxin B1 in cattle 374 feed: collaborative study[END_REF], such as 52 enzyme linked immunosorbent assay (ELISA) [START_REF] Aldao | Competitive ELISA for quantifying small 277 amounts of aflatoxin B1[END_REF], HPLC (Sharma and Marquez, 53 2001;Stroka et al., 2003;[START_REF] Arranz | 285 Determination of aflatoxin B1 in medical herbs: interlaboratory study[END_REF] or TLC [START_REF] Bradburn | A comparative study of solvent extraction efficiency and the 293 performance of immunoaffinity and solid phase columns on the determination of aflatoxin B 1 . 294[END_REF]. All these techniques need 54 an efficient sample extraction method. Several studies have been conducted to investigate the 55 extraction capacity of different organic/aqueous solvents, like methanol [START_REF] Reif | Determination of aflatoxins in medical herbs and plant extracts[END_REF]56 Stroka et al., 1999;Sharma and Marquez, 2001;[START_REF] Senyuva | Immunoaffinity column cleanup with liquid chromatography using post-366 column bromination for determination of aflatoxins in hazelnut paste: interlaboratory study[END_REF][START_REF] Brera | Immunoaffinity 296 column cleanup with liquid chromatography for determination of aflatoxin B1 in corn samples: 297 interlaboratory study[END_REF]), acetone 57 (Brandurn et al., 1995;Stroka et al., 2003;[START_REF] Arranz | 285 Determination of aflatoxin B1 in medical herbs: interlaboratory study[END_REF], acetonitrile [START_REF] Stroka | 372 chromatography using post-column bromination for determination of aflatoxin B1 in cattle 374 feed: collaborative study[END_REF] and 58 chloroform (Moller and Nyberg, 2004) solvents. Some studies investigated the organic solvent to water 59 ratio (ml solvent/ml water), the ratio of solvent to sample (ml solvent/g sample) and the matrix effects 60 (Brandburn et al., 1995;[START_REF] Stroka | 372 chromatography using post-column bromination for determination of aflatoxin B1 in cattle 374 feed: collaborative study[END_REF]Moller and Nyberg, 2004). 61

The AFB 1 method based on a methanol:water (80:20 v/v) extraction procedure (MeOH) and on 62 HPLC determination after an immunoaffinity clean-up step, seems to be the most common method in 63 AFs-specialized laboratories (Trucksess and Wong, 1994;[START_REF] Stroka | 372 chromatography using post-column bromination for determination of aflatoxin B1 in cattle 374 feed: collaborative study[END_REF]Sharma and Màrquez, 64 2001;Moller and Nyberg, 2004). However, the method based on an acetone:water (85:15 v/v) solvent 65 (AC) to extract AFs from feeds is also used in many laboratories, being the AOAC reference method 66 (2003.2) for AFB 1 analysis (Stroka et al., 2003;AOAC, 2006). 67

One of the most recent approaches to the prevention of mycotoxicoses in livestock is the addition of 68 adsorbents (ADSs) in the diet, that bind mycotoxins in the gastro-intestinal tract and are capable of 69 reducing their bioavailability [START_REF] Jouany | Methods for preventing, decontaminating and minimizing the toxicity of mycotoxins 323 in feeds[END_REF][START_REF] Masoero | Effects of the procedure of inclusion of a 333 sequestering agent in the total mixed ration on proportional aflatoxin M 1 excretion into milk of 334 lactating dairy cows[END_REF]. Certain ADSs can decrease 70 the aflatoxin CO in milk of dairy animals [START_REF] Diaz | Mycotoxin sequestering agents: practical tools for the neutralisation of 302 mycotoxins[END_REF][START_REF] Jouany | Methods for preventing, decontaminating and minimizing the toxicity of mycotoxins 323 in feeds[END_REF][START_REF] Jouany | Methods for preventing, decontaminating and minimizing the toxicity of mycotoxins 323 in feeds[END_REF]. Mycotoxin binders 71 belong to three different groups: silicate materials or clay minerals [START_REF] Phillips | Prevention of aflatoxicosis in farm 344 animals via selective chemisorption of aflatoxin[END_REF]Ramos and 72 Hernandez, 1996), yeast cell wall-based products [START_REF] Karaman | Evaluation of the detoxifying effect of yeast 325 glucomannan on aflatoxicosis in broilers as assessed by gross examination and histopathology[END_REF][START_REF] Yiannikouris | Reducing mycotoxin impact: the science behind 387 Mycosorb®. Nutritional biotechnology in the feed and food industries[END_REF], and 73 activated charcoals [START_REF] Galvano | Reduction of carryover 314 of aflatoxin from cow feed to milk by addition of activated carbons[END_REF]. However, these additives are not at present authorized in 74 based products) or anti-caking agents to improve feed pelleting efficiency (clay minerals) (Jaynes et al., 76 2007). 77

No specific work has been published regarding the AF extraction efficiency of solvents (acetone and 78 methanol mixed with different percentages of water) in animal feedstuffs containing mycotoxin ADSs, 79 even if some authors (Veldman, 1992b;[START_REF] Galvano | Reduction of carryover 314 of aflatoxin from cow feed to milk by addition of activated carbons[END_REF] indicated that the presence of clay ADSs 80 in feeds could reduce the analytical recovery of AFB 1 . 81

The aim of this study was to examine if the inclusion of sequestering agents in AFB 1 contaminated 82 feedstuffs can affect the extraction capacity of AC or MeOH extracting solvents. 83 84

Materials and methods 85

Preparation of feeds 86

Two AFB 1 contaminated complete feedstuffs (1350 kg each) were produced in an industrial feed 87 mill, using AFB 1 naturally contaminated ingredients: two corn meals (10.21 ± 1.27 and 32.87 ± 2.32 µg 88 kg -1 ), wheat bran (1.40 ± 0.31 µg kg -1 ), and soybean meal (1.11 ± 0.23 µg kg -1 ); the other ingredients 89 were uncontaminated barley and sunflower meal, and a mineral/vitamin supplement. The two maize 90 meals were used in order to obtain, respectively, a low contaminated (LC; 7.57 ± 0.65 µg kg -1 ) 91 feedstuff with a contamination close to the EC limit of 5 µg kg -1 (European Commission, 2003) and a 92 highly contaminated (HC; 15.33 ± 1.12 µg kg -1 ) feedstuff with a contamination three times higher than 93 the EU limit (Table 1). Both feeds, free of clay minerals or other anti-caking agents, were mixed for 4 94 minutes in a 2000 kg industrial mixer (MO/20, Grespan, Treviso, Italy). 95

The two contaminated feeds were divided into 108 sub-samples (25 kg each), 54 for LC and 54 for 96 HC, and tested for the AFB 1 contamination homogeneity, randomly selecting and checking 9 samples 97 for LC and 9 samples for HC. 1). 99

In this study we tested four different types of silicate minerals (sodium and calcium bentonite clays; 100 zeolite and kaolinite), one yeast cell wall-based product, an activated carbon, and three commercial 101 products commonly used in industrial feed mills and in dairy farms (Table 2) [START_REF] Masoero | Effects of the procedure of inclusion of a 333 sequestering agent in the total mixed ration on proportional aflatoxin M 1 excretion into milk of 334 lactating dairy cows[END_REF]. 102

The ADSs were characterized for elementary composition (Table 2) and used at two inclusion levels 103 (10 and 20 g kg -1 ) in LC and HC feedstuffs. The nine ADSs were a sodium bentonite (Amcol 104 International Corp., Arlington Heights, IL, USA), a calcium bentonite (Tecnozoo, Padova, Italy), a 105 zeolite (Fluka 96096, Sigma-Aldrich Chemie Gmbh, Switzerland), a kaolinite (Fluka 03584, Sigma-106 Aldrich Chemie Gmbh, Switzerland); a yeast cell wall-based product (Mycosorb ® , Alltech Italy, 107 Bologna, Italy), an activated carbon product (Acque Nymco, Milan, Italy), and three commercial ADSs 108 (Atox ® , Grupo Tolsa, Madrid, Spain; Myco AD AZ, Ascor Chimici, Forlì-Cesena, Italy; Novasil TM 109 plus, Trouw Nutrition Int., Verona, Italy). The manufacturer's specifications of the commercial 110 products classify Atox® and Myco AD AZ as clay mixtures where the presence of aluminosilicates of 111 the smectite group exceeds 85% of the product. In particular, the first could be considered a magnesium 112 bentonite, being magnesium the dominant cation, while the second is a mixture of sodium and calcium 113 bentonite. Novasil TM plus is generally described by the producer as a hydrated sodium calcium 114 aluminosilicate. Recently, some authors reported that this product could be classified as a 115 montmorillonite clay [START_REF] Pimpukdee | Aflatoxin-348 induced toxicity and depletion of hepatic vitamin A in young broiler chicks: protection of 349 chicks in presence of low levels of NovaSil PLUS in the diet[END_REF][START_REF] Bailey | Efficacy of 288 Page 12 of 21 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co[END_REF]. 116

The 108 feed sub-samples were randomly assigned to the 9 ADSs (12 sub-samples each) to obtain 3 117 replicates for the two inclusion levels (10 and 20 g kg -1 ) and the two contamination levels (LC and 118 HC). Then, all the sub-samples were mixed for 4 minutes in a 50 kg mixer before being analyzed for 119 the AFB 1 content. 120

The experimental model studied the effects of: contamination levels (LC and HC); ADSs (n=9); 121 doses (10 and 20 g kg -1 ) and replicates (n = 3) for a total of 108 samples. 122 Solvents and reagents. Solvents used were of grade ACS-ISO. Acetonitrile, acetone and methanol were 125 HPLC grade (purity 99.5%, 99.0% and 99.9%; respectively) from Merck (Darmstadt, Germany). 126

Water. Purified water was obtained from a Milli-Q Gradient A10 water purification device (Millipore,127 Bedford, MA, USA). 128

Phosphate-buffered saline (PBS). PBS was prepared by dissolving 0.20 g KCl, 0.20 g KH 2 PO 4 , 1.16 g 129 anhydrous Na 2 HPO 4 and 8.00 g NaCl in 1 l of water. The pH was adjusted to 7.4 with NaOH (0.1 mol 130 l -1 ). 131 132 Standards. The AFB 1 standard was obtained from Sigma-Aldrich (St. Louis, Mo, USA). A stock 133 solution (9.517 mg l -1 ) was prepared and checked according to the AOAC method 970.44 (AOAC, 134 1995) and stored at -20°C when not in use. The working standard solution was prepared after 135 evaporation at room temperature under nitrogen of an aliquot (100 µl) of the stock solution and re-136 dissolution in chloroform (10 ml) by ultrasonication, resulting in an AFB 1 concentration of 95.176 µg l - 137

1 . An aliquot (100 µl) of this solution was evaporated at room temperature under nitrogen and re-138 dissolved in the HPLC mobile phase (0.5-20 ml), to obtain 11 calibration solutions at individual 139 concentrations between 0.475 and 19.035 µg l -1 . 140 141

Extraction procedures 142

Sample preparation and clean up. To determine AFB 1 in feeds, 25 g of sample were extracted with 250 143 ml of a methanol/water mixture (MeOH, 80:20, v/v) according to [START_REF] Stroka | 372 chromatography using post-column bromination for determination of aflatoxin B1 in cattle 374 feed: collaborative study[END_REF] the solution was purified through an immunoaffinity column (R-Biopharm Rhône Ltd, Glasgow, UK), 148 previously conditioned with 20 ml of PBS. After washing, the column with 5 ml distilled water, AFB 1 149 was slowly eluted with 2.5 ml of methanol. 150

The eluate was dried under a gentle stream of nitrogen, re-dissolved in 1 ml of acetonitrile:water 151 of a cereal mix meals; 115 g kg -1 of a soybean meal; 50 g kg -1 of a sunflower meal; and 5 g kg -1 of a 171 mineral/vitamin supplement) without addition of any ADSs. The recovery values were estimated by 172 spiking eight blank samples (25 g each) with 0.5 ml of an AFB 1 standard solution (250 µg l -1 dissolved 173 in methanol) in order to obtain a concentration of 5 µg kg -1 . After addition of the spiking solution, the 174 organic solvent was evaporated at room temperature (22°C) under a ventilated hood for 2 hours. The 175 spiked samples were then analysed according to the two extraction procedures (MeOH and AC,, four 176 replicates each) as described above. Four replicates of a certified reference material (ground corn, R-177 Biopharm Rhône LTD) were also analysed. 178 179

Statistical analyses 180

The AFB 1 contents in feedstuffs without ADSs were tested for homogeneity using the one-way 181 analysis of variance procedure of SAS ® (version 9.1, SAS Institute Inc., Cary, NC). 182

The AFB 1 contents of the feedstuffs supplemented with ADSs were evaluated in a completely 183 randomized design using the general linear model procedure of SAS ® . A 2 x 2 x 9 factorial 184 arrangement for each AF contamination level (HC and LC) was used and fixed effects in the model 185 included extraction procedure (Method; 2 levels), inclusion doses (Dose; 2 levels), ADSs (ADS; 9 186 levels) and associated first order and second order interactions. Dunnett's test was used for comparing 187 treatments with the appropriate control (Lowry, 1992). Significance was declared at P < 0.05. 188 189

Results and discussion 190

The average recovery values were 96.6±1.8% and 97.8±2.1% for MeOH and AC extraction 191 procedures, respectively. The declared AFB 1 contamination of the certified reference material was 192 4.1±1.0 µg kg -1 ; the results obtained were 4.2±0.2 and 4.3±0.1 µg kg -1 using the MeOH and AC 193 procedures, respectively. The limit of detection (LOD, signal-to-noise ratio of 3:1) and of 194 quantification (LOQ, signal-to-noise ratio of 10:1) were respectively 0.02 and 0.05 µg kg -1 . 195 No statistical differences were found in AFB 1 levels of feedstuffs non containing ADSs, when 196 extracted with AC or MeOH, even if numerically higher values were obtained with AC. The F-test at 197 the 95% confidence level demonstrated that the sub-sample variance was not different from the 198 analytical variance (F calc =0.479 and F calc =0.358 versus F crit =3.500, respectively for HC and LC), thus 199 demonstrating good homogeneity of the prepared feeds (table 1). 200

Considering the composition of commercial clays (table 2), Novasil TM plus can be classified as a 201 calcium montmorillonite [START_REF] Pimpukdee | Aflatoxin-348 induced toxicity and depletion of hepatic vitamin A in young broiler chicks: protection of 349 chicks in presence of low levels of NovaSil PLUS in the diet[END_REF][START_REF] Bailey | Efficacy of 288 Page 12 of 21 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co[END_REF][START_REF] Afriyie-Gyawu | 273 NovaSil clay does not affect the concentrations of vitamins A and E and nutrient minerals in 274 serum samples from Ghanaians at high risk for aflatoxicosis[END_REF], a 202 mineral clay that represents the main constituent of bentonite clays [START_REF] Diaz | Mycotoxin sequestering agents: practical tools for the neutralisation of 302 mycotoxins[END_REF]. Atox ® , 203 which is characterized by a high Mg level (14.8 ± 0.39%), can be classified as a magnesium bentonite, 204 in agreement with the manufacturer's specifications; Myco AD AZ exhibited the highest carbon and 205 the lowest ash level (41.0 and 75%, respectively) among clays. 206

The statistical analysis showed a dose-dependent effect (P < 0.01) of ADSs inclusion on AFB 1 207 recoveries, that were lower when the higher ADS dose (20 g kg -1 ) was included in the HC and LC 208 feedstuffs (tables 3 and 4). 209

In particular, in HC feedstuff integrated with ADSs and extracted using the AC solvent, the average 210 recovery was 75.0%, while a very low AFB 1 recovery (12.0%) was obtained when the MeOH solvent 211 was used. A similar trend, but higher AFB 1 recoveries, was observed for the LC feedstuffs (84.0 and 212 22.8% using AC and MeOH, respectively). Therefore, the AFB 1 extraction capacity of MeOH in 213 feedstuffs containing ADSs resulted significantly lower (P < 0.001) with respect to AC: the MeOH 214 method in presence of ADSs showed figures that are far from performance requirements for AF 215 methods fixed in the EC Regulation 401/06 (recoveries of 70-110% and 80-110% in the range 1-10 and 216 >10 µg kg -1 , respectively). Besides, when the MeOH extraction method was applied to HC feedstuffs 217 integrated with ADSs, the AFB 1 concentrations resulted lower (P < 0.001) than the control value (13.8 218 µg kg -1 ) for all the samples (table 3) and under the EU limit of 5 µg kg -1 (EC, 2003). On the contrary, 219 when AC was used the observed AFB 1 concentrations exceeded this limit, with values ranging from 5.7 220 µg kg -1 (activated carbon) to 13.6 µg kg -1 (Novasil TM plus). Similar results were obtained in LC 221 feedstuffs (table 4), with AFB 1 concentrations exceeding the EU limit only when the analyses were 222 performed using the AC solvent (with the exception of activated carbon). 223

In particular when the activated carbon was added to the feedstuffs the AFB 1 content measured using 224 the AC method differed (P < 0.001) from control values (15.3 and 7.6 µg kg -1 , respectively for HC and 225 LC feeds) in all the experimental conditions (Tables 3 and4). In presence of activated carbon, the 226 AFB 1 recoveries measured with AC at 10 and 20 g kg -1 were respectively 52 % and 37 % in the HC; 55 227 % and 39 % in the LC feeds,. This can be due to a high affinity of the activated carbons versus the 228 AFB 1 molecule [START_REF] Lemke | Development 328 of a multi-tiered approach to the in vitro prescrenning of clay-based enterosorbents[END_REF][START_REF] Vekiru | Investigation of various 381 adsorbents for their ability to bind Aflatoxin B 1[END_REF] that could cause a reduction of extraction 229 capacity of the AC mixture. In agreement with our data, [START_REF] Galvano | Reduction of carryover 314 of aflatoxin from cow feed to milk by addition of activated carbons[END_REF] reported a similar 230 reduction (from 41 % to 74 %) of analytical content of AFB 1 in a pelleted feed containing activated 231 carbons. 232 Also when the sodium bentonite was added to contaminated feeds, lower (P < 0.05) AFB 1 233 concentrations with respect to controls were measured both in HC (20 g kg -1 dose) and LC (10 and 20 g 234 kg-1 doses) feedstuffs. However, the AFB 1 recoveries were higher than those obtained for activated 235 carbon, ranging from 63 % to 76 %. 236

The data obtained in this experiment indicate that a routine use of the MeOH solvent for AFB 1 237 analysis of unknown feedstuffs, can produce misleading results if they contain an ADS. Consequently, 238 when an ADS is included in a contaminated feed, the analytical result for AFB 1 could comply with or 239 largely exceed the EU limit in feedstuffs for dairy animals (EU, 2003) according to whether it was 240 obtained using MeOH or AC as extracting solvent, respectively. In any case, also AC did not result 241 fully adequate for AFB 1 quantification in experimental feeds containing two types of ADS (i.e., sodium 242 Erroneous data regarding the true AFB 1 contamination level of a feedstuff may lead to incorrect 247 managerial decisions in dairy farms and consequently to higher than expected AFM 1 levels in milk. In 248 fact, the AFM 1 level in bulk milk (µg kg -1 ) depends on the quantity of AFB 1 ingested (µg per cow per 249 day). According to Veldman et al. (1992a), this relationship can be described by the following 250 equation: 251AFM 1 (µg kg -1 of milk) = (1.19 * x + 1.9) / 1000 252 where x is the AFB 1 (µg) ingested daily by each cow in the herd. 253

According to our study, if 10 kg of the HC feedstuff is daily administered to cows, considering the 254 AFB 1 result obtained by AC extraction (15.33±1.18 µg kg -1 ), 153.3 µg per cow per day can be 255 calculated and the predicted AFM 1 bulk milk concentration should be 0.184 µg kg -1 . Otherwise, if 10 256 kg of the HC feedstuff containing 10 g kg -1 of an ADS is given to cows, the AFB 1 level in the feed will 257 be 12.4 or 2.3 µg kg -1 (mean values excluding the activated carbon thesis) according to whether the AC 258 or MeOH solvent had been adopted, respectively. Consequently, a daily AFB 1 consumption of 123.7 or 259 23.3 µg per cow per day can be calculated, and a milk contamination of 0.149 or 0.030 µg kg -1 of 260 AFM 1 can be predicted. The latter value, calculated on the basis of the MeOH result, is well below the 261 limit of 0.050 µg kg -1 set by the EU (EU, 2006), but the real situation is quite different, as reported in 262 our previous work [START_REF] Masoero | Effects of the procedure of inclusion of a 333 sequestering agent in the total mixed ration on proportional aflatoxin M 1 excretion into milk of 334 lactating dairy cows[END_REF]. In conclusion, it is clear that the ascertainment of the real 263 AFB 1 concentration of feedstuffs containing ADS is essential to avoid putting dairy farmers at risk of 264 unknowingly producing contaminated milk, which will have to be discarded. 1. AFB 1 content (µg kg -1 ) of ingredients and feedstuffs using acetone:water (AC; 85:15 v/v) and methanol:water (MeOH;80:20 v/v) extraction solvents and feedstuff composition (g kg -1 ).

Ingredients

AFB 1 (µg kg -1 ) Feedstuff composition (g kg 3.8 ± 0.79 53.7 ± 0.58 1.6 ± 0.04 21.8 ± 0.47 1.5 ± 0.03 14.8 ± 0.39 0.4 ± 0.02 0.6 ± 0.25 0.9 ± 0.12 94.6 ± 0.9

Myco AD AZ 41.0 ± 0.62 34.6 ± 0.38 5.2 ± 0.17 14.4 ± 0.57 1.2 ± 0.03 0.9 ± 0.02 0.5 ± 0.04 0.6 ± 0.07 1.2 ± 0.10 75.1 ± 0.

  photochemical derivatization to AFB 2α . The detector was set at 365 nm excitation and 440 nm emission 162

  carbon). This fact suggests that other solvent mixtures should be evaluated to 243 improve AFB 1 extraction from feeds containing ADSs. 244 245 Conclusions 246

  The 18 samples were analyzed in duplicate with AC and MeOH 98

	extraction solvents (Table
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	O n
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Table 2 .

 2 Elementary composition and total ash content of the tested adsorbents. 1

	-1 )

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

Table 3 .

 3 AFB 1 concentrations (µg kg -1 ) detected using acetone:water (AC, 85:15 v/v) and methanol:water (MeOH, 1 80:20 v/v) extraction solvents in HC feedstuff mixed with different adsorbents at two doses (10 and 20 g kg -1 ). The 2 AFB 1 concentrations in untreated HC (control) were 15.33 ± 1.18 and 13.81 ± 1.05 µg kg -1 using AC and MeOH,

	1

53 ± 1.66 1.05 ± 0.14*** 13.59 ± 1.94 0.84 ± 0.13***

					Deleted: ¶
			F o r
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			R		Deleted: 01 a
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		P of the model < 0.001	S.E.M. a 0.6124	w	Formatted: Font: 10 pt
	5 6	Source of variation (P value) ADS < 0.001 Dose < 0.01 Method < 0.001 ADS x Dose < 0.05 ADS x Method < 0.001 Dose x Method = 0.8503 ADS x Dose x Method = 0.0702 a S.E.M.: standard error of the mean. Superscripts signify means differ from respective controls: *P < 0.05, **P < 0.01, ***P < 0.001. O n l y	Formatted: Font: 10 pt Formatted: Font: Italic Formatted: Font: 10 pt Formatted: Font: Italic Formatted: Font: 10 pt Formatted: Font: Italic Formatted: Font: 10 pt Formatted: Font: 10 pt

Table 4 .

 4 AFB 1 concentrations (µg kg -1 ) detected using acetone:water (AC, 85:15 v/v) and methanol:water (MeOH, 1 80:20 v/v) extraction solvents in LC feedstuff mixed with different adsorbents at two doses (10 and 20 g kg -1 ). The 2 AFB 1 concentrations in untreated LC (control) were 7.57 ± 0.65 and 7.02 ± 0.63 µg kg -1 using AC and MeOH,

	3
	4	respectively.
					Dose
		Adsorbent	10 g kg -1			20 g kg -1
			AC	MeOH	AC	MeOH
		Sodium bentonite	5.46 5.39	0.55 0.52	6.80 4.90	0.44 0.41
			5.41	0.51	5.11	0.48
		mean	5.42 ± 0.46*	0.53 ± 0.02***	5.60 ± 1.04*	0.45 ± 0.03***
			8.31	2.28	6.90	1.35
		Calcium bentonite	7.19	1.66	7.78	1.44
			7.25	1.89	6.78	1.33
		mean	7.58 ± 0.63	1.94 ± 0.31***	7.15 ± 0.55	1.37 ± 0.06***
			8.29	2.36	7.11	2.55
		Zeolite	7.23	2.78	6.49	2.54
			7.15	2.15	6.56	2.36
		mean	7.56 ± 0.64	2.43 ± 0.32***	6.72 ± 0.34	2.48 ± 0.11***
			5.89	2.27	6.07	2.16
		Kaolinite	7.32	2.17	6.61	1.97
			6.29	2.35	6.12	2.09
		mean	6.50 ± 0.73	2.27 ± 0.09***	6.27 ± 0.30	2.07 ± 0.09***
			6.96	2.16	6.19	2.36
		Yeast cell wall-based	6.73	2.50	6.74	2.40
			6.75	2.13	6.53	2.56
		mean	6.81 ± 0.13	2.26 ± 0.20***	6.49 ± 0.28	2.44 ± 0.11***
		Activated Carbon	4.38 4.03	1.40 1.20	2.88 3.04	0.71 0.83
			4.11	1.30	3.01	1.04
		Mean	4.17 ± 0.18***	1.30 ± 0.10***	2.98 ± 0.09***	0.86 ± 0.17***
			7.10	0.86	7.66	0.58
		Atox ®	7.74	0.84	6.70	0.66
			6.92	0.82	7.38	0.55
		Mean	7.25 ± 0.43	0.84 ± 0.02***	7.25 ± 0.49	0.60 ± 0.06***
			6.91	4.19	6.50	2.68
		Myco AD AZ	7.06	4.94	6.26	2.94
			6.07	5.59	6.36	2.92
		Mean	6.68 ± 0.53	4.91 ± 0.70***	6.37 ± 0.12	2.85 ± 0.14***
			8.11	0.80	5.54	0.57
		Novasil TM plus	6.90	0.88	5.47	0.69
			7.21	0.83	5.74	0.54
		mean	7.

41 ± 0.63 0.83 ± 0.04*** 5.58 ± 0.14 0.60 ± 0.08***

  P of the model < 0.001 S.E.M. a 0.2254

Source of variation (P value)

  Superscripts signify means differ from respective controls: *P < 0.05, **P < 0.01, ***P < 0.001.

	ADS < 0.001 Dose < 0.010 Method < 0.001
	ADS x Dose = 0.001 ADS x Method < 0.001 Dose x Method = 0.3331
	ADS x Dose x Method = 0.0610

a S.E.M.: standard error of the mean. 5 6 Formatted: Font: Italic Formatted: Font: Italic Formatted: Font: Italic Deleted:

Acknowledgments 267

This research was supported by the AFLARID project of Ministero delle Politiche Agricole, 268 Alimentari e Forestali (MiPAAF -Italy). 269


H Barton
email: mfbarton@cyf-kr.edu.pl

Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 5: Zinc

Keywords: Exposure assessment, FAAS, Metals -uptake Additives/Contaminants: Food contact materials, Trace elements (nutritional), Trace elements (toxic drinking water, zinc intake, water contamination, health protection, children

Zinc(Zn) exposure in pre-school children via household drinking water collected by double sampling method (morning, evening) was evaluated in a sample of the Polish population. The Zn concentration was measured by the Flame Atomic Absorption Spectrometry. Rural and sub-urban Krakow sites were nondistinguishable in respect of Zn concentrations. However, significantly lower Zn was found in urban as compared to non-urban sites, (geometric mean(95% confidence interval) 0.14 (0.01-1.95) mg L -1 vs. 0.52 (0.03-10.2) mg L -1 , p<0.001. Zn levels in water standing overnight in pipelines were higher in all sites by 0.36 mg L -1 on average, but observed contaminations were higher. The Zn limit based on taste and colour of for drinking water (3 mg L -1 ) was exceeded in 1 and 10% of households, from urban and non-urban sites, respectively. The Zn intake predictions for evening water samples for 6 years old children averaged between 2% and 9% of the Recommended Dietary Allowance (RDA, 10 mg day -1 ) for urban and nonurban sites, respectively. Mean Zn intake prediction for the exceedance fraction was 64% of RDA. In conclusion, over-night contamination of drinking water from in-house pipelines was common to a significant and similar extent at all sites investigated. Secondly, drinking water can be a considered a significant contributor to dietary Zn intake by children in non-urban sites and may shift the population borderline of deficiency.

Introduction

Multi-factorial implication of zinc (Zn) in human functioning results in complex aspects to be considered including nutritional adequacy, borderlines of malnutrition and overload, toxicity and numerous interferences [START_REF] Who | Zinc in drinking-water. Background document for preparation of WHO Guidelines for drinking-water quality[END_REF]. There are several known beneficial but disadvantageous effects of zinc. Acute zinc toxicity is rare, and mild toxic events were mainly related to supplemental overload. Recent studies in focus suggest that Zn can impair cognitive functions and memory [START_REF] Flinn | Enhanced zinc consumption causes memory deficits and increased brain levels of zinc[END_REF]) and seems to be involved in neuro-degeneration events (e.g. [START_REF] Zatta | Alzheimer's disease, metal ions and metal homeostatic therapy[END_REF]) together with copper and iron.

Both, zinc overload as well as its deficiency can impair human health, suggesting that Zn balance is of a key importance. Steady supply, or its lack, from every-day dietary source, namely drinking water, is thus worth for closer look-up.

The major health concern of zinc is focussed on nutritional inadequacy of the population, since the population at risk of deficiency worldwide was estimated as high as 20.5% [START_REF] Hotz | Assessment of the risk of zinc deficiency in populations and options for its control[END_REF][START_REF] Walker | Global and regional child mortality and burden of disease attributable to zinc deficiency[END_REF]. Zn absorption varies depending on diet and Zn content and reaches up to 92% at low Zn intakes [START_REF] Hunt | Adaptation in human zinc absorption as influenced by dietary zinc and bioavailability[END_REF]). Zn absorption is strongly associated with protein content in foods [START_REF] Wapnir | Zinc deficiency, malnutrition and the gastrointestinal tract[END_REF], and insufficient protein intake may be the cause of zinc deficiency.

A recent study of populations in four EU countries revealed significant regional differences related to dietary profiles [START_REF] Marcellini | Zinc status, psychological and nutritional assessment in old people recruited in five European countries: Zincage study[END_REF]) and suggested a risk of Zn deficiency [START_REF] Cruz | Dietary habits and nutritional status in adolescents over Europe-Southern Europe[END_REF]. Some ad hoc evaluation studies in Poland suggested a significant deficit of zinc in the Polish population [START_REF] Stopnicka | The evaluation of nutrition quality of adolescents living in residential schools at the province of Białystok][END_REF]. A study of women with low physical activity indicated Zn intake to be below recommended levels [START_REF] Bronkowska | Evaluation of minerals contents in daily food rations of low physically active women[END_REF]. In the study in southern Poland a marginal zinc deficiency was identified in about 16% of 11-year-old children [START_REF] Schlegel-Zawadzka | Comparative analysis of zinc status, food products frequency intake and food habits of 11-year-old healthy children[END_REF]. Similarly, significant risk of Zn deficiency was suggested in about a half of female population of Polish university students [START_REF] Szymelfejnik | Magnesium, Zinc and Copper Intake by Polish University Students[END_REF]) and adolescents [START_REF] Augustyniak | Nutrients intake of the adolescents in Poland-ten years literature review (1990-2000)[END_REF].

DW was rarely included as explicit contributor to intake of nutrients. According to studies reviewed in the background WHO document on zinc in DW, tap-water can provide up to 10% of the daily intake [START_REF] Who | Zinc in drinking-water. Background document for preparation of WHO Guidelines for drinking-water quality[END_REF]. In the study in Poland, DW was found to be a considerable source of zinc intake for elderly [START_REF] Kaluza | Contribution of food products and drinking water to the intake of minerals by elderly (in Polish)[END_REF].

Besides, natural waters zinc, like copper, is as low as at microgram levels and can reach milligrams levels at tap, depending on corrosion of metallic supply systems. Corrosion-derived fractions of zinc and copper in DW originate from different parts in pipeline system. However, mixed iron-zinccopper (and lead) pipeline systems are especially liable to electrochemical processes and dissolution of less noble metal. Zinc in drinking water at concentrations above about 3 mg L -1 can give rise to problems with appearance and taste to humans. Because of low Zn levels observed in DW and its organoleptic properties at excess, the presence of Zn in drinking water was not regarded to be of human exposure concern. WHO guideline value for Zn in DW was suggested at 3 mg L -1 , and 5 mg L -1 by US EPA (2002), while no regulation was established in EC (1998). In 2003 WHO agreed the Zn risk assessment to be brought forward to the current edition of the Guidelines for Drinking-Water Quality [START_REF] Who | [END_REF]. Polish regulation in force until 2002 allowed 3 mg Zn L -1 , then abstained from defining an allowable Zn limit ((PMH 2007) following EC regulation.

Based on former WHO recommendations, Dietary Allowance values suggested for Polish population (RDA, safe level) ranged depending on age and gender between 5-21 mg day -1 [START_REF] Ziemlanski | Recommended dietary Allowances for the Polish population (energy, protein, fat, vitamins and minerals)[END_REF]. New Dietary Reference Intakes (DRI) for North Americans were set at 2-13 mg day -1 and upper intake levels was set at 40 mg day -1 (US DRI 2000). An evaluation of methodological approaches of current nutritional recommendations in EC countries has been published recently [START_REF] Doets | Current micronutrient recommendations in Europe: towards understanding their differences and similarities[END_REF]). As one of the highest priority nutrients, zinc was scheduled for early updating actual Dietary Reference Values (DRV) for EC (EFSA 2008). Zinc is a subsequent element in our studies [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 4[END_REF] analysed in household drinking water and evaluated for extent of contamination in pipelines and for nutrient intake predictions in 6-year-old children.

Materials and methods

The study area and population were described previously [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow, Poland. Part 3: Aluminium[END_REF]). Briefly, the study comprised ca. 600 households and pre-schools and was performed in the period 1997-2004. From about a half of households 5-7 year-old pre-school children were included. The drinking water (DW) samples were collected in households by double sampling method, in the morning (W1 or DW1) and in the evening (W2, DW2), in Kraków urban (U) and suburban (P) sites and rural (R) areas of south eastern Poland.

The anthropometrical data of children were previously published [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 2: Cadmium (year 1997-2001)[END_REF]). Characteristics of the current group of children for Zn evaluation were (mean±standard deviation): N=314, gender structure 45.5% boys; age 6.6±0.6; body weight 24.1±4.5 kg; height 1.23±0.07 m; body mass index (BMI) 16.0±2.4 kg m -2 ; adequate water intake (AWI) 1.56±0.06 liter was calculated as described previously [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 1: Lead (year 2000)[END_REF].

General methodology

The analytical method fulfilled the best laboratory approaches for trace elemental analysis, as described earlier [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 1: Lead (year 2000)[END_REF]. High purity deionised water (Milli-Ro & Milli-Q, Millipore), reagents and standards for calibration and rigorous quality control of analyses were applied. All measurements were done in 0.5% (v/v) nitric acid.

Analytical characterisation

Zinc analyses were performed by means of flame atomic absorption spectrometry (F-AAS, Perkin-Elmer 5100ZL) at parameters: 10 cm long burner, hollow-cathode lamp (HCL), analytical wavelength 213.9 nm, slit 0.7 nm, flame gas air-acetylene flow rates ratio (in litre/minute) 10 : 2, injection flow rate ca. 1 ml/minute, analytical signal -3 sec time averaged absorbance, measurement run -three successive signals, estimation -duplicate successive runs accepted if the relative standard deviation was below 5%.

The analytical characteristics were as follows: calibration range 0-2 mg L -1 , analytical limit of detection (LOD, 3SD) and quantitation (LOQ, 10SD) was obtained at 0.005 mg L -1 and 0.017 mg L -1 (N=27), respectively; the method LOD and LOQ was 0.013 mg L -1 and 0.043 mg L -1 , respectively; precision for Zn standard 0.1 mg L -1 was 2.6%, and 1.3-1.6% in the range 0.25-2.0 mg L -1 ; recovery 97-102%.

Data processing

The non-linear curves were obtained within the calibration range. Sensitivity of analytical system was tracked during the analyses with control standard and blank measured every ten runs. Machine concentration estimations were tentative only and final results were obtained by more sophisticated procedure described previously. The software-collected internal signals were subjected to postmeasurement processing consisting of: 1) precise re-calibration via estimation of analytical form of calibration equation, 2) estimation of numerical time(run)-functions with non-linear fitting, describing the signals of cyclic quality controls. The equations were further used for correction of the sensitivity drift and slow waving by interpolation and with combination of recalibration equations lead to final estimations, as described earlier [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow, Poland. Part 3: Aluminium[END_REF]. All numerical processing were smoothly performed with home-made macros for commercial software.

Calculations and statistics

Concentrations below limit of detection were replaced for convenience by the ½ LOD values.

The metal intakes were calculated from approximated adequate daily water requirement approximated by 1.5±0.25 litre, as described previously [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 1: Lead (year 2000)[END_REF]]. The relative intake was calculated as percentage of RDA values at safe level 10 mg day -1 for 4-6 year-old Polish children (Ziemlanski et al.1998).

The cumulative uncertainty of the metal intake was approximated by the sum of particular Relative indices of changes in metal concentration in water during standing in pipelines were expressed as a combination of morning and evening concentrations (W1, W2): R 1,2 -ratio of W1:W2; D 1,2 -difference of W1 -W2 and D 1,2% -as its percentage (relative difference) vs. higher metal concentration, W1 or W2, obtaining two sets of values, positive (fraction 'a') -contamination and negative (fraction 'b') -deposition.

Statistical analysis was performed with the use of Statistica for Windows (StatSoft, inc.). Both non-parametric and parametric tests were applied, if necessary. The t-test or Kruskal-Wallis ANOVA and χ 2 (chi-square) were used, if were applicable. All mean values were geometric means (GM) or/and medians (MED), if not stated otherwise. The 95% confidence interval (CI) was estimated from distribution profile as GM*SDg ±1.96 or from frequencies as 2.5 and 97.5 percentiles.

Results

Zinc concentrations in drinking water

Among ca. 600 investigated households, the maximum zinc concentration in DW was 17.3 and 9.0 mg L - 1 , for morning (W1) and evening (W2) series, respectively. No significant time-trend in Zn concentration was observed comparing the period before and after year 2000 in any site and sample series. Peripheral and rural sub-sites were comparable, thus these sites can be discussed as a uniform non-urban site (NU).

Distribution of Zn concentrations in evening DW series for U and NU-sites is shown in Figure 1.

[Insert Figure 1 about here] The frequency profiles were strict lognormal for both U and NU subsets. Number of analytical outliers below LOD was marginal (<1%). The distribution for U sites was significantly different (p<0.001) and shifted down vs. NU concentrations. There is no visible indication of multi-modal structure of the both profiles.

Mean Zn concentrations in W1, W2 samples for U, P and R and combined sites are collected in Table I.

[Insert Table I about here]

Zn concentration was substantially lower at U sites: GM in W2 samples (mg L -1 ) were 0.14 while Strong differences were observed between W1 and W2 series in every site (p<0.001). W1 concentrations were two-three times higher, as indicated R 1,2 values in Table I. The related parameters (difference and ratio) were calculated for the major fraction of households, where metal concentration increased after overnight stagnation in pipelines. The contamination was not site dependent, if absolute values (D 1,2 ) were compared for U vs. NU (p>0.05). Relative contaminations (D 1,2% as D 1,2 per cent) or a ratio (R 1,2 ) were different. Mean relative increase of Zn in DW due to interior contamination was 66% and 49% for U and NU sites, respectively.

The exceedance of aesthetic limit of 3 mg L -1 was negligible in U sites and significant in NU sites (18-22% for W1 and twice less for W2).

Metal concentration in morning and evening samples

Distribution of metal concentrations in DW samples was shown as two-dimensional projection (evening vs. morning) in Figure 2. Each point represents one household for which a pair of samples was collected.

[Insert Figure 2 about here] The two cut-off lines refer to the aesthetic Zn limit in drinking water in force in the period of sample collection, while line 1:1 refers to W1 and W2 equality. The sectors A -C comprise the households for which metal concentration fell below the limit for both W1 and W2 samples (A), over the morning or evening (B1 or B2) and over the limit for both (C). Inserted box in Figure 2 shows percentages of households in particular sectors.

Significant number of households, about 10% from NU sites, contained Zn over the aesthetic limit both in W1 and W2. The sum of percentages in respective sectors refers to the exceedance given in Table 1 at some approximation due to single values. Zn concentrations in DW from sources A-E were within the range (GM in mg L -1 ) 0.37-0.97 and 0.16-0.42, in W1 and W2, respectively. The differences between sources were significant in both W1 (p<0.01) and W2 (p<0.05), and between pairs W1 and W2 in each group (p<0.05 at least).

Metal concentrations in water from the major water treatment plants

Weighted mean metal concentration by contributions of five supply systems to water consumption, reflecting average Zn concentration in water potentially consumed by population of Krakow was 0.49 and 0.18 mg L -1 , for W1 and W2, respectively.

Influence of the pipelines

The effect of overnight water stagnation in pipelines on the changes in metal concentration depending on its background concentration in W2 was shown by different projections in Figures 4A-B. W2 taken in the evening was assumed to be fully flushed water not influenced by pipeline interior and to correspond to metal concentrations in water supplied by the WTPs. The households were divided into two fractions, and those where Zn concentration increased were designated as 'a' ( D 1,2 >0) or decreased, 'b' (D 1,2 < 0).

The plots show absolute values of concentration change (D 1,2 ), its percent (D 1,2 %), and the ratio (R 1,2 ) of W1 to W2.

[Insert Figure 4A and 4B about here] In ca. 80% households Zn concentration increased in over-night standing water due to contamination (mode 'a') and a decrease was observed for a remaining households ('b'). Both effects were accelerated with increase in background Zn (W2).

In the Figure 4A, in the mode 'a' a plateau at the average D 1,2 value 0.70 mg L -1 was observed in the middle range of Zn concentrations and comprised 49% of fraction 'a'. For fraction 'b' the percentage of deposition (Figure 4B) was practically independent of Zn in W2 and the average was ca. -40% for most of 'b' samples.

The above plots drawn separately for U and NU domains albeit qualitatively similar show certain quantitative differences, what will be described elsewhere.

Zinc intake with drinking water by children

The intake predictions were calculated using adequate water intake (1.5 L day -1 ) and anthropometric data of study group of children. The intakes were expressed as daily intakes, daily intakes per kilogram of body weight and as a percent of Polish RDA for 4-6 year old children, separately for both, W1 and W2 water.

Two criteria were applied for selection of 'risk groups', i.e. exceedance of the Zn concentration aesthetic limit (risk group 1) and RDA for 4-6 year old children (risk group 2). Mean predicted Zn intakes from W1 and W2 drinking water by 6-year-old children for selected subgroups were collected in Table II.

[Insert Table II about here]

Mean predicted Zn intakes for the whole group were (GM) 0.82 and 0.38 mg day -1 for W1 and W2, respectively, and contributed by 5.6-17.6 and 2.0-11.7 % RDA, for W1 and W2, respectively. The lowest predictions were for urban group, while for non-urban one were several times higher. Exceedance the aesthetic limit (risk group 1) included 10 (7) % of the children studied, and contribution of W1 (W2) in this group to RDA was 81%(64 %).

RDA was exceeded for about 2% of children (risk group 2) taking W1, while none for W2. There is certain difference in exceedance values between the study group of children and total population comprising all households with and without children (Table 1), and from which the risk group 1 included less households, i.e. 9 (4) %. However, Zn concentrations for households with children included and whole population were statistically homogeneous among major sites and the difference was just random. This allows for alternative evaluations of parameters with the same significance for which anthropometrical data are not required.

Discussion

Zn levels among sites

The DW Zn concentrations were low in urban areas if compared to non-urban sites. Within non-urban category peripheral and rural sites were not distinguishable for most parameters of zinc. The above results confirmed substantial differences of DW quality between urban and non-urban sites, similarity of spread, private houses, independent of environment (rural or sub-urban) and contamination at stagnating of similar extent in all site types. The significant differences between urban and non-urban sites were also observed for several metals (Pb, Cd, Al) described earlier [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 1: Lead (year 2000)[END_REF][START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 2: Cadmium (year 1997-2001)[END_REF][START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow, Poland. Part 3: Aluminium[END_REF]).

The possible reason of low Zn in U-sites can be that large apartment houses were built in the urban areas few decades ago, at a defined period, and steel-pipelines interior were aged to the same extent. Zinc can be leached off from new zinc platted pipelines in higher amounts than from older ones. During corrosion in water the Zn layer gets thinner or/and is covered with insoluble zinc compounds (carbonates).

In both cases, Zn corrosion can be slowed down.

In non-urban sites the mean Zn concentrations were several times higher than in U-sites and accordingly a substantial number of households exceeded the aesthetic limit for Zn. Private houses in the non-urban areas were build in different periods and were supplied with the variety of water sources via a variety of pipeline systems available in the market and selected following the local habits, especially endpipes and taps. Moreover, lifetime of small houses is shorter and they are more frequent rebuild and renewed than large urban apartment houses. Particularly in recent two decades in Poland, there was increasing trend in building new houses and renewing old ones due to economic grow, especially in peripheral and rural areas.

Besides the possible presence of domain of higher Zn in sites studies, overall Zn distribution profile in DW was not resolved into or not indicated additional modes at higher Zn. However, higher variation of Zn in NU in comparison to U sites is clearly evident from standard deviations and larger positive differences between medians and GMs, and suggests the presence of such a subtle sub-fraction.

Water contamination

For most households, a significant, over two-fold increase in Zn concentration was observed during stagnating overnight independently of the site. For a significant part of population, the contamination was not dependent on background Zn reflected by plateau of contamination-concentration relationship. The constant D 1,2 value at plateau (0.7 mg L -1 ) presents average characteristic contamination for the sites studied. The presence of plateau means that after overnight stagnation period (a constant parameter designed in this study), the corrosion reached near-by or saturation level in the thinnest interior part of pipeline. Possibly the process was no longer or weakly dependent on water corrosiveness or is slow enough, taking background Zn (in W2) as its rough measure. The contamination with the metal is then mainly related to quality of pipelines near the household tap and less to water properties. Similar plateaus were also observed for contamination with other metals (e.g. [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 2: Cadmium (year 1997-2001)[END_REF] and subsequent parts).

The relative extent of DW contamination with Zn from internal pipeline/pipe system, expressed by R 1,2 or D 1,2% values, is comparable to that of cadmium [START_REF] Barton | Predicted intake of trace elements and minerals via household drinking water by 6year-old children from Krakow (Poland). Part 2: Cadmium (year 1997-2001)[END_REF] or lead. "Zero level" of such a contamination is the ideal expectation for the quality of future pipeline systems. In the case of Zn, however, the contamination did not introduce a significant risk for health, rather on the contrary, may be desired to some extent.

Diversity among supply systems

Zn concentrations in household water supplied from five major WTPs in urban Kraków differed significantly in Zn in W1, suggesting that many intermediate factors might be involved. However, this could be expected, since these sources differed in water hardness and mineral composition (MPWiK), and underwent different treatment methods or none. The interior contaminations were also very different. The contaminations were only slightly related to background Zn, but this is just another projection of the same effects discussed above for the whole population. The highest Zn was in the least treated water from deep well E. The highest background contamination (in W2) was associated with the slowest exchange rate in storage containers. High differentiation in DW Zn between sites is rather typical of zinc in DW, as can be deduced from other studies, e.g. [START_REF] Xu | Summer exposure assessment of Cu and Zn in drinking water in Shanghai, China[END_REF]).

Zinc intake

The Zn intake predictions in this study showed that DW can significantly contribute to Zn intake by 6year-old children by 9-10% RDA in NU sites but to a negligible extent in U-sites. For 7% of total children or up to 20% from NU sites, where Zn exceeded the aesthetic limit of 3 mg L -1 , 1.5 L portion of DW taken in the morning (W1) for whole-day food preparation may introduce 64% of recommended daily Zn.

If limit is based on RDA, only 2% of children may be at risk of exceedance of Zn RDA with W1, and none with W2. The estimation is thus similar to that found by [START_REF] Kaluza | Contribution of food products and drinking water to the intake of minerals by elderly (in Polish)[END_REF] for Polish population accounting for 9% contribution of DW to dietary Zn intake by elderly.

In the light of studies suggesting Zn deficiencies worldwide, the Zn in DW contributing even by few percent of RDA is desirable for the populations, and may shift the borderline of deficiency due to dietary food inadequacy. Additional zinc, e.g. from supplementation seems beneficial in diseases such as diarrhoea, chronic hepatitis C, shigellosis, leprosy, tuberculosis, pneumonia, acute lower respiratory infection, and leishmaniasis [START_REF] Overbeck | Modulating the immune response by oral zinc supplementation: a single approach for multiple diseases[END_REF]. It is required especially for the immune system and may give support to control of cold-related diseases typical of children (Fischer [START_REF] Walker | Global and regional child mortality and burden of disease attributable to zinc deficiency[END_REF]). It has been recently found in a children population study that 3 mg daily Zn supplementation reduced the incidence of diarrhoea by 21-42% (p<0.01) [START_REF] Wuehler | Dose-response trial of prophylactic zinc supplements, with or without copper, in young Ecuadorian children at risk of zinc deficiency[END_REF]). Moreover, Zn seems to have a protective effect against toxicity of several other metals, e.g. copper, lead or cadmium [START_REF] Rogalska | Enhanced zinc consumption prevents cadmium-induced alterations in lipid metabolism in male rats[END_REF]), all elements present in drinking water.

Since no particular problems with Zn in DW were encountered, no health-based Zn guideline value was introduced by WHO (2006). However, the lack of obligatory limit may not prevent the excessive Zn in DW used for food preparation (drinks, soups etc.), where unacceptable taste can be masked. It may also be a concern in formula fed infants and people of weakened taste abilities, or others, disabled for self-control.

Apart from prevalence of global Zn deficiencies, there are also studies that can argue for limitation of Zn exposure or overload, however, it may apply rather to supplementation not to the Zn levels observed in drinking water. Zn was placed within nutrients at high risk of excessive intake, for which the margin between the RDA (or actual intake) and UL is very narrow [START_REF] Grossklaus | Derivation of Maximum Levels of Vitamins and Minerals Added to Foods Based on Risk Assessment[END_REF]. It is known that Zn excess can disturb copper intake [START_REF] Wapnir | Inhibition of copper absorption by zinc. Effect of histidine[END_REF]. However, this point can be relevant mostly to individuals with or at near-deficiency since the population Cu intake was generally adequate. Further, animal studies have shown that enhanced Zn consumption may cause impairments in cognitive function [START_REF] Flinn | Enhanced zinc consumption causes memory deficits and increased brain levels of zinc[END_REF]. The latter finding is questioned, however, and other authors suggested that trace Cu but not Zn influenced inflammatory [START_REF] Becaria | Aluminum and copper in drinking water enhance inflammatory or oxidative events specifically in the brain[END_REF]) and Alzheimer-like pathology [START_REF] Sparks | Trace copper levels in the drinking water, but not zinc or aluminum influence CNS Alzheimer-like pathology[END_REF]). Due to different metal intakes applied in the above studies these observations may not be in opposition.

Review of the topic literature allows for earning conviction of significance of steady, even low Zn intake, which warrants high intake efficiency. Possible disadvantage of Zn intake variation, e.g. adaptive response, i.e. restriction, was proved by the study of [START_REF] Hunt | Adaptation in human zinc absorption as influenced by dietary zinc and bioavailability[END_REF] in the absence of phytates. It also appeared, that balance between Zn and other metals (iron, copper, and probably other divalent cations, or even selenium) [START_REF] Mocchegiani | Zinc, Metallothioneins and Longevity: Interrelationships with Niacin and Selenium Current[END_REF]) as dietary as well as for the body level seems to be of a key importance due to their strong interactions. The effects of large temporary intake variation, e.g. high and irregular supplementation, should be studied. This may hypothetically induce adaptive enforcement in intake restricting system and resistance, which may not quickly relax and synchronize with further low intake level. Although, a true marker Zn deficiency of population is still lacking, and there are many attempts (Fischer [START_REF] Walker | Functional indicators for assessing zinc deficiency[END_REF]) and proposals for new markers to be evaluated [START_REF] Gibson | Indicators of zinc status at the population level: a review of the evidence[END_REF], de Benoist et al. 2008). Due to multifactorial linking of Zn with several biochemical processes, strong and multiple interactions and adaptations, the future marker should comprise a larger part of Zn-dependent equilibrium system rather than its particular member. Current knowledge about these equilibria and dynamics of the adaptive mechanisms is yet still limited. Because of increasing usage of Zn and other microelemental supplements, nutrient imbalance as well its intake variations should be included as a factor of evaluations of nutritional and health status in populations.

As regards the water, some studies found an association between low groundwater concentration of zinc and later development of childhood onset diabetes [START_REF] Haglund | Evidence of a relationship between childhood-onset type I diabetes and low groundwater concentration of zinc[END_REF]), and on contrary, possible protective effect of zinc in DW on 1 type diabetes mellitus [START_REF] Zhao | Drinking water composition and childhood-onset Type 1 diabetes mellitus in Devon and Cornwall, England[END_REF]). On the other hand, increased acidity of tap water was associated with many-fold higher risk of type 1 diabetes [START_REF] Stene | Acidic drinking water and risk of childhood-onset type 1 diabetes[END_REF], but direct factors have not been identified. This possible indirect effect might be associated with microorganisms, as the authors suggested. However, increased levels of other heavy metals (not studied there) as an effect of enhanced leaching from the ground at increased acidity, corrosion of pipelines, pots and bars during food preparation, what was not studied but should also be considered by the authors.

Other comments

Due to lack of safety limit for Zn in DW, the only health-based criteria are dietary recommendations, RDAs or ULs. An appreciation of DW Zn as a nutrient source is that it is minimal, not much fluctuating pool of food-independent daily portion of Zn intake. Although Zn shows a strong availability synergism with dietary proteins, availability of metals from DW is generally greater then from food, because of lack of many antagonistic interactions observed with the presence of food, on otherwise. Moreover, effectivity of Zn absorption at low intakes is significantly higher than at high Zn intake. This suggests that Zn from DW, albeit non-intentional, can be considered very valuable in a serious population deficit, and whole Zn intake may practically be quantitatively absorbable. In the light of these suggestions, the intake predictions in this paper can be considered as maximal and practically realistic Zn intake from DW in the deficiency, and they can be truer than for other metals for which biological filters are more restrictive.

Unfortunately, pipeline-derived Zn accompanied several toxic metals present as impurities in Zn used for platting or galvanizing. However, it should be emphasised, the end-part of household pipeline system should rather conform quality criteria of metals for kitchen pots. The production of corrosion resistant pipelines and pipes for household water supply seems to be difficult. Thus to this purpose one may propose for the future new water systems the use of pipelines made from or platted with high purity Zn, especially for the thinnest end-part of in-house just before a tap in the kitchen. This additionally can increase their resistance to electrochemical corrosion and lifetime of Zn layer. This could preserve overnight contamination with some lead and cadmium, observed in current systems. And as the best, it can increase Zn intake by population and allow better control extreme cases of Zn deficit and may shift a population borderline of zinc deficiency. Such an intentional use of zinc and iron bars and pots to enforce these nutrients intake was recently studied [START_REF] Lechtig | Release of iron, zinc, and lead from common iron construction bars and zinc metallic bars in water solutions and meals[END_REF]). This proposal is also in line of very recent attempts to control copper levels in the body -an 'anti-copper campaign' -suspected to be involved (among others) in neuro-degenerative diseases (e.g. [START_REF] Zatta | Alzheimer's disease, metal ions and metal homeostatic therapy[END_REF]). The proposed system warrants further studies.

Conclusions

The study evaluated levels of Zn in household drinking water using two different criteria, exceedance of aesthetic limit in DW, and predicted contribution to dietary requirements of 6-year-old children.

Rural and peripheral sites to the urban areas are homogenous for Zn in DW, and in these sites DW contained two-three-fold higher Zn than in urban site. Accordingly, the intake predictions are significant in the nonurban areas amounting to near 10% RDA. The exceedances of aesthetic concentration limit were between 4-7% in total population, and the risk of exceedance RDA was quite negligible. point that using morning portion of drinking water taken after stagnation can increase Zn intake from DW by 2-3 times, since this was associated with the increase in toxic element concentrations from current pipeline systems, it is not recommended. However, for the future, the use of higher quality zinc for endpart of pipelines was proposed.. In conclusion, over-night contamination of DW from pipelines was common, significant and of similar extent at all sites. DW can be a considered significant contributor to Zn intake by children in nonurban sites and may shift the population borderline of deficiency. none † metal intake was calculated at assumed water consumption 1.5 L day -1 by 6-years-old children and the value of safe level of RDA for Polish population of 4-6 year old children -10 mg Zn day -1 , GM -geometric mean; MED -median; P90 (P10) -90 th (10 th ) percentile ; SDg -geometric standard deviation; P2.5, P97.5 -95% confidence interval for median was calculated as 2.5 -97.5 percentiles; ‡ number of children and its percent in group (in parentheses); * minimum and maximum; ** Note: these values were 10 times daily intakes from next columns ¶ the children from whole population derived via risk criteria: 1) Zn concentration > 3 mg L -1 , 2) at Zn intake from DW exceeding the RDA value of 10 mg day -1 .

  adjusted to the coverage of 95%, obtaining the values 63% or 67% for intake per kg b.wt.

Five

  major water treatment plants (WTP) supplying water to study areas in Kraków were shown on the map in Part 3 (Barton 2008). The largest area is supplied by soft water from the Raba River (A) and the other sources are local rivers (B-D) and a deep well (E).Mean metal concentrations in household tap water (W1, W2) from the suppliers and percentage of contribution to the total water consumption are shown in Figure3.[InsertFigure 3 about]

  Contamination with Zn during overnight stagnation was wide-spread throughout all sites and generally of similar magnitude independently of the background Zn level. Besides attractive nutritional

Figure 1 .

 1 Figure captions

Figure 2

 2 Figure 2 Correlation of Zn concentrations in morning (W1) and evening water samples (W2), for urban (U) and non-urban (NU) households.

Figure 3

 3 Figure 3 Mean Zn concentrations in household drinking water according to the supply systems in Kraków.

Figure

  Figure 4A-B Changes of Zn concentration in DW after overnight stagnation in pipelines as a function of supplied Zn (in W2) for total population. Upper curves -fraction 'a' -contamination, lower curvesfraction 'b' -deposition.Figure A: absolute changes of Zn (D 1,2 ) as a difference W1 -W2 ; Figure B:

Food

  Figure A: absolute changes of Zn (D 1,2 ) as a difference W1 -W2 ; Figure B: relative Zn changes as a difference in percent (D 1,2 %) or ratio (R 1,2 ) of W1 : W2. Page 20 of 27 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

FormattedFigure 1 .Figure 2 Figure 3 FoodFigure

 123 Figure 1. Distribution of Zn concentrations in flashed household drinking water (W2) from urban (U) and non-urban (NU) sites. 816x486mm (72 x 72 DPI)

  Figure 4A-B Changes of Zn concentration in DW after overnight stagnation in pipelines as a function of supplied Zn (W2) for total population. Upper curves -fraction 'a' -contamination, lower curvesfraction 'b' -deposition.Figure A: absolute changes of Zn (D1,2) as a difference W1 -W2 ; Figure B: relative Zn changes as a difference in percent (D1,2%) or ratio (R1,2) of W1 : W2. 770x530mm (72 x 72 DPI)

  Table II Zinc concentration in drinking water and related parameters †

	Table II Predicted Zn intake via drinking water by 6-year-old children †
	Group					Concentration (mg L -1 )				Related parameters for major fraction ('a' -	Exceed
				% RDA ** Intake (mg kg		Daily intake (mg day -1 )				contamination, D 1,2 >0) ‡	ance #
	or parameter Group	N (N%) ‡	Morning water samples b.wt. -1 day -1 ) (MED); GM GM (MED)	GM (MED)	Evening water samples SDg Quartiles P10 -P90 P2.5 -P97.5	p-level ¶	Concentration, W2 ‡	Ratio	Difference	3 mg L-1
	W1 Urban	169	(standing water), W1 P90 6 (6); 18 0.024 (0.028)	0.56 (0.61)	(flushed water), W2 3.03 0.3 -1.1 0.1 -1.83	0.0 -3.3	W1 vs. W2	(mg L -1 )	R 1,2	D 1,2 (mg L -1 ) D 1,2 %	(per cent)
	Non-urban	GM 135	N SDg Quartiles 13 (16); 81 0.055 (0.066) 1.32 (1.56) GM 4.64	N SDg Quartiles Concentrations (variances) 0.7 -3.7 0.2 -8.14 0.0 -12.5	GM	N	GM	GM	AM	W 1	W 2
	Total	304		8 (9); 45	0.035 (0.039)	0.82 (0.88)	3.97	0.4 -1.8 0.2 -4.47	0.0 -9.7
	(Median) 0.46 (0.53) 0.75 (0.80) 0.93 (1.44) Nonurban, NU 0.81 (1.03) 196 4.89 Urban, U 359 3.27 Peripheral, P 131 4.59 Rural, R 65 5.52 Total 0.56 (0.62) 555 3.92 p ¶ : Uvs.P ** (***) p ¶ : Uvs.R *** (***) p ¶ : Pvs.R 0.39 (0.27) p ¶ : Uvs.NU *** (***) † W1, W2 -samples of drinking water collected in the morning and evening, respectively; AM -arithmetic mean; GM -geometric mean; N -number of samples; N% -percent of the major (CI) (Median) (CI) (Median) (N%) (Median) (Median) (Median) 0.22 -1.04 0.14 (0.13) 394 3.79 0.06 -0.40 *** (*) 0.12 (0.11) 290 4.73 (3.63) 0.33 (0.37) 66 (72) 3 (0.04 -4.63) (0.01 -1.95 (81) 0.30 -2.28 0.51 (0.51) 139 4.55 0.23 -1.46 * (0.94) 0.44 (0.48) 89 2.40 (2.15) 0.40 (0.42) 49 (53) 18 (0.04 -14.97) (0.03 -9.93 (68) 0.49 -2.83 0.55 (0.85) 71 4.65 0.16 -1.88 0.06 (0.38) 0.60 (0.87) 44 2.58 (2.09) 0.62 (0.77) 51 (52) 22 (0.03 -26.50) (0.03 -11.09) (68) 0.36 -2.48 0.52 (0.61) 210 4.57 0.01 -4.49 ** (0.54) 0.48 (0.54) 133 2.46 (2.14) 0.46 (0.58) 49 (53) 19 (0.04 -18.13) (0.03 -10.24) (68) 0.26 -1.38 0.22 (0.24) 604 4.61 0.08 -0.65 *** (**) 0.18 (0.19) 423 3.85 (2.75) 0.36 (0.40) 61 (64) 9 (0.04 -8.12) (0.01 -4.49 (76) *** (0.06) *** (0.61) *** (***) 0.70 (***) *** (0.81) *** (0.10) *** (0.27) * (*) ** (0.33) *** (0.52) 0.76 (0.87) 0.20 (0.54) 0.62 (0.67) 0.17 (0.15) 0.69 (0.69) *** (*) *** (0.33) *** (***) 0.11 (***) *** (0.66) fraction 'a' in whole group, SDg -geometric standard deviation (transformed from SD for Log Zn_concentrations, SDg = 10 SD Log Zn ); CI -95% confidence interval. ¶ p-level of t-test for difference in concentrations as logarithms and homogeneity of variances (in parentheses). Notations for p-level, if explicit value was not given: n.s. p≥0.05, * p<0.05, ** p<0.01, *** p<0.001 o r R e v i e w Risk group 1 ¶ 30 (10%) 81 (79) 0.33 (0.29) 8.09 (7.94) 1.46 6.0 -9.7 5.3 -12.5 4.9 -25.9* Risk group 2 ¶ 5 (2%) 150 (126) 0.63 (0.50) 15.04 (12.64) 1.40 12.5 -16.5 -11.4 -25.9* W2 Urban 170 2 (2); 10 0.008 (0.007) 0.20 (0.18) 3.68 0.1 -0.5 0.0 -0.98 0.0 -3.8 F Non-urban 136 9 (11); 52 0.036 (0.045) 0.86 (1.08) 4.35 0.3 -2.7 0.2 -5.19 0.0 -7.8 P Total 306 4 (4); 34 0.016 (0.017) 0.38 (0.39) 4.75 0.1 -1.1 0.0 -3.40 0.0 -7.2 e r Risk group 1 ¶ 21 (7%) 64 (63) 0.26 (0.25) 6.38 (6.26) 1.26 5.2 -7.7 4.8 -8.9 4.6 -9.4* e Risk group 2 ¶	1 10 11 10 4
								O n l
									y

‡

the concentrations and values of related parameters are given for fraction 'a' (D 1,2 >0, i.e. W1>W2) -the major fraction of samples. Mean metal concentrations in W1 can be calculated from the equation: W1 = R 1,2 * W2. # Percent of samples exceeding the limit of 3 mg L

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Acknowledgements

The author wishes to acknowledge Maria Folta for laboratory and analytical assistance; students of The University for partial assistance in sample collection and preparation; and Professor dr. hab. Zofia Zachwieja for interest in this study and for comments.