Method for the quantification of current use and persistent pesticides in cow milk, human milk and baby formula using gas chromatography tandem mass spectrometry

Accepted Manuscript Title: Method for the quantification of current use and persistent pesticides in cow milk, human milk and baby formula using gas chromatography tandem mass spectrometry Author: Xianyu Chen Parinya Panuwet Ronald E. Hunter Anne M. Riederer Geneva C. Bernoudy Dana Boyd Barr P. Barry Ryan PII: DOI: Reference:

S1570-0232(14)00535-2 http://dx.doi.org/doi:10.1016/j.jchromb.2014.08.018 CHROMB 19080

To appear in:

Journal of Chromatography B

Received date: Revised date: Accepted date:

3-3-2014 14-7-2014 13-8-2014

Please cite this article as: X. Chen, P. Panuwet, R.E. Hunter, A.M. Riederer, G.C. Bernoudy, D.B. Barr, P.B. Ryan, Method for the quantification of current use and persistent pesticides in cow milk, human milk and baby formula using gas chromatography tandem mass spectrometry, Journal of Chromatography B (2014), http://dx.doi.org/10.1016/j.jchromb.2014.08.018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Method for the quantification of current use and persistent pesticides in cow milk, human milk and baby formula using gas chromatography

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tandem mass spectrometry Article Type: Full Length Article

Corresponding Author: P. Barry Ryan, Ph.D. Corresponding Author’s Institution: Emory University First Author: Xianyu Chen, Ph.D.

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Keywords: current use pesticide; persistent pesticides; whole milk; human milk; baby formula; tandem mass spectrometry; gas chromatography

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Dana Boyd Barr, Ph.D.; P. Barry Ryan, Ph.D.

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Order of Authors: Xianyu Chen, Ph.D.; Parinya Panuwet, Ph.D.; Ronald E. Hunter, Jr., Ph.D.; Anne M. Riederer, Sc.D..; Geneva C. Bernoudy, MS;

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Method for the quantification of current use and persistent pesticides in cow milk, human milk and baby formula using gas chromatography tandem mass spectrometry

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Xianyu Chena,b, Parinya Panuweta, Ronald E. Hunter, Jr.a, Anne M. Riederera, Geneva C. Bernoudya, Dana Boyd Barra, and P. Barry Ryana,b Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA

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Department of Chemistry, Emory University, Atlanta, GA, USA

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A Contribution from the Analytical Exposure Science and Environmental Health Laboratory, Department of Environmental Health, Rollins School of Public Health, Emory University.

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Corresponding author: P. Barry Ryan, Ph.D. Professor Department of Environmental Health Rollins School of Public Health, Emory University 1518 Clifton Road NE Rm 2041 Atlanta, GA 30322 Office Tel: +1(404) 727-3826 Fax: +1(404) 727-8744 Email: [email protected]

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 First method for multiple classes of pesticides in milk and infant formula

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Highlights  Developed a single method quantifying 29 pesticides drawn from four classes

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 Tested the method on and on cow milk and baby formulae purchased at local stores  Tested the method on human milk from local volunteers  Noted the general presence of pesticides media tested

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Abstract: The aim of this study was to develop an analytical method for the quantification of organochlorine (OC), organophosphate (OP), carbamate, and pyrethroid insecticide residues in cow milk, human milk, and baby formula. A total of 25 compounds were included in this method. Sample extraction procedures combined liquid-liquid extraction, freezing-lipid filtration, dispersive primary-secondary amine cleanup,

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and solid-phase extraction together for effective extraction and elimination of matrix interferences. Target compounds were analyzed using gas chromatography with electron impact ionization-tandem mass spectrometry (GC-EI-MS/MS) in the multiple reaction monitoring (MRM) mode. Average extraction recoveries obtained from cow milk samples fortified at two different concentrations (10 ng/mL and 25 ng/mL), ranged from 34% to 102%, with recoveries for the majority of target compounds falling between 60% and 80%. Similar ranges were found for formula

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fortified at 25 ng/mL. The estimated limits of detection for most target analytes were in the low pg/mL level (range 3-1600 pg/mL). The accuracies and precisions were within the range of 80-120% and less than 15%, respectively. This method was tested for its viability by analyzing 10 human milk samples collected from anonymous donors, 10 cow milk samples and 10 baby formula samples purchased from local grocery stores in the United States. Hexachlorobenzene, p,p-dicofol, o,p-DDE, p,p-DDE , and chlorpyrifos were found in all samples analyzed. We found detectable levels of permethrin, cyfluthrin, and fenvalerate in some of the cow milk samples but not in human milk or baby formula samples. Some of the pesticides, such as azinphos-methyl, heptachlor epoxide, and the pesticide synergist piperonyl butoxide were detected in some of the cow milk and human milk samples but not in baby formula samples.

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Keywords: current use and persistent pesticides; whole milk; human milk; baby formula; tandem mass spectrometry; gas chromatography

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1. Introduction Pesticides have been widely used in both agricultural and residential settings and they provide benefits such as increased supply of crops, fruits and vegetables, as well as control of diseases transmitted through insects that affect humans and livestock. Despite their benefits, many pesticides are neurotoxicants that are acutely toxic at high doses and can potentially exert more subtle effects at lower doses though different exposure routes. Because of the neurodevelopmental concerns posed by current-use and historically-used pesticides [1-5], four classes of insecticide are of particular concern because of their potential neurodevelopmental toxicity, i.e., adverse cognitive, behavioral, sensory, motor and/or morphological effects in children: organochlorines (OCs), organophosphates (OPs), carbamates, and pyrethroids. Further, pesticide concentrations in human milk, infant formula, and baby food, primary sources of nutrition for infants and young children, are likely to be important factors to measure as neurodevelopmental effects are most important during this period [6]. Although banned in most countries, the environmentally persistent OCs are still routinely detected in food worldwide. Dichlorodiphenyldichloroethane (DDE), a degradation product or metabolite of DDT, is one of the most studied OCs because of its ubiquity and potential toxicity [7, 8]. DDT is neurotoxic through multiple mechanisms including interference with sodium and calcium ion channels in nerve cells, while DDT and its metabolites are also suspected endocrine disruptors in humans [9].

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Among currently used pesticides, the organophosphorus insecticides (OPs) are the most widely studied. Their acute toxicity is exerted through acetylcholinesterase (AChE) inhibition and hyper-excitation of post-synaptic cholinergic receptors. Toxicological studies have shown that some OPs can cause long-term neurochemical and behavioral changes in rats exposed both prenatally and post-natally to levels producing no clinically measureable toxicity [10]. We recently reviewed the epidemiologic literature and found that 26 of 27 of studies meeting our data quality criteria showed negative effects of early OP exposure on neurodevelopment, with dose-response relationships detected in all but one of the 12 studies that evaluated dose-response [11]. Like the OPs, the carbamates are acutely toxic AChE inhibitors but are less well-studied with respect to developmental neurotoxicity. OC use has been strongly curtailed in the United States with only very specific uses allowed. OP use has been substantially reduced through deregistration of residential use; however, agricultural uses of many OPs are still allowed [12]. Given the reduction in use of many OPs and OCs, pyrethroids have become widely both residentially and agriculturally. They comprised a quarter of the world market as early as 1995 [13].

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Like DDT, pyrethroids exert their acute toxicity by altering sodium channel kinetics [14]. Because animal studies have shown that some pyrethroids are more acutely toxic to developing animals than adults [15-19], concern has been raised regarding their potential developmental neurotoxicity. The low volatility of pyrethroids suggested limited exposure through the inhalation route for pyrethroids (include Tsuzuki reference here). However, recent studies have shown that children are still exposed to these materials during development suggesting that alternative routes, e.g., ingestion, although inhalation of pyrethroids bound to re-entrained house dust, and dermal contact, may be more important for these compounds [15, 16, 19]. One U.S. study, however, showed no association between prenatal exposure to the pyrethroid permethrin and adverse neurodevelopmental outcomes in young children [20].

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Epidemiologic studies to date of pesticides and neurodevelopment have focused on prenatal pesticide exposures. However, many critical neurodevelopmental processes continue from birth through infancy and into early childhood [6]. Despite these vulnerabilities, there is a gap in scientific knowledge on pesticide exposures during infancy. One potential explanation for this gap is that collecting biological samples from neonates and infants can be challenging. However, pre-weaning infants have homogeneous diets, consuming only breast milk or baby formula. Therefore, pesticide concentrations in human milk and baby formula may be good indicators of pesticide exposure for neonates and preweaning infants. Once children begin to crawl, non-dietary exposures may become more important, especially in homes actively using pesticides.

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Human milk is a complex matrix with total fat content in the range of 30-50 g/L [21, 22] or 3.5-4.5% [23]. Persistent lipid-soluble pesticides, such as OCs, can bioaccumulate in human milk [24]. Analytical methods exist for measuring OCs in human milk and a more limited number of studies describe methods for measuring OPs and pyrethroids in human milk [25-27]. However, no methods exist for measuring all four insecticide classes for which developmental neurotoxicity is a concern. An efficient, high-throughput method for measuring these multiple classes, and perhaps other classes of pesticides, in human milk is important for capturing a more complete picture of infants’ pesticide exposure through breastfeeding. Despite the conceptual simplicity of assessing pesticides exposure through human milk for neonates and infants, a limited number of methods have been reported on measurement of multiple classes of pesticides in a single sample. Many studies focus on OCs in human milk, while some non-U.S. studies concentrate on OPs and pyrethroids [25-27]. However, no studies report levels of all four classes for which developmental neurotoxicity is a concern. Thus, development of new, efficient, high-throughput methods for multiple classes of pesticides is of importance in evaluating exposures experienced by infants through breast feeding. The aim of this study was to develop a single, highly selective and sensitive analytical method that eliminates the interferences from the complicated milk matrix, improves separation of the target pesticides, and identifies and quantifies concentrations of OC, OP, carbamate, and pyrethroid insecticides in human milk in a single sample. Atrazine, a triazine

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herbicide, was also measured in this study, to evaluate the potential for using such methods to measure this class of compounds in biological fluids. While this compound has not been shown to be a contributor to adverse outcomes in neurodevelopment, its metabolites have been measured in children [28]. A secondary aim was to evaluate the accuracy and sensitivity of this method for measuring the target analytes in cow milk and infant formula, other important foods in early life.

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2. Materials and methods 2.1 Chemical Compounds Table 1 shows the compounds used in this method development, their abbreviations, analytical purities, and suppliers. We selected widely-used OCs, OPs, carbamates, and pyrethroids to represent each insecticide class, atrazine, as aand piperonyl butoxide, a potentially carcinogenic synergist widely-used in pyrethroid formulations [29] and shown in one human study to adversely affect neurodevelopment after prenatal exposure [Horton et al. 2011]. Although DDT has a number of metabolites, we opted to include only DDE and DDD in our method since these are the most widely studied in the epidemiological literature. Atrazine, a triazine herbicide was also measured in this study, to evaluate the potential for using such methods to measure this class of compounds in biological fluids. All solvents used were of analytical grade. We obtained acetonitrile, hexane, and toluene from Fischer Scientific (Phillipsburg, NJ, USA), Sigma Aldrich (St. Louis, MO, USA), and Macron (Phillipsburg, NJ, USA), respectively. Acetic acid (glacial) was purchased from Avantor Performance Materials (Phillipsburg, NJ). Bondesil-PSA (40μm) was purchased from Agilent Technologies (Santa Clara, CA, USA). Dual-Layer Envi-Carb II/PSA (6ml/500/300mg) SPE cartridges and PSA bonded silica (6mL/500mg) SPE cartridges were both purchased from Supelco (Bellefonte, PA, USA). Oasis HLB cartridges (3 ml/60mg) were purchased from Waters Corporation (Milford, MA, USA).

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Organic whole cow milk was used for method development and validation in our study for the following reasons: (1) cow milk and human milk have similar general composition and cow milk is much easier to obtain, (2) whole milk contains higher fat content (~4%) than reduced-fat (2%), low-fat (1%), or skimmed milk and falls in the range of fat content of human milk 30-50 g/L [21, 22] or (3.5-4.5%) [23], and (3) it may reasonably be expected that organic milk has lower background pesticide levels than non-organic milk. 2.2 Standard and Internal Standard (ISTD) Preparation Individual stock solutions of the native standards were prepared for each analyte by weighing a known amount of neat standards and diluting with acetonitrile. Concentrations are corrected for purity. Stock solutions were stored at -20oC. Ten working standard solutions (spiking

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solutions) were prepared by adding individual stock solutions of analytes in acetonitrile:toluene (3:1, v/v . Their concentrations were as follows:

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1.00, 2.50, 5.00, 10.0, 25.0, 50.0, 100, 250, 500, 1000 ng/mL). These spiking solutions were stored at 4oC.

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Individual stock solutions of the isotopically labeled analogues, used as internal standards, were prepared in acetonitrile. Stock solutions were stored at -20oC. An internal standard working solution, that included five labeled analytes, was prepared at 400 ng/mL in acetonitrile:toluene (3:1, v/v) and stored at 4 oC. The calibration standards were freshly made for each analytical run by adding 100 µL native standard working solution and 50 µL internal standard working solution into 1 mL organic cow milk followed by a complete sample preparation procedure.

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2.3 Sample Collection and Preparation Different brands of cow milk with different fat contents were selected based on availability in local grocery stores in metropolitan Atlanta, USA. Powdered baby formula samples were selected in a similar fashion and prepared according to the manufacturers’ instructions. Human milk samples were manually expressed and collected in 2010-2011 from local volunteers using protocols approved by Emory University’s Institutional Review Board. These samples were stored at -20 oC until analysis. All the samples were divided into appropriate aliquots before storage. The sample preparation procedure is shown in Figure 1. Because of the heterogeneity noted in formula samples as indicated by the presence of undissolved formula particulate matter, an additional sonication step was needed. Also, longer mixing and sonication times were needed during the extraction step, as compared to cow milk and human milk samples.

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2.5 Chromatography and Mass Spectrometry Conditions The sample analysis was carried out with an Agilent 7890A gas chromatograph (GC) with a 7693 autosampler connected to an Agilent 7000 triple quadrupole mass spectrometer (MS/MS). An HP-5MS column (30 m, 0.25 mm ID, 0.25 μm film) (Restek, Bellefonte, PA) was used with a GC temperature program to optimize the separation. A 2 μl injection was used with an injection port temperature of 250 0C under pulsed splitless mode. The temperature program began at 100 0C and was held for 2 min, increased at 10 0C/min to 205 0C and held for 3 min, increased at 10 0C/min to 280 0C and held for 4 min, and finally increased at 25 0C/min to 310 0C and held for 12 min. The total run time was 40.2 min. The flow rate of the helium carrier gas began at 1.2 mL/min and was held for 28 min, and was increased at 1 mL/min to 1.8 mL/min and held until the end of the run. We extend the GC run for an additional 12 minutes after the last target compound has eluted to afford removal of any remaining low volatility compounds remaining on the column. Quantification and confirmation ions were monitored in multiple-reaction monitoring mode for

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each native pesticide, while only quantification ions were monitored for the isotopically labeled internal standards. “Multi-segment analysis” (i.e., monitoring a few ions in a given chromatographic timed segment) was introduced to increase sensitivity of the method. Masses for each ion monitored for analysis are shown in Table 2. Quantification and confirmation ions were selected by monitoring the intensity, peak shape, signal-to-noise ratio, and potential interferences in milk samples

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2.6 Determination of Limits of Detection (LOD) Procedural matrix blanks were analyzed and three pesticides were consistently detected in both cow milk and baby formula: hexachlorobenzene, p, p’-DDE, and resmethrin. For these three pesticides, the LODs were determined from the blank value precision: LOD=Mean Blank + 3×SD, where Mean Blank is the mean and SD is the standard deviation of the detected values of the analyte in blank samples.

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For compounds with no observable concentration in the blanks, we noted the lowest standard providing a signal to background noise (S/N) ratio of three or greater and with appropriate peak shape. Note that the next lower standard would not meet these dual criteria. The concentration for the LOD was determined from this sample by back-extrapolation to a concentration that would just meet the S/N > 3 criterion. This was taken as the LOD for the given compound. It should be noted that this value must fall between the lowest standard for which the criteria were met, and the standard just below that for which the criteria were not met.

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2.7 Extraction Efficiency The extraction efficiency of the method was determined by analysis of replicate 1 mL milk samples (n=3) spiked with two different concentration levels of the target pesticides (10 ng/mL and 25 ng/mL). In this experiment, samples were separated randomly into two groups (Group A and Group B). Replicate milk samples in Group A were spiked with the designated native standard before extraction and internal standard right before the final evaporation step, while replicate milk samples in Group B were spiked with the designated native standard and ISTD both before the final evaporation step. The extraction recovery was calculated by comparing the response ratio (i.e., area of native standard/area of internal standard) of Group A to that of Group B. 2.8 Accuracy The method accuracy was determined by calculating the difference in the mean of repeated measurements (N=9) of milk samples spiked at two different concentration levels (5 ng/mL and 25 ng/mL) from the known values. 2.9 Precision

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The method precision was determined by calculating the root-mean square difference of repeated measurements of milk samples spiked with native standard pesticides at two different concentration levels (5ng/mL and 25ng/mL). Replicate samples (3 samples/day at each concentration level) were prepared and analyzed daily during a 3-day period to determine the between-day and within-day precision.

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2.10 Storage Stability Study and Analytical Degradation We determined the storage stability of analytes in milk by repeated analysis (n=3) of spiked cow milk samples (5ng/mL and 25ng/mL) that were stored at -20 0C. The samples were extracted and analyzed at days 0, 30, 60, and 90. We demonstrated the storage stability of analytes by comparing the response ratios of the analytes in milk samples extracted on each day. We checked for analytical degradation during the analysis of samples for up to 72 hours and noted none.

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2.11 Method Application in human milk, cow milk, and baby formula We collected 10 different samples of cow milk and baby formula samples for analysis. The 10 human milk samples analyzed came anonymously from 6 different donors. Multiple un-pooled samples were collected from each donor at different breastfeeding stages.

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3. Results 3.1 Chromatographic Separation Figure 2 shows the chromatogram from a typical whole cow milk sample analysis. Ions were selected based upon the relative abundance observed in electron ionization (EI) spectra and the S/N ratio for that specific ion. For each isotopically labeled analogue, the selected fragment ion must also retain the label to distinguish from its corresponding native form. In addition, for cypermethrin, the selected fragment ion of its corresponding labeled analogue must have its naturally occurring isotope peak. We have included three figures in the supplemental material that each contain examples of actual chromatograms of blank samples, real samples, and internal standards. These show the retention-time window for chlorpyrifos, DDT, and cypermethrin respectively. The last analyte, deltamethrin, eluted around 27 minutes. Afterwards, the oven temperature was increased to 310°C and held for 12 min to eliminate the remaining non-polar matrix components prior to the next injection. This procedure allowed us to gain better chromatographic resolution and avoid accumulation of undesirable components in the capillary column.

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3.2 Limits of Detection (LOD) Table 3 shows that, with the exception of deltamethrin, our sample preparation method allows the detection of pesticides in cow milk samples at concentration levels lower than 1 ng/mL.

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3.3 Extraction Efficiency As shown in Figure 3, the extraction recoveries for the two different spiking levels in cow milk were relatively consistent. These recoveries for cow milk ranged from 34-102%, with the majority of the target compounds (75%) having extraction recoveries of between 60 and 80%. For the 25 ng/mL sample, the relative standard deviations (RSDs) ranged from 1.2% to 12.4% for all the pesticides. However, the RSDs of hexachlorobenzene and deltamethrin at 10 ng/mL were closer to 50%. The extraction recoveries of baby formulas were lower than those found for cow milk, but most were still within the range of 50-80%. These extraction recoveries are shown in Table 4. Table SM-2 in Supplemental Material contains means and standard deviations for Recoveries from cow’s milk at two different concentrations: 25 ng/mL and 10 ng/mL. Table SM-3 in Supplemental Materials presents similar data for baby formula at a single concentration.

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3.4 Precision and Accuracy The results are shown in Table 4. For majority of the analytes, the accuracy and precision fall within the range of 80-120% and 0-20% respectively, which are acceptable ranges based upon FDA criteria for analytical methods [30]. A table giving calibration parameters, R2 and Standard errors for all compound can be found in the supplemental material as Table SM-1.

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3.5 Storage Stability Study and Autosampler Stability Our results indicated that the majority of the analytes display degradation over the time scales we measured. For analytes atrazine, chlorpyrifos, parathion, p,p-dicofol, o,p-DDE, o,p-DDT, endosulfan-β, and resmethrin, degradation observed was < 10%. Analytical degradation results for other analytes (not shown) were negligible. 3.6 Analysis of human milk, cow milk and baby formulas Some of OCs and OPs such as hexachlorobenzene, p,p-dicofol, o,p-DDE, p,p-DDE, and chlorpyrifos were detected in all the samples we analyzed. Because OCs are persistent in the environment and bioaccumulate in lipid-rich human matrices like breast milk, 100% detection frequency was expected. We found detectable levels of permethrin, cyfluthrin, and fenvalerate in some of the cow milk samples but not in human milk and baby formula. Some of the analytes, such as piperonyl butoxide (a synergist associated with pyrethroid use), azinphos-methyl, and heptachlor epoxide, were only detected in some of the cow milk and human milk samples but not in baby formula samples. Lower detection frequencies of

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some analytes in baby formula were expected because most pesticides had higher LODs in baby formulas than in cow milk. The results in Table 5 indicate that the method we developed is a valid method to measure the target pesticides in milk and baby formula.

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Because the targeted pesticides in Table 5 are widely distributed in the global food supply [31, 32] and there is evidence that some of these pesticides can transfer from maternal circulation to human milk, all neonates and infants who are breastfed are potentially exposed no matter if they are in households or areas where pesticides are actively used. In the United States, about 83% of mothers initiate breastfeeding and 50% of infants continue to breastfeed until 6 months [33]. Given that 3.9 million U.S. women annually give births [34], approximately 3.6 million U.S. neonates and infants are potentially exposed to pesticides through human milk each year. The global figure might be more than 30 times the number exposed in the United States. As for baby formula, infants are potentially exposed to pesticides through baby formula which are made from both cow milk or soybeans [31]. The multi-residue method we developed for measuring OCs, OPs , carbamates, pyrethroids, a triazine, and a pyrethroid synergist in cow milk, human milk, and baby formula can have a major impact on our ability to evaluate pesticides exposures during the first year of life. If paired with appropriate studies, this method can also contribute to an improved understanding of their longer-term health effects.

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4. Discussion Optimizing the method performance for every individual compound from different classes of pesticides is challenging, especially in complicated matrices, such as milk. Because of the diverse chemical and physical properties of these pesticides, performance for individual analytes must be balanced to obtain optimum performance of the overall method thus compromising performance for some individual analytes. The method we present herein was the best compromise to obtain satisfactory extraction efficiency. Those choosing to implement this method should determine whether the precision and accuracy of a specific compound is sufficient to meet the needs of their investigations. For the method, outlined, LODs were generally <1 ng/mL. However, the spiking concentration level of 10 ng/mL was close to the LOD of deltamethrin, which was partially responsible for its higher RSD. Also, the ion transitions obtained for hexachlorobenzene occasionally did not respond well on the MS and might have caused a higher RSD. One of the possibilities is that the MRM ion transition pair we picked for hexachlorobenzene might be affected by the matrix that generated m/z 249 and 214 at similar retention time as hexachlorobenzene. Therefore, we suggest viewing results for these compounds with caution. Because cyfluthrin and cypermethrin both have multiple isomers, they typically display four peaks on a GC chromatogram [35]. However, with our temperature program, all three transitions for either cyfluthrin or cypermethrin only have three peaks. The third and fourth peaks were not

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resolved and appeared as single peak on the chromatogram. For compounds that nominally should have two peaks, such as permethrin and fenvalerate, baseline resolution was achieved between the isomeric peaks. Quantifications of the isomeric compounds, that were not baseline separated, were achieved through summation of all peaks in a complex.

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Azinphos-methyl displayed high mean recovery (151.9%) and a large RSD (56.1%). The ion transitions for this compound are in the low m/z range where a great deal of chemical noise is present. Additionally, these ions may be strongly influenced by matrix components co-eluting with it or even other pesticide fragments. Because of the potential matrix effects, caution should be used in quantifying this compound using the proposed method.

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The initial liquid-liquid extractions were conducted with two different solvents: acetonitrile and hexane. Different combinations of the volumes of solvents and their extraction order were tested. For the majority of the pesticides, better recoveries were achieved when the milk samples were extracted with acetonitrile first followed by hexane extraction. Increasing the volume of the extraction solvent did not necessarily give better results.

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During the method development, different solid-phase extraction (SPE) media and elution solvents were also tested. Graphitized carbon black (GCB) adsorbents are usually preferred in removing chlorophyll from green vegetable extracts but perform poorly in eliminating fatty acids from such matrices [36]. However, primary-secondary amines (PSA) is one of the most effective SPE adsorbents for clean-up of fatty matrices used in multi-pesticide residue analysis [37]. Dual layer SPE extraction cartridges consisting of a combination of GCB and PSA are available, but at higher cost. In milk samples, since the main matrix interferences are likely to come from fatty acids, PSA would be the preferred extraction medium and would have enabled us to have a less costly method. However, our experimental results show that using PSA only did not work as well as carbon/PSA cartridges as much lower extraction recoveries were obtained. Different volume combinations of eluting solvents, acetonitrile and hexane, were also tested to optimize extraction recoveries. The one we selected in the method section. acetonitrile/toluene (3:1, v/v), gave the best extraction recoveries for majority of the analytes. One of the biggest challenges of this method was the clean-up process. The successful approaches included dispersive PSA and freezing-lipid filtration, which were included in the method. Other less successful approaches, including using acetonitrile with 1% acetic acid and Oasis HLB mixed mode SPE (3 mL/60 mg) in cleanup, either gave inconsistent results or failed to deliver clean samples. Originally, we tried to adapt the sample preparation method for milk to baby formulas directly, but the extraction recoveries were much lower than those of milk samples. Compared to milk, which is an emulsion, baby formula (made from powder-based material and according to

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manufacturer instructions) were heterogeneous and contained some relatively large, suspended particles. These particles might contain pesticide molecules trapped inside, which may have affected the recovery. In order to achieve better results for baby formula samples, they were sonicated to reach homogeneity before extraction. A longer vortex and sonication time was needed during the extraction step, as compared to cow milk and human milk samples. With the addition of the sonication at the beginning and longer vortex time, especially for the pesticides with relatively low extractions recoveries, results were significantly improved. Suspended formula particles in the baby formula likely have little effects on nutritional value to children as they receive the nourishment once the particles are taken in, but for our purposes, such heterogeneity results in substantial sample-to-sample variability that was overcome by the sonication. Our method provided values that are consistent with other single-class methods, but produced results for multiple classes suggesting that our method is a useful one, especially since only a small amount (i.e., 1 mL) of milk is needed. We find that the extended run time reduces the amount of instrument maintenance needed.

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5. Conclusions An analytical method for the measurement of selected OCs, OPs, carbamates, pyrethroids, and the herbicide atrazine, and a pyrethroid synergist in cow milk, human milk, and baby formulas was successfully developed. This method involves a liquid-liquid extraction, freezing-lipid filtration, and solid-phase extraction procedure followed by GC-MS/MS) for the separation, identification, and quantification of 25 pesticides. The multistep cleanup employed in our method results in optimum extraction recoveries for different classes of pesticides, which allows the majority of pesticides to be extracted and analyzed with reasonable LODs as well as good accuracy and precision. This method was used to analyze 10 human milk samples, 10 cow milk samples and 10 baby formula samples purchased from local grocery stores in the United States. Some OCs and OPs, such as hexachlorobenzene, p,p-dicofol, o,p-DDE, p,p-DDE, and chlorpyrifos, exist in all the samples we analyzed. There are detectable levels of permethrin, cyfluthrin, and fenvalerate in some of the cow milk samples but not in human milk and baby formula samples. Some of the pesticides, such as azinphos-methyl, and heptachlor epoxide, and the pyrethroid synergist piperonyl butoxide, were detected in a few of the cow milk and human milk samples but not in baby formula samples. To our knowledge, this is the first human milk method to include OCs, OPs, carbamates, pyrethroids, a triazine, and a pyrethroid synergist in a single analytical method. Acknowledgements We acknowledge the aid of Kanstantin Kartavenka and Albert Lee for their work in laboratory analysis. This work was support by NIH Grant 5RC1ES01829902 under the American Recovery and Reinvestment Act of 2009, the National Children’s Study under contract number HHSN267200700007C.

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References

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[1] B. Eskenazi, A.R. Marks, A. Bradman, K. Harley, D.B. Barr, C. Johnson, e. al, Environ Health Perspect, 115 (2007) 792-798.

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[2] B. Eskenazi, L.G. Rosas, A.R. Marks, A. Bradman, K. Harley, N. Holland, e. al, Basic Clin Pharmacol Toxicol, 102 (2008) 228-236. [3] P.J. Kostyniak, C. Stinson, H.B. Greizerstein, J. Vena, G. Buck, P. Mendola, Environmental Research, 80 (1999) S166-174.

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[4] M.P. Longnecker, M.A. Klebanoff, H. Zhou, J.W. Brock, Lancet, 358 (2001) 110-114. [5] W.J. Rogan, A. Chen, Lancet, 366 (2005) 763-773.

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[6] D. Rice, S.J. Barone, Environ Health Perspective, 108 (2000) 511-533. [7] D.B. Barr, Studying the relation between pesticide exposure and human development. In: Human Developmental Neurotoxicology D.C. Bellinger (Ed.) New York:Taylor & Francis, 2006, pp. 253-285 Accessed Online

Ac

[8] J.R. Roberts, C.J. Karr, H. Council On Environmental, Pediatrics, 130 (2012) e1765-1788. [9] ATSDR, Toxicological Profile for DDT, DDE, and DDD Agency for Toxic Substances and Disease Registry (Ed.), 2002, http://www.atsdr.cdc.gov/toxprofiles/tp35.pdf, Accessed Online February 24, 2014. [10] I.N. Damgaard, N.E. Skakkebaek, J. Toppari, H.E. Virtanen, H. Shen, K.-W. Schramm, J.H. Petersen, T.K. Jensen, K.M. Main, N.C.S. Group, Environmental Health Perspectives, 114 (2006) 1133-1138.

Page 15 of 31

ip t

us

cr

[11] M.T. Munoz-Quezada, B.A. Lucero, D.B. Barr, K. Steenland, K. Levy, P.B. Ryan, V. Iglesias, S. Alvarado, C. Concha, E. Rojas, C. Vega, Neurotoxicology, 39 (2013) 158-168.

M an

[12] USEPA, Pesticide News Story: EPA Releases Report Containing Latest Estimates of Pesticide Use in the United States., 2011, http://epa.gov/oppfead1/cb/csb_page/updates/2011/sales-usage06-07.html, Accessed Online February 19, 2014. [13] J.E. Casida, G.B. Quistad, Annu Rev Entomol, 43 (1998) 1-16.

[14] D. Ray, J. Fry, Pharmacology & Therapeutics, 111 (2006) 174-193.

ed

[15] C.S. Lu, D.B. Barr, M.A. Pearson, L.A. Walker, R. Bravo, J. Expo. Sci. Environ. Epidemiol., 19 (2009) 69-78.

ce pt

[16] M. Morgan, L. Sheldon, C. Croghan, P. Jones, J. Chuang, N. Wilson, Environmental Research, 104 (2007) 266-274. [17] T.J. Shafer, D.A. Meyer, K.M. Crofton, Environ Health Perspect, 113 (2005) 123-136.

Ac

[18] L.P. Sheets, Neurotoxicology, 21 (2000).

[19] R.M. Whyatt, D.E. Camann, P.L. Kinney, A. Reyes, J. Ramirez, J. Dietrich, D. Diaz, D. Holmes, F.P. Perera, Environ Health Perspect, 110 (2002) 507-514. [20] M.K. Horton, A. Rundle, D.E. Camann, D. Boyd Barr, V.A. Rauh, R.M. Whyatt, Pediatrics, 127 (2011) e699-706. [21] M.F. Picciano, Pediatric clinics of North America, 48 (2001) 53-67.

Page 16 of 31

ip t cr

[22] M.F. Picciano, Pediatric clinics of North America, 48 (2001) 263-264.

M an

[24] W.A. Anwar, Environ. Health Perspect., 105 (1997) 801-806.

us

[23] R.G. Jensen, J. Bitman, S.E. Carlson, S.A. Couch, M. Hamosh, D.S. Newburg, Academic Press San Diego, (1995) 495-575.

[25] H. Bouwman, B. Sereda, H.M. Meinhardt, Environmental Pollution, 144 (2006) 902-917. [26] R. Sanghi, M.K.K. Pillai, T.R. Jayalekshmi, A. Nair, Human & Experimental Toxicology, 22 (2003) 73-76.

ed

[27] M. Zehringer, Food additives and contaminants, 18 (2001) 859-865.

ce pt

[28] J.L. Adgate, D.B. Barr, C.A. Clayton, L.E. Eberly, N.C. Freeman, P.J. Lioy, L.L. Needham, E.D. Pellizzari, J.J. Quackenboss, A. Roy, K. Sexton, Environ Health Perspect, 109 (2001) 583-590.

Ac

[29] TOXNET, Piperonyl butoxide, National Library of Medicine, 2010, http://toxnet.nlm.nih.gov/cgibin/sis/search/a?dbs+hsdb:@term+@DOCNO+1755, Accessed Online 20 February 2014. [30] USFDA, Guidance for Industry: Bioanalytical Method Validation, United States Food and Drug Administration, 2001, http://www.fda.gov/downloads/Drugs/Guidances/ucm070107.pdf, Accessed Online 17 February 2014. [31] USDA, Pesticide Data Program Annual Summary, Calendar Year 2011 United States Department of Agriculture, Washington, DC, 2013, http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=stelprdc5102692, Accessed Online 17 February 2014.

Page 17 of 31

ip t

us

cr

[32] USFDA, Pesticide Monitoring Program 2011 Pesticide Report, United States Food and Drug Adminstration, 2014, http://www.fda.gov/downloads/Food/FoodborneIllnessContaminants/Pesticides/UCM382443.pdf, Accessed Online 17 February 2014. [33] L.M. Grummer-Strawn, K.S. Scanlon, S.B. Fein, Pediatrics, 122 Suppl 2 (2008) S36-42.

M an

[34] B.E. Hamilton, J.A. Martin, S.J. Ventura, National vital statistics reports : from the Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System, 62 (2013) 1-20. [35] M.B. Woudneha, D.R. Oros, Journal of Chromatography A, 1135 (2006) 71-77.

ed

[36] M. Anastassiades, S.J. Lehotay, D. Štajnbaher, F.J. Schenck, J. AOAC Int. , 86 (2003) 412-431.

ce pt

[37] Y. He, Y.-H. Liu, Chromatographia, 65 (2007) 581-590.

Ac

Table 1. Compounds used in methods development. Name

Abbreviation

CAS number

Class

% Purity

Manufacturers

fenobucarb hexachlorobenzene atrazine fonofos bendiocarb diazinon chlorpyrifos-methyl

fen hcb atr fon ben dia chlm

3766-81-2 118-74-1 1912-24-9 944-22-9 22781-23-3 333-41-5 5598-13-0

Carbamate Organochlorine Triazine Organophosphate Carbamate Organophosphate Organophosphate

97.4 99.5 98.9 99.3 98.4 99.5 98.6

Sigma-Aldrich, St. Louis. MO USA Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Ultra Scientific, N. Kingston, RI USA Chem Service, West Chester, PA USA Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA

Page 18 of 31

10453-86-8 86-50-0 52645-53-1 68359-37-5 52315-07-8 51630-58-1 52918-63-5 N/A 285138-81-0 350820-04-1 N/A N/A

Ac

† Two different standards used at differing

ip t

res azm per cyf cyp fev del IS_chlm IS_cpy IS_par IS_ddepp IS_cyp

Supelco Analytical, Bellefonte, PA, USA Chem Service, West Chester, PA USA Ultra Scientific, N. Kingston, RI USA Ultra Scientific, N. Kingston, RI USA Chem Service, West Chester, PA USA Chem Service, West Chester, PA USA Supelco Analytical, Bellefonte, PA, USA Chem Service, West Chester, PA USA Crescent Chemical Co. Chem Service, West Chester, PA USA

97.6

Chem Service, West Chester, PA USA

99.5 99.5 99 98; 99.5† 98 98.7 99; 99.5† 98 99 98 98 99

Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Los Alamos National Laboratories Chem Service, West Chester, PA USA Chem Service, West Chester, PA USA Supelco Analytical, Bellefonte, PA, USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA

cr

resmethrin azinphos-methyl permethrin cyfluthrin cypermethrin fenvalerate deltamethrin chlorpyrifos-methyl D6 chlorpyrifos D10 parathion D10 13C-p,p-DDE 13C-cypermethrin

99.5 98.7 97.6 99 >98 98 99.5 98 99.5 99.5

us

pbo

Organophosphate Organophosphate Organochlorine Organochlorine Organochlorine Pyrethroid Organochlorine Organochlorine Organochlorine Organochlorine Synergist for Pyrethroids Pyrethroid Organophosphate Pyrethroid Pyrethroid Pyrethroid Pyrethroid Pyrethroid Organophosphate Organophosphate Organophosphate Organochlorine Pyrethroid

M an

piperonyl butoxide

2921-88-2 56-38-2 115-32-2 1024-57-3 3424-82-6 23031-36-9 959-98-8 72-55-9 33213-65-9 789-02-6 51-03-6

ed

cpy par dic hep ddeop pral endoA ddepp endoB ddtop

ce pt

chlorpyrifos parathion p,p-dicofol heptachlor epoxide o,p-DDE prallethrin endosulfan-α p,p-DDE endosulfan-β o,p-DDT

mes.

Page 19 of 31

Table 2. Quantification and confirmation ions monitored for the analytes in this study Fragmentation

13.70 15.05 15.09 18.07 24.47

328.6 360.6 301.3 330.0 422.3

M

IS_chlm IS_cpy IS_par IS_ddepp IS_cyp

121.2 284.0 200.3 246.2 151.2 304.3 286.2 314.2 291.3 139.1 353.1 246.2 123.2 241.1 246.2 241.1 235.2 176.2 171.2 160.2 183.2 163.1 163.1 125.2 253.1

d

207.3 284.8 215.7 246.3 223.2 304.3 322.6 350.6 291.3 370.5 389.3 318.0 300.4 406.9 318.0 406.9 354.5 338.4 382.5 317.3 391.3 434.3 416.3 419.9 505.2

te

10.51 11.75 12.09 12.48 12.65 12.65 13.76 15.19 15.22 15.26 16.28 17.18 17.18 17.38 18.08 18.93 19.25 20.63 20.67 22.00 23.22 23.95 24.36 25.78 26.78

291.1 324.0 301.0 258.0 170.0

Ac ce p

fen hcb atr fon ben dia chlm cpy par dic hep ddeop pral endoA ddepp endoB ddtop pbo res azm per cyf cyp fev del

CE (eV)

Q1

20 25 20 5 15 15 26 25 40 15 10 35 15 20 35 15 15 30 5 20 40 5 15 20 20

121.2 284.0 200.3 109.1 151.2 179.3 288.2 314.2 291.3 139.1 353.1 248.2 123.2 239.1 248.2 239.1 235.2 176.2 123.2 132.2 183.2 206.2 163.1 167.2 181.2

an

Q1

Quantification Ions Q3 Native Pesticides 103.1 249.1 104.1 137.2 84.1 179.3 93.2 258.0 81.0 111.1 263.1 176.2 87.1 206.1 176.2 206.1 199.1 103.1 143.2 77.2 77.0 127.2 127.1 89.0 93.2 Internal Standards 99.0 260.0 115.0 188.0 98.0

Confirmation Ions Q3 CE (eV)

25 20 15 40 15

51.2 214.2 122.2 63.1 68.2 121.0 93.0 286.1 90.9 75.1 282.1 176.3 105.2 204.1 176.2 204.1 165.1 91.1 95.2 77.1 153.2 151.1 91.1 89.2 152.2

40 40 10 15 25 40 20 5 35 30 15 30 20 15 30 20 25 40 6 15 15 25 25 40 30

274.0 292.0 134.0

30 10

ip t

MW

cr

RT (min)

us

Analyte

291.9 324.0

170.0

10

RT- Retention time (minutes) MW- Molecular weight (g/mol) Q1, Q3- Quad 1 and 3 transition monitored. CE- Collision energy (Quad 2) in eV

Page | 20 Page 20 of 31

Analytes

LOD (ng/mL)

0.1749

ddtop

0.0033

hcb

0.0675

pbo

0.0194

atr

0.0145

res

0.2430

fon

0.0135

azm

0.2119

ben

0.0101

per-I

0.1292

dia

0.0051

per-II

0.2263

chlm

0.0060

cyf-I

0.0735

0.0076

cyf-II

0.0771

par

0.6431

cyf-III

0.2963

dic

0.0099

cyp-I

0.0829

hep

0.0096

cyp-II

ddeop

0.0068

cyp-III

pral

0.3408

fev-I

endoA

0.0060

fev-II

0.0572

ddepp

0.0138

del-I

1.6692

endoB

0.0123

del-II

1.6428

an

cpy

cr

LOD (ng/mL)

fen

us

Analytes

ip t

Table 3 Limit of Detection in Cow Milk

0.0984

0.7745

Ac ce p

te

d

M

0.0309

Page | 21 Page 21 of 31

Table 4. Accuracy and precision for analysis of targeted compounds from replicate samples at two different concentration levels (5ng/mL and 25ng/mL) in cow milk

an

us

cr

ip t

Relative Standard Deviation (%) Within-day (N=3) Between-day (3-day period) 5ng/mL 25ng/mL 5ng/mL 25ng/mL 17.7 14.2 21.4 12.6 14.0 13.6 14.0 1.2 4.0 6.5 8.8 14.1 9.6 8.2 27.8 25.6 5.3 6.1 11.6 10.7 6.1 5.9 11.3 11.5 2.4 1.6 2.9 3.7 3.6 1.9 20.7 4.6 5.5 3.8 10.9 1.1 3.8 3.6 0.8 11.2 5.0 4.4 8.9 3.9 3.8 2.6 1.5 2.6 5.9 2.1 12.2 8.4 3.6 2.9 6.9 1.5 1.9 1.4 9.4 4.6 5.6 2.4 6.0 8.8 2.3 3.9 6.1 6.1 4.1 3.1 0.3 1.8 8.0 5.8 9.2 17.7 8.4 9.0 17.3 5.3 4.5 8.5 11.3 9.7 6.4 5.1 9.8 4.1 3.9 2.8 5.8 9.5 5.5 2.4 3.3 6.5 7.6 4.4 3.2 10.8 5.4 5.2 8.6 3.3 2.8 2.4 4.7 5.0 7.5 3.7 4.1 4.6 2.9 3.5 13.6 11.4 3.6 4.4 11.7 11.8

d

M

5ng/mL 25ng/mL 82.1 86.3 84.3 89.8 84.6 102.2 90.8 97.5 92.3 98.9 89.8 103.4 87.7 95.7 106.8 101.6 105.5 96.7 95.7 105.0 101.1 108.6 96.1 105.3 108.6 100.2 93.7 103.4 92.1 101.3 86.8 93.6 82.1 90.2 85.9 90.8 119.0 109.7 107.5 100.6 91.8 92.3 90.2 94.7 91.6 102.0 89.7 101.4 92.1 100.5 90.1 95.2 90.1 98.5 98.7 103.2 97.3 99.0 95.3 100.9

Ac ce p

fenobucarb hexachlorobenzene atrazine fonofos bendiocarb diazinon chlorpyrifos-methyl chlorpyrifos parathion p,p-dicofol heptachlor epoxide o,p-DDE prallethrin endosulfan-α p,p-DDE endosulfan-β o,p-DDT piperonyl butoxide resmethrin azinphos-methyl permethrin-I permethrin-II cyfluthrin-I cyfluthrin-II cyfluthrin-III cypermethrin-I cypermethrin-II cypermethrin-III fenvalerate-I fenvalerate-II

Accuracy (%) N=9

te

Name

Page | 22 Page 22 of 31

Figure 1

Sample Preparation Flow Diagram for pesticide analysis in breast milk, cow milk, and baby formula

15mL test tube Vortex @ 1000 rpm for 3min Sonicate for 10min

4 mL hexane

Vortex @ 1000 rpm for 3min Centrifuge for 5min

ip t

Vortex @ 1000 rpm for 2min Centrifuge for 5min

4 mL acetonitrile extract

4 mL hexane extract

an

300 mg NaCl

4 mL acetonitrile

cr

1 mL milk

us

Figure 1.

Evaporate to dryness

M

Reconstitute with 1 mL acetonitrile 0

-20 C refrigerator overnight & filter

Vortex, centrifuge, collect supernatant, and evaporate to ~2 mL

GCB/PSA SPE

Ac ce p

Precondition with 5 mL acetonitrile/toluene (3:1, v/v)

te

d

100 mg PSA 300 mg Na2SO4

Elute with 10 mL acetonitrile & 10 mL toluene Collect eluent

Evaporate to dryness

Reconstitute with 50µL acetonitrile/toluene (3:1, v/v)

Centrifuge @ 2500rpm for 30min

Take 45 µL for analysis

Page 23 of 31

ce pt

ed

M an

us

cr

Chromatogram of the analytes. (1. fenobucarb, 2. hexachlorobenzene, 3. atrazine, 4. fonofos, 5. bendiocarb, 6. diazinon, 7. chlorpyrifos-methyl, 8. chlorpyrifos, 9. parathion, 10. p,p-dicofol, 11. heptachlor epoxide, 12. o,p-DDE, 13. prallethrin, 14. endosulfan-α, 15. p,p-DDE, 16. endosulfan-β, 17. o,p-DDT, 18. piperonyl butoxide, 19. resmethrin, 20. azinphos-methyl, 21. permethrin, 22. cyfluthrin, 23. cypermethrin, 24. fenvalerate, 25. deltamethrin, A. chlorpyrifos-methyl D6, B. chlorpyrifos D10, C. parathion D10, D. 13C-p,p-DDE, E. 13C-cypermethrin.)

Ac

Figure 2.

ip t

Figure 2

Page 24 of 31

Figure 3

Figure 3. Recoveries of cow milk under two different concentration levels (25 ng/mL and 10 ng/mL).

ip t

del-II del-I fev-II fev-I cyp-III cyp-II cyp-I cyf-III cyf-II cyf-I per-II per-I azm res pbo ddtop endoB ddepp endoA pral ddeop hep dic par cpy chlm dia ben pro fon atr hcb fen

10ppb

Ac ce p

te

d

M

an

us

cr

25ppb

0

20

40

60

80

100

120

140

160

Recovery (%)

Page 25 of 31

Figure 4

cr us an M d te

Ac ce p

del-II del-I fev-II fev-I cyp-III cyp-II cyp-I cyf-III cyf-II cyf-I per-II per-I azm res pbo ddtop endoB ddepp endoA pral ddeop hep dic par cpy chlm dia ben pro fon atr hcb fen

ip t

Figure 4 Recoveries of baby formulas under the concentration level of 25 ng/mL. (* The error bar for azm is cut off to give the rest better resolution.)

-40.00

10.00

60.00

110.00

160.00

Recovery (%)

Page 26 of 31

Table 1. Compounds used in methods development.

cr

ip t

Tables

Abbreviation

CAS number

Class

fenobucarb hexachlorobenzene atrazine fonofos bendiocarb diazinon chlorpyrifos-methyl chlorpyrifos parathion p,p-dicofol heptachlor epoxide o,p-DDE prallethrin endosulfan-α p,p-DDE endosulfan-β o,p-DDT

fen hcb atr fon ben dia chlm cpy par dic hep ddeop pral endoA ddepp endoB ddtop

3766-81-2 118-74-1 1912-24-9 944-22-9 22781-23-3 333-41-5 5598-13-0 2921-88-2 56-38-2 115-32-2 1024-57-3 3424-82-6 23031-36-9 959-98-8 72-55-9 33213-65-9 789-02-6 51-03-6

Carbamate Organochlorine Triazine Organophosphate Carbamate Organophosphate Organophosphate Organophosphate Organophosphate Organochlorine Organochlorine Organochlorine Pyrethroid Organochlorine Organochlorine Organochlorine Organochlorine Synergist for Pyrethroids Pyrethroid Organophosphate Pyrethroid Pyrethroid Pyrethroid Pyrethroid Pyrethroid Organophosphate Organophosphate Organophosphate Organochlorine Pyrethroid

M an

ed

ce pt

piperonyl butoxide

res azm per cyf cyp fev del IS_chlm IS_cpy IS_par IS_ddepp IS_cyp

Ac

resmethrin azinphos-methyl permethrin cyfluthrin cypermethrin fenvalerate deltamethrin chlorpyrifos-methyl D6 chlorpyrifos D10 parathion D10 13C-p,p-DDE 13C-cypermethrin

pbo

10453-86-8 86-50-0 52645-53-1 68359-37-5 52315-07-8 51630-58-1 52918-63-5 N/A 285138-81-0 350820-04-1 N/A N/A

% Purity

Manufacturers

97.4 99.5 98.9 99.3 98.4 99.5 98.6 99.5 98.7 97.6 99 >98 98 99.5 98 99.5 99.5

Sigma-Aldrich, St. Louis. MO USA Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Ultra Scientific, N. Kingston, RI USA Chem Service, West Chester, PA USA Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Chem Service, West Chester, PA USA Ultra Scientific, N. Kingston, RI USA Ultra Scientific, N. Kingston, RI USA Chem Service, West Chester, PA USA Chem Service, West Chester, PA USA Supelco Analytical, Bellefonte, PA, USA Chem Service, West Chester, PA USA Crescent Chemical Co. Chem Service, West Chester, PA USA

97.6

Chem Service, West Chester, PA USA

99.5 99.5 99 98; 99.5† 98 98.7 99; 99.5† 98 99 98 98 99

Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Supelco Analytical, Bellefonte, PA, USA Los Alamos National Laboratories Chem Service, West Chester, PA USA Chem Service, West Chester, PA USA Supelco Analytical, Bellefonte, PA, USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA Cambridge Isotope Laboratories, Andover, MA USA

us

Name

† Two different standards used at differing times.

Page 27 of 31

Table 2. Quantification and confirmation ions monitored for the analytes in this study Fragmentation

13.70 15.05 15.09 18.07 24.47

328.6 360.6 301.3 330.0 422.3

M

IS_chlm IS_cpy IS_par IS_ddepp IS_cyp

121.2 284.0 200.3 246.2 151.2 304.3 286.2 314.2 291.3 139.1 353.1 246.2 123.2 241.1 246.2 241.1 235.2 176.2 171.2 160.2 183.2 163.1 163.1 125.2 253.1

d

207.3 284.8 215.7 246.3 223.2 304.3 322.6 350.6 291.3 370.5 389.3 318.0 300.4 406.9 318.0 406.9 354.5 338.4 382.5 317.3 391.3 434.3 416.3 419.9 505.2

te

10.51 11.75 12.09 12.48 12.65 12.65 13.76 15.19 15.22 15.26 16.28 17.18 17.18 17.38 18.08 18.93 19.25 20.63 20.67 22.00 23.22 23.95 24.36 25.78 26.78

291.1 324.0 301.0 258.0 170.0

Ac ce p

fen hcb atr fon ben dia chlm cpy par dic hep ddeop pral endoA ddepp endoB ddtop pbo res azm per cyf cyp fev del

CE (eV)

Q1

20 25 20 5 15 15 26 25 40 15 10 35 15 20 35 15 15 30 5 20 40 5 15 20 20

121.2 284.0 200.3 109.1 151.2 179.3 288.2 314.2 291.3 139.1 353.1 248.2 123.2 239.1 248.2 239.1 235.2 176.2 123.2 132.2 183.2 206.2 163.1 167.2 181.2

an

Q1

Quantification Ions Q3 Native Pesticides 103.1 249.1 104.1 137.2 84.1 179.3 93.2 258.0 81.0 111.1 263.1 176.2 87.1 206.1 176.2 206.1 199.1 103.1 143.2 77.2 77.0 127.2 127.1 89.0 93.2 Internal Standards 99.0 260.0 115.0 188.0 98.0

Confirmation Ions Q3 CE (eV)

25 20 15 40 15

51.2 214.2 122.2 63.1 68.2 121.0 93.0 286.1 90.9 75.1 282.1 176.3 105.2 204.1 176.2 204.1 165.1 91.1 95.2 77.1 153.2 151.1 91.1 89.2 152.2

40 40 10 15 25 40 20 5 35 30 15 30 20 15 30 20 25 40 6 15 15 25 25 40 30

274.0 292.0 134.0

30 10

ip t

MW

cr

RT (min)

us

Analyte

291.9 324.0

170.0

10

RT- Retention time (minutes) MW- Molecular weight (g/mol) Q1, Q3- Quad 1 and 3 transition monitored. CE- Collision energy (Quad 2) in eV

Page 28 of 31

LOD (ng/mL)

fen

0.1749

ddtop

0.0033

hcb

0.0675

pbo

0.0194

atr

0.0145

res

0.2430

fon

0.0135

azm

0.2119

ben

0.0101

per-I

0.1292

dia

0.0051

per-II

0.2263

chlm

0.0060

cyf-I

0.0735

cpy

0.0076

cyf-II

0.0771

par

0.6431

cyf-III

0.2963

dic

0.0099

cyp-I

0.0829

hep

0.0096

cyp-II

0.0984

ddeop

0.0068

cyp-III

0.7745

0.3408

fev-I

0.0060

fev-II

ddepp

0.0138

del-I

endoB

0.0123

del-II

0.0309 0.0572 1.6692

M

pral endoA

cr

Analytes

us

LOD (ng/mL)

an

Analytes

ip t

Table 3 Limit of Detection in Cow Milk

Ac ce p

te

d

1.6428

Page 29 of 31

Table 4. Accuracy and precision for analysis of targeted compounds from replicate samples at two different concentration levels (5ng/mL and 25ng/mL) in cow milk

an

us

cr

ip t

Relative Standard Deviation (%) Within-day (N=3) Between-day (3-day period) 5ng/mL 25ng/mL 5ng/mL 25ng/mL 17.7 14.2 21.4 12.6 14.0 13.6 14.0 1.2 4.0 6.5 8.8 14.1 9.6 8.2 27.8 25.6 5.3 6.1 11.6 10.7 6.1 5.9 11.3 11.5 2.4 1.6 2.9 3.7 3.6 1.9 20.7 4.6 5.5 3.8 10.9 1.1 3.8 3.6 0.8 11.2 5.0 4.4 8.9 3.9 3.8 2.6 1.5 2.6 5.9 2.1 12.2 8.4 3.6 2.9 6.9 1.5 1.9 1.4 9.4 4.6 5.6 2.4 6.0 8.8 2.3 3.9 6.1 6.1 4.1 3.1 0.3 1.8 8.0 5.8 9.2 17.7 8.4 9.0 17.3 5.3 4.5 8.5 11.3 9.7 6.4 5.1 9.8 4.1 3.9 2.8 5.8 9.5 5.5 2.4 3.3 6.5 7.6 4.4 3.2 10.8 5.4 5.2 8.6 3.3 2.8 2.4 4.7 5.0 7.5 3.7 4.1 4.6 2.9 3.5 13.6 11.4 3.6 4.4 11.7 11.8

d

M

5ng/mL 25ng/mL 82.1 86.3 84.3 89.8 84.6 102.2 90.8 97.5 92.3 98.9 89.8 103.4 87.7 95.7 106.8 101.6 105.5 96.7 95.7 105.0 101.1 108.6 96.1 105.3 108.6 100.2 93.7 103.4 92.1 101.3 86.8 93.6 82.1 90.2 85.9 90.8 119.0 109.7 107.5 100.6 91.8 92.3 90.2 94.7 91.6 102.0 89.7 101.4 92.1 100.5 90.1 95.2 90.1 98.5 98.7 103.2 97.3 99.0 95.3 100.9

Ac ce p

fenobucarb hexachlorobenzene atrazine fonofos bendiocarb diazinon chlorpyrifos-methyl chlorpyrifos parathion p,p-dicofol heptachlor epoxide o,p-DDE prallethrin endosulfan-α p,p-DDE endosulfan-β o,p-DDT piperonyl butoxide resmethrin azinphos-methyl permethrin-I permethrin-II cyfluthrin-I cyfluthrin-II cyfluthrin-III cypermethrin-I cypermethrin-II cypermethrin-III fenvalerate-I fenvalerate-II

Accuracy (%) N=9

te

Name

Page 30 of 31

Table 5 Results in 10 cow milk, 10 human milk, and 10 baby formulas samples Cow Milk

Human Milk

Baby Formula

Min Conc. (ng/mL)

Max Conc. (ng/mL)

Med Conc. (ng/mL)

FD (%)

Min Conc. (ng/mL)

Max Conc. (ng/mL)

Med Conc. (ng/mL)

FD (%)

Min Conc. (ng/mL)

Max Conc. (ng/mL)

Med Conc. (ng/mL)

hcb

100

0.054

0.277

0.153

100

0.224

1.852

0.655

100

0.133

0.362

0.215

atr

90

0.032

0.205

0.067

40

0.028

0.105

0.052

60

0.030

0.077

0.049

fon

100

0.045

0.278

0.081

0

0.000

0.000

-

20

0.008

0.014

0.011

dia

100

0.040

0.209

0.073

50

0.028

0.100

0.044

40

0.019

0.023

0.020

ben

80

0.043

0.199

0.141

10

0.106

0.106

0.106

10

0.044

0.044

0.044

chl m

100

0.027

0.128

0.046

0

0.000

0.000

-

cpy

100

0.035

0.220

0.113

100

0.022

0.711

0.063

dic

100

0.033

0.230

0.091

100

0.029

1.115

0.109

hep

50

0.074

0.270

0.097

100

0.356

3.670

100

0.026

0.169

0.055

100

0.007

0.070

90

0.037

0.179

0.063

0

0.000

0.000

100

0.036

0.164

0.069

100

0.675

40

0.078

0.165

0.092

10

0.008

100

0.023

0.143

0.047

70

0.017

100

0.041

0.205

0.105

40

30

0.068

0.751

0.166

90

0.042

0.255

0.090

90

0.070

0.348

0.118

70

0.106

0.297

0.152

70

0.034

0.172

0.060

10

70 80 80 80 40 40

cr

0.021

100

0.000

0.062

0.036

100

0.029

0.096

0.047

0.967

0

0.000

0.000

-

0.025

100

0.011

0.057

0.022

-

60

0.020

0.052

0.036

5.644

1.365

100

0.012

0.057

0.023

0.008

0.008

0

0.000

0.000

-

0.076

0.027

80

0.008

0.046

0.017

0.009

0.150

0.020

0

0.000

0.000

-

50

0.173

0.620

0.386

0

0.000

0.000

-

0

0.000

0.000

-

0

0.000

0.000

-

0

0.000

0.000

-

0

0.000

0.000

-

10

0.488

0.488

0.488

0

0.000

0.000

-

0.352

0.352

0.352

0

0.000

0.000

-

M

an

us

0.046

d

az m per -I per -II cyfI cyfII cyfIII cyp -I cyp -II cyp -III fevI fevII

0.013

te

pbo

50

Ac ce p

dde op end oA dde pp end oB ddt op

ip t

FD (%)

0.030

0.189

0.056

10

0.276

0.276

0.276

0

0.000

0.000

-

0.066

0.198

0.085

20

0.258

0.356

0.307

80

0.056

0.128

0.070

0.030

0.229

0.089

20

0.087

0.393

0.240

80

0.055

0.190

0.095

0.033

0.233

0.117

20

0.150

0.431

0.291

80

0.065

0.164

0.084

0.105

0.173

0.120

0

0.000

0.000

-

0

0.000

0.000

-

0.089

0.170

0.095

0

0.000

0.000

-

0

0.000

0.000

-

*FD, Min Conc., Max Conc., and Med Conc. in this table represent Frequency of Detection, Minimum Concentration, Maximum Concentration, and Concentration at 50th % in 10 samples under each category (cow milk, human milk, and baby formulas).

Page 31 of 31