Mélissa Buscato

Coralie Fontaine

Aurélie Fabre

Alexia Vinel

Marie-Cécile Valera

Emmanuelle Noirrit

Maeva Guillaume

Bernard Payrastre

Raphaël Métivier

Jean-François Arnal

Jean- François Arnal

Jean François Arnal

The antagonist properties of Bazedoxifene after acute treatment are shifted to stimulatory action after chronic exposure in the liver but not in the uterus

Keywords: estrogen receptor (ER), Bazedoxifene, tissue-selective estrogen complex (TSEC), hormone therapy, menopause, liver

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Introduction

The decline of estrogen levels after menopause is associated with bone loss, hot flushes and vulvar-vaginal atrophy, affecting sexual function, relationships, and quality of life. Estrogenprogestin therapy was previously considered as the standard for managing moderate to severely bothersome symptoms associated with menopause but this drug combination is now controversial due to the increased risk of breast cancer and thromboembolism [START_REF] Anderson | Effects of conjugated equine estrogen in postmenopausal women with hysterectomy: the Women's Health Initiative randomized controlled trial[END_REF][START_REF] Chlebowski | Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the Women's Health Initiative Randomized Trial[END_REF][START_REF] Rossouw | Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women's Health Initiative randomized controlled trial[END_REF]. The combination of conjugated estrogen (CE) with Bazedoxifene (BZA) is known as the tissue-selective estrogen complex (TSEC). It was designed to minimize the undesirable effects of hormone therapy on breast tissue yet allow the beneficial effects of estrogen on other estrogen-target tissues, thus suppressing climacteric symptoms and preventing osteoporosis [START_REF] Mirkin | Tissue-selective estrogen complexes for postmenopausal women[END_REF].

This drug combination was developed by Pfizer and has been marketed in the US for two years as Duavee ® (CE, 0.45 mg / BZA, 20 mg). It has also been approved by the European Medicines Agency (EMA) [START_REF] Komm | Evolution of the tissue selective estrogen complex (TSEC)[END_REF]. The efficacy and safety of CE+BZA in postmenopausal women, and the impact of this drug combination on quality of life was evaluated through a series of five pivotal phase 3 randomized, double-blinded, multicentered, active and/or placebo-controlled studies, called the Selective estrogens, Menopause And Response to Therapy (SMART) trials [START_REF] Kagan | A randomized, placebo-and activecontrolled trial of bazedoxifene/conjugated estrogens for treatment of moderate to severe vulvar/vaginal atrophy in postmenopausal women[END_REF], Mirkin and Komm, 2013, Pickar et al., 2009, Pinkerton et al., 2009[START_REF] Umland | Bazedoxifene and Conjugated Equine Estrogen: A Combination Product for the Management of Vasomotor Symptoms and Osteoporosis Prevention Associated with Menopause[END_REF]. From these trials, CE+BZA was found to be associated with significant benefits such as a reduction in the frequency and severity of vasomotor symptoms, the prevention of bone loss, improved sleep and better menopausespecific quality of life, whilst also providing a reasonable level of protection against endometrial hyperplasia. Additionally, CE+BZA exhibited promising effects on breast tissue since it did not increase mammographic breast density [START_REF] Goldberg | Conjugated Estrogens/Bazedoxifene (Duavee): A Novel Agent for the Treatment of Moderate-to-Severe Vasomotor Symptoms Associated With Menopause And the Prevention of Postmenopausal Osteoporosis[END_REF][START_REF] Lobo | Evaluation of bazedoxifene/conjugated estrogens for the treatment of menopausal symptoms and effects on metabolic parameters and overall safety profile[END_REF], Pinkerton et al., 2014[START_REF] Pinkerton | Bazedoxifene when paired with conjugated estrogens is a new paradigm for treatment of postmenopausal women[END_REF], Pinkerton et al., 2009[START_REF] Ronkin | Endometrial effects of bazedoxifene acetate, a novel selective estrogen receptor modulator, in postmenopausal women[END_REF][START_REF] Stovall | Tissue-selective estrogen complex bazedoxifene and conjugated estrogens for the treatment of menopausal vasomotor symptoms[END_REF]. The SMART trials also suggested that CE+BZA treatment was associated with similar rates of coronary heart disease, stroke, venous thromboembolism and menorrhea as placebo-treated patients [START_REF] Skouby | Effects of conjugated estrogens/bazedoxifene on lipid and coagulation variables: a randomized placebo-and active-controlled trial[END_REF], although definitive conclusions cannot yet be made on these aspects due to the total number of women enrolled in these trials and the trial durations.

The molecular mechanisms underlying TSEC action are far from fully understood. CE is a mixture of different natural estrogens and BZA is one of a new generation of selective estrogen receptor modulators (SERM) that demonstrate selective binding to the estrogen receptors (ER) over other members of the nuclear receptors family [START_REF] Del Barrio | Cellular Therapy With Human Autologous Adipose-Derived Adult Stem Cells for Advanced Keratoconus[END_REF]. SERMs are thought to be ER agonists or antagonists depending on the tissue involved.

Contrary to the action of 17-β-estradiol (E2) or CE that allow ER to recruit coactivators, leading to an enhanced transcription of target genes, SERM is reported to rather provoke the mobilization of corepressors to the ERs [START_REF] Shang | Molecular determinants for the tissue specificity of SERMs[END_REF]. This differential recruitment of ER coregulators by estrogens versus SERMs can be attributed, at least in part, to the different ER conformational changes induced by the binding of these ligands (Alio Del [START_REF] Del Barrio | Cellular Therapy With Human Autologous Adipose-Derived Adult Stem Cells for Advanced Keratoconus[END_REF]. In addition, TSEC was shown to cause ERα degradation via the ubiquitin proteasome system in the breast and uterus, which was at least in part responsible for the suppression of ERα-mediated transcription [START_REF] Han | The Dual Estrogen Receptor alpha Inhibitory Effects of the Tissue-Selective Estrogen Complex for Endometrial and Breast Safety[END_REF]. However, this ERα modulation appears to be cell-and tissue-specific since BZA treatment was able to exert an estrogenmimetic action on bone [START_REF] Palacios | A 7-year randomized, placebo-controlled trial assessing the long-term efficacy and safety of bazedoxifene in postmenopausal women with osteoporosis: effects on bone density and fracture[END_REF] and on the metabolism contributing to beneficial glucidic and lipidic effects [START_REF] Barrera | Bazedoxifene and conjugated estrogen prevent diet-induced obesity, hepatic steatosis, and type 2 diabetes in mice without impacting the reproductive tract[END_REF][START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF].

Thus, the consequences of the co-administration of estrogens and SERM at the molecular, cellular and whole body levels are undoubtedly highly complex. Here, our goal was to explore the tissue-specific effects of BZA combined with CE in vivo in mice comparing in two major targets of estrogens, the uterus and the liver [START_REF] Ahlbory-Dieker | DNA binding by estrogen receptor-alpha is essential for the transcriptional response to estrogen in the liver and the uterus[END_REF][START_REF] Boverhof | Temporal-and dose-dependent hepatic gene expression changes in immature ovariectomized mice following exposure to ethynyl estradiol[END_REF][START_REF] Gao | Genome-wide identification of estrogen receptor alpha-binding sites in mouse liver[END_REF][START_REF] Gordon | Research resource: Aorta-and liver-specific ERalpha-binding patterns and gene regulation by estrogen[END_REF][START_REF] Handgraaf | Prevention of obesity and insulin resistance by estrogens requires ERalpha activation function-2 (ERalphaAF-2), whereas ERalphaAF-1 is dispensable[END_REF][START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF][START_REF] Kobayashi | Gastric estradiol-17beta (E2) and liver ERalpha correlate with serum E2 in the cholestatic male rat[END_REF][START_REF] Palierne | Changes in Gene Expression and Estrogen Receptor Cistrome in Mouse Liver Upon Acute E2 Treatment[END_REF][START_REF] Pedram | Estrogen reduces lipid content in the liver exclusively from membrane receptor signaling[END_REF]. Our results indicate that the effects of BZA treatment varies according to the duration of treatment (acute versus chronic administration) and the tissue, with the responses observed in the liver being dramatically different from those observed in the uterus.

Materials and Methods

Mice

Female C57BL/6J mice were purchased from Charles River Laboratories. All procedures were performed in accordance with the principles established by the National Institute of Medical Research and were approved by the local Ethical Committee of Animal Care. Mice were anesthetized by intraperitoneal injection of ketamine (25 mg/kg) and xylazine (10 mg/kg) and ovariectomized at 4 weeks of age. To study the chronic effects of CE, BZA and BZA+CE, 2 weeks after ovariectomy mice were implanted with subcutaneous osmotic minipumps (Alzet; Alza, Palo Alto, CA) that released CE (3 mg/kg/day) or BZA (10 mg/kg/day) alone or in combination diluted in a solution of hydroxypropyl-β-cyclodextrinwith a 0.63 degree of substitution -in HEPES buffer for a 3 week period. For acute treatment, ovariectomized mice were orally administered with vehicle (PBS containing 0.5% methylcellulose, 2% Tween 80 and 5% DMSO), CE (3 or 10 mg/kg) or E2 (1 mg/kg) alone or in combination with BZA (10 mg/kg). These dose have been chosen based on previous studies [START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF][START_REF] Barrera | Bazedoxifene and conjugated estrogen prevent diet-induced obesity, hepatic steatosis, and type 2 diabetes in mice without impacting the reproductive tract[END_REF][START_REF] Della Torre | The conundrum of estrogen receptor oscillatory activity in the search for an appropriate hormone replacement therapy[END_REF][START_REF] Fontana | Estrogen replacement therapy regulation of energy metabolism in female mouse hypothalamus[END_REF][START_REF] Naqvi | Treatment with bazedoxifene and conjugated estrogens results in regression of endometriosis in a murine model[END_REF][START_REF] Oliva | Global profiling of TSEC proliferative potential by the use of a reporter mouse for proliferation[END_REF][START_REF] Peano | Effects of various selective estrogen receptor modulators with or without conjugated estrogens on mouse mammary gland[END_REF][START_REF] Song | Effects of the conjugated equine estrogen/bazedoxifene tissue-selective estrogen complex (TSEC) on mammary gland and breast cancer in mice[END_REF] (Supplementary Table 1) and in particular on those realized by Peano et al. in which uterus weight was used as final endpoint to determine the minimal dose of CE (i.e 3 mg/kg/day) inducing uterine hypertrophy and that of BZA (i.e 10 mg/kg/day) antagonizing this effect.

Histological analysis

Paraffin-embedded transverse sections (4 µm) from formalin-fixed uterine specimens was stained as previously described [START_REF] Abot | The AF-1 activation function of estrogen receptor alpha is necessary and sufficient for uterine epithelial cell proliferation in vivo[END_REF] with anti-Ki-67 (RM-9106; Thermoscientific) and anti-ERα antibodies Santa Cruz Biotechnology,Santa Cruz,California). Sections were examined after numerization using a NanoZoomer Digital Pathology®. To examine the proliferative effects of each treatment, the ratio of Ki-67-positive epithelial cell/total cell number was evaluated from two microscopic fields of measurement at x20 magnification for each uterine section.

Analysis of mRNA levels by qPCR

Tissues were homogenized using a Precellys tissue homogenizer (Bertin Technology, Cedex, France), and total RNA from tissues was extracted using the TRIzol reagent (Invitrogen, Carlsbad, CA). A total of 500 ng to 1 µg (depending on the tissue) was reverse transcribed for 10 minutes at 25°C and 2 hours at 37°C in a 20 μL final volume using the High Capacity cDNA Reverse Transcriptase Kit (Applied Biosystems, Villebon sur Yvette, France). We evaluated genes expression levels in liver by high throughput qPCR, using 6.5 ng cDNA from each sample in 96.96 Dynamic Arrays analyzed in the microfluidic BioMark system (Fluidigm Corporation, CA, USA). For gene expression in uterus, qPCR was performed using SsoFast EvaGreen Supermix (Bio-Rad) on a StepOne instrument (Applied Biosystems).

Primers (Supplementary Table 2) were validated by testing PCR efficiency using standard curves (95% ≤ efficiency ≤ 105%). Gene expression was quantified using the comparative C T method. Genes' functional annotations were retrieved from different databases. Kegg and

Reactome

were obtained under the webgestalt platform (http://www.webgestalt.org/option.php) and wikipathways directly from their website (http://www.wikipathways.org/). Genes with no clear annotations were then manually curated in the Biosystem database from the ncbi gene portal (https://www.ncbi.nlm.nih.gov/gene).

Genes involved in the regulation of metabolic pathway in at least one of these databases are highlighted in yellow in the supplementary tables of results (Supplementary Tables 3 to 5).

Statistical analysis

Results are expressed as means ± SEM. Statistical analyses were performed using graph pad.

1-way ANOVA was used to determine significance. * P<0.05, ** P<0.01, *** P<0.001.

RESULTS

Similar inhibitory action of BZA after acute treatment in the uterus and the liver.

To determine the relative effects of TSEC after acute treatment (4 hours), we first used 2 doses of CE (3 or 10 mg/kg) and the expression profile of selected genes known to be regulated by E2 was evaluated in the uterus [START_REF] Abot | The AF-1 activation function of estrogen receptor alpha is necessary and sufficient for uterine epithelial cell proliferation in vivo[END_REF]. We found that acute CE treatment (3 mg/kg) induced a weak transcriptional response whereas a higher dose of CE (10 mg/kg) was able to induce gene expression changes to a similar extent as E2 (1 mg/kg) (Figure 1A). The addition of BZA to E2 or to CE significantly attenuated these effects, while BZA alone had no effect. Analysis of protein levels by Western blot indicated that BZA alone or in combination with E2 or CE markedly down-regulated the amounts of ERα protein (Figures 1B and 1C). In contrast, none of these treatments had a significant impact of on ERα mRNA levels (Figure 1D).

Then, we analyzed the transcriptional response of liver to these acute treatments (Tables 3 and4) analyzing a set of genes described to be regulated by estrogens or selective ER modulators exposure in the liver [START_REF] Palierne | Changes in Gene Expression and Estrogen Receptor Cistrome in Mouse Liver Upon Acute E2 Treatment[END_REF][START_REF] Boverhof | Temporal-and dose-dependent hepatic gene expression changes in immature ovariectomized mice following exposure to ethynyl estradiol[END_REF][START_REF] Gordon | Research resource: Aorta-and liver-specific ERalpha-binding patterns and gene regulation by estrogen[END_REF][START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF][START_REF] Pedram | Estrogen reduces lipid content in the liver exclusively from membrane receptor signaling[END_REF][START_REF] Ahlbory-Dieker | DNA binding by estrogen receptor-alpha is essential for the transcriptional response to estrogen in the liver and the uterus[END_REF][START_REF] Kobayashi | Gastric estradiol-17beta (E2) and liver ERalpha correlate with serum E2 in the cholestatic male rat[END_REF]. As observed in the uterus, a dose of 3 mg/kg CE was less efficient than 10 mg/kg CE to induce an optimal transcriptional response. Only around 40% of the genes induced by 10 mg/kg CE or 1 mg/kg E2 were induced by 3 mg/kg CE (Figures 2A and2B). Co-administration of BZA strongly attenuated the transcriptional induction observed with E2 (Figure 2A and Supplementary Table 3) or CE (Figure 2B and Supplementary Table 4). Acute BZA treatment, both alone and when combined with estrogens, elicited a clear-cut down-regulation of ERα at the protein level (Figures 3A and 3B), but not at the level of mRNA (Figure 3C).

Altogether, these results demonstrated that acute BZA treatment is able to exert similar antagonistic action on the transcriptional modulations induced by E2 or CE in both uterus and liver. Concomitantly, we observed reduced amounts of ERα protein in response to BZA in these two tissues, an effect that occurred in a post-transcriptional manner as no differences in ERα mRNA expression were observed following drug treatment.

Chronic BZA treatment exerts inhibitory action on uterus and stimulatory effect

on liver.

To determine the relative effects of TSEC after a chronic treatment of the animals, 4-week-old ovariectomized female mice were treated with placebo, BZA (10 mg/kg/day), CE (3 mg/kg/day) or CE+BZA for 3 weeks, as previously described [START_REF] Barrera | Bazedoxifene and conjugated estrogen prevent diet-induced obesity, hepatic steatosis, and type 2 diabetes in mice without impacting the reproductive tract[END_REF][START_REF] Della Torre | The conundrum of estrogen receptor oscillatory activity in the search for an appropriate hormone replacement therapy[END_REF][START_REF] Fontana | Estrogen replacement therapy regulation of energy metabolism in female mouse hypothalamus[END_REF][START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF][START_REF] Naqvi | Treatment with bazedoxifene and conjugated estrogens results in regression of endometriosis in a murine model[END_REF][START_REF] Oliva | Global profiling of TSEC proliferative potential by the use of a reporter mouse for proliferation[END_REF][START_REF] Peano | Effects of various selective estrogen receptor modulators with or without conjugated estrogens on mouse mammary gland[END_REF][START_REF] Song | Effects of the conjugated equine estrogen/bazedoxifene tissue-selective estrogen complex (TSEC) on mammary gland and breast cancer in mice[END_REF] (Supplementary Table 1). Analysis of the uterine wet weight confirmed that BZA antagonized the uterotrophic effect of CE (Figure 4A).

Accordingly, epithelial proliferation was significantly decreased in CE+BZA-treated mice compared to CE-treated mice, as indicated by the immunohistochemical detection of the Ki-67 antigen (Figures 4B and4C). After chronic exposure, large changes in uterine cellular populations induced by CE treatment did not allow for a relevant comparison of protein expression in tissue homogenates by Western blotting. Thus, ERα protein levels were evaluated by immunohistochemistry (Figure 4D) which is essentially qualitative rather than quantitative, and no obvious effect of BZA or CE+BZA on ERα abundance was apparent.

Altogether, the analysis of different parameters including uterine weight and epithelial proliferation clearly shows that BZA antagonizes the action of CE and E2 in the uterus.

No difference in body weight was observed between ovariectomized untreated mice (mean = 22.4 ± 2.1 g, n = 20), CE-treated mice (23.8 ± 0.5 g, n = 16), BZA-treated mice (21.8 ± 1.6 g, n = 23) and CE+BZA-treated mice (21.4 ± 1.2 g, n = 22), showing that CE, BZA or CE+BZA administrated subcutaneously for 3 weeks had no detectable impact on weight gain. Although some genes were found to be regulated by either CE or BZA, the majority of the genes studied were regulated by both CE and BZA (Figure 5 and Supplementary Table 5). Overall, chronic BZA and CE+BZA elicited agonistic effects similar to those of CE alone (Figure 5).

For example, whereas BZA antagonizes CE-induced transcriptional activation of gene such as p21, Trim2, Psen2, Pgep1 or Inf2 after acute exposure (Supplementary Table 4), these genes are induced by CE+BZA treatment after chronic exposure (Supplementary Table 5A). Genes described to be involved in the regulation of metabolic pathways do not correspond to a specific regulatory profile in response to estrogens or BZA and are found in all the analyzed cases (i,e regulated by estrogens only, BZA only or after combination of BZA + CE) (Supplementary Table 5). In addition, chronic CE administration increased ERα protein and mRNA abundance in the liver, whereas BZA alone or CE+BZA had no effect compared to vehicle (Figures 6). Altogether, these data highlight a new aspect of the action of BZA on liver tissue, where it can have antagonistic effects after acute treatment and agonistic effects after chronic exposure.

DISCUSSION

The approval of Duavee ® CE (0.45mg)/BZA(20mg) was based on Selective Estrogen, Menopause, and Response to Therapy (SMART) trials that aimed to evaluate CE/BZA's safety and efficacy in the management of moderate-to-severe vasomotor symptoms, bone mineral density, endometrial hyperplasia, moderate-to-severe vulvar/vaginal atrophy, and overall safety [START_REF] Kagan | A randomized, placebo-and activecontrolled trial of bazedoxifene/conjugated estrogens for treatment of moderate to severe vulvar/vaginal atrophy in postmenopausal women[END_REF], Mirkin and Komm, 2013, Pickar et al., 2009, Pinkerton et al., 2009[START_REF] Umland | Bazedoxifene and Conjugated Equine Estrogen: A Combination Product for the Management of Vasomotor Symptoms and Osteoporosis Prevention Associated with Menopause[END_REF]. In parallel, preclinical studies in animal models reported beneficial effect on metabolic parameters [START_REF] Barrera | Bazedoxifene and conjugated estrogen prevent diet-induced obesity, hepatic steatosis, and type 2 diabetes in mice without impacting the reproductive tract[END_REF][START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF] and have

shown that, when combined with CE, BZA attenuates CE-induced uterine and mammary gland cell proliferation [START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF][START_REF] Barrera | Bazedoxifene and conjugated estrogen prevent diet-induced obesity, hepatic steatosis, and type 2 diabetes in mice without impacting the reproductive tract[END_REF][START_REF] Peano | Effects of various selective estrogen receptor modulators with or without conjugated estrogens on mouse mammary gland[END_REF][START_REF] Song | Effects of the conjugated equine estrogen/bazedoxifene tissue-selective estrogen complex (TSEC) on mammary gland and breast cancer in mice[END_REF]. However, assessing the relative effects of estrogens or SERMS in vivo in rodents is complicated by the fact that contrary to human, mice do not express the sex hormone binding globulin (SHBG) which modulates the bioactivity of sex steroids by limiting their diffusion into target tissues. Based on the uterine weight as endpoint, dose response study determinates CE (3mg/kg/day) and BZA (10 mg/kg/day) as reference doses (minimum fully effective agonist and antagonist doses respectively) for combination studies with SERMS [START_REF] Peano | Effects of various selective estrogen receptor modulators with or without conjugated estrogens on mouse mammary gland[END_REF]. Our results confirm that BZA (10 mg) antagonizes CE (3 mg) on uterus weight and proliferative response after chronic treatment in uterus and also show that BZA inhibits the CE-mediated transcriptional gene regulations (10 mg) after acute treatment extending this particular mechanism of action of BZA on sex targets. Furthermore, in cellular models of breast cancer, BZA was shown to function as a pure ERα antagonist and effectively inhibited the growth of both tamoxifen-sensitive and tamoxifen-resistant breast tumor xenografts [START_REF] Wardell | Bazedoxifene exhibits antiestrogenic activity in animal models of tamoxifen-resistant breast cancer: implications for treatment of advanced disease[END_REF]. The antiestrogens that are currently available fall into two general classes, acting as selective estrogen receptor modulators (SERMs) and/or selective estrogen receptor down-regulators (SERD). We found that, after acute treatment, BZA led to a decrease in ERα protein levels in both uterus and liver without impacting ERα mRNA levels.

Indeed, BZA has been described to induce a unique conformational change in ERα that results in its proteosomal degradation, although this property was shown to be dispensable for its antagonistic activity [START_REF] Wardell | Bazedoxifene exhibits antiestrogenic activity in animal models of tamoxifen-resistant breast cancer: implications for treatment of advanced disease[END_REF]. ERα immunodetection generated similar signals in tissues from untreated, CE-, BZA-and CE+BZA-treated ovariectomized mice, suggesting that BZA behaves as a SERM rather than a SERD after chronic treatment. Interestingly, a very specific profile of BZA was previously reported in biochemical and cell-based assays, as its combination with CE displayed different properties from those observed following the combination of CE with other SERMs [START_REF] Berrodin | Differential biochemical and cellular actions of Premarin estrogens: distinct pharmacology of bazedoxifeneconjugated estrogens combination[END_REF][START_REF] Chang | Gene expression profiling studies of three SERMs and their conjugated estrogen combinations in human breast cancer cells: insights into the unique antagonistic effects of bazedoxifene on conjugated estrogens[END_REF][START_REF] Wardell | Research resource: Transcriptional profiling in a cellular model of breast cancer reveals functional and mechanistic differences between clinically relevant SERM and between SERM/estrogen complexes[END_REF]. Indeed, in vitro, whereas raloxifene and lasofoxifene completely inhibited the CEmediated recruitment of all cofactor peptides by ER, BZA inhibited the CE-mediated recruitment of only some of the evaluated peptides. Furthermore, in MCF-7 breast cancer cells, the combination of BZA with CE did not totally abrogate the transcriptional response of a subset of CE-responsive genes which were, in contrast, completely antagonized by raloxifene and lasofoxifene. Interestingly, the CE-regulated genes antagonized by all three SERMs were involved in cell cycle regulation and cell-to-cell signaling [START_REF] Berrodin | Differential biochemical and cellular actions of Premarin estrogens: distinct pharmacology of bazedoxifeneconjugated estrogens combination[END_REF][START_REF] Chang | Gene expression profiling studies of three SERMs and their conjugated estrogen combinations in human breast cancer cells: insights into the unique antagonistic effects of bazedoxifene on conjugated estrogens[END_REF]. Subsequent studies of differential gene regulation by TSEC, estrogen or the SERM alone highlighted the importance of the promoter context on the activity of these ER ligands [START_REF] Wardell | Research resource: Transcriptional profiling in a cellular model of breast cancer reveals functional and mechanistic differences between clinically relevant SERM and between SERM/estrogen complexes[END_REF]. However, these studies only questioned the short term action of CE, BZA or TSEC using in vitro models.

Here, we used an in vivo model to show that BZA acts as an antagonist after acute treatment in the liver, but displays agonistic effects in the liver following chronic exposure. This underlines the importance of the time-and tissue-specific action of BZA, which induces a very similar action to that of CE or E2 following chronic treatment. Our transcriptional analyses also revealed a group of genes for which CE and BZA cooperatively regulated their expression under chronic treatment. This means that the effect of CE+BZA cannot be simply extrapolated from its short-term action and suggests that additional pathways facilitating combined agonist/antagonist action must exist. It was previously proposed that, in addition to the competitive inhibition of BZA on CE, BZA and CE could also cooperatively activate gene transcription with one ER monomer bound to CE and the other one occupied by BZA [START_REF] Liu | Cooperative activation of gene expression by agonists and antagonists mediated by estrogen receptor heteroligand dimer complexes[END_REF]. High-throughput sequencing of chromatin immunoprecipitation experiments (ChIP-seq) performed on livers from mice subjected to acute treatment with E2 led us to recently show that the ERα cistrome (all of the ER binding sites in the genome) in mouse liver has unique properties [START_REF] Palierne | Changes in Gene Expression and Estrogen Receptor Cistrome in Mouse Liver Upon Acute E2 Treatment[END_REF]. In order to acquire novel insights into the specific mechanisms involved in the shift of action of BZA from antagonism to agonism, it would therefore be of major interest to compare the liver cistrome of ERα in response to acute and chronic treatment with CE, BZA and CE+BZA. These experiments would question: i)

whether ERα bound to CE or BZA targets different/specific chromatin regions, which would explain the difference in gene regulation; ii) whether these cistromes vary according to the acute or chronic administration of these hormones, in relation to differences in gene regulation; and iii) whether the specific properties of the E2-bound ERα cistrome are conserved using these treatments. Interestingly, the cistrome of ERα bound to 4hydroxytamoxifen (OHT), another SERM, has been determined in MCF-7 cells and was found to be comparable with that of E2-bound ERα (with 60-75% similarity) [START_REF] Hurtado | FOXA1 is a key determinant of estrogen receptor function and endocrine response[END_REF], although this SERM had no agonist activity on gene transcription. It was therefore proposed that, in these cells, OHT-bound ERα is able to target the same sequences on chromatin (although with less efficiency than E2-bound ERα) but as an inactive complex or repressive form since OHT-bound ERα is able to recruit corepressors [START_REF] Shang | Molecular determinants for the tissue specificity of SERMs[END_REF]. Hence, the shift of the action of BZA from antagonism to agonism may have a limited impact on the cistrome of ERα and instead reflect a corepressor to coactivator exchange. The mass spectrometry analysis of proteins associated with ER on chromatin (ChIP-MS) when bound to these different ligands [START_REF] Mohammed | Endogenous purification reveals GREB1 as a key estrogen receptor regulatory factor[END_REF] would also generate important knowledge to further decipher the mechanisms of action of TSEC.

Finally, Mauvais-Jarvis and coworkers recently reported that BZA and TSEC exhibits estrogen-mimetic action with regard to glucose and energy homeostasis [START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF].

Interestingly, they reported that lipid oxidation and increased energy expenditure promoted by CE, BZA and TSEC involved different pathways as revealed by different target gene pattern in the liver for these ERα ligands. Thus, the shift reported here from antagonist to agonist activities of BZA in the liver, and potentially in other tissues, have undoubtedly contributed to the metabolic benefit of BZA alone or in TSEC that mimic those provided by estrogens in female mice on high fat diet.

In conclusion, these observations provide novel insights into the mechanisms underlying BZA action which can not only act as an agonist or antagonist in a tissue-specific fashion, but can also, in a given tissue such as the liver, be acutely antagonistic and chronically agonistic. This could help to explain, among other reasons, the reported beneficial effects of TSEC such as its favorable effects on glucidic and lipidic metabolism [START_REF] Barrera | Bazedoxifene and conjugated estrogen prevent diet-induced obesity, hepatic steatosis, and type 2 diabetes in mice without impacting the reproductive tract[END_REF][START_REF] Kim | Tissue-selective estrogen complexes with bazedoxifene prevent metabolic dysfunction in female mice[END_REF].

Figure legends 478 479 Figure 1 :

 4791 Figure legends

Figure 2 :

 2 Figure 2: Effect of acute administration of E2 and CE alone or in combination with BZA

Figure 3 :Figure 4 :

 34 Figure 3: Effect of acute administration of E2 and CE alone or in combination with BZA

Figure 5 :

 5 Figure 5: Effect Effect of chronic administration of E2 and CE alone or in combination

Figure 6 :

 6 Figure 6: Effect of chronic administration of E2 and CE alone or in combination with

Acknowledgments

The staff of the animal facilities and of the "Plateforme d'experimentation fonctionnelle" are acknowledged for their skillful technical assistance. We also thank M.J. Fouque and G.

Carcasses as well as J.J. Maoret and F. Martins for their excellent technical assistance and contribution to the qRT-PCR experiments carried out at the GeT-TQ Genopole Toulouse Facility. L. Fontaine and I. Raymond Letron at EVNT are also acknowledged for their help with the immunohistochemistry experiments.

Funding: This study was financially supported by Pfizer Pharmaceuticals, Inc., Pfizer IIR WI191216. This work was also supported by the INSERM, the Université de Toulouse III, the Faculté de Médecine Toulouse-Rangueil, the Institut Universitaire de France, the Fondation pour la Recherche Médicale, the Fondation de France, CNRS, the University of Rennes1 and La Ligue Contre le Cancer.


A Mayer

H Siebert

K D Mcdonald-Maier

Debug Support, Calibration and Emulation for Multiple Processor and Powertrain Control SoCs

The introduction of complex SoCs with multiple processor cores presents new development challenges, such that development support is now a decisive factor when choosing a System-on-Chip (SoC). The presented developments support strategy addresses the challenges using both architecture and technology approaches. The Multi-Core Debug Support (MCDS) architecture provides flexible triggering using cross triggers and a multiple core break and suspend switch. Temporal trace ordering is guaranteed down to cycle level by on-chip time stamping. The Package Sized-ICE (PSI) approach is a novel method of including trace buffers, overlay memories, processing resources and communication interfaces without changing device behavior. PSI requires no external emulation box, as the debug host interfaces directly with the SoC using a standard interface.

Introduction

Strong consumer demand for more refined automatic gearboxes and engines, combined with tough new emissions standards drive increased requirements for power train controllers. Significant adoption of direct injection Diesel technology in Europe has also lead to further increases in real-time demands. Migration from system-on-Printed Circuit Board (PCB) to single processor core System-on-Chip (SoC) has so far supported the corresponding rise in system complexity. The new generations of SoCs, containing many active peripherals and now multiple processor cores are increasingly more difficult to program, especially for mission critical real-time systems such as automotive control.

Developers are increasingly overwhelmed by development challenges such that system reliability is decreasing. A recent study has shown that 77 percent of electronic failures in cars were due to software [START_REF] Jacobi | Software ist im Auto ein Knackpunkt[END_REF]. Detecting and correcting these bugs early in the product cycle before the customer discovers them prevents loss of reputation and customer loyalty, or even loss of life in safety critical applications. For complex systems like automotive power-train control it is of particular importance to understand and analyze the behaviour in all possible scenarios, in support high quality software and reliable products. With the right tools, developers can overcome the challenges, bringing a new world of exciting and dependable products on time and on budget. The development support's effectiveness is now a decisive factor when system developers choose between SoCs.

Rising development time and increased product failures provide clear motive for improved tools, as verification and development tasks after the first silicon is produced consume about half a system's development effort [START_REF]International Technology Roadmap for Semiconductors[END_REF]. Furthermore the US national institute of standards and technology has estimated that bugs and glitches cost the US economy alone approximately $59.9 billion a year. Increased testing and more effective debugging could reduce this by a third [START_REF]The economic impacts of inadequate infrastructure for software testing[END_REF].

System development has traditionally been aided by replacing production SoCs with special development devices or In-Circuit Emulators (ICE) [START_REF]The Nexus 5001 Forum™, Standard for a global embedded processor debug interface[END_REF][START_REF] Mayer | Debug Support for Complex System-on-Chips[END_REF][START_REF] Macnamee | Emerging on-chip debugging techniques for real-time embedded systems[END_REF]]. An ICE is intended to have similar behaviour as the production SoC but provide increased debug support resources. One approach to constructing ICEs is the Bond-Out chip (BO), which is realised by wire bonding internal nodes to additional external device pins, thus making the internal nodes visible to bench equipment such as logic analysers. BO based emulation techniques have a number of significant disadvantages: 1) Internal system nodes in the BO the must drive extra connections which results in changed its behaviour from the production SoC. 2) SoCs targeted at harsh environments have external pins limited to frequencies lower than the internal circuits [START_REF]International Technology Roadmap for Semiconductors[END_REF][START_REF] Mayer | Debug Support for Complex System-on-Chips[END_REF], preventing production speed real-time operation. 3) BOs are large and fragile, preventing them being used for applications like gearbox control where the controller is mounted within the gearbox. 4) BOs have a different footprint to production devices, forcing the development of two different printed circuit board layouts, each with many high speed wires. 5) Construction of a BO requires a custom mask set which is already expensive, and the cost rises aggressively with increased integration. The fundamental flaw of BO devices is that systems using BO based ICEs behave significantly differently to production systems. This has led to a steep decline in BO based development systems.

The now more relevant alternative to dedicated ICEs, is on-chip debug support. The on-chip debug support circuits provide development infrastructure for run and control of processors by external debugging tools [START_REF] Macnamee | Emerging on-chip debugging techniques for real-time embedded systems[END_REF]. Onchip hardware breakpoint triggers allow developers to halt processor cores when a defined program address is reached, enabling 'post-mortem' debugging. Some cores support watchpoints to stop them when data locations are accessed. The on-chip debug support based ICE solution is widely used, as the ICE behavior closely matches the production SoC with debug support disabled. Postmortem debugging has the disadvantage that developers are only able to get a good look at the system after it is halted, rather than while it is running

Mechanical systems

Mechanical systems require continuous control until they are safely shut down, which makes 'post-mortem' debugging impractical. Systems such as hard-disk drives and engines can be irreparably damaged if the controlling electronics are switched off or suddenly stopped by a processor's breakpoint. Many mechanical systems also require extensive calibration, i.e. tuning of control loop parameters after assembly and at run-time, making unobtrusive access to internal memories essential.

Multiple processors

Debugging systems with concurrency is seldom straightforward, but when multiple processors are unsynchronized development is especially challenging. Observation of shared variable accesses is critical to debugging such systems. Tracing with on-chip infrastructure to ensure temporal ordering of messages provides such observation, and fulfills the requirements for mechanical systems. Many high quality trace solutions already exist, such as the Nexus standard [START_REF]The Nexus 5001 Forum™, Standard for a global embedded processor debug interface[END_REF], however they fail to define the infrastructure required to guarantee the correct trace order.

For single processor core SoCs there is already a growing mismatch between circuit frequency and device pin frequency [START_REF]International Technology Roadmap for Semiconductors[END_REF], making external trace interfaces less feasible. For two cores the trace data doubles making the problem worse. Furthermore developers only require key pieces of information not millions of cycles of unrelated trace.

The presented solution tackles the problem on two fronts. At the architecture level, complex triggers qualify or 'filter' the trace down to only the required messages. At the technology level, new techniques have been developed to store the trace within the device package and provide additional emulation resources.

Multi-core debug solution

The Multi-Core Debug Solution MCDS is a trigger and trace logic block including trace qualification and compression. The MCDS block shown by figure 1 is placed at each processor core, therefore trace from one or several cores can be recorded in parallel. Scalable time stamping not shown in the figures ensures that all messages are stored in correct temporal order. The time stamping allows a time resolution down to cycle level. For heterogeneous cores only the adaptation logic differs, making the solution sufficiently flexible for design reuse. The system centric approach supports tracing of on-chip multi-master buses and general system states, independently from the processor cores.

Figure 1. MCDS trace and trigger block

The trigger resources are implemented for the program and data accesses and are further enhanced using statemachines based on counters. They are compact but effective, especially with cross-triggering as shown by figure 2. Combining triggers from multiple sources is undefined by most previous solutions including the Nexus standard [START_REF]The Nexus 5001 Forum™, Standard for a global embedded processor debug interface[END_REF]. For example should a trigger stop one or multiple cores? The best solution is to let the developer decide by providing a reconfigurable break and suspend switch. When processor cores can be stopped the multicore break and suspend switch is vital, as it halts synchronized cores without excessive slippage. The switch manages the response to both on-chip and external trigger inputs. The Package Sized In-circuit emulator (PSI) is a new approach to in-circuit emulation. With contemporary ICEs an external box contains some of the resources, however with PSI everything is included within the chip package. Integrating large calibration overlay memories and trace memories within a high volume SoC is not cost effective, as they are left idle in the final product. For high volume SoCs PSI overcomes these costs by moving the resources into a development specific part. Low volume SoCs do not justify the extra design effort for a development part, so the extra resources can be included in every chip as with conventional solutions. Crucially PSI uses the same footprint as the production SoC, a significant difference compared to bond-out based ICEs. A common foot print eliminates the vast effort of designing then debugging two versions of a system, including its PCB. A range of communication interfaces are possible with PSI, although Universal Serial Bus (USB) provides a straightforward connection to the debugging host computer, avoiding unwieldy proprietary interfaces. PSI allows full emulation support in the target system, even under extreme form factor constraints, allowing use within a gearbox. It is even possible to avoid a dedicated debugger interface altogether and use spare bandwidth on any accessible system interface.

Adaptation

A range of construction techniques have been developed for PSI, including both one and two chip versions. Maintaining consistent behavior between production and development SoCs is paramount, especially for analogue circuits, so the same manufacturing technology and flow are used for both development and production SoCs. For single chip PSI a development specific integrated circuit is created, where the entire production SoC layout, including bonding pads is treated as a hard macro. Single chip PSI is so far realized as an emulation side booster, which is a region located at the edge of the SoC macro as shown by figure 3. The main disadvantage of any solution requiring extra mask sets is that for future technologies cost may be prohibitive.

Implementation

The emulation side booster concept has been realized for the TC1796 power train controller SoC manufactured in 0.13µm technology. Figure 5 shows the packages used for the TC1796 production part and the corresponding TC1796 development part. The development SoC includes an extra 512Kbytes of SRAM, a USB 1.1 peripheral and a further processor core to service debug requests. Both versions of the SoC are interchangeable with complete transparency to the application system, while significantly boosting development support.

Figure 2 .

 2 Figure 2. Multiple core cross trigger unit 5 Package sized ICE

Figure 3 .

 3 Figure 3. Single chip emulation extensionPSI with two chips adds extra development resources using an emulation extension chip. The emulation extension chip can either take the form of a carrier chip to which the production SoC is bonded, or as a booster chip attached to the production SoC. The extension chip PSI approaches are shown by figure4. One advantage of the two chip approach is that the development specific chip could be reused across a product range.

Figure 4 .

 4 Figure 4. Two chip emulation extension

Proceedings of the Design, Automation and Test in Europe Conference and Exhibition (DATE'05) 1530-1591/05 $ 20.00 IEEE

Proceedings of the Design, Automation and Test in Europe Conference and Exhibition (DATE'05)

Acknowledgements A.B.T. Hopkins provided valuable support and feedback during the writing of this paper. The research of the author K.D. McDonald-Maier is supported in part through EPSRC grant GR/S13361/01.

Figure 5. Production and PSI devices

The USB 1.1. interface has significant software overhead, but the system is unaffected as an extra PCP2 processor core is integrated to run the supplied driver. The extra processor can also be used for performance monitoring and consistency checking, and provides a new programmable tool not found in previous ICEs. Furthermore a robust calibration system is implemented using the universal measurement and calibration protocol XCP [START_REF] Lemon | Introduction to the Universal Measurement and Calibration Protocol XCP[END_REF] over USB, or for extreme form factors an existing CAN interface. The only equipment needed besides the development SoC is a galvanically decoupled USB cable and the supplied XCP driver. For control actions requiring low latency the JTAG based interface's 2µs latency is more suitable than the 3ms of the USB interface. Cold booting of the extra processor is supported by having a separate power connection for the emulation memory.

Application development and calibration

The TC1796ED provides greatly increased flexibility over conventional parts due to its significant extra resources and configurability. During testing developers found using the 512kByte emulation RAM to hold the program highly beneficial for initial development. Not only does this avoid continuous reprogramming of the large 2 MByte program flash memory, but unlimited software breakpoints are possible, as with development of desktop applications. The emulation RAM is segmented into 64 kByte blocks for use as either overlay or trace memory. An address-mapping block resides on the production chip. It allows memory access redirection for up to 16 address ranges, with individual block sizes from 1 kByte to 32 kBytes of the overlay Emulation RAM. The access timing matches the flash memory being overlaid, ensuring consistent behavior. The overlay memory is divided into two pages that can be swapped atomically by a single control access. The large size of the RAM is determined by the automotive specific flash overlay requirements for calibration. The trace features used for system debug of mission critical real-time systems require just a fraction of that. The on-chip time stamping maintains temporal message ordering for all program and data flows including the full data activity of the multimaster busses.

Conclusion

The combination of MCDS and PSI provide the features developers need to manage the rising challenges of using complex SoCs within complex systems. The functionality of PSI scales well with technology advancement as it uses the same manufacturing flow as the production SoC. The main limitation of current PSI solutions is that extra mask sets will be more expensive in the future, but not prohibitive for a few more generations. There is however a smooth path then to integrate PSI part on each production SoC in particular for the case when no large calibration overlay memory is required. Selective integration of the emulation side booster using only a single set of masks is one alternative solution. Selective integration of PSI is an area of active research, and has been possible for a small region on one side of the SoC. No matter which implementation used, PSI with MCDS boosts development support firmly into the multiple processor core era.


Mathieu Cladière
email: mathieu.cladiere@agroparistech.fr

Even Grégoire Delaporte

Le Roux

Valérie Camel

of pesticides, mycotoxins, process-induced toxicants and packaging contaminants in tea

Keywords: Acrylamide, UHPLC-TOF-MS, C18-PFP, food safety, multi-residue analysis

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Food safety remains an everyday challenge toward the globalization of production and sometimes the lack of traceability of products. There are numerous sources of chemical contaminants in food products, ranging from the raw material itself (pesticides, mycotoxins and veterinary drugs in case of food of animal origin), its transportation, its processing (process-induced toxicants), and finally its packaging (migrants). Most analytical strategies, developed by laboratories and food safety authorities around the world, rely on the carrying out of several targeted analyzes in order to cover this broad range of contamination sources and quantify as many contaminants as possible. Such a multi-analysis approach is both very costly and time consuming; on top of that, the environmental footprint of the analysis is increased by the use of larger amounts of solvent and reagent compared with the singleanalysis approach. As a result, recent reviews have underlined the need for multi-class methods capable of analyzing a large number of compounds in a single analysis [START_REF] Antignac | Mass spectrometry-based metabolomics applied to the chemical safety of food[END_REF][START_REF] Castro-Puyana | Metabolomics approaches based on mass spectrometry for food safety, quality and traceability[END_REF]. Indeed, the current technology based on liquid chromatography coupled to mass spectrometry (LC-MS) offers the feasibility of developing new approaches thanks to the increasing sensibility and possibility of full scan analysis using high resolution apparatus. As a consequence, few multi-class methods have emerged in recent years [START_REF] Danezis | Multi-residue analysis of pesticides, plant hormones, veterinary drugs and mycotoxins using HILIC chromatography -MS/MS in various food matrices[END_REF][START_REF] Jin | Development and validation of a multiclass method for the quantification of veterinary drug residues in honey and royal jelly by liquid chromatography-tandem mass spectrometry[END_REF][START_REF] Petrarca | Multiclass pesticide analysis in fruit-based baby food: A comparative study of sample preparation techniques previous to gas chromatography-mass spectrometry[END_REF]). Yet, although these methods are able to quantify hundreds of contaminants simultaneously, they generally focus on only one or two classes of contaminants with close physicochemical properties. To the best of our knowledge, only one study deals with the analysis of various classes of contaminants including migrants from packaging and process-induced toxicants, but it focuses on LC-MS optimization without assessing efficiency of sample treatment [START_REF] Pérez-Ortega | A feasibility study of UHPLC-HRMS accurate-mass screening methods for multiclass testing of organic contaminants in food[END_REF]. The authors pointed out the difficulties of this approach since the structural diversity of targeted compounds leads to heterogeneous behaviors during the LC-MS analysis, both in terms of retention and matrix effects. Consequently, developing a multi-class method capable of analyzing contaminants having a wide-range of chemical structures remains a challenge, particularly in real food matrices due to their complexity. To reach this objective, tea has been chosen as development matrix for four main reasons. Firstly, this is the most consumed manufactured beverage in the world with 4.8 million tons (of tea leaves) produced in 2013, increasing by 5% per year since 2008 [START_REF] Chang | World tea production and trade. Current and future development[END_REF]; medium term outlooks suggest a slightly higher increasing of tea consumption (black or green) until 2023. Secondly, tea is produced in remote countries where contamination risks may be difficult to manage; as a consequence, monitoring and regulatory control analyzes regularly show the presence of chemical contaminants (especially pesticide residues) exceeding their European maximum limits [START_REF] Efsa | Chemicals in food 2016: Overview of selected data collection[END_REF]. Thirdly, tea can be analyzed in both solid and liquid states, through tea leaves or brew, which is an interesting feature when developing analytical methods for food matrices. Finally, tea is a complex food product regarding its organic composition with a wide variety of phytochemicals (such as antioxidants, aroma compounds, xanthins and alkaloids) which commonly bring strong matrix effects during analysis, therefore making it an interesting real complex food matrix to consider.

This study reports the development and validation of a method for simultaneous extraction and quantification of multi-class contaminants (covering a wide range of chemical structures and properties) for both liquid and solid tea matrices. Until now, this is the first multi-class method covering four classes of food contaminants including pesticides, mycotoxins, process-induced toxicants and migrants from packaging. A total of 32 target compounds were carefully chosen in order to cover the diversity of classes and physicochemical properties encountered. As an illustration, for pesticides, organochlorinated, organophosphates, organosulfites, triazines, auxinic herbicides, neonicotinoids, benzoylureas, pyrazoles, dinitrophenols and carbamates have been considered; as far as we know, all these pesticide families are considered together for the very first time [START_REF] Eitzer | Interlaboratory Comparison of a General Method To Screen Foods for Pesticides Using QuEChERs Extraction with High Performance Liquid Chromatography and High Resolution Mass Spectrometry[END_REF][START_REF] Hou | A multi-residue method for the determination of pesticides in tea using multi-walled carbon nanotubes as a dispersive solid phase extraction absorbent[END_REF]. In addition, 4 mycotoxins, 2 process-induced toxicants (including acrylamide which has never been considered in any multi-residue method before) and 5 migrants from packaging have been examined. The challenge of our method lies in the different behaviors of these 32 compounds regarding extraction and chromatographic separation, in order to propose the best compromise and provide analytical performances in compliance with the European regulation on food contaminants (European Commission, 2005, 2006).

Materials and methods

Targeted contaminants

For developing our multi-class method, several target food contaminants were selected from different classes, namely process-induced toxicants (n=2), migrants from packaging (n=5), mycotoxins (n=4), herbicides (n=11), insecticides (n=6) and acaricides (n=4). The selection of these 32 compounds was based on two main criteria; their physicochemical properties to offer a broad range and a large diversity (i.e. hydrophobicity, aromaticity, functional groups) so as to be representative of other contaminants not considered here, and their relevance for tea. As an example, propargite (acaricide) has been quoted 11 times by the European Rapid Alert System for Food and Feed (RASFF) in 2016, leading to border rejections of black and green teas, while acetamiprid and imidacloprid (insecticides) were cited more than 40 times between 2012 and 2015.

The 32 compounds as well as their analytical information are listed in Table 1.

Analytical standards (100 µg/mL) for pesticides, mycotoxins, process-induced toxicants and labelled compounds acrylamide-d3, dimethoate-d6 and malathion-d6 (purity > 99%) were supplied by CIL Cluzeau (France).

Ochratoxin-d5, bisphenol A, F and S, BADGE, BFDGE and bisphenol A-d14 (purity > 99%) were provided by Sigma Aldrich (France).

Materials and reagents

Acetonitrile (ACN) (HPLC plus gradient, LC-MS), water, methanol (MeOH) and formic acid (FA) (all LC-MS grade) were purchased from Carlo Erba. Ultrapure water (Milli-Q ® ) was produced by an Integral 3 water purification system from Millipore ® . The compound used for MS calibration was Leucine Enkephalin (LC-MS grade), purchased from Waters ® . Magnesium sulphate (MgSO 4 ) and sodium citrate (NaCit) salts (analytical grade) were provided by VWR France. Analyzes of trace contaminants have been performed on a Waters® Acquity H-Class UPLC ® system, composed of a quaternary solvent manager pump (QSM), a refrigerated sample manager Flow-Through-Needle (SM-FTN) and a column oven, coupled to a Waters ® high resolution mass spectrometer with a Time of Flight analyzer Xevo ® G2-S ToF (UHPLC/MS-ToF). An electrospray ionization source was used in both positive (ESI + ) and negative (ESI -) modes.

Analysis conditions

Chromatographic conditions

Chromatographic separation was done on a column made of silica based particles bonded with C18pentafluorophenyl functions (C18-PFP) (dimensions were 150 x 2.1 mm; 2µm particles diameter, from ACE, provided by AIT, France). In addition to conventional hydrophobic interactions (provided by C18 chains), the PFP groups enable hydrogen bonds, - and dipole-dipole interactions, affording a higher capacity for retaining the highly polar compounds (such as acrylamide or acidic herbicides) than a regular C18-silica column.

MS analysis

Since different mobile phases were used for positive and negative ionization, analyzes were performed separately for both modes. All analyzes were done using the resolution mode (30,000 FWHM at 200 m/z) for a scan time of 0.5 s, with mass range between 60 and 800 m/z and data acquired in centroid. Internal calibration of ToF analyzer was performed with a continuous flow at 5µL/min of Leucine Enkephalin for one scan every 30 s during 0.1 s.

For ESI + the mobile phase was composed of water (A), ACN (B), both acidified with 0.1% FA, and MeOH (C), flowing at 0.4 mL/min. The gradient started at 100% A and reached 100% B in 10 min, this composition being kept for 6 min before switching to 100% C to rinse the system in 1 min, being hold for 5 min, returning back to 100% A in 1 min and finally equilibrating for 3 min, with a total run duration of 26 min. For ESI -, the mobile phase was composed of water buffered with 10 mM of ammonium formate (A) and MeOH (B) flowing at 0.3 mL/min.

The gradient started at 100% A and reached 100% B in 13 min, holding this condition for 7 min before turning back to 100% A in 1 min and finally equilibrating for 3 min, with a total run duration of 24 min. For both chromatographic methods the column was heated at 30°C. The optimized parameters for ESI + and ESI -are presented in Supplementary data, Table S1.

Based on the instrument factory settings, detection of acrylamide remained unsuccessful. Indeed, the ion path dedicated to discard neutral molecules before analysis (called "StepWave" by Waters ® , which is the ionic path between the source and the mass analyzer) proved to be the limiting step for small molecules (m < 90 m/z).

Therefore, its settings were set according to Waters ® instructions for extending the range of mass detected in a single run (60 -800 m/z) and ensuring acrylamide detection.

Quantification and quality controls

In order to select the best compromise for quantification of targeted contaminants in tea samples, two main quantification methods were considered: solvent calibration and matrix-matched calibration. Each time, classical external calibration was considered and compared with labelled molecules correction.

For external calibration, 11 standard solutions were prepared in a ACN/water mix (20/80 v/v) acidified with 0.1% FA, with concentrations ranging from 0.1 to 120 ng/mL for most compounds, except for a few molecules exhibiting lower sensitivity (namely hydroxymethylfurfural (HMF), deoxynivalenol (DON), bisphenol A (BPA) and bisphenol F (BPF)) with concentrations five times higher (from 0.5 to 600 ng/mL), as well as acrylamide (AA) with concentrations 10 times higher (1 to 1,200 ng/mL).

For labelled molecules correction, deuterated isotopes were used in addition to external calibration, either in positive mode (acrylamide-d3, dimethoate-d6, ochratoxin A-d5 and malathion-d6) and/or in negative mode (ochratoxin A-d5 and bisphenol A-d14). These five molecules were associated to the non-labelled analytes they are supposed to mimic according to their similarities and the closeness of their retention time. All labelled molecules were added before sample treatment in order to reach a concentration in the final extract of 40 ng/mL for dimethoate-d6, ochratoxin A-d5 and malathion-d6, 200 ng/mL for bisphenol A-d14 and 400 ng/mL for acrylamide-d3. Last but not least, for matrix-matched calibration, 8 calibration points were prepared directly in sample extract, with concentrations ranging from 2 to 80 ng/mL (with respectively the same multiplicative factors as for external calibration).

The analytical sequence was randomized and a mobile phase blank as well as a quality standard (standard solution containing all of 32 compounds at 16 ng/mL) were analyzed every 10 samples. No cross-contamination was detected during long sequences.

Data treatment

The entire data processing was done using open-source, freely available tools. Data files were first converted in mzXML with proteowizard [START_REF] Chambers | A cross-platform toolkit for mass spectrometry and proteomics[END_REF], and then processed with MZmine 2 (Pluskal, Castillo, Villar-Briones, & Oresic, 2010), using its "Targeted peak detection" module. When necessary, the instrumental drift along the analytical sequence was addressed by performing "All Loess Pool" correction using the Workflow4Metabolomics Galaxy interface [START_REF] Giacomoni | Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics[END_REF][START_REF] Van Der Kloet | Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping[END_REF]. Briefly, analytical drift was modelled based on the quality standard samples, and then the signal was corrected for all samples according to their injection order. Corrected data were then processed with Microsoft Excel.

Tea samples and brew preparation

Tea leaves used for optimization of extraction procedures came from a bulk green tea bought in a tea shop in Paris (France). Tea brew was prepared in accordance with the ISO 3103:1980 norm ensuring a reproducibility of infusion (International Organization for Standardization, 1980). Briefly, 200 mL tap water were heated at 100°C and infusion was prepared using 2 g of tea leaves weighted in a tea filter and then put in contact with hot tap water for 6 min. Blank sample was performed under the same procedure but without tea leaves, in order to investigate possible contamination from tap water, tea filter, preparation or extraction protocols; no contamination was detected along the analytical process. Non-spiked tea samples were also systematically considered in order to check the absence of native target contaminants (only native HMF could be found in our tea samples), to avoid overestimation of recoveries for the spiking.

Sample treatment protocols

Tea brew

Two different sample preparation methods were evaluated for tea brew. These two methods were already developed by other authors as mentioned below, but they needed to be adapted here to match our initial chromatographic conditions (i.e. mobile phase: 100% water) and our tea matrix.

The first method is based on liquid-liquid extraction (LLE) commonly used for multi-residue analyzes in food products, and adapted from [START_REF] Mol | Toward a Generic Extraction Method for Simultaneous Determination of Pesticides, Mycotoxins, Plant Toxins, and Veterinary Drugs in Feed and Food Matrixes[END_REF]. Briefly, 2 mL of tea brew were mixed with 4 mL of ultrapure water, and 3 mL of ACN were added with 2 g of MgSO 4 and 1 g of NaCit. The sample was then agitated during 1 h before centrifugation at 3,000 g for 5 min. Aliquot (1 mL) of supernatant was sampled and diluted with 4 mL of water. Finally, 0.5 mL was sampled and filtered at 0.2 µm with a syringeless filter (miniuniprep G2, Whatmann) before analysis.

The second sample treatment tested, named dilute and shoot (D&S), comes from metabolomic approaches [START_REF] Tengstrand | A concept study on non-targeted screening for chemical contaminants in food using liquid chromatography-mass spectrometry in combination with a metabolomics approach[END_REF]. It is intended to favor the analysis of numerous targeted organic compounds in complex matrices. In our case, 2 mL of tea brew were diluted with 6 mL of pure water plus 2 mL of ACN, both acidified with 0.1% FA, and agitated during 5 min. Then 0.5 mL of the mixture was sampled and filtered at 0.2 µm with a syringeless filter (mini-uniprep G2) before analysis.

Tea leaves

Tea leaves were crushed with a pestle and a mortar in order to obtain a homogenous powder. Firstly the extraction protocol described by [START_REF] Mol | Toward a Generic Extraction Method for Simultaneous Determination of Pesticides, Mycotoxins, Plant Toxins, and Veterinary Drugs in Feed and Food Matrixes[END_REF] (using water and acetonitrile containing formic acid -"proposed method A") was chosen. This method derives from QuEChERS extraction protocols that proved their efficiency for multiresidue analyses in food samples (recoveries between 80 and 110%) [START_REF] Dong | Modified QuEChERS combined with ultra high performance liquid chromatography tandem mass spectrometry to determine seven biogenic amines in Chinese traditional condiment soy sauce[END_REF][START_REF] Dzuman | Multi-analyte high performance liquid chromatography coupled to high resolution tandem mass spectrometry method for control of pesticide residues, mycotoxins, and pyrrolizidine alkaloids[END_REF], except that the dispersive solid-phase clean-up step has been removed to avoid losses of targeted compounds. In addition, considering the low sensitivity and high matrix effects for some compounds, changes were required. In particular, an evaporation step was needed and acidified ACN was selected to recover the dry residue as inspired by [START_REF] Cotton | High-Resolution Mass Spectrometry Associated with Data Mining Tools for the Detection of Pollutants and Chemical Characterization of Honey Samples[END_REF]. Since this solvent was unable to recover fumonisins B1 and B2, two more options were further investigated to improve the efficiency of the extraction: 1) increasing the percentage of FA or 2) adding MeOH to the mixture (Hans G. J. [START_REF] Mol | Toward a Generic Extraction Method for Simultaneous Determination of Pesticides, Mycotoxins, Plant Toxins, and Veterinary Drugs in Feed and Food Matrixes[END_REF]. The first option led to strong matrix effects for acrylamide without improving fumonisins recovery. Therefore a mixture of ACN/MeOH (90/10 v/v) acidified with 0.1% FA was finally chosen as extracting solvent.

Finally, 5 mL of ACN/MeOH (90/10 v/v) mixture acidified with 0.1% FA were added to 1 g and agitated during 1 h before centrifugation at 3,000 g for 5 min. Then, the supernatant was collected and an aliquot (1 mL) was evaporated to dryness under a gentle stream of nitrogen. The extract was further reconstituted in 0.2 mL of ACN + 0.1% FA. Then 0.8 mL of ultrapure water with 0.1% FA was added in order to reconstitute 1 mL of final volume. Finally, 0.5 mL were sampled and filtered at 0.2 µm using syringeless filters (mini-uniprep G2) before analysis.

Method validation

Instrumental limits of detection and quantification (LOD, LOQ) were evaluated based on repeatability and reproducibility of analyzes of standard solutions at different low levels (from 0.1 to 100 ng/mL). For each level, 3 replicates were analyzed 5 times. Relative standard deviation (RSD) was plotted against concentration for each compound, and LODs or LOQs were then graphically assessed when RSDs reached 30% or 10% respectively according to IUPAC recommendation [START_REF] Currie | Nomenclature in evaluation of analytical methods including detection and quantification capabilities (IUPAC Recommendations 1995)[END_REF][START_REF] Thompson | Harmonized guidelines for single-laboratory validation of methods of analysis (IUPAC Technical Report)[END_REF]. The overall method limits of quantification (MLOQs) were determined according to the guideline from the SANTE document of the European Commission -Directorate General for Health and Food Safety (2015) by the lowest spiked level reaching the following criteria: recovery 70-120% and RSD <20%.

Trueness and precision were evaluated based on triplicates spiked with a mixture solution of all investigated contaminants. Spiking levels were established in accordance with the European regulation for some contaminants (such as maximum residue limits for pesticides) or the lowest concentration expected for other contaminants. Thus, for tea brew, spiking levels were 10 ng/mL for level 1 and 100 ng/mL for level 2 for most of compounds, and 50 ng/mL (level 1) and 500 ng/mL (level 2) for the less sensitive compounds (AA, HMF, DON, BPA, BPF). For tea leaves, three levels were set: 10, 50 and 100 µg/kg for most of compounds; 50, 250 and 500 µg/kg for HMF, DON, BPA and BPF; 100, 500 and 1,000 µg/kg for AA. Spiking was performed with 100 µL of standard solution in ACN followed by equilibrium overnight. For non-spiked samples, 100 µL of ACN was added. The trueness was considered acceptable for recoveries between 70 and 120%, and precision (assessed by RSD) lower than 20% was required (European Commission -Directorate General for Health and Food Safety, 2015; H. G. J. Mol, Reynolds, Fussell, & Štajnbaher, 2012).

Results and discussion

Choice of analytical conditions and validation

Chromatographic separation

The first challenge for the chromatographic separation was the retention of acrylamide, since it is a very small and highly polar molecule (log Kow = -0.67). This probably explains why acrylamide has never been considered in a multi-residue approach, as its physicochemical properties are too far from those of the other contaminants.

A preliminary test performed on a Hypersil C18 Gold column (150x2.1 mm and 2 µm particles, Thermo Fisher Scientific) gave a retention factor (k) value of 0.33, showing insufficient acrylamide retention, probably due to the fraction of ACN in the extract (20%) that was needed to avoid severe losses of hydrophobic compounds upon extract filtration (PTFE filter). Facing the impossibility to change the fraction of ACN, the only choice was to change the stationary phase of the column. Therefore the C18-PFP phase, combining the strength of C18-chains (hydrophobicity) and PFP-groups (hydrogen bonds, dipole-dipole and - interactions) and affording possible enhanced retention of polar compounds, has been chosen. To date, while some studies combined C18 and PFP phases using two successive columns in LCxLC applications (Mena-Bravo, Priego-Capote, & Luque de Castro, 2016), only two applications dealing with a C18-PFP column have been published yet, for analyzes in rat plasma [START_REF] Zgair | Development of a simple and sensitive HPLC-UV method for the simultaneous determination of cannabidiol and Δ9-tetrahydrocannabinol in rat plasma[END_REF] and markers of lung cancer in human serum [START_REF] Klupczynska | Study of early stage non-small-cell lung cancer using Orbitrap-based global serum metabolomics[END_REF]. Thus, the potential of this new stationary phase for the separation of multi-class contaminants in food samples is described here for the first time. Retention tests for acrylamide on C18-PFP with the previously mentioned conditions revealed a k value about 1.16, showing a significant enhancement of acrylamide retention on this stationary phase, still operating in a reversed phase mode. Such a retention factor above 1 opens new perspectives for the separation of acrylamide from the very first matrix compounds eluting with the dead volume (dead time near 0.6 min here -see Figure 1). Dealing with highly polar compounds is an important challenge for multi-class analysis as pointed out by Pérez-Ortega et al., who faced the co-elution of most polar compounds (among hundreds of targeted contaminants) with the dead volume upon analysis using a conventional C18-silica stationary phase, resulting in poor analytical performances [START_REF] Pérez-Ortega | A feasibility study of UHPLC-HRMS accurate-mass screening methods for multiclass testing of organic contaminants in food[END_REF]. New combined phases such as C18-PFP may represent key tools to solve retention problems of very polar compounds in multi-class contaminants analysis on reversed phase columns. The second challenge for the chromatographic separation is to ensure a good distribution of compounds along the analysis to reduce the probability of co-elution of compounds (with associated potential interferences) as highlighted by [START_REF] Pérez-Ortega | A feasibility study of UHPLC-HRMS accurate-mass screening methods for multiclass testing of organic contaminants in food[END_REF]. Such a good separation of compounds is particularly crucial for very complex matrices like food products since they contain several thousands of molecules. Figure 1 displays the distribution of compounds all along the chromatographic run, and the effective separation of targeted contaminants from the major ions of the BPI of tea extracts. Limiting co-elution of targeted contaminants and major compounds (such as polyphenols, caffeine, amino acids) of tea may play a key role in reducing matrix effects as discussed below.

MS analysis

Table 1 displays some information about the 32 targeted compounds such as their class, log Kow, retention time and quantification ion selected. In ESI + , most of compounds where analyzed using [M+H] + ion; in the case of aldicarb, BADGE and BFDGE, the most abundant ion was [M+Na] + adduct. For propargite, although [M+Na] + adduct was still the most abundant, a fragment was used instead for quantification since the [M+Na] + adduct signal showed interfering ions. In ESI -, most of compounds were analyzed using [M-H] -ion, except some acidic herbicides for which fragmentation occurred (in that case, the most abundant and specific fragment was selected for quantification). This fragmentation was suspected to occur in the StepWave which is a specificity of some Water ® mass spectrometers, as the energy involved to curve the trajectory of ions is higher than the energy needed to fragment some molecules (3 eV) leading to in-instrument fragmentation. Therefore, the intensities of these fragments are specific of the instrument we used and may not be as intense on other HRMS analyzers set in full scan mode.

Instrumental performances

Table 1 shows instrumental LODs and LOQs for our targeted contaminants using our LC-HRMS system. LOQs range from 0.1 ng/mL for BPS to 50 ng/mL for BPF. Generally speaking, for most investigated contaminants, our estimated LOQs are higher than LOQs mentioned in the literature for targeted analytical methods. For example a recent study reported LOQ as low as 5 ng/mL for acrylamide in standard solution while the current method only reaches 51.5 ng/mL [START_REF] Troise | Quantitation of Acrylamide in Foods by High-Resolution Mass Spectrometry[END_REF]. For pesticide compounds the gap is tighter since most of recent studies deal with multi-residue analysis, except for acidic herbicides because of the fragmentation of those compounds in our instrument (LOQ ranging from 4.6 to 19.4 ng/mL) [START_REF] Hou | A multi-residue method for the determination of pesticides in tea using multi-walled carbon nanotubes as a dispersive solid phase extraction absorbent[END_REF]. The slightly higher LOD and LOQ values for our method were expected since they are linked to the compromise required for multi-class analysis of contaminants exhibiting wide differences in their physicochemical properties, meaning that individual optimization of instrumental conditions (LC and MS) is impossible.

Sample treatment recoveries

Tea brew

For tea brew, two sample treatments commonly used for multi-residues analyzes were compared, namely LLE and D&S. Considering the moderate matrix effects observed, quantification was performed using labelled molecules correction here (matrix-matched calibration was not needed).

The percent of the 32 compounds in the different recovery ranges for LLE and D&S at two spiking levels (10 and 50 ng/mL for most compounds) are displayed in Figure 2, while the complete results for recoveries and RSDs are gathered in supplementary Data Table S2. Based on guidelines for multi-residue analysis proposed by [START_REF] Mol | Guidelines for the validation of qualitative multi-residue methods used to detect pesticides in food[END_REF] and the European Commission (European Commission -Directorate General for Health and Food Safety, 2015), the recovery range should be 70 -120% and the precision (RSD) lower than 20% in order to validate quantification of compounds. In the case of multi-residue analysis, recoveries lower than 70% are acceptable for some compounds provided that RSDs are low (European Commission -Directorate General for Health and Food Safety, 2015). With the D&S method, all compounds were detected at the lowest level, while 80 and 83% of target compounds for levels 1 and 2 respectively met the quantification criteria. The percentages were much lower for LLE method with 33% for level 1 and 60% for level 2. Surprisingly, whatever the level considered, tolfenpyrad and propargite were not recovered by LLE despite their hydrophobicity (log K ow > 5); on the opposite, both compounds reached 86 and 92% recoveries at 10 ng/mL using the D&S method. No similar results or explanation was found in the literature. Nonetheless, considering the European RASFF alerts for tea, these two pesticides are commonly cited so that their quantification at low concentrations is crucial. D&S method led to some overestimations (R > 120%) especially for fumonisins B1 and B2 with respectively 178 and 161%, possibly due to matrix effects since similar signal enhancement was found in tea leaves (Figure 3) and reported in the literature [START_REF] Zhang | Multi-mycotoxins analysis in Pheretima using ultra-high-performance liquid chromatography tandem mass spectrometry based on a modified QuEChERS method[END_REF].

The repeatability of extraction, based on triplicates per level, revealed that for level 1 using D&S preparation, 90% of compounds have an acceptable RSD (<20%), when this value dropped to 60% for LLE. For D&S, only HMF, acrylamide and 2,4-D showed RSDs higher than 20% owing to native contamination for the former and a signal close to the quantification limits of overall method for the latter. For level 2, 96% of compounds met the requirement of repeatability for D&S, but only 79% in the case of LLE. At last, considering the overall results, the D&S method seems more appropriate for contaminants quantification in tea brew.

Tea leaves

 Matrix effects

Matrix effects were determined based on comparison between external calibration and matrix-matched calibration.

The ratio of slopes from both calibration curves (external / matrix-matched), shown in Figure 3, is informative on the presence of matrix effects for ESI + and ESI -. Based on these results, 8 compounds (25% of target contaminants) do not undergo significant matrix effects (essentially in ESI -), 17 compounds (around 50%) present low matrix effects (ratios between 0.6 and 1.4), while for the remaining compounds strong matrix effects were observed, mainly with signal suppression. Only fumonisins B1 and B2 (ESI + ) and 2,4,5-T (ESI -) revealed strong signal enhancement. According to our results no correlation between matrix effects and retention time was observed. These results are close to those reported by [START_REF] Mol | Toward a Generic Extraction Method for Simultaneous Determination of Pesticides, Mycotoxins, Plant Toxins, and Veterinary Drugs in Feed and Food Matrixes[END_REF] for other types of food (feed, maize, milk) on 172 analytes showing more intense signal reductions for methanol extraction than for acetonitrile. Signal enhancement for fumonisin B1 was also reported by [START_REF] Danezis | Multi-residue analysis of pesticides, plant hormones, veterinary drugs and mycotoxins using HILIC chromatography -MS/MS in various food matrices[END_REF] for most of foods studied (between 163 and 175% of standard signals). Our results are in agreement with [START_REF] Dzuman | Multi-analyte high performance liquid chromatography coupled to high resolution tandem mass spectrometry method for control of pesticide residues, mycotoxins, and pyrrolizidine alkaloids[END_REF] who reported 65% overall signal suppression for hundreds of contaminants in tea using a QuEChERS approach.

 Recoveries

The recoveries were determined based on three different calibration methods: external standard, labelled molecules correction and matrix-matched calibration.

With the use of labelled molecules, in order to correct the extraction losses and matrix effects, the 32 molecules were corrected by the most relevant labelled molecules of our mix (close retention time and related physicochemical properties). In that case, our results underline decreases of overall recoveries as compared to the use of external calibration. Hence, at 10 and 50 µg/kg only 38% of molecules meet the requirement for recovery (70-120%) for external calibration, and this percentage drops respectively to 28 and 31% at 10 and 50 µg/kg using labelled molecules correction. This drop is surprising since labelled correction (also called isotope dilution) is often used for quantification of contaminants in various food matrices (European Commission -Directorate General for Health and Food Safety, 2015). It has been attributed to strong matrix effects in ESI -analyzes due to the absence of clean-up. Indeed, ochratoxin A-d5 undergoes a strong signal enhancement in negative mode (value ratio: 2.2) which affects quantification of compounds after labelled correction. Unsurprisingly, the correction of labelled molecules was only efficient for the corresponding non-labelled molecules and, therefore, for matrixmatched calibration we decided to avoid labelled correction for other molecules.

In the case of matrix-matched calibration, recoveries were in accordance with results reported by Kaczyński et al. for 300 pesticides in fish tissues [START_REF] Kaczyński | Multiclass pesticide residue analysis in fish muscle and liver on one-step extraction-cleanup strategy coupled with liquid chromatography tandem mass spectrometry[END_REF] or by Mol et al. for 258 molecules in different types of food (Hans G. J. [START_REF] Mol | Toward a Generic Extraction Method for Simultaneous Determination of Pesticides, Mycotoxins, Plant Toxins, and Veterinary Drugs in Feed and Food Matrixes[END_REF], with around 63-78% of molecules within the recovery range 70-120% (see detailed results in Table 2). Only six molecules (19%) were not detected at the first spiking level: fumonisins B1 and B2 and propargite (10 µg/kg), BPA and BPF (50 µg/kg) and acrylamide (100 µg/kg), owing to a reduced sensitivity of the overall method for these contaminants. Fortunately, BPA, BPF and acrylamide were recovered with satisfying recoveries from spiking level 2 (250 and 500 µg/kg). On the opposite, fumonisins B1 and B2 as well as propargite exhibited recoveries lower or close to 50% even at the highest spiking level (Table 2). At last, the repeatability for the 32 molecules was acceptable since 72% of compounds have RSD lower than 20%.

The high RSD values found for BADGE and BFDGE result from matrix compounds competition for Na + adducts, and in the case of HMF it is attributed to the native presence of this molecule and its isomers at "high" concentration ( 265 µg/kg) in tea leaves (Table 2).  Analytical performances The MLOQs determined in accordance with the European guidance document (European Commission -Directorate General for Health and Food Safety, 2015) clearly show that our method performances are sufficient to ensure the compliance of a tea sample with the maximum residue limits (MRLs) fixed by the European Commission (European Commission, 2005). These results may open routine analysis field to broad-scale multiclass methods within the next years. Among the lowest MRLs set for ametryn, tolfenpyrad and fenoprop at 10 µg/kg of tea leaves, only tolfenpyrad do not meet the quantification requirement with a recovery around 45% and RSD of 11%. However, according to the European guidance document, such performances are still acceptable in the case of multi-residue methods (European Commission -Directorate General for Health and Food Safety, 2015). Finally, 69% of targeted molecules could be quantified at concentrations equal to or lower than their MRLs or usual levels in tea for non-regulated compounds (European Commission, 2005, 2006), and additional 22% could be detected but not quantified without labelled correction (recoveries below 70% or above 120%). As an example, fenoprop and ametryne were correctly quantified at 10 µg/kg (respective recoveries: 76.4 and 89.7% and RSD <20%) while recovery for tolfenpyrad (about 45%) should require correction before quantification. For molecules with low concentration limits, improvement of our method would be to add their corresponding labelled molecule to ensure a correct quantification at low levels.

Finally, despite the large diversity of the 32 selected compounds coming from 4 different classes of contaminants, our analytical method displays equivalent performances than recent multi-residue methods dedicated for hundreds of compounds belonging to only 1 or 2 classes.

Conclusion

For the very first time, we have developed an analytical method dedicated to the simultaneous determination of food contaminants belonging to 4 different classes (pesticides, mycotoxins, process-induced toxicants and migrants from packaging) and exhibiting extremely different physicochemical properties. This method, based on metabolomics sample treatment and a new liquid chromatographic column stationary phase coupled to high resolution mass spectrometry, has been validated on 32 target contaminants, ranging from highly polar acrylamide (log K ow = -0.67) to less polar tolfenpyrad (log K ow = 5.61), in both tea brew and leaves. All these molecules could be detected and correctly quantified at trace levels (near µg/kg in tea leaves or µg/L in tea brew) generally below their respective regulation limits. Only fumonisins B1 and B2 could not be quantified at any concentrations assessed in tea leaves due to low recoveries for these molecules, while quantification was correct at 10 µg/L in tea brew. Matrix-matched calibration was required to hinder strong matrix effects for several molecules for tea leaves while only labelled correction was needed for tea brew (lower matrix effects). Our method can be considered as a new step beyond current multi-residue analyzes, and its applicability to other food matrices would be valuable to be investigated in a near future. This research did not receive any specific grant from funding agencies in the public, commercial, or non-profit sectors.

Figure 1 :

 1 Figure 1 : Base Peak Ion chromatogram (BPI) of tea leave extracts along with signal intensity and retention of targeted contaminants in ESI + and ESI-

Figure 2 :

 2 Figure 2: Percentage of 32 target contaminants in recovery range for spiked tea brew. (Lv1: 10 ng/mL for most compounds except 50 ng/mL for AA, HMF, BPA, BPF, DON; Lv2: 100 ng/ml for most compounds except 500 ng/mL AA, HMF, BPA, BPF, DON)

Figure 3 :

 3 Figure 3 : Matrix effects observed upon analysis of tea leave extracts.

Table 1 : Targeted compounds along with their instrumental optimized parameters and method performances.

 1

							RT	ESI			LOD	LOQ
	N°	Name	Abbrev.	Class	Chemical family	log Kow	(min)	(+/-)	Ion	m/z	(ng/mL)	(ng/mL)
	1	Acrylamide	AA	Process-induced	Amide	-0.67	1.28 + [M+H] + 72.044	5	51.5
	2	Hydroxymethylfurfural	HMF	Process-induced	Furan	-0.09	3.11 + [M+H] + 127.039	2.5	7
	3	Deoxynivalenol	DON	Mycotoxin	Trichothecene	0.29	3.56 6.24	+ -	[M+H] + [M-H] -	297.133 295.119	2.5	18
	4	Imidacloprid	IMID	Pesticide (insecticide)	Neonicotinoid	0.57	5.05 + [M+H] + 256.059	0.5	19.5
	5	Dimethoate	DIME	Pesticide (acaricide)	Organophosphate	0.7	5.07 + [M+H] + 230.006	0.1	0.5
	6	Acetamiprid	ACET	Pesticide (insecticide)	Neonicotinoid	0.8	5.24 + [M+H] + 223.074	0.5	0.5
	7	Fumonisin B1	FB1	Mycotoxin	Fumonisin	-0.5	5.57 + [M+H] + 722.395	0.5	6.4
	8	Aldicarb	ALD	Pesticide (acaricide)	Carbamate	1.15	5.63 + [M+Na] + 213.0674	0.1	0.5
	9	Ametryn	AME	Pesticide (herbicide)	Triazine	2.63	5.78 + [M+H] + 228.127	0.1	0.4
		Dichlorvos	DIVO	Pesticide (acaricide)	Organochlorinated	1.9	6.11 + [M+H] + 220.953	0.5	3.9
		Fumonisin B2	FB2	Mycotoxin	Fumonisin	1.2	6.17 + [M+H] +	706.4	0.5	1.8
		Atrazine	ATZ	Pesticide (herbicide)	Triazine	2.7	6.61 + [M+H] + 216.101	0.5	1.6
		Diuron	DION	Pesticide (herbicide)	Phenylurea	2.87	7.09 + [M+H] + 233.024	0.5	9.5
		Ochratoxin A	OTA	Mycotoxin	Ochratoxin	4.74	7.55 10.85	+ -	[M+H] + [M-H] -	404.089 402.075	0.5 0.5	19 4.5
		BFDGE 1	BFDGE Migrant from packaging	Diglycidyl ether		8.17 + [M+Na] + 335.125	0.5	22.8
		Malathion	MLT	Pesticide (insecticide)	Organophosphate	2.75	8.22 + [M+H] + 331.043	0.5	1.6
		Diflubenzuron	DIFLU	Pesticide (insecticide)	Benzoylurea	3.89	8.46 + [M+H] + 311.039	0.5	0.8
		BADGE 2	BADGE Migrant from packaging	Diglycidyl ether		8.52 + [M+Na] + 363.157	4	21.2
		Pirimiphos-methyl	PIRI	Pesticide (insecticide)	Organophosphate	3.9	8.72 + [M+H] + 306.103	0.1	0.6
		2,4-Dichlorophenoxyacetic acid	2,4-D	Pesticide (herbicide)	Auxinic herbicide	-0.82	9.41	-	[M-H] -218.9621	6.9	19.4
		Bisphenol S	BPS	Migrant from packaging	Bisphenol	2.91	9.42	-	[M-H] -249.022	0.1	0.1
		Tolfenpyrad	TOLF	Pesticide (insecticide)	Pyrazole	5.61	9.43 + [M+H] + 384.147	0.1	0.9
		2-Methyl-4-chlorophenoxyacetic acid MCPA	Pesticide (herbicide)	Auxinic herbicide	-0.81	9.58	-	[M-H] -199.017	1	3.6
		Propargite	PROP	Pesticide (acaricide)	Organosulfite	5.7	9.88 +	Frag 3	231.174	0.6	3.2
		Dichloprop	DIPRO	Pesticide (herbicide)	Auxinic herbicide	2.29	10.17 -	[M-H] -232.977	1.7	18.8
		Mecoprop	MCPP	Pesticide (herbicide)	Auxinic herbicide	-0.19	10.21 -	[M-H] -213.032	0.7	1
		2,4,5-Trichlorophenoxyacetic acid 2,4,5-T	Pesticide (herbicide)	Auxinic herbicide	2.88	10.61 -	[M-H] -252.9232	1	4.6
		Bisphenol F	BPF	Migrant from packaging	Bisphenol	1.65	10.73 -	[M-H] -199.076	40	50
		Fenoprop	2,4,5 TP	Pesticide (herbicide)	Auxinic herbicide	2.84	11.12 -	Frag 3	194.917	0.8	5.3
		Dinoseb	DINO	Pesticide (herbicide)	Dinitrophenol	2.29	11.43 -	[M-H] -239.067	0.2	0.4
		Bisphenol A	BPA	Migrant from packaging	Bisphenol	3.3	11.51 -	[M-H] -227.107	10	42
		4-(2,4-Dichlorophenoxy)butyric acid 2,4-DB	Pesticide (herbicide)	Auxinic herbicide	1.35	11.62 -	Frag 3	160.957	6.9	19.4
	BFDGE : Bisphenol F diclycidyl ether; BADGE 2 : Bisphenol A diglycidyl ether; Frag 3 : Fragment

Table 2 : Recovery, RSD, method limit of quantification (MLOQ) and maximum residue limit (MRL) for the 32 targeted compounds in tea leaves quantified with matrix-matched calibration. N° Compound Level 1 (10 µg/kg a = 50 µg/kg b = 100 µg/kg) Level 2 (50 µg/kg a = 250 µg/kg b = 500 µg/kg) Level 3 (100 µg/kg a = 500 µg/kg b = 1000 µg/kg) MLOQ (µg/kg) MRL (µg/kg)

 2

			Recovery	RSD	Recovery	RSD	Recovery	RSD
			(%)	(%)	(%)	(%)	(%)	(%)
	1	Acrylamide b	ND	-	86.4	19.0	110.2	21.1	500	-
	2	Hydroxymethylfurfural a	89.4	77.5	51.3	41.1	51.0	23.3	-	-
	3	Deoxynivalenol a	282.4	12.1	138.6	24.1	91.7	19.8	500	1,250
	4	Imidacloprid	103.8	13.0	103.8	16.1	96.5	14.9	10	50
	5	Dimethoate	113.8	15.8	96.6	15.8	107.0	2.4	10	50
	6	Acetamiprid	115.4	17.4	115.4	14.8	100.4	16.9	10	50
	7	Fumonisin B1	ND	-	13.4	58.5	22.4	5.0	-	-
	8	Aldicarb	87.7	13.4	87.7	15.7	78.9	12.0	10	50
	9	Ametryn	106.3	15.3	106.3	13.3	96.5	12.1	10	10
	10	Dichlorvos	114.7	16.1	96.2	16.1	112.3	14.9	10	20
	11	Fumonisin B2	ND	-	24.6	36.9	28.7	6.1	-	-
	12	Atrazine	147.9	16.9	103.5	19.6	105.8	16.4	50	100
	13	Diuron	101.8	11.6	88.0	7.1	91.0	8.3	10	50
	14	Ochratoxin A	95.1	6.1	106.6	4.1	108.7	3.6	10	10
	15	BFDGE 1	77.4	26.4	73.1	12.0	78.9	17.0	50	-
	16	Malathion	108.7	5.7	105.4	3.6	106.6	2.3	10	500
	17	Diflubenzuron	76.3	15.9	77.0	6.8	80.0	7.3	10	100
	18	BADGE 2	107.1	51.6	105.3	11.2	103.9	16.0	50	60,000
	19	Pirimiphos-methyl	84.6	12.4	80.1	11.3	86.5	6.1	10	50
	20	2,4-D	66.1	17.8	68.8	11.6	71.4	10.0	50	100
	21	Bisphenol S	80.3	11.4	80.1	13.1	76.8	11.2	10	50
	22	Tolfenpyrad	45.2	11.4	56.4	8.6	62.1	8.0	(50)	10
	23	MCPA	73.6	8.1	94.8	10.2	71.1	10.3	10	100
	24	Propargite	ND	-	38.5	18.5	52.6	20.3 (100)	100
	25	Dichloprop	83.9	18.1	91.6	19.8	87.6	15.2	10	100
	26	Mecoprop	79.9	6.0	98.1	12.3	74.1	11.5	10	100
	27	2,4,5-T	82.9	8.8	91.3	8.8	88.3	18.9	10	50
	28	Bisphenol F a	ND	-	75.8	25.8	72.3	21.4 (500)	-
	29	Fenoprop	76.4	5.5	71.5	9.5	70.9	8.5	10	10
	30	Dinoseb	62.1	6.1	66.3	15.9	60.5	11.6	(10)	100
	31	Bisphenol A a	ND	-	78.2	36.7	74.7	22.5 (500)	600
	32	2,4-DB	61.8	17.6	68.8	11.6	72.3	8.9	100	50
	ND= Not detected. Values under bracket mean that validation criteria were not reached but were still acceptable
	according to the European commission guideline (European Commission -Directorate General for Health and
	Food Safety, 2015)