Fabien Robert-Peillard

El Mountassir

El Mouchtari

Damien Bonne

Stéphane Humbel

Jean-Luc Boudenne

Bruno Coulomb
email: bruno.coulomb@univ-amu.fr

Determination of dissolved nickel in natural waters using a rapid microplate fluorescence assay method

Keywords: Fluorescent chemical sensor, nickel, lophine derivative, high-throughput analysis, natural waters

A new microplate analytical procedure is described for the determination of nickel (Ni 2+ ) ions in natural water samples. A lophine analogue fluorescent sensor was synthesized and a spectral study showed a selective fluorescence quenching effect of chemical sensor by Ni 2+ under optimized conditions. Density functional theory (DFT) calculations confirmed the formation of a Ni(II)L3 complex obtained by the Job plot. The calculations showed that the fluorescence emission peak of L collapses due to the distortion of L in the complex. The simple and fast microplate procedure allowed us to quantify Ni 2+ with a linear response from 1.6 to 40 µg L -1 and a quantification limit of 5.4 µg L -1 without the need of a preconcentration step. The optimized procedure using high-throughput microplate assay has been applied for the determination of Ni 2+ in natural water samples with good analytical performances.

Introduction

Nickel is naturally present in small quantities in the earth's crust (about 0.02%), mainly in the form of sulfide, oxidized and silicate ores, and has a very important role in various enzymatic activities of some plant and bacterial enzymes. However, nickel is widely used in many industrial sectors such as electroplating, battery or painting industries leading to releases into the aquatic environment. Nickel can become harmful to the environment, causing pollution of water and soil, and orally ingested nickel may have adverse effects on kidneys and lungs and can promote the development of dermatitis, eczema, respiratory diseases or even cancer [START_REF] Grimsrud | Lung cancer incidence among Norwegian nickel-refinery workers 1953-2000[END_REF][START_REF] Food | Opinion of the Scientific Panel on Dietetic Products, Nutrition and Allergies on a request from the Commission related to the Tolerable Upper Intake Level of Nickel[END_REF].

For the environment, the European Community has established an annual average value of environmental quality standard (AA-EQS) of 4 µg L -1 for inland surface water and a maximum allowable concentration value of environmental quality standard (MAC-EQS) of 34 µg L -1 irrespective of the kind of water bodies. The presumed carcinogenicity of nickel and its compounds have led the health authorities to establish limit values in water intended for human consumption, to limit human exposure. In Europe, this limit has been set at 20 µg L -1 while the World Health Organization (WHO) recommends a maximum guideline value of 70 µg L -1 . In laboratory, nickel is typically quantified by several analytical techniques including inductively coupled plasma-atomic emission spectrometry (ICP-AES), inductively coupled plasma-mass spectrometry (ICP-MS) and graphite furnace atomic absorption spectrometry (GF-AAS) or flame atomic absorption spectrometry (F-AAS). The analytical performance of these methods can be improved by sample processing steps such as liquid-liquid extraction [START_REF] Chakraborti | Determination of trace metals in natural waters at nanogram per liter levels by electrothermal atomic absorption spectrometry after extraction with sodium diethyldithiocarbamate[END_REF] or solid-phase extraction [START_REF] Baytak | Determination of lead and nickel in environmental samples by flame atomic absorption spectrometry after column solid-phase extraction on Ambersorb-572 with EDTA[END_REF][START_REF] Vellaichamy | Preconcentration and separation of copper, nickel and zinc in aqueous samples by flame atomic absorption spectrometry after column solid-phase extraction onto MWCNTs impregnated with D2EHPA-TOPO mixture[END_REF], to pre-concentrate the analyte and facilitate its detection or to limit interference from sample matrix. These techniques however often require expensive equipment and complex and time-consuming analytical procedures. These disadvantages have led researchers to develop in recent years more sustainable chemical techniques, to reduce the cost and environmental impact of the analyses. This can be achieved by reducing the volumes used (principles 1 and 2 of green chemistry: waste prevention and atoms economy, respectively) and energy consumption (principle 6: design for energy efficiency), or even by real-time monitoring with a view to preventing pollution (principle 11: real-time analysis for pollution prevention). To achieve these objectives, the use of microplates is advantageous, thus taking advantage of low consumption of samples and reagents, possibilities of automation, rapid preparation, and multisampling analyses. However, the development of such a microplate method requires the use of a sensitive and selective chemical probe allowing spectrophotometric or fluorescence detection. Spectroscopic techniques (UV-visible spectrophotometry or fluorescence) are of great interest due to their robustness, low cost, and ease of use, but they often suffer from interference from transition metals, especially Fe (II), Co (II), Cu (II), Pb (II) and Zn (II) [START_REF] Ferreira | Derivative spectrophotometric determination of nickel using Br-PADAP[END_REF] and from high quantification limits which prevent their use for environmental analyses. To overcome these problems, three ways have been considered in recent years: the development of extraction/preconcentration processes, the use of chemometrics and the synthesis of selective chemical probes. Solid-phase extraction has been applied by Mizuguchi et al. [START_REF] Mizuguchi | A rapid enrichment technique for the ultratrace determination of nickel in water samples using a nanofiber-composite membrane filter[END_REF] and by Liu et al. [START_REF] Liu | Solid-phase spectrophotometric determination of nickel in water and vegetable samples at sub-µg l -1 level with ocarboxylphenyldiazoaminoazobenzene loaded XAD-4[END_REF], respectively using a Nylon 6 membrane and Amberlite XAD-4 resin beads, to preconcentrate nickel as a metal complex and perform the detection by solid-phase spectrophotometry. Likewise, Adewuyi et al. [START_REF] Adewuyi | A highly selective and sensitive pyridylazo-2-naphthol-poly(acrylic acid) functionalized electrospun nanofiber fluorescence ''turn-off'' chemosensory system for Ni 2+[END_REF] have proposed an analytical method based on the preconcentration of nickel on nanofibers of poly-(acrylic acid) functionalized with pyridilazo-2naphthol and followed by fluorescence detection. Concerning chemometrics, overlapping peaks of UV-visible spectra of interferent metal complexes for nickel determination has been solved by derivative spectroscopy [START_REF] Ferreira | Derivative spectrophotometric determination of nickel using Br-PADAP[END_REF], Partial Least Squares calibration [START_REF] Kaur | Simultaneous spectrophotometric dtermination of cobalt and nickel by partial least square regression in micellar media[END_REF][START_REF] Guo | Simultaneous spectrophotometric determination of trace copper, nickel, and cobalt ions in water samples using solid phase extraction coupled with partial least squares approaches[END_REF] or light-absorption ratio variation approach (LARVA) [START_REF] Gao | Light-absorption ratio variation approach to determination of nickel (II) in ng/ml level with 1, 5-di(2-hydroxy-5-sulfophenyl)-3cyanoformazan[END_REF]. However, solid-phase extraction procedures or exploitation of UV-visible spectra are difficult to apply to microplate analyses. Some studies have also focused on the synthesis of various chemical sensors for the selective complexation of nickel, but in 2012 only 6% of studies on synthesis of chemical probes concerned the determination of nickel [START_REF] Dutta | Recent developments in fluorescent sensors for trace-level determination of toxic-metal ions[END_REF] and few of them had been applied to nickel analysis in real water samples. We can cite for example Chowdhury et al. [START_REF] Chowdhury | Salen Type Ligand as a Selective and Sensitive Nickel(II) ion Chemosensor: A Combined Investigation with Experimental and Theoretical Modelling[END_REF] and Wang et al. [START_REF] Wang | Acridine-based fluorescence chemosensors for selective sensing of Fe 3+ and Ni 2+ ions[END_REF] who have respectively synthesized a Schiff base and an acridine based fluorescent chemosensors for selective nickel determination by chelation-enhanced fluorescence. In the same way, a hydrazide compound was synthetized by Liu et al. [START_REF] Liu | A new acylhydrazine N'-(1,3 dimethylbutylene)-3-hydroxy-naphthohydrazide based fluorescent sensor for the detection of Ni 2+[END_REF] and was applied to direct nickel determination of nickel in river water samples.

Table 1 presents a comparison of various spectroscopic methods (UV-Vis spectrophotometry or fluorescence) applied to nickel quantification in tap water, natural waters (river water, lake water, groundwater) or in wastewater. Data analysis of this table shows that few methods are available and applicable, particularly considering the whole operational parameters required for quantification of nickel in natural or drinking water (ease of use, duration, limit of quantification, selectivity),. Some of these methods are extremely sensitive with satisfactory detection limits for the analysis of nickel in drinking or natural water but are either complex and long to implement [START_REF] Mizuguchi | A rapid enrichment technique for the ultratrace determination of nickel in water samples using a nanofiber-composite membrane filter[END_REF][START_REF] Liu | Solid-phase spectrophotometric determination of nickel in water and vegetable samples at sub-µg l -1 level with ocarboxylphenyldiazoaminoazobenzene loaded XAD-4[END_REF][START_REF] Guo | Simultaneous spectrophotometric determination of trace copper, nickel, and cobalt ions in water samples using solid phase extraction coupled with partial least squares approaches[END_REF][START_REF] Gao | Light-absorption ratio variation approach to determination of nickel (II) in ng/ml level with 1, 5-di(2-hydroxy-5-sulfophenyl)-3cyanoformazan[END_REF][START_REF] Chen | A Supersensitive Probe for Rapid Colorimetric Detection of Nickel Ion Based on a Sensing Mechanism of Anti-etching[END_REF], or not sufficiently selective for environmental matrices [START_REF] Adewuyi | A highly selective and sensitive pyridylazo-2-naphthol-poly(acrylic acid) functionalized electrospun nanofiber fluorescence ''turn-off'' chemosensory system for Ni 2+[END_REF]. The other methods do not have a detection limit low enough to be applied to the analysis of drinking water according to European regulations: for water sanitary control, an analytical method must be capable of measuring concentrations equal to 30% of the parametric value with an uncertainty of measurement of 25%, i.e. for nickel determination, this corresponds to a limit of quantification of 6 µg L -1 and a limit of detection of approximately 2 µg L -1 [24]. The development of a rapid, sensitive, and selective determination of nickel in water samples is therefore still a challenge. Ideally this method should be robust, low cost and with simple operational conditions so that it can be easily applied to various environmental matrices. In this paper we report the synthesis of a new fluorescent chemosensor L (4-[4,5-di(pyridin-2yl)-1H-imidazol-2-yl]benzoic acid). This chemical sensor L can be considered as an analogue of lophine (2,4,5-triphenylimidazole) and lophine and its derivatives are known to be highly fluorescent and have already been reported as chemiluminescence compounds using hydrogen peroxide [START_REF] Nakashima | Evaluation of lophine derivatives as chemiluminogens by a flow-injection method[END_REF][START_REF] Kuroda | Lophine derivatives and analogues as new phenolic enhancers for the luminol-hydrogen peroxide-horseradish peroxidase chemiluminescence system[END_REF] or for determination of trace amounts of cobalt [START_REF] Marino | Determination of cobalt by lophine chemiluminescence[END_REF]. In this study, we investigated sensing possibilities of sensor L towards metal ions and optimized analytical parameters of a rapid, direct, and simple microplate procedure to reach low detection limit. This procedure was applied to selective nickel detection in drinking and natural water samples.

Experimental

Chemicals and reagents

All reagents and solvents used were of analytical grade. Aqueous solutions were prepared with ultrapure deionized water using a Millipore Milli-Q purification system (Millipore, USA, resistivity > 18 MΩ cm). A 0.1 M phosphate buffer solution was prepared by dissolving appropriate amount of potassium dihydrogen phosphate (Merck, Germany) in ultrapure water and adjusted to pH = 7 by adding a few drops of 1 M NaOH solution. 10 mM stock solution of 4-[4,5-di(pyridin-2-yl)-1H-imidazol-2-yl]benzoic acid (sensor L) was prepared in dimethylsulfoxide (DMSO) and stored at +4 •C. This stock solution was then diluted in phosphate buffer to give 10 µM working solution.

Ni 2+ and interferents (Ag + , Al 3+ , Ca 2+ , Cd 2+ , Co 2+ , Cr 3+ , Cu 2+ , Fe 3+ , Hg 2+ , Mg 2+ , Mn 2+ , Pb 2+ , Pt 4+ , Ti 3+ , Zn 2+ ) standards were prepared daily by dilution of 1 g L -1 commercial standards solutions (AAS solution 1 mg mL -1 Acros Organics, France) with ultrapure water. A 10 mM masking agent stock solution was prepared by diluting commercial thioglycolic acid (Acros Organics, France) in phosphate buffer solution. This stock solution was then diluted daily in phosphate buffer to give the working solutions.

Synthesis and characterization of sensor L

The synthetic route reported by Slater et al. [START_REF] Slater | Metal-metal interactions in dinuclear tuthenium complexes containing bridging 4,5-di(2-pyridyl)imidazolates and related ligands[END_REF] was modified to introduce a carboxylate group in the structure of the sensor through formylbenzoic acid and improve water solubility. The synthesis of sensor L is briefly described hereafter (Scheme 1). 4-Formylbenzoic acid (0.50 g, 3.33 mmol, 1.0 equiv) was added to a solution of 2,2'-pyridil (0.71 g, 3.33 mmol, 1.0 equiv) and ammonium acetate (2.10 g, 27.2 mmol, 8.0 equiv) in acetic acid (10 mL). The mixture was heated in a microwave for 5 minutes at 180 °C. The reaction mixture was allowed to cool to room temperature and neutralized with ammonia solution in an ice bath. The pale-yellow precipitate formed was collected, washed with water, and recrystallized from acetone to afford the desired product as a light-yellow solid (0.

Fluorescence measurements

Fluorescence study of sensor L was carried out on a SAFAS Xenius fluorescence spectrometer (SAFAS, Monaco) equipped with a Xenon lamp and controlled by SP2000 V7 software. Sensor L and metal ion were mixed into a quartz cell following a ML3 ratio and fluorescence spectrum of each mixture was measured using an excitation wavelength of 340 nm (excitation and emission bandpass: 10 nm; wavelength step: 1 nm; scan speed: 260 nm.min -1 ; photomultiplier voltage: 600 V). Microplate fluorescence was measured on a multi-mode microplate reader (Synergy HTX, Biotek, France), equipped with excitation and emission filter wheels and controlled by Gen5 version 3.03 software (Biotek). Top fluorescence detection was performed in polypropylene black 96-well U-bottom microplates (Nunc) from above the microplate wells, at λex = 340 nm and λem = 440 nm.

Computational study

The computed results correspond to single point calculations with the B3LYP DFT method [START_REF] Becke | A new mixing of Hartree-Fock and local density-functional theories[END_REF][START_REF] Becke | Density-functional thermochemistry. III. The role of exact exchange[END_REF][START_REF] Lee | Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density[END_REF] and the def2-TZVP [START_REF] Schäfer | Fully optimized contracted Gaussian basis sets for atoms Li to Kr[END_REF]33] basis set on top of BP86 optimized geometries [START_REF] Becke | Density-functional exchange-energy approximation with correct asymptotic behavior[END_REF][START_REF] Vosko | Accurate spin-dependent electron liquid correlation energies for local spin density calculations: a critical analysis[END_REF][START_REF] Perdew | Density-functional approximation for the correlation energy of the inhomogeneous electron gas[END_REF] with the def2-SVP basis set [START_REF] Schäfer | Fully optimized contracted Gaussian basis sets for atoms Li to Kr[END_REF]33]. All the computations used the maximum symmetry group (C3 for the (NiL3) 2+ complexes, Cs for the isolated lophine). All structures were characterized as minimum with frequency calculation. The D3 dispersion correction was applied in all computations [START_REF] Grimme | A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu[END_REF]. The Ni complex structures were dications at the triplet state. Counter anions were not considered. The Turbomole suite of program [START_REF]a development of University of Karlsruhe and Forschungszentrum Karlsruhe GmbH[END_REF][START_REF] Ahlrichs | Electronic structure calculations on workstation computers: The program system turbomole[END_REF][START_REF] Treutler | Efficient molecular numerical integration schemes[END_REF] was used throughout with the resolution of identity method [START_REF] Eichkorn | Auxiliary basis sets to approximate Coulomb potentials[END_REF][START_REF] Eichkorn | Auxiliary basis sets for main row atoms and transition metals and their use to approximate Coulomb potentials[END_REF][START_REF] Sierka | Fast evaluation of the Coulomb potential for electron densities using multipole accelerated resolution of identity approximation[END_REF][START_REF] Bauernschmitt | Calculation of excitation energies within time-dependent density functional theory using auxiliary basis set expansions[END_REF][START_REF] Deglmann | Nuclear second analytical derivative calculations using auxiliary basis set expansions[END_REF]. The calculation levels were very similar to that of Dowling et al. [START_REF] Dowling | Preparation, electrochemical behavior and variable temperature magnetic properties of transition metal complexes containing 2-phenyl-4,5-di-(2-pyridyl)imidazole, Transition Met[END_REF]. The UV-Vis spectra of the lophines were computed at the B3LYP/def2-TZVP level within the TDDFT framework. [START_REF] Casida | Time-dependent density functional response theory for molecules, in Recent advances in density functional methods[END_REF]. For the planar lophine a total of 12 states were requested (8 of a' symmetry, and 4 of a"). For the lophine distorted as in the Ni(II)L3 complex, 15 states were requested. A 9 states computation showed that the part of the spectrum that is low in energy is not sensitive to the number of states. 2+ determination 100 μL of sample or Ni 2+ standard solution was dispensed into the wells of the microplate, followed by 100 μL of a 10 µM sensor L solution in phosphate buffer pH = 7 and 30 µL of masking agent solution. The plate was shaken for 20 sec in the microplate reader and fluorescence was subsequently measured at λex=340 nm and λem=440 nm. All experiments were performed in triplicate.

Microplate assay for Ni

Validation on real samples

Groundwater samples were collected from sources and drillings used to produce water intended for human consumption, in the Aubagne region, near Marseille (Provence Alpes Côte d'Azur region, South-East of France). A river water sample was collected from the Huveaune River (Aubagne, France). A location map of the sampling points is provided in supplementary materials (Fig. S2). Samples were filtered on-site using 0.45 μm polyether sulfone (PES) filters and stored in high density polyethylene flasks at +4 • C until analysis.

Samples were analyzed both by the developed microplate assay described above and by inductively coupled plasma mass spectrometry (ICP/MS; Agilent 7800, Agilent Technologies, France) controlled by Agilent MassHunter version 4.5 software for data acquisition and analysis. Instrumental settings were as follows: plasma energy, 1000 W; carrier gas, 12 L min - 1 ; makeup gas, 0.4 L min -1 . Instrument performance for elemental analysis was verified with a diluted of multi-element JYICP-MIX21 100 mg L -1 solution in 5% nitric acid (Jobin-Yvon, France).

Sustainability evaluation of the method

The greenness and the sustainability of the method were evaluated by the RGB12 model [START_REF] Nowak | What color is your method? Adaptation of the RGB additive color model to analytical method evaluation[END_REF][START_REF] Koscielniak | Comprehensive assessment of flow analytical methods dedicated to the determination of zinc in water[END_REF] and compared to similar methods for the detection of nickel in aqueous samples by spectrophotometry with an azocalix [START_REF] Baytak | Determination of lead and nickel in environmental samples by flame atomic absorption spectrometry after column solid-phase extraction on Ambersorb-572 with EDTA[END_REF]arene [START_REF] Ma | Determination of nickel by a new chromogenic azocalix[4]arene, Ana[END_REF], solid-phase spectrophotometry with o-CDAA [START_REF] Liu | Solid-phase spectrophotometric determination of nickel in water and vegetable samples at sub-µg l -1 level with ocarboxylphenyldiazoaminoazobenzene loaded XAD-4[END_REF], and fluorescence with BMH [START_REF] Liu | A new acylhydrazine N'-(1,3 dimethylbutylene)-3-hydroxy-naphthohydrazide based fluorescent sensor for the detection of Ni 2+[END_REF] or with murexide [START_REF] Kargosha | Spectrofluorimetric Determination of Nickel (ΙΙ) with Murexide[END_REF]. The RGB model allows the comparison of methods according to 12 rules divided into 3 components: the red component (principles R1-R4) for the evaluation of analytical performance and the green (principles G1-G4) and blue (principles B1-B4) components for the evaluation of the method's ecological and practical criteria respectively. The criteria used are detailed in Table S1. For each method, the evaluation was based on the analytical part of the method, the chemical probe synthesis steps were not considered. The criteria are evaluated individually and an overall score of the method is calculated in a range between 0 and 100, the closer the score is to 100 the more satisfactory the method is in terms of analytical performance, greenness, and sustainability.

Results and discussion.

Fluorescence study of L towards Ni 2+

The sensing possibilities of sensor L towards metal ions were first investigated by fluorescence spectra measurement in aqueous solutions. The carboxylate group introduced in the structure of the sensor through formylbenzoic acid helped to improve water solubility and enabled application in aqueous solutions. Excitation and emission wavelengths were determined by performing a 3D fluorescence scan of sensor L in phosphate buffer (Fig. S3). The results showed an excitation wavelength and an emission wavelength centered at 340 nm and 417 nm respectively, which is consistent with the wavelengths reported previously for lophine derivatives [START_REF] Kuroda | Lophine derivatives and analogues as new phenolic enhancers for the luminol-hydrogen peroxide-horseradish peroxidase chemiluminescence system[END_REF][START_REF] Fridman | Crystal structures and solution spectroscopy of lophine derivatives[END_REF]. The fluorescence spectra of L with the presence of various metal ions were recorded and are shown in Fig. 1a. From these results, we can observe that sensor L exhibited a high fluorescence at 417 nm while fluorescence strongly decreased in the presence of Ni 2+ . Fluorescence is also slightly decreased in the presence of Cu, Co and Hg while other metals tested do not appear to cause fluorescence quenching.

The stoichiometry of the complex between sensor L and Ni 2+ was established using Job's plot analysis (Fig. 1b). The plot of fluorescence intensity versus molar ratio of L and Ni 2+ showed a maximum quenching effect of fluorescence around 0.25, which indicated a 3:1 stoichiometry between L and Ni 2+ .

(NiL3) 2+ complexes

Our DFT computations converged to a stable C3 symmetric structure, where each lophine interacts with the metal with  2 coordination (Fig. 2). This structure is in agreement with the study of Dowling and Lemaire [START_REF] Dowling | Preparation, electrochemical behavior and variable temperature magnetic properties of transition metal complexes containing 2-phenyl-4,5-di-(2-pyridyl)imidazole, Transition Met[END_REF] in which an imidazole-based ligand complexed transition metals through bonds with the N atoms of pyridine and imidazole rings. The π system of the lophines in the complexes is very different from that of a free lophine: (i) π systems of lophines see each other via π-stacking and/or CH-π interactions and (ii) the rings are partly deconjugated by rotations. Hence, it is not surprising that the π π* transition observed in free lophine is lost in the ML3 complexes. The energy cost of the lophine's distortion can be as large as 119.8 kJ mol -1 (Fig. 3a). Moreover, the simulated UV spectrum shows that the quenching effect can be at least partly attributed to this lophine's distortion (Fig. 3b). The computed free lophine shows 2 bands at 350 nm and 385 nm (Fig. 3b, plain black). The massive band observed experimentally at 417 nm must correspond to the coalescence of these two bands, with a large contribution of the most intense peak, at 385 nm. Hence, the computed spectrum is blue shifted by about 30-40 nm. In the distorted lophine the computations show that the most intense peak at 385 nm collapses, and the peak at 350 nm was the only one to remain. Hence, we attribute the fluorescence quenching, at least partly, to the distortion of the lophine in the complex. As stated above, π stacking effects in the complex shall also contribute to the quenching.

Optimization of the analytical protocol 3.3.1 pH and buffer solution

pH of the reaction mixture between L and a metal solution plays an important role because it can modify the characteristics of the functional coordination groups. A judicious choice of pH can allow both to obtain the best response for the determination of Ni 2+ but also to limit interference from other metal elements. The effect of pH value was investigated here in the range 5 to 9 by addition of few drops of HNO3 or NaOH diluted solutions (Fig. 4). From Fig. 4, we can observe that the nickel response (quenching effect) was maximal and stable for pH values between 6 and 9. Most metals partially quenched the fluorescence of L for a pH value equals to 8 (Hg, Co, Cu) or 9 (Cd, Zn). Finally, the best compromise between the response of nickel and the response of interfering metals seemed to be at a pH equal to 7 because this value could limit the interference of Hg, Co, and Zn. Only copper displays a similar profile as nickel, complexation by L appeared rather independent of pH between 6 and 9. Two buffers at pH=7 were tested: a phosphate buffer and a HEPES buffer (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid). During the experiments, the phosphate buffer showed a slight increase in the IFmetal/IFblank fluorescence ratio compared to the HEPES buffer for cobalt and mercury, making it possible to limit their possible interferences. The phosphate buffer at pH=7 was therefore chosen for subsequent experiments, but the results also showed that the interferences of copper, and to a lesser extent of cobalt and mercury, will have to be considered and eliminated by the addition of a masking agent.

Selectivity towards Ni and masking agent

The selectivity of a chemical probe for a metal ion is a paramount parameter for measurements in environmental samples. This is particularly important for metal ions whose environmental concentrations are in the range of µM (Ni 2+ , Cu 2+ , Zn 2+ ) while other metal ions could be present at levels of mM (Ca 2+ , Mg 2+ ). In most publications, the selectivity study is carried out with the metal of interest in the presence of 1 to 10 equivalents of other metal ions, but for some metal elements these concentration levels are not representative of real environmental amounts. For this study, we set the Ni 2+ concentration at 10 µg L -1 (0.17 µM) and the concentrations of interfering metal ions were based on parametric values defined by European legislation on water intended for human consumption (Cu 2+ , Pb 2+ , Cd 2+ ) or based on environmental values encountered in surface waters (Ca 2+ , Mg 2+ , Zn 2+ ). The response was studied with each metal ion separately at environmental level in absence and in presence of masking agent (Fig. 5). The selectivity study clearly demonstrated the strong interference of copper in the absence of a masking agent. The other metals at environmental levels showed no interference problems. Various masking agents have thus been tested to eliminate interference from copper with no masking of the response of nickel: tetraethylenepentamine (TETREN), triethanolamine (TEA), thiourea, thioglycolic acid, diethyldithiocarbamate (DDTC) [START_REF] Artiss | Spectrophotometric study of several sensitive reagents for serum iron[END_REF]. TETREN, TEA and thiourea were shown to be not effective in masking interference from copper. DDTC eliminated the interference from copper but also masked the response of nickel. Finally, thioglycolic acid was found to be the most effective masking agent, helping to eliminate interference from other metallic elements at environmental concentrations (Fig. 5a). The concentration of thioglycolic acid was studied and experiments showed that a concentration of 2 mM of thioglycolic acid eliminated copper interference up to a concentration of about 1 mg L -1 , corresponding to a molar ratio Cu/Ni of 92. A higher concentration of thioglycolic acid led to a slight decrease in the nickel response (increased IF/IF0 ratio) (Fig. 5b).

Analytical features of microplate analytical procedure

A simple microplate analytical procedure with sensor L was developed and evaluated using the optimized experimental conditions: 0.1 M buffer phosphate adjusted to a pH value of 7 and 2 mM thioglycolic acid used as masking agent solution. Analytical features of this procedure are presented in Table 2.

Very good linear regression coefficient was obtained with Ni 2+ standards in the range 1.6 -40 µg L -1 (Fig S4). The limit of quantification (LOQ), defined as the concentration corresponding to (blank+10), was lower than 6 µg L -1 , which corresponds to 30% of the parametric value for the quality of water intended for human consumption in Europe for nickel, without the need of a preconcentration step by solid-phase extraction.

The intra-day (8 consecutive repeated measurements on the same day) and inter-day (5 repeated measurements over 5 consecutive days) precision (RSD) of the microplate measurement were evaluated at 2 concentration levels: in the middle of the analytical range, i.e. 20 µg L -1 , and at 30% of the parametric value for the quality of water intended for human consumption in Europe for nickel, i.e. 6 µg L -1 . The results (Table 2) showed that the developed analytical procedure has the adequate precision recommended by the European legislation for water sanitary control (uncertainty of measurement of 25% at a concentration equals to 30% of the parametric value) with intra-day and inter-day RSD performed at 6 µg L -1 , respectively of 7.75 and 8.87%.

By comparing these analytical characteristics with those of methods from the literature (Table 1), this developed analytical procedure seems to be a good compromise between ease of use (the procedure only requires a microplate reader and takes less than a minute), good detection and quantification limits and consideration of interference from metal ions at environmental levels. The certified groundwater material ERM®-CA615 was first used for the validation of the microplate procedure (Table 3), and the t-test for comparison of means showed there were no significant differences, at 95% confidence level.

The optimized microplate procedure was then applied to Ni 2+ determination in natural waters sampled in Aubagne region (near Marseille city, south-east of France). The samples were UV-photooxidized at 254 nm for 30 minutes before analysis to degrade natural organic ligands, inorganic ligands, or even anthropogenic organic ligands and to quantify total dissolved nickel. Ni 2+ was measured in samples in duplicate by the developed microplate procedure and by ICP-MS as reference analytical method. The results are summarized in Table 3. The complete physical-chemical characteristics of the samples are given in Table S2 to give an overview of the possible interferences in the samples measured.

The values obtained by the two methods were consistent despite a slight underestimation by the microplate method. The mean difference between the two methods was -2.94%, (min -0.73%; max -5.4%) but this difference should be put into perspective given the low concentration of nickel in the samples. The results obtained for nickel determination by the proposed microplate method with L were compared (paired t-test) with the reference method values (ICP-MS). A risk of 1.94% difference was calculated between the two methods. a Certified mass concentration of cations: As: 9.9 ± 0.7 µg L -1 ; Cd: 0.106 ± 0.011 µg L -1 ; Fe: 5.11 ± 0.26 µg L -1 ; Hg: 0.037 ± 0.004 µg L -1 ; Mn : 107 ± 5 µg L -1 ; Pb : 7.1 ± 0.6 µg L -1

Greenness and sustainability evaluation of the method

The greenness and the sustainability of the method were evaluated using RGB model according to the procedure described in Section 2.7 and were compared to four other methods. The results of the evaluation of the different criteria and the overall score obtained for each method are presented in Figure S5.

For the analytical aspects (red scores), the best scores are obtained by the proposed method and by the methods based on the use of azocalix [START_REF] Baytak | Determination of lead and nickel in environmental samples by flame atomic absorption spectrometry after column solid-phase extraction on Ambersorb-572 with EDTA[END_REF]arene [START_REF] Ma | Determination of nickel by a new chromogenic azocalix[4]arene, Ana[END_REF] or murexide [START_REF] Kargosha | Spectrofluorimetric Determination of Nickel (ΙΙ) with Murexide[END_REF] with red scores of 76.3%, 71.5% and 77.5% respectively. The scores of other methods are penalized either by a lower selectivity (criterion R1 scope of application, corresponding to acceptable molar ratio between Ni and interferents) [START_REF] Liu | Solid-phase spectrophotometric determination of nickel in water and vegetable samples at sub-µg l -1 level with ocarboxylphenyldiazoaminoazobenzene loaded XAD-4[END_REF][START_REF] Liu | A new acylhydrazine N'-(1,3 dimethylbutylene)-3-hydroxy-naphthohydrazide based fluorescent sensor for the detection of Ni 2+[END_REF], or by a low measurement range [START_REF] Liu | A new acylhydrazine N'-(1,3 dimethylbutylene)-3-hydroxy-naphthohydrazide based fluorescent sensor for the detection of Ni 2+[END_REF]. Methods using fluorescence measurement [this work, [START_REF] Liu | A new acylhydrazine N'-(1,3 dimethylbutylene)-3-hydroxy-naphthohydrazide based fluorescent sensor for the detection of Ni 2+[END_REF][START_REF] Kargosha | Spectrofluorimetric Determination of Nickel (ΙΙ) with Murexide[END_REF] or solid phase spectrophotometry (thus integrating a pre-concentration step on the solid phase) [START_REF] Liu | Solid-phase spectrophotometric determination of nickel in water and vegetable samples at sub-µg l -1 level with ocarboxylphenyldiazoaminoazobenzene loaded XAD-4[END_REF] have better detection limits than simple spectrophotometric methods [START_REF] Ma | Determination of nickel by a new chromogenic azocalix[4]arene, Ana[END_REF] and are therefore capable of measuring concentrations equal to 30% of the parametric value (approximately 6 µg L -1 ).

Concerning ecological aspects, the proposed method is the most environmentally friendly. Particular attention can be paid to the high score obtained by the developed method compared to other methods in the case of criterion G2 (reagent consumption and waste production), which have been considerably minimized thanks to the adaptation of the analytical method to microplate configuration. The green score of most of the methods is however downgraded by the G1 criterion (toxicity of reagents used) with the use of reagents that are toxic to human health and/or the environment, even more by excluding the chemicals used during the synthesis steps of the chemical probes.

All methods obtain similar blue scores around 80%, except for the one developed by Liu et al [START_REF] Liu | Solid-phase spectrophotometric determination of nickel in water and vegetable samples at sub-µg l -1 level with ocarboxylphenyldiazoaminoazobenzene loaded XAD-4[END_REF], based on solid phase spectrophotometry, which obtains a significantly lower score, mainly due to the analysis time (criterion B2) and the large sample volume required (criterion B3).

Finally, the proposed method appears to present best overall score (80.4%), with well-balanced scores between ecological, practical, and analytical performance aspects.

Conclusion

This study demonstrated the performance of a simple and rapid microplate analytical method for the determination of dissolved nickel in environmental aqueous samples based on a newly synthesized fluorescent chemosensor L (4-[4,5-di(pyridin-2-yl)-1H-imidazol-2-yl]benzoic acid). Optimization of the pH value and the nature of the buffer improved the selectivity of the chemical probe L. The limit of quantification obtained (lower than 6 µg L -1 ) is low enough to apply this method to the analysis of drinking water according to European regulations: for water sanitary control, an analytical method should be capable of measuring concentrations equal to 30% of the parametric value (20 µg L -1 for nickel). The optimized microplate procedure has been successfully applied to real natural water samples, demonstrating applicability of our new methodology for Ni 2+ detection.

Figure 1 :

 1 Figure 1: (a) Emission fluorescence spectra (exc =340nm ) of L (10 µM) in phosphate buffer (pH=7) and L with addition of various metal ions M (M:L3 ratio); (b) Job's plot analysis of L (10 µM) regarding Ni 2+ ion (10 µM).

Figure 2 :

 2 Figure 2: Possible complexation on Ni(II) with 2 coordination of each lophine. The green axis is the C3 axis.

Figure 3 :

 3 Figure 3: Lophine distortion for the complexation on Ni(II) : (a) bottom free lophine, top as extracted from the  2 complex. The number on the right is the energy destabilization with respect to a free lophine (bp86 def2-SVP values, in kJ mol -1 ); (b) TD-DFT simulated spectrum.

Figure 4 :

 4 Figure 4: Fluorescence intensity ratio (IF/IF0 is the ratio between the fluorescence response of the metal ions solution and the blank) as a function of pH (L at 10 µM and metal ions at 1 µM).

Figure 5 :

 5 Figure 5: (a) Selectivity study (n=3) with sensor L (10 µM) in phosphate buffer (pH=7) towards interfering ions at environmental levels in absence and presence of masking agent (thioglycolic acid 2 mM); (b) Masking effect (n=3) of thioglycolic acid at different concentrations (sensor L 10 µM in phosphate buffer (pH=7), Ni 10 µg L -1 , Cu 1 mg L -1 ).

Table 1 :

 1 Comparison of analytical features of spectroscopic techniques for nickel determination in environmental water

samples 1 Method Ligand or sensor Matrix Linear range (µg L -1 ) Detection limit (µg L -1 ) Quantification limit (µg L -1 ) Analytical procedure duration (min) Main tolerance limit (molar ratio relative to Ni 2+ ) Reference

	Spectrophotometry	GSH-AgNPR f	Tap water, lake water	0.3 -17	0.3	n.d.	> 15	Co interference	[17]
	Spectrophotometry dimethylglyoxime	River water, wastewater	50 -600	20	n.d.	n.d.	Cu 2+ : 10 Co 2+ : 100	[22]
	Fluorescence	BNQDs g	River water, lake water	5.9 -5900	5.9	n.d.	> 5	Some interferences	[23]
	Microplate fluorescence	L	Natural Groundwater water ;	1.6 -40	1.6	5.4	< 1	Cu 2+ : 92 h	This work
	Spectrophotometry n.d. : not determined	DSPCF a	River water, wastewater	5 -200	1.3	n.d.	> 15	Mn 2+ : 10 Fe 2+ : 10	[12]
	Fluorescence	BMH b	River water	4.7 -117	3.5	n.d.	< 1	Co 2+ : 1 Mg 2+ : 2	[16]
	Solid phase spectrophotometry	o-CDAA c	Tap water	0.48 -25	0.14	0.48	> 20	Co 2+ : 1	[8]
	Spectrophotometry	azocalix[4]arene d	Drinking water	10 -299	8.2	n.d.	< 1	Co 2+ : 3 Cu 2+ : 3	[18]
	Solid phase spectrophotometry	-furil dioxime	Rainfall water	1 -12	0.7	n.d.	> 15	Cu 2+ : 10 Co 2+ : 100	[7]
			Water
	Solid phase fluorescence	Pyridylazo-2-naphthol	Certified Reference	100 -1000	0.07	n.d.	< 1	Co 2+ : 1 Fe 2+ : 1	[9]
			Material
	Fluorescence	Schiff base e	Water	100 -1200	99	n.d.	< 1	Cu 2+ : 1	[19]
	Spectrophotometry	Xylenol orange	Water	1 -5000	0.13	n.d.	> 13	n.d.	[11]
	Fluorescence	Schiff base	Tap water, river water	50 -1700	50	n.d.	< 1	Hg interference	[20]
	Fluorescence	Murexide	Groundwater, seawater, rainwater	7 -100	4	n.d.	< 1	Co 2+ : 5 Cu 2+ : 5	[21]

a 1,5-di(2-hydroxy-5-sulfophenyl)-3-cyanoformazan ; b N'-(1,3 dimethylbutylene)-3-hydroxy-naphthohydrazide ; c ocarboxylphenyldiazoaminoazobenzene ; d 5,17-bis(quinolyl-8-azo)-25,26,27,28-tetrahydroxycalix

[START_REF] Baytak | Determination of lead and nickel in environmental samples by flame atomic absorption spectrometry after column solid-phase extraction on Ambersorb-572 with EDTA[END_REF]

arene ; e N'-(2-hydroxy-3methoxybenzylidene)-2-(benzamido)benzohydrazide ; f silver nanoprisms (AgNPRs) stabilized with glutathione (GSH) ; g boron nitride quantum dots; h in presence of thioglycolic acid as masking agent.

1 H NMR (400 MHz, DMSO-d6) δ (ppm

35 g, 35% yield). Mp : 308 -310 °C; ) δ 9.91 (brs, 1H), 8.60 (d, J = 4.9 Hz, 2H), 8.30 (d, J = 8.1 Hz, 2H), 8.11 (d, J = 8.1 Hz, 2H), 8.03 (d, J = 8.1 Hz, 2H), 7.84 (td, J = 7.5, 2.0 Hz, 2H), 7.32 (dd, J = 7.5, 4.8 Hz, 2H);

13 C NMR (100 MHz, DMSO-d6) δ (ppm) δ 172

										.54, 168.12, 149.00,
	145.84, 136.85, 133.56, 133.24, 130.01, 125.93, 123.61, 122.75 (Fig. S1); HRMS-ESI + (m/z)
	: found [M+H] + 343.1186, calculated C20H15N4O2 requires 343.1190.
	N	O	+	NH 4 OAc	+	OHC	AcOH, 180 microwave, 5 min °C	N	N	CO 2 H
	N	O				CO 2 H		N	N H

Scheme 1 : Synthetic route for 4-[4,5-di(pyridin-2-yl)-1H-imidazol-2-yl]benzoic acid (sensor L).

Table 2 :

 2 Analytical features of the microplate protocol with L.

	Limit of detection (µg L -1 )	1.62
	Limit of quantification (µg L -1 )	5.41
	Linear working range (µg L -1 )	1.6 -40
	R²	0.9972
	Intra-day RSD (%)
	20 µg L -1 (n=8)	1.84
	6 µg L -1 (n=8)	7.75
	Inter-day RSD (%)
	20 µg L -1 (n=5)	2.98
	6 µg L -1 (n=5)	8.87
	3.4 Application to real samples

Table 3 :

 3 Nickel determination in natural waters with microplate procedure.

		Microplate	ICP-MS
	Samples	procedure with L (µg L -1 )	(µg L -1 )
	#1 Drilling	4.47 ±0.12	4.62 ±0.009
	#2 River	5.41 ±0.23	5.38 ±0.003
	#3 Drilling	6.73 ±0.14	6.88 ±0.004
	#4 Source	5.71 ±0.17	5.79 ±0.002
	#5 Source	8.15 ±0.15	8.21±0.006
		Found value	Certified value
	Groundwater ERM®-CA615 a	24.94±0.31	25.3±1.1

Acknowledgements

The work presented in this publication was funded by the French Research Agency ("SMART-3D" project, ANR-18-CE04-0005).


Alice Normand

Frédérique Autin

Jean-Claude Croizet

Running head: EVALUATIVE PRESSURE AND PERCEPTUAL LOAD Evaluative Pressure Overcomes Perceptual Load Effects

Keywords: Evaluative pressure, Attentional set, Perceptual load, Top-down attention, Response conflict

come

Evaluative pressure overcomes perceptual load effects

The ability to ignore irrelevant information to focus on what is important is essential for everyday life. Being distracted from one's ongoing activity can have negative repercussions, from slight disturbance (e.g., breaking your reading flow) to some vital issue (e.g., taking your attention off the road). A great deal of research in psychology has attempted to identify the determinants of focused attention in order to better understand the conditions under which distraction occurs. The present article investigates an overlooked determinant of attentional distraction: the evaluative context of the performance situation.

The reasons why task-irrelevant stimuli can drift attention away from one's primary goal are multiple. Some stimuli have the potential to capture our attention in a bottom-up way, e.g. when they appear abruptly [START_REF] Yantis | Stimulus-driven attentional capture[END_REF], are of a specific color [START_REF] Theeuwes | Perceptual selectivity for color and form[END_REF], or are in motion [START_REF] Folk | The structure of attentional control: Contingent attentional capture by apparent mo-tion, abrupt onset, and color[END_REF], but the extent to which they distract us can be modulated by top-down control settings that tune attention towards the most relevant features to task resolution [START_REF] Folk | Selectivity in distraction by irrel-evant featural singletons: Evidence for two forms of attentional capture[END_REF]. As you drive along and are searching for a green sign indicating a highway direction, you will be more distracted by a flashy billboard if it is green (i.e., a taskrelevant distractor) than if it is blue (i.e., a task-irrelevant distractor; see [START_REF] Gronau | Distractor interfer-ence in focused attention tasks is not mediated by attention capture[END_REF]. Thus whether one distractor carries some prioritized features or not will determine its distracting effect.

Although much effort has been devoted to understanding how the features of irrelevant stimuli interact with the ongoing activity, research has only just begun to investigate the potential influence of external factors, such as the immediate situation of performance.

Selective attention rarely operates in situations that are neutral for individuals. On the contrary, in many situations performing at one's best carries implications for both future opportunities and self-evaluation [START_REF] Decaro | Choking under pressure: Multiple routes to skill failure[END_REF]. Research in social cognition has well established that self-evaluative performance situations affect selective attention and the ability to resist cognitive distraction. Evaluative situations are known to trigger evaluative pressure and represent a potential threat to self image [START_REF] Decaro | Choking under pressure: Multiple routes to skill failure[END_REF], which often brings about concerns that take away attention from the task at hand and reduces the amount of information that can be processed [START_REF] Autin | Improving working memory efficiency by reframing metacognitive interpretation of task difficulty[END_REF][START_REF] Crouzevialle | Performance-approach goals deplete working memory and impair cognitive performance[END_REF]. Attention must then be prioritized to the most relevant information at the expense of less relevant information, thereby generating attentional focusing [START_REF] Muller | The focusing effect of self-evaluation threat in coaction and social comparison[END_REF]. Initial evidence revealed that individuals in evaluative situations show less Stroop interference [START_REF] Huguet | Social presence effects in the Stroop task: Further evidence for an atten-tional view of social facilitation[END_REF], make less illusory conjunctions [START_REF] Muller | Coaction and upward social comparison reduce the illusory conjunction effect: Support for dis-traction-conflict theory[END_REF], and appear less sensitive to nonrelevant abrupt onsets [START_REF] Muller | The focusing effect of self-evaluation threat in coaction and social comparison[END_REF][START_REF] Normand | Upward social comparison gener-ates attentional focusing when the dimension of comparison is self-threatening[END_REF].

Although evaluative pressure may enhance attentional engagement on relevant information at the expense of distractors, [START_REF] Normand | Does evaluative pressure make you less or more distractible? Role of top-down attentional control over response selection[END_REF] have demonstrated that this is actually dependent on the matching between distractors' attributes and task goals. When the task required locating a green target, participants under evaluative pressure gave greater priority to any green stimulus. Consequently, distractors that did not carry this prioritized feature (red distractors) were filtered out and did not disturb individuals' attention, while distractors carrying this prioritized feature (green distractors) received attention and created greater distraction [START_REF] Normand | Does evaluative pressure make you less or more distractible? Role of top-down attentional control over response selection[END_REF]study 2). Under evaluative pressure, individuals' attentional processing becomes more contingent on distractor features, specifically at the response level [START_REF] Normand | Does evaluative pressure make you less or more distractible? Role of top-down attentional control over response selection[END_REF]study 4). By reinforcing featurebased attentional sets, evaluative pressure results in more (or less) distraction by the irrelevant information when it matches (does not match) the individuals' attentional set.

Nevertheless, according to the load theory of attention [START_REF] Lavie | Blinded by the load: Attention, awareness and the role of perceptual load[END_REF], the contingency of attentional distraction only applies when the focus task does not exhaust perceptual resources (cf. [START_REF] Lavie | Blinded by the load: Attention, awareness and the role of perceptual load[END_REF]p. 2). The core assumption of the load theory of attention is that when the task exhausts the perceptual resources, it prevents attention from spilling over to distractors, which then no longer interfere [START_REF] Lavie | Attention, Distraction, and Cognitive Control Under Load[END_REF].

Distractors would interfere with performance on low perceptual load tasks (e.g., involving just one relevant stimulus) but not on high perceptual load tasks (e.g., involving six or more stimuli; [START_REF] Lavie | Distracted and confused?: Selective attention under load[END_REF].

The load theory of attention does not address the possibility that distractor's properties and feature-based selection modulate the perceptual load effect on attentional distraction. In high perceptual load conditions, irrelevant information would not receive attention, regardless of the match between its features and the task at hand [START_REF] Forster | Failures to ignore entirely irrelevant distractors: The role of load[END_REF]Experiment 4).

Nevertheless, individuals under evaluative pressure are more sensitive to the match between one stimulus' features and the attentional set (i.e., the prioritized features that allow task resolution), which can increase interference from perceptually task-relevant distractors [START_REF] Normand | Does evaluative pressure make you less or more distractible? Role of top-down attentional control over response selection[END_REF]. The stricter attentional set hypothesis thus predicts that task-relevant distractors receive attentional priority and conflict with response selection when individuals are under evaluative pressure, regardless of the level of perceptual load. The present research aims to test the attentional impact of evaluative pressure under high perceptual load conditions, which according to the load theory [START_REF] Lavie | Blinded by the load: Attention, awareness and the role of perceptual load[END_REF] should fully prevent attentional distraction.

To test the stricter attentional set hypothesis under different levels of perceptual load, we borrowed the modified flanker paradigm widely used in research on perceptual load [START_REF] Lavie | Distracted and confused?: Selective attention under load[END_REF][START_REF] Lavie | Load theory of selective attention and cognitive control[END_REF]. This task consists of identifying a target letter (an X or an N) in low or high perceptual load sets flanked by a compatible or an incompatible distractor (a X or a N). Incompatible flankers conflict with response identification thereby creating a flanker-compatibility effect. Following the perceptual load hypothesis, we predicted that high perceptual load prevents individuals in a control condition from allocating attention to the flanker, thereby annihilating the flanker-compatibility effect.

However, the flanker is a task-relevant distractor since it carries the important features for task resolution (i.e., it is identical to the targets; [START_REF] Buetti | The flanker effect does not reflect the processing of "task-irrelevant" stimuli: Evidence from inattentional blindness[END_REF]. According to the recent findings that evaluative pressure reinforces feature-based attention settings, we hypothesized that high perceptual load would not prevent individuals in the evaluative pressure condition from processing the flanker. We expected them to show greater flankercompatibility effects under high perceptual load conditions than control participants. They all had normal or corrected-to-normal vision. They were randomly assigned to one of the two experimental conditions: evaluative pressure or no evaluative pressure. Three participants were excluded from the analysis, two due to high error rates and abnormal reaction times (high studentized deleted residuals and Cook's distances) and one for expressing suspicion.

Method

Material and procedure. On arrival, participants were informed that they were about to take an attentional task. In the evaluative pressure condition, the experimenter introduced the task as "an evaluation of attentional capacity that is linked to intellectual ability".

Participants were also led to believe that they would get a final score and the experimenter sat next to them throughout the session [START_REF] Harkins | Mere effort as the mediator of the evaluation-performance relationship[END_REF]. In the control condition, the task was introduced as a device to "study the effects of training on perception" and the experimenter stated that individual performance would automatically be merged with the others' performances, and left the participant alone in the cubicle [START_REF] Normand | Does evaluative pressure make you less or more distractible? Role of top-down attentional control over response selection[END_REF].

Participants then completed the flanker task, which was identical to that of [START_REF] Forster | High perceptual load makes everybody equal eliminating individual differences in distractibility with load[END_REF]. Each trial started with a 500-ms presentation of a fixation cross ("+"), which was immediately followed by the presentation of the task display for 100 ms. The task display consisted of a circle (1.61° radius) of six letters centered at the fixation cross, plus a peripheral distractor letter, the flanker, presented to the left or to the right of the circle, 1.41° away from the nearest circle letter. Each of the letters in the circle subtended 0.6° by 0.4°, and the distractor letter subtended 0.8° by 0.5°. Each circle contained one of the targets (X or N) and participants had to indicate which of the target letters was present in the circle by pressing a key on the numerical pad as quickly as possible without sacrificing accuracy. The flanker was equally likely to be X, N, or Z, and participants were instructed to ignore it. Then for onethird of the trials, the flanker was the same as the target lettere.g., a flanker X and a target X (i.e., compatible trials)and was not expected to conflict with response selection. For twothirds of the trials, the flanker was different from the target letter: for half of these trials, the flanker was a neutral letter, Z (i.e., control trials). For the other half of these trials, the flanker was the alternate target lettere.g., X for an N target or N for an X target (i.e., incompatible trials)which could create a response conflict and delay in responding. In the high-load condition, the letters H, M, K, Z, and W were randomly placed in the non-target circle positions in a different order in one trial from the other. In the low-load condition, the nontarget letters were all small o's (0.15°). Target position, distractor position and identity, and their combinations were counterbalanced. Examples of the trials are presented in Fig. 1A.

After two example trials and 12 practice trials for each load condition, participants completed four blocks of 72 trials: two low-load (L) and two high-load (H) blocks in a counterbalanced order. Four versions of the task were then created: HLHL, HLLH, LHHL, and LHLH.

After the flanker task, manipulation checks were administered, and participants were thoroughly debriefed and thanked.

Results

Manipulation checks. Participants in the evaluative condition reported the task measured intellectual capacities to a greater extent (M = 6.41; SD = 0.71) than control participants (M = 2.89; SD = 1.94), F(1, 33) = 49.84, p < .001,  2 p = .60. They also reported feeling more evaluated (M = 4.65; SD = 1.58) than control participants (M = 3.44; SD = 1.85), F(1, 33) = 4.24, p = .047,  2 p = .11.

Reaction time.

Reaction times (RT) less or greater then 3 SD from the individual mean reaction time were excluded from the analyses; eliminating less than 0.5 % of the data.

Correct RTs 1 were subject to a 2 (evaluative pressure: evaluative, non evaluative) x 2 (flanker compatibility: compatible, incompatible) x 2 (perceptual load: high, low) mixed ANOVA, with the first factor varying between participants. Results indicated no main effect of evaluative pressure, F(1, 33) = 0.25, p = .619. Analyses showed a main effect of flanker compatibility indicating longer RTs on incompatible trials (M = 671; SD = 113) than on compatible trials (M = 647; SD = 106), F(1, 33) = 20.66, p < .001,  2 p = .20. Perceptual load also had a main effect on RTs, F(1, 33) = 80.81, p < .001,  2 p = .71. RTs on high-load trials 1 Mean error rate was .14. Error rate was greater in the high-load condition than in the low-load condition, F(1, 33) = 49.71, p < .001,  2 p = .60 and the flanker compatibility effect on error rates was greater in the low-load than in the high-load condition, F(1, 33) = 5.15, p = .03,  2 p = .13. No main effect or interaction with evaluative pressure was found, Fs < 1.

were longer (M = 805; SD = 184) than RTs on low-load trials (M = 513; SD = 93). A nonpredicted interaction between evaluative pressure and perceptual load reached significance, F(1, 33) = 4.23, p = .048,  2 p = .11. Focused contrast comparisons revealed that, when perceptual load was low, participants under evaluative pressure were slower (M = 556; SD = 89) than control participants (M = 471; SD = 78), F(1, 33) = 8.98, p = .005,  2 p = .21. When perceptual load was high, RTs did not differ according to pressure conditions, F(1, 33) = 0.59, p = .447 2 . The interaction between flanker compatibility and perceptual load predicted by the load theory of attention did not reach significance, F(1, 33) = 1.78, p =.191. However the expected three-way interaction between evaluative pressure, flanker compatibility and perceptual load was significant, F(1, 33) = 5.47, p = .026,  2 p = .14. This interaction, shown in Figure 1B, was further decomposed by pressure conditions. Reproducing previous findings from [START_REF] Lavie | Load theory of selective attention and cognitive control[END_REF], participants in the control condition showed a reduced flankercompatibility effect as perceptual load increased (M low perceptual load = 41 ms and M high perceptual load = -18 ms), F(1, 33) = 6.95, p = .013,  2 p = .17. However and as predicted by the stricter attentional set hypothesis, participants in the evaluative pressure condition showed a persistent flanker effect regardless of perceptual load level (M low perceptual load = 31 ms and M high perceptual load = 47 ms), F(1, 33) = 0.48, p = .489. While evaluative pressure did not moderate the effect of the flanker at a low-level of perceptual load [F(1, 33) = 0.62, p = .435], the flanker-compatibility effect at a high level of perceptual load was stronger for participants under evaluative pressure (47 ms) than for control participants (-18 ms), F(1, 33) = 4.29, p = .046,  2 p = .11. In other words, being under evaluative scrutiny made participants more prone 2 Slowing down responses could be interpreted as a motivation to be accurate [START_REF] Mcfall | Testing the mere effort account of the evaluation-performance relationship[END_REF]). Yet even if evaluated participants were slower on the low-load trials, they were neither more accurate nor slower on the high-load trials precluding a clear interpretation in terms of motivation.

to the attentional interference of the flanker even in a high-perceptual load condition that usually exhausts perceptual capacity.

Discussion

The present study investigated the effect of evaluative pressure on attentional distraction in task load conditions that normally prevent individuals from being distracted.

Individuals under the scope of evaluation exert higher control over their attention by being more selective [START_REF] Muller | The focusing effect of self-evaluation threat in coaction and social comparison[END_REF]. Recent research showed that this higher selectivity translates into stricter feature-based priority settings that are contingent on task requirements [START_REF] Normand | Does evaluative pressure make you less or more distractible? Role of top-down attentional control over response selection[END_REF]. The goal of the present study was to investigate whether the higher sensitivity to task-relevant distractors in conditions of evaluative pressure remains at a high level of perceptual load, known to reduce distractibility. The load theory of attention proposes that distraction diminishes as perceptual loadusually the number of task goal-relevant items increases [START_REF] Lavie | Distracted and confused?: Selective attention under load[END_REF]. Perceptual load would exhaust perceptual resources, leaving no resource for distractor processing, which no longer interfere. To put together the predictions from the evaluative pressure and perceptual load frameworks, we used a flanker task with a manipulation of perceptual load. In this response conflict task, the distractors are task-relevant distractors (i.e., they are identical to the targets; [START_REF] Buetti | The flanker effect does not reflect the processing of "task-irrelevant" stimuli: Evidence from inattentional blindness[END_REF]. As evaluative pressure enhances feature-based selection, we hypothesized that participants in an evaluative situation process the flankers to a greater extent than control participants, irrespective of the level of perceptual load.

Replicating previous findings from the literature, we found the bottom-up effect that increasing perceptual load decreased the flanker-compatibility effect for participants in the control condition. Nevertheless and in line with the stricter attentional-set hypothesis, perceptual load did not moderate the flanker interference for participants under evaluative pressure. As compared to control participants, participants who believed that their intelligence was being assessed kept on processing the flanker even though the level of perceptual load was supposed to prevent them from doing so. This finding supports the idea that evaluative pressure biases individuals' attention and response elaboration towards any stimuli that carry task-relevant features such as the flankers, especially as task difficulty increases (i.e., when the perceptual load is high). This top-down influence on attention overcomes the bottom-up effect of perceptual load. Our paper thus contributes to refining the conditions under which distractibility is reduced by pointing out an overlooked alternative factor influencing attentional selection even at high levels of perceptual load: the situational context in which selective attention occurs, and more specifically its potential threat for self-evaluation.

The present finding that perceptual load did not reduce participants' distraction when they were under evaluative pressure challenges the theoretical assumptions of the perceptual load theory [START_REF] Lavie | Distracted and confused?: Selective attention under load[END_REF]. Using the resource limitation metaphor, the load theory of attention makes the assumption that when perceptual load is high, relevant items capture all attentional resource in a bottom-up way, leaving no resource to distractors. Such a unitary resource view of attentional selection cannot account for the present findings. Indeed, when participants were under evaluative pressure, a high load of relevant processing did not prevent them from allocating attention to the distractors. To reconcile this finding with the resource view of the load theory, one would need to assume that evaluative pressure increases attentional resources, which not only does not find any support in the literature but also contradicts numerous studies showing that evaluative threat actually exhausts cognitive resources (see [START_REF] Schmader | An integrated process model of stereotype threat effects on performance[END_REF] for a review). In fact, our results echo fairly well a growing body of studies that have obtained similar interference effects in both low and high load conditions as a result of negative emotional stimuli (Srinivasan & Gutpa, 2010; study 2) or top-down attentional sets [START_REF] Benoni | Attentional sets influence perceptual load effects, but not dilution effects[END_REF][START_REF] Theeuwes | Attentional set interacts with perceptual load in visual search[END_REF] and that have consequently raised conceptual issues for the perceptual load theory (see [START_REF] Benoni | Conceptual and methodological concerns in the theory of perceptual load[END_REF] for a review). [START_REF] Tsal | Diluting the burden of load: Perceptual load effects are simply dilution effects[END_REF] demonstrated that what were conceived as perceptual load effects were simply 'dilution' effects. Based on the attention gradient theory [START_REF] Laberge | Theory of attentional operations in shape identification[END_REF][START_REF] Logan | Cumulative progress in formal theories of attention[END_REF], the dilution account argues that a distractor causes interference when its representation is strong enough to activate the target opposite-response. When neutral stimuli are added to a display to increase perceptual load, their features compete with those of the distractor, thereby degrading the quality of its representation. A degraded representation of the distractor may not be strong enough to activate any response and to create interference. It would therefore be the dilution of distractor interference, not the unavailability of spare perceptual resources that eliminates the flanker interference in large set-size displays [START_REF] Benoni | Conceptual and methodological concerns in the theory of perceptual load[END_REF][START_REF] Chen | Perceptual load vs. dilution: The roles of attentional focus, stimulus category, and target predictability[END_REF]. The dilution account of distractor processing is in better accordance with our findings. Increasing the number of items to scan in order to identify the target in the flanker task would dilute the distractor effect to a lesser extent for participants going through evaluative stress. Indeed, their higher prioritization of task-relevant features [START_REF] Normand | Does evaluative pressure make you less or more distractible? Role of top-down attentional control over response selection[END_REF] may contribute to lower thresholds that allow behavioral interference from a task-relevant distractor [START_REF] Gronau | Distractor interfer-ence in focused attention tasks is not mediated by attention capture[END_REF][START_REF] Gronau | Dissociations of personally significant and task-relevant distractors inside and out-side the focus of attention: A combined behavioral and psychophys-iological study[END_REF][START_REF] Ro | Covert orienting to the locations of targets and distractors: Effects on response channel activation in a flanker task[END_REF].

As a result, evaluative pressure would make people more disturbed by task-relevant distractors even when their attention is diluted by an increased number of relevant stimuli.

Finally, the present research has important implications with regard to the impact of evaluative situations on performance. During an important test or exam, individuals will process and answer in priority any information that carries relevant features for task resolution, even when the information is potentially misleading. Such a feature-based selection is inappropriate for filtering out highly distracting stimuli whose features are identical to the important features for the task. Here we highlight the robustness of this selection bias under evaluative pressure by demonstrating that it keeps on creating distraction even though there is much relevant information to deal with in the task at hand. Unlike the perceptual load theory's claim that high perceptual load makes everybody equal [START_REF] Forster | High perceptual load makes everybody equal eliminating individual differences in distractibility with load[END_REF], the present research suggests that increasing processing load of important information in high-stake evaluative situations does not prevent individuals from unwanted distraction.

  Participants and design. Based on previous studies manipulating evaluative pressure, we set the sample size at 40. Two scheduled participants did not show up, leaving us with a sample of 38 undergraduates at the University of Poitiers who participated for course credit.

Figure 1 .

 1 Figure 1. Sample of trials in the flanker task as a function of perceptual load and flanker

Acknowledgments Frédérique Autin is now at Institut des Sciences Sociales, University of Lausanne, Switzerland. This research is based on the doctoral dissertation presented at the University of Poitiers by Alice Normand under the supervision of Jean-Claude Croizet. The research was supported by grants from the Contrat Projet Etat Région (13e CPER programme 11-Contexte), a Fulbright scholarship, and a bourse de mobilité from the Region Poitou Charentes awarded to Jean-Claude Croizet.

This research is based on the doctoral dissertation presented at the University of Poitiers by the first author under the supervision of the third author. The research was supported by grants from the Contrat Projet Etat Région (13e CPER programme 11-Contexte), a Fulbright scholarship and a bourse de mobilité from the Region Poitou Charentes awarded to the third author.