Eng-Poh Ng
email: epng@usm.my

Aleid Ghadah

Séverinne Rigolet

T Jean Daou

Svetlana Mintova

Tau Chuan

Severinne Rigolet

Micro-and Macroscopic Observations of the Nucleation Process and Crystal Growth of Nanosized Cs-Pollucite in Organotemplate-free Hydrosol

teaching and research institutions in France or abroad, or from public or private research centers.

Introduction

Zeolites are crystalline microporous minerals composed of aluminate and silicate tetrahedral units. These molecular sieves are generally used in adsorption, ion-exchange and catalysis owing to their high ion exchange capacity and porosity, and unique framework structure. [1][2][3][4][5] In recent years, decreasing the scale of crystallite size of zeolites to nanometer regime (<100 nm) has attracted immense research interest because of their exceptional properties (e.g. high external surface area, fast diffusivity, high surface charge density, high colloidal stability, etc.) and greater potentiality that is directly related to their particle size. [6][7][8][9] Up to now, more than 240 types of zeolite frameworks have been synthesized with only about 20 types of zeolites and related microporous materials can be obtained in nanocrystal forms (ABW, 10 AEI, 11 AFI, 12 AFO, 13 ANA, 14 *BEA, 15 CHA, 16 EDI, 7 EMT, 17 FAU, 18,19 GIS, 20 LTA, 21 LTJ, 22 LTL, 23 MEL, 24 MER, 25 MFI, 26,27 MOR, 28 SOD 29 ).

Cs-pollucite (CsAlSi2O6) is a rare alkali metal zeolite. It has three-dimensional channel with 8-membered ring pore size (pore opening 2.43 Å) forming ANA framework structure. [START_REF]IZA-SC Database of Zeolite Structures[END_REF] Cs-pollucite has recently been reported as a promising basic catalyst and host for storing radioactive cesium. [START_REF] Yokomori | [END_REF] In general, the synthesis of Cspollucite involves hydrothermal treatment at high temperature (200-300 °C) and pressure (300-850 bar) where natural zeolite [START_REF] Yokomori | [END_REF] and soil 32 are used as aluminosilicate sources. Its synthesis condition which uses high pressure and temperature, however, is considerably dangerous and proper reaction vessels with safety build in have to be employed.

The synthesis of nanosized zeolites requires a specific environment called supersaturation where such conditions allow control of the ultimate crystal size via nucleation process. In order to achieve this condition, harmful and costly organic templates in large excess amount are needed which makes the industrial scaleup process to be unfeasible and environment-unfriendly. 21 Hence, fast crystallization of Cs-pollucite nanocrystals under very mild (low pressure and temperature) and eco-friendly (organotemplate-free) condition is still a great challenge in zeolite research.

In this paper, the induction, nucleation and crystal growth of Cs-pollucite zeolite nanocrystals in the organotemplate-free precursor suspension are reported. Unlike previous work, [START_REF] Yokomori | [END_REF]32 the formation evolution of zeolite is studied using a very reactive hydrosol under microscopy and spectroscopy where the crystallization time is significantly reduced from hours to minutes.

Experimental Section

Synthesis of Cs-pollucite zeolite nanocrystals

Initially, cesium hydroxide monohydrate (10.500 g, 99.5%, Sigma-Aldrich), aluminum hydroxide (1.242 g, extra pure, Acros) and distilled water (8.063 g) were stirred at 105 °C for 18 h until a clear solution was obtained. A clear silicate solution was prepared by dissolving HS-40 (6.581 g, 40% SiO2, Sigma-Aldrich) and cesium hydroxide monohydrate (5.550 g) into distilled water (6.400 g). Then, the aluminate solution was slowly mixed into to the silicate solution under magnetic stirring (450 rpm). A clear precursor suspension with a chemical composition of 5.5SiO2:1Al2O3: 6Cs2O:140H2O was obtained. The precursor solution was transferred into an autoclave and heated at 180 °C for 120 min before the solid product was separated, purified using high-speed centrifugation (10000 rpm, 8 min) and freeze-dried. The samples heated at different time intervals (10, 25, 30, 45 and 60 min) were also prepared following the same procedure.

Characterization

The solid products were analyzed by using a PANalytical X'Pert PRO XRD instrument system with CuKα radiation (λ = 1.5406 Å). The degree of crystallinity was computed by comparing the intensity of the three most important peaks at 24.3, 26.1 and 30.7 of Cs-pollucite sample (120 min) as 100% crystalline. The average sizes of zeolite crystals were estimated by using the Scherrer equation. TEM images of amorphous, semi-crystalline and crystalline solids were recorded using a Philips CM12 transmission electron microscope operating at 200 kV. The average crystal sizes of zeolites were also estimated using the Image J software by randomly selecting the 50 particles through TEM images. The functional groups of the solids were identified by Fourier Transform Infrared spectroscopy (FTIR) using a Perkin Elmer's System 2000 spectrometer in the wavenumber range of 400-4000 cm-1 (KBr: sample ratio = 50:1). The composition, or Si/Al ratio, of the solids was measured by using ICP-OES spectrometry (Vista MPX, Varian Inc.). Prior to analysis, the solid was first dissolved in a 0.5 M HF solution where boric acid was also added to minimize interferences of fluoride during the analysis. The 29 Si MAS NMR spectroscopy measurement was performed using a Bruker Avance II 400 MHz spectrometer system (9.4 Tesla). The sample powder was packed into a 4 mm ZrO2 rotor and spun at 12 kHz. The chemical shifts were referred to TMS. A single pulse excitation was applied with a /6 length of 2.1 µs, a recycle delay of 80s, accumulated during 2000 scans. 33 The 27 Al MAS NMR spectra were recorded using different configurations (9.4 Tesla; rotor 2.5 mm; 50000 scans; p/12 rf pulse length of 0.7 ms; recycle delay of 1 s; spinning rate 25 kHz). The chemical shifts was referred to external [Al(H2O)6] 3+ in AlCl3 aqueous solution.

Catalytic reaction study in cyanoethylation of amines

Initially, dried Cs-ABW (0.50 g, 100 °C, 6 h), acrylonitrile (19 mmol, 99%, Merck) and dipropylamine (76 mmol, 99%, Merck) were mixed in a quartz tube (10 mL). The tube was sealed with a silicone cap and subjected to instant heating using a Monowave 50 non-microwave instant heating reactor (Anton Paar) at 180 °C for specific time periods. The resulting reaction solutions after being isolated from the solid catalyst were injected into a GC-FID (Agilent 7890A) and a GC-MS (Agilent 7000 Series Triple Quad GC/MS) instruments for chromatography identification purpose where toluene was used as an internal standard. For the reactions using NaOH and KOH as the catalysts, 1.984 mmol of hydroxide, which is equivalent to 0.50 g of nanosized Cs-pollucite, was used.

Results and discussion

Macroscopic study of the formation of nanosized Cs-pollucite

The kinetics of the formation of Cs-pollucite nanozeolite from a clear precursor solution was initiated by mixing both the silicate and aluminate solutions. The solution was subjected to hydrothermal treatment at 180 C for 7 min. It was found that the precursor remained clear and no solid product was recovered. However, it turned to cloudy after 15 min of heating. A soft gel was separated upon centrifugation and an amorphous solid with 15.70% yield was collected after purification and freeze-drying (Figures 123). As seen from the TEM image, the amorphous solid exhibited thin sheet like structure (Figure 4a).

A soft gel was still obtained with heating time extended to 25 min. At this stage, the solid yield significantly dropped to 8.45%. According to XRD analysis, the sample was still amorphous, but the amorphous hump at 2θ = 18-30° has shifted to 2θ = 24-33° (Figure 2b). The TEM image showed that morphological change of amorphous solid occurred where the amorphous entities (ca. 15 nm) with irregular shape was formed (Figure 4b). The solid yield increased gradually to 21.26% upon heating to 30 min. At this time, several diffraction peaks slowly appeared at 2 = 24.3 [321], 26.1 [400], 30.7 [332] and 37.2 [440] while the amorphous phase was still dominant (17.78% crystallinity) (Figures 123). Thus, it revealed the formation of Cs-pollucite nuclei in this sample. The XRD investigation was further supported by TEM study where crystalline particles (ca. 21 nm) embedded in the amorphous solid were observed (Figure 4c). As seen, the semi-crystalline nuclei had nearly identical crystallite size as the amorphous single particles. The solid yield kept increasing and reached 31.93% when the hydrothermal heating time was extended to 45 min (Figure 1). All the diffraction peaks corresponding to ANA-type structure were clearly shown with the crystallization rate increasing up to 46.25% (Figure 2d). Further prolonging of the heating time to 60 min shows an enhancement of crystallization rate reaching 83.20%. At this stage, the intensity of all diffraction peaks became stronger and the amorphous phase was no longer dominant in the sample (83.20%). The TEM image also showed that the shape of pollucite was becoming more pronounced where the single nanocrystals of pollucite with trapezohedron shape identical to that of theoretical one, were captured (Figure 4d). As can be seen, amorphous thin layer was still covering the surface of nanocrystals and the nanocrystals were about to dissociate from each other to become an independent single crystal particle (ca. 29 nm) (Figure 4d,e). After 120 min of heating, discrete and fully crystalline Cs-pollucite nanoparticles were obtained (Figure 123). As seen, no amorphous (d,e) 60 min and (f, g, h) 120 min. Inset of (d) is the theoretical shape of ANA crystalline solid while inset of (g) is the SAED pattern of sample heated for 120 min. entities were detected. Instead, the nanocrystals grew further and reached ca. 53 nm (Figure 4f,g). The selected area electron diffraction (SAED) pattern of nanosized Cs-pollucite single crystal viewed along [111] zone axis was also recorded (inset Figure 4g). The SAED pattern showed the nanoparticles to be highly crystalline in nature. The HRTEM image of nanosized Cs-pollucite after 120 min was also captured (Figure 4h). Clear lattice fringes with a spacing of 0.42 nm were observed which corresponded to ANA-type zeolite (theoretical pore size is 0.42 × 0.16 nm 2 ). 30

Microscopic study of the formation of nanosized Cs-pollucite

The structural evolution of nanosized Cs-pollucite not only can be explained by their macroscopic properties but also by their microscopic properties. The atomic and molecular spectroscopy analyses were hence used to follow the induction, nucleation and crystallization of pollucite nanocrystals. Figure 5 shows the IR spectra of the samples heated at different time intervals. For the sample heated for 15 min, four IR absorption bands were recorded at 1228, 1114, 800 and 474 cm -1 which were attributed to the amorphous aluminosilicate solid (Figure 5a). 7 Two signals which were assigned to the stretching and bending vibrations of O-H groups of water were also detected at 3470 and 1646 cm -1 , respectively.

The IR spectrum pattern changed completely when the sample was further heated to 25 min. For instance, the bands at 474 and 800 cm -1 , which were assigned to the bending vibration of TO4 (T = Si or Al) and symmetric stretching vibration of Si-O-T, respectively, were disappeared (Figure 5b). 34 In addition, the IR bands at 1228 and 1114 cm -1 assigning to the internal vibrations of Si-O-T (T = Si, Al) asymmetric stretching mode were red shifted to 1133 and 1053 cm -1 . A new IR signal corresponded to Si-OH bending mode was also detected at 863 cm -1 . 35 Further heating the precursor to 30 min evidenced the emergence of weak peaks at 769, 725 and 620 cm -1 which are characteristic of highly distorted 8-rings subunits present in the pollucite zeolite (Figure 5c). 14 Furthermore, the IR band due to the bending vibration of TO4 (T = Si or Al) re-appeared again at 447 cm -1 . The intensity of these four bands kept increasing with heating time indicating phase transformation of sample from amorphous to crystalline solid (Figure 5c-e). Moreover, the bands at around 1130 and 1020 cm -1 were red shifted to lower wavenumbers during crystallization process due to participation and insertion of Al into the pollucite zeolite framework that resulted in a decrease in the Si/Al ratio.

The change in the chemical composition (e.g. Si/Al ratio) was further supported by ICP-OES spectroscopy. As shown in Table 1, the initial Si/Al was 8.11. With increasing the heating time to 25 min, the Si/Al ratio significantly dropped to 4.74 showing the direct participation of Al in the crystallization process. The Si/Al ratio continued to drop but with slower rate to 3.27 after 30 min of heating. The Al content in the solid became almost constant after 60 min and an Si/Al ratio of 2.12 was reached at the end of the crystallization process. On the other hand, the Cs content in the solids showed opposite trend. The initial Cs/Al ratio which was 0.37 increased to 0.76 after 25 min and the Cs content slowly raised and reached to nearly unity after 60 min. 27 Al and 29 Si solid state MAS NMR spectroscopy is a very powerful technique to follow the evolution of zeolites and microporous aluminophosphates. [36][37][38][39] Hence, the 27 Al solid state MAS NMR spectra of all samples were also recorded. All spectra only indicated a strong peak at 56-59 ppm which was attributed to the Al species in tetrahedral coordination (Figure 6). Hence, the NMR spectroscopy study could prove the direct participation of Al in the formation of pollucite nanocrystals but it did not give much detailed information on the samples with different crystallinity since this tetrahedral Al species is one of the basic building units in both amorphous and zeolite solids. Nevertheless, the AlTetrahedral peak at ca. -58 ppm became more symmetrical and narrower in the solid sample heated after 30 min, revealing the chemical surrounding of the Al species is becoming more homogeneous when the samples are more crystalline (Figure 6c-e). The 29 Si MAS NMR spectra for samples heated at different time intervals were also recorded (Figure 7). As shown, it provided more useful information on the chemical environment around the Si atoms in the amorphous, semi-and fully crystalline solids. A broad and non-symmetrical peak was observed from -70 to -120 ppm which could be deconvoluted into 4 peaks (Figure 7a). The peak at -111.4 ppm revealed the presence of non-reacted silica species in the form of Si(OSi)4. The peaks at -102.2 ppm was due to the Q4 (Si(OSi)3(OAl)) and/or Q3 (Si(OSi)3(OH)) units, while the peak at -96.8 ppm was attributed to the Q3 (Si(OSi)2(OAl)2) and/or Q3 (Si(OSi)2(OAl)(OH)) units. 36 Another peak observed at -85.5 ppm was due to the Q2 (Si(OSi)(OAl)3) and/or Q3 (Si(OAl)2(OSi)(OH)) units. When the sample was heated to 25 min, the peak at -111.4 ppm disappeared (Figure 7b). Only 2 peaks were observed at -88.7 and -96.6 ppm which were due to Q3 and Q4 units, respectively. Thus, the NMR investigation was in line with the XRD observation on the phase reorganization of amorphous solid. The symmetry peaks attributing to the unique Si crystallographic sites (Q1: Si(OAl)4 and Q2: Si(OSi)(OAl)3) of ANA structure started to appear at ca. -85.5 and -91.0 ppm, respectively after 30 min while another peak due to amorphous Q3 species, viz. (Si(OSi)2(OAl)2) and/or (Si(OSi)2(OAl)(OH)) groups, was slightly shifted due to the change of the chemical environment in semi-crystalline solids (Figure 7c). [START_REF] Engelhardt | Solid state NMR spectroscopy applied to zeolites[END_REF] The latter peak slowly disappeared with time and only 2 peaks at -85.2 and -92.1 ppm were observed by the fully crystalline sample (120 min) (Figure 7d,e).

Nucleation process and crystal growth mechanism of nanosized Cs-pollucite

Cs-pollucite zeolite is normally synthesized under extreme condition (200-300 °C, 300-850 bar) where it is inter-converted from natural zeolite and clay. In order to reduce the zeolite crystal size, supersaturation environment is essential to allow nucleation more favourable than crystal growth. Such condition can be achieved by increasing the pH of precursor via increasing the concentration of organic template and metal hydroxide, or reducing the water content. 41 Furthermore, the use of low temperature allows exploration of metastable crystalline phase with open-framework structure and unique properties. 42 In this work, the crystal growth of nanosized Cs-pollucite zeolite is studied in a very reactive hydrosol free of organic template and using more gentle synthesis condition (180 C, <120 min).

The hydrothermal formation of nanosized Cs-pollucite via organotemplate-free pathway is shown in Figure 8 after visual, spectroscopy and microscopy investigations are considered. Initially, the precursor solution is clear upon mixing of both aluminate and silicate solutions even after stirring for 1 h at room temperature. The precursor is then heated at higher temperature (180 C) to enhance the crystallization rate. In the first 7 min of heating, the precursor solution remains clear and no solid product is formed. In this stage (Stage 1), the Si and Al atoms exist in simple monomeric, dimeric and/or trimeric species forms.

Polymerization starts to take place when the precursor is further heated to 15 min. A cloudy colloidal solution is formed but the solid yield is considerably low (15.70%). The inorganic nutrients are composed of Si(OSi)4, Si(OSi)3(OAl), Si(OSi)3(OH), Si(OSi)2(OAl)2, Si(OSi)2(OAl)(OH), Si(OSi)(OAl)3 and Si(OAl)2(OSi)(OH) units which are present, along with free Cs + and tetrahedral Al species as well, in the precursor (Stage 2).

When the precursor is further heated to 25 min, the solid yield reduces to 8.45% due to the successive dissolution of initial amorphous entity to generate soluble nutrient species for nuclei growth. The XRD, IR and NMR spectroscopy data also show that amorphous phase reorganization into more reactive amorphous intermediate has taken place (Stage 3). The functional groups and the chemical environment of the solid change significantly. Furthermore, the morphology of the solid changes into 3D solid with irregular shape. At this stage, Al 3+ and Cs + species are actively participated in the construction of amorphous framework where Al 3+ is incorporated in the solid as Al tetrahedral form while Cs + serves as extraframework cation and mineralizer.

Polymerization further takes place at 30 min (Stage 4). The -OH groups bound to Al and Si atoms polycondense to form longer polymer chains containing Si(OSi)2(OAl)2), Si(OSi)2(OAl)(OH), Si(OAl)4 and Si(OSi)(OAl)3 units. As a result, more solids precipitate out (solid yield increases). At this stage, Cs-pollucite nuclei, which has almost similar size as the amorphous single particles, are formed and embedded in the bulk amorphous solid as confirmed by XRD and NMR analyses. The crystallization rate speeds up, and the degree of crystallinity is significantly enhanced after 30 min onwards. The nutrients from the amorphous material are gradually consumed and phase transformation from amorphous entity to crystalline particles occurs. After 60 min, the ANA crystalline phase is becoming more dominant (83.20% crystallinity) (Stage 5). Cs-pollucite nanocrystals (ca. 29 nm) with trapezohedron shape are formed but they are still slightly covered by an amorphous thin layer. The nanocrystals are about to dissociate from each other to become an independent single crystal particle. After 120 min of heating, the nutrients in the amorphous entity are completely consumed forming discrete and fully crystalline Cs-pollucite nanocrystals (Stage 6). The crystalline framework of Cs-pollucite is made up of Si(OAl)4 and Si(OSi)(OAl)3 units, producing a high-alumina zeolite (Si/Al ratio = 2.12). The Cs/Al ratio reaches nearly unity because every framework Al species (in tetrahedral form) carrying a negative charge is counterbalanced by a Cs + cation. Furthermore, the nanocrystals also grow further (ca. 55 nm) by consuming the nutrients released from the re-dissolution of less stable and smaller crystal domains by the Oswald ripening rule.

Catalytic reaction study in cyanoethylation of amines

Cyanoethylation of dipropylamine was used as a model reaction to investigate the catalytic properties of nanosized Cs-pollucite. The reaction was performed under non-microwave instant heating condition (180 °C) where this heating mode provides very fast and homogeneous heating similar to microwave heating but with different heating mechanism. 43,44 The results show that the nanosolid catalyst is very active with 89.6% conversion after 50 min of heating (Figure 9). The catalytic performance is also compared with two most common homogeneous base catalysts, namely NaOH and KOH. Interestingly, nanosized Cs-pollucite exhibits stronger catalytic activity than KOH (84.8%) and NaOH (79.7%). Thus, it indicates that Cs-pollucite nanocrystals can be used as an eco-friendly and reusable solid base catalyst in organic syntheses.

Conclusion

A detailed macroscopic and microscopic investigation of crystallization of nanosized Cs-pollucite zeolite in organotemplate-free and clear precursor suspension has been reported. The study shows that Cs-pollucite nanocrystals can be easily obtained within 120 min when a very reactive precursor sol is used. The formation of Cs-pollucite zeolite involves mixing of Al and Si simple units, oligomerization of inorganic species to form initial amorphous solid, successive dissolution and polymerization of oligomers to form active amorphous entity (induction), nucleation, crystallization and finally crystal growth. The resulting nanocrystals, which have crystallite size of ca. 55 nm, display trapezohedron morphology. The colloidal stable Cs-pollucite nanocrystals are high-alumina zeolite (Si/Al ratio = 2.12) and the negative charges induced by the presence of Al atoms in the framework are counter-balanced by Cs + cations. The synthesis reported in this paper is highly appreciated since colloidal stable Cs-pollucite nanozeolite can be crystallized free of organic template and under mild condition (180 °C, < 120 min, < 25 bar) enables safe and simple scale-up operation. Furthermore, the cyanoethylation of dipropylamine catalytic study concludes that Cs-pollucite nanocrystals are a potential solid base catalyst and can be an alternative replacement to NaOH and KOH homogeneous base catalysts.

Figure 1 .

 1 Figure 1. Solid yield after different heating times of hydrothermal treatment.

Figure 2 .

 2 Figure 2. XRD patterns of samples after (a) 15 min, (b) 25 min, (c) 30 min, (d) 45 min, (e) 60 min and (f) 120 min.

Figure 3 .

 3 Figure 3. Crystallization rate of solid products after various heating times.

Figure 4 .

 4 Figure 4. TEM images of samples after (a) 15 min, (b) 25 min, (c) 30 min, (d, e) 60 min and (f, g, h) 120 min. Inset of (d) is the theoretical shape of ANA crystalline solid while inset of (g) is the SAED pattern of sample heated for 120 min.

Figure 5 .

 5 Figure 5. IR spectra of solid products after hydrothermal synthesis for (a) 15 min, (b) 25 min, (c) 30 min, (d) 60 min and (e) 120 min.

Figure 6 .

 6 Figure 6. 27 Al solid state MAS NMR spectra of samples heated after (a) 15 min, (b) 25 min, (c) 30 min, (d) 60 min and (d) 120 min.

Figure 8 .

 8 Figure 8. Mechanism of the formation of nanosized Cs-pollucite zeolite. Inset: Framework structure of solid. Pink: Si or Al atom, and white: O atom. Cs atom is not shown.

Figure 7 .

 7 Figure 7. 29 Si solid state MAS NMR spectra of samples heated after (a) 15 min, (b) 25 min, (c) 30 min, (d) 60 min and (e) 120 min.

Figure 9 .

 9 Figure 9. Cyanoethylation of dipropylamine over (a) nanosized Cspollucite, (b) KOH and (c) NaOH under non-microwave instant heating at 180 °C.

Table 1 .

 1 Si and Al elemental analysis of the solid products obtained after various heating times.

	Samples	Si mg/L mmol/L mg/L mmol/L mg/L mmol/L Al Cs	Cs/Al ratio	Si/Al ratio
	15 min 220.7 7.9	26.2	1.0	47.7	0.4	0.37 8.11
	25 min 146.6 5.2	29.9	1.1 111.4 0.8	0.76 4.74
	30 min 121.5 4.3	35.7	1.3 151.0 1.1	0.86 3.27
	45 min 123.2 4.4	49.1	1.8 222.5 1.7	0.92 2.41
	60 min 121.7 4.3	53.5	2.0 269.4 2.0	1.02 2.19
	120 min 133.4 4.8	60.6	2.2 301.2 2.3	1.01 2.12

Acknowledgments

The financial support from FRGS (203/PKIMIA/6711642) grant is gratefully acknowledged. The doctoral scholarship from University of Hail, Saudi Arabia is also acknowledged.

Micro-and Macroscopic Observations of the Nucleation and Crystal Growth of Nanosized Cs-Pollucite in Organotemplate-free Hydrosol

Eng-Poh Ng, † Aleid Ghadah Mohammad S, Severinne Rigolet, T. Jean Daou, Svetlana Mintova, Tau Chuan Ling Nucleation and crystal growth of nanosized cesium pollucite zeolite from organotemplate-free hydrosol under mild conditions (low pressure and temperature) are followed and reported.


Sophie Goyard

Bianca Balbino

Rebecca S Chinthrajah

Shu-Chen Lyu

Yves L Janin

Pierre Bruhns

Pascal Poncet

Stephen J Galli

Kari C Nadeau

PhD (ORCID ID Laurent L Reber
email: laurent.reber@inserm.fr

PhD Thierry Rose
email: rose@pasteur.fr

A highly sensitive bioluminescent method for measuring allergen-specific IgE in microliter samples

Keywords: IgE, allergy diagnosis, ImmunoCAP, ELISA, bioluminescence, luciferase, nanobody

To the Editor, Measurement of allergen-specific IgE (sIgE), along with the patient's clinical history and results of allergen provocation tests, are fundamental in diagnosing allergic disease [START_REF] Canonica | A WAO -ARIA -GA(2)LEN consensus document on molecular-based allergy diagnostics[END_REF] . The ImmunoCAP assay is used as a standard to quantify sIgE levels [START_REF] Van Hage | ImmunoCAP assays: Pros and cons in allergology[END_REF] . Although this method is sensitive (range, 0.1-100 kUA/L), it requires relatively large amount of plasma (which can be problematic when testing young children), and is also limited by its cost and the need for a specific instrument to analyze the test's results. Therefore, further developments are needed to improve the sensitivity of sIgE detection methods, while markedly reducing the volume of sample required and the cost, without sacrificing assay robustness, reproducibility and accuracy.

Here, we report development of a highly sensitive method for quantifying sIgE levels using a luciferase-linked immunosorbent assay (LuLISA). The IgE LuLISA allows bioluminescent detection of sIgE using an anti-IgE nanobody (single variable heavy immunoglobulin domain [sdAb] or VHH) which recognizes the constant C3 region of human IgE 3 , and is expressed in tandem with the catalytic domain of the enzyme luciferase (nanoKAZ) [START_REF] Inouye | Luminescence enhancement of the catalytic 19 kDa protein (KAZ) of Oplophorus luciferase by three amino acid substitutions[END_REF] (Figure 1A and Figure S1). The anti-IgE nanobody we used for this assay (sdAb026) has an affinity for IgE similar to that of the therapeutic anti-IgE antibody omalizumab (KD 1.4 nM vs. 2.6 nM, respectively [START_REF] Jabs | Trapping IgE in a closed conformation by mimicking CD23 binding prevents and disrupts FcepsilonRI interaction[END_REF][START_REF] Gasser | The mechanistic and functional profile of the therapeutic anti-IgE antibody ligelizumab differs from omalizumab[END_REF] ), and was reported to inhibit interactions between IgE and the two receptors FcεRI and CD23 3 .

To establish a proof-of-concept for the specific detection of sIgE using this method, we prepared dilution series in PBS of recombinant IgE, IgG1 (the major IgG subclass) or IgG4 (the main IgG subclass overproduced during allergen-specific immunotherapy) directed against the house dust mite allergen Der p 2 (Figure 1B). The 3 groups of samples were analyzed using IgE LuLISA. As expected, a concentration-dependent signal arose only for the sample containing anti-Der p 2 sIgE, with a detection limit of ~5x10 -13 M sIgE (~1 pg/mL; ~0.0004 kUA/L) (Figure 1B). We also obtained high sensitivity with recombinant anti-ovalbumin (OVA) IgE, which was detectable by LuLISA at concentrations as low as 5 pg/mL (~0.002 kUA/L) (Figures S2 andS3). The sensitivity of LuLISA was also much higher than that of standard ELISA for the detection of sIgE with an extended dynamic range over 4 orders of magnitude instead of 2 (Figure S3).

Next, we compared the dynamic range and sensitivity of IgE LuLISA versus standard ImmunoCAP, using recombinant OVA sIgE diluted in plasma pooled from 30 healthy donors (Figure 1C). This head-to-head comparison revealed a markedly increased (250-fold) analytical sensitivity of LuLISA compared with ImmunoCAP (Figure 1C). We performed similar experiments with dilution series of a plasma sample from a highly peanut allergic subject, which was again diluted in a pool of plasma from 30 healthy donors (Figure 1D).

ImmunoCAP allowed detection of peanut sIgE in plasma diluted up to 4,050 times, while peanut sIgE was still detected by LuLISA in allergic plasma diluted 100,000 to 300,000 times (Figure 1D). Dilution series of the anti-IgE nanobody-luciferase tandem gave a concentrationdependent signal at a fixed (1:50) dilution of this peanut allergic plasma sample, and confirmed the very low bioluminescent background signal of the IgE LuLISA (Figure S4).

Altogether, these results indicate that the IgE LuLISA has a very high sensitivity and specificity, and could thus potentially be used to quantify IgE in samples from patients with very low sIgE.

However, the cut-off level commonly used in clinical practice to define IgE positivity is 0.35 kUA/L, which can be measured by ImmunoCAP and is much higher than the sensitivity of the IgE LuLISA. Thus, the main advantage of the IgE LuLISA over ImmunoCAP is that it requires extremely low volume of sample. In the case of the sample from the peanut-allergic patient used in Figure 1D, peanut sIgE could still be detected using less than 1 nanoliter of the initial patient's sample. Thus, very large screens of sIgE against arrays of potential allergens can be envisioned using IgE LuLISA, even when patient's sample sizes are limited, automatable in 96 and 384-well plates.

We then sought to further validate this approach by measuring sIgE against total peanut extract, or against the major peanut allergens Ara h 1 and Ara h 2 using 1 L of plasma from 31 healthy donors (obtained from the French blood bank EFS with unknown allergic status) and 82-105 peanut-allergic subjects (collected upon their enrollment into the institutional review boardapproved peanut oral immunotherapy study: safety, efficacy and discovery trial; ClinicalTrials.gov identifier: NCT02103270) [START_REF] Mukai | Assessing basophil activation by using flow cytometry and mass cytometry in blood stored 24 hours before analysis[END_REF] . Dilution series from reference samples with titrated high peanut sIgE were used for assay calibration, to ensure that all plasma samples were analyzed within the linear range of detection of our method (Figure S5). As expected, significantly higher levels of peanut sIgE, Ara h 1 sIgE and Ara h 2 sIgE were detected in plasma samples from peanut allergic subjects as compared to healthy donors (Figure 2A,C,E).

Head-to-head comparison between LuLISA and ImmunoCAP in allergic patients showed a high correlation between both methods (R 2 =0.89, 0.84 and 0.83 for peanut sIgE, Ara h 1 sIgE and Ara h 2 sIgE, respectively) (Figure 2B,D,F). These correlations were calculated using all plasma samples for which sIgE levels were above the detection cut-off of ImmunoCAP (0.1 kUA/L). This was the case for all samples for peanut sIgE. However, 17 out of 82 samples (19.7%) for Ara h 1 sIgE and 3 out of 96 samples (3.1%) for Ara h 2 sIgE were below the detection limit of ImmunoCAP (Figure 2B,D,F). However, all these subjects had clear clinical reactivity to peanut, as assessed by performing double-blind, placebo-controlled food challenge (DBPCFC) and skin prick tests (Table S1). Altogether, these results demonstrate that the IgE 6 LuLISA is highly sensitive and accurate for the clinical detection of sIgE, and requires very low volumes of plasma.

Besides ImmunoCAP, several other methods have been reported for the detection of sIgE, including IMMULITE and, more recently, isotype-specific agglutination-PCR (ISAP) [START_REF] Hamilton | In vitro assays for the diagnosis of IgE-mediated disorders[END_REF][START_REF] Tsai | Isotype-specific agglutination-PCR (ISAP): A sensitive and multiplex method for measuring allergen-specific IgE[END_REF] . IMMULITE appears to be the closest method to LuLISA as it uses a chemiluminescent approach to detect sIgE. However, the reported detection limit for sIgE with IMMULITE is the same as for ImmunoCAP (0.1 kUA/L) [START_REF] Hamilton | In vitro assays for the diagnosis of IgE-mediated disorders[END_REF] . Similarly to LuLISA, detection of sIgE by ISAP can be performed using 1 l of clinical sample. Moreover, the two tests are based on different approaches as ISAP requires chemically-synthesized allergen-DNA (for each type of allergen) and secondary anti-IgE antibody-DNA conjugate for the detection of sIgE by quantitative PCR.

In summary, the IgE LuLISA is a new method for the detection of sIgE of ultra-high sensitivity requiring only very small (1 L or less) plasma sample volumes. The use of bioluminescence offers markedly increased sensitivity and extended dynamic range over classical colorimetric (ELISA) or fluorescent (ImmunoCAP) IgE detection methods. The method is fully automatable and uses commercialized plates and a standard luminometer for the bioluminescent detection of IgE. Thus, IgE LuLISA should be very cost-effective over conventional ImmunoCAP.

Further tests will be performed to extend the potential use of IgE LuLISA for multiplexed detection of sIgE against arrays of allergens.

Figure 1 .

 1 Figure 1. Sensitive and specific detection of allergen-specific IgE by LuLISA. (A) Cartoon

Figure 2 .

 2 Figure 2. Detection of sIgE levels by LuLISA in 1 L plasma samples from healthy donors

  Figure 1

Funding source This work was supported by the Institut Pasteur initiative for valorizing the applications of research (ValoExpress 2016-2017, Innov-IARP Pasteur-Carnot 2019-2020 S.G., Y.L.J., P.P., T.R.) and NIH/NIAID U19AI104209 (S.J.G, R.S.C, S-C.L., and K.C.N). B.B. acknowledges support from the Pasteur -Paris University (PPU) International PhD program and a fellowship from the French "Fondation pour la Recherche Médicale FRM". L.L. Reber acknowledges support from the INSERM and an ATIP-Avenir grant.

Authorship Contributions

Conflicts of interest

The authors declare no competing interests.


Emilie Salvia

Katell Mevel

Grégoire Borst

Nicolas Poirel

Grégory Simon

François Orliac

Olivier M Etard

Astrid Hopfensitz

Olivier Houdé

Jean-François Bonnefon

+ Katell Mevel

Wim De Neys
email: wim.de-neys@parisdescartes.fr

AGE-RELATED NEURAL CORRELATES OF FACIAL TRUSTWORTHINESS DETECTION DURING ECONOMIC INTERACTION +

Keywords: trust game, amygdala, fMRI, trustworthiness detection

come

AGE-RELATED NEURAL CORRELATES OF FACIAL TRUSTWORTHINESS DETECTION DURING ECONOMIC INTERACTION

The human species shows a remarkable ability to trust and cooperate (Thielman & Hilbig, 2015;[START_REF] Tomasello | Why We Cooperate[END_REF]. This ability to trust is considered to be one of the main reasons behind the success of human societies. But while trusting others has many potential benefits, our trust can also be abused and exploited. Consequently, it can be beneficial for humans to accurately judge the trustworthiness of others.

Available evidence suggests that people have a strong tendency to judge the trustworthiness of their interaction partners on the basis of their facial appearance [START_REF] Adolphs | From Faces to Prosocial Behavior: Cues, Tools, and Mechanisms[END_REF][START_REF] Van 't Wout | Friend or foe: The effect of implicit trustworthiness judgments in social decision-making[END_REF][START_REF] Todorov | Face value: The irresistible influence of first impressions[END_REF]. Put differently, we tend to trust people who "look" trustworthy. Research indicates that these facial trustworthiness judgments show very high inter-rater agreement and are made effortlessly in a mere 100 ms or less [START_REF] Todorov | Evaluating faces on trustworthiness after minimal time exposure[END_REF]Wilis & Todorov, 2006). Neuroscientific studies have pointed to a critical role of the amygdala in this process (e.g., [START_REF] Adolphs | The human amygdala in social judgment[END_REF][START_REF] Santos | The role of the amygdala in facial trustworthiness processing: A systematic review and meta-analyses of fMRI studies[END_REF].

In general, the amygdala has long been connected with basic emotional processing and threat detection [START_REF] Pessoa | Emotion and the brain: multiple roads are better than one[END_REF]. Numerous fMRI studies on trustworthiness evaluation found that the amygdala shows an increased activation when participants are presented with untrustworthy looking face stimuli (e.g., [START_REF] Bzdok | ALE meta-analysis on facial judgments of trustworthiness and attractiveness[END_REF][START_REF] Engell | Implicit trustworthiness decisions: Automatic coding of face properties in the human amygdale[END_REF][START_REF] Todorov | Social judgments from faces[END_REF]Mende-Siedlecki, Said, & Todorov, 2013;[START_REF] Freeman | Amygdala responsivity to high-level social information from unseen faces[END_REF][START_REF] Rule | Accuracy and consensus in judgments of trustworthiness from faces: Behavioral and neural correlates[END_REF][START_REF] Winston | Automatic and intentional brain responses during evaluation of trustworthiness of faces[END_REF]. This increased response to untrustworthy faces is sometimes described as following a linear trend while others have found a quadratic response pattern with higher responses at the extremes of the trustworthiness dimension [START_REF] Santos | The role of the amygdala in facial trustworthiness processing: A systematic review and meta-analyses of fMRI studies[END_REF]. In addition, lesion studies indicate that patients with amygdala damage judge faces to look abnormally trustworthy and approachable [START_REF] Adolphs | From Faces to Prosocial Behavior: Cues, Tools, and Mechanisms[END_REF][START_REF] Adolphs | The human amygdala in social judgment[END_REF].

While it is well established that people readily make facial trustworthiness judgments, it is also clear that these judgments are rarely accurate. That is, people who look untrustworthy do not necessarily behave untrustworthily [START_REF] Efferson | Viewing men's faces does not lead to accurate predictions of trustworthiness[END_REF][START_REF] Olivola | Social attributions from faces bias human choices[END_REF][START_REF] Todorov | Social attributions from faces: Determinants, consequences, accuracy, and functional significance[END_REF][START_REF] Wilson | Facial trustworthiness predicts extreme criminal sentencing outcomes[END_REF]; but see also [START_REF] Little | Accuracy in discrimination of selfreported cooperators using static facial information[END_REF][START_REF] Tognetti | Is cooperativeness readable in static facial features? An inter-cultural approach[END_REF]. For example, Rule et al. ( 2013) created an experimental setting in which participants could cheat on a test or not. When a different group of participants were shown pictures of the cheating and non-cheating participants, their ratings showed high agreement on who looked trustworthy and who did not. However, the pictures of people who actually cheated on the test were not rated differently than the pictures of people who did not.

Critically, in an fMRI study with the same pictures, Rule et al. found that the amygdala activation for the pictures of cheating and non-cheating individuals did also not differ. This suggests that the amygdala activation tracks perceived trustworthiness but does not provide an accurate (i.e., so-called "honest") trust signal.

Taken together, the available evidence indicates that people's trustworthiness ratings of faces are generally inaccurate. However, recent behavioral work also indicates that under specific conditions people's trust decisions can retain some minimal but observable accuracy (e.g., Bonnefon, Hopfensitz, & De Neys, 2013;Stirrat & Perret, 2010;see Bonnefon, Hopfensitz, & De Neys, 2017 for review). These specific conditions concern cases in which people evaluate faces in the context of an incentivized Trust Game [START_REF] Berg | Trust, reciprocity, and social history[END_REF]. The Trust Game is a popular behavioral economic paradigm that allows researchers to capture trusting decisions in a controlled but reasonable realistic economic setting. This simple game involves two players, A and B. Player A, the Investor or Trustor, is endowed with an initial amount of money (e.g., $10) and can choose to invest this money and transfer it to player B, the Trustee. If player A decides to transfer their money, the experimenter multiplies the amount by a factor larger than 1 (typically 3) before giving it to player B. Player B then decides how much of this enlarged endowment (e.g., $30), if any, they would like to return to player A. Both players are completely informed about the procedure but cannot communicate during the game. In essence, in this game the Investor needs to decide whether or not to trust the Trustee, and the Trustee has the option between honoring and abusing trust. If the Investor transfers their endowment and the Trustee honors this trust by returning more money than originally transferred, the Investor will make a nice profit and will end up with more money than the initial $10. However, if the Trustee abuses trust and returns no or only little money, the Investor ends up with less money than their initial endowment.

In a set of studies [START_REF] Bonnefon | The modular nature of trustworthiness detection[END_REF] first asked a group of participants to play the role of Trustee in the Trust game. Participants were fully instructed about the structure of the game and were asked what they would do if the Investor transferred their endowment: Would they keep all of the money or split it equally and return half of it? After the experiment, Trustees were then paired with a random Investor and paid depending on their decision. Hence, this initial phase is giving us an operationalization of the actual trustworthiness of the Trustee: We know whether they abused the Investor's trust and kept all of the money, or honored trust and split the money. In the second stage of the study, another group of participants played several Trust game rounds in the role of Investor. Before each round they were shown a picture of the Trustee (taken from the first phase of the study) and decided whether or not they wanted to transfer their endowment to the Trustee. One of the rounds was randomly selected and the Investors received whatever money they made in that round. Hence, both the Investor and Trustees were playing for real monetary pay-offs. The critical observation was that participants transferred more frequently (i.e., a 5% to 7% transfer increase) to Trustees who honored trust than to Trustees who abused trust. This indicates that people have some minimal accuracy in reading trustworthiness from the faces of unknown adults when they play the Trust Game (see also De Neys, Hopfensitz, & Bonnefon, 2013[START_REF] Todorov | Face value: The irresistible influence of first impressions[END_REF]Stirrat & Perret, 2010).

Here we report the first fMRI study that looks at the neural basis of this accurate facial trustworthiness detection in the Trust Game. In the scanner our participants played a series of trust games as Investor with Trustees whose strategy had been previously recorded. Participants were shown the picture of the Trustee before making a transfer decision. We contrasted the neural activation when participants saw pictures of Trustees who abused and honored trust. We were especially interested in the possible role of the amygdala in this trustworthiness signaling: Does amygdala activation indicate we're looking at an abuser when deciding to trust them with our money? This would suggest that the amygdala response can serve as an honest trust signal in the context of the Trust Game.

Critically, we tested both a group of young adults (age 19-26) and young adolescents (age 11-16). In general, amygdala responsiveness is known to show important age-related development [START_REF] Gee | A developmental shift from positive to negative connectivity in human amygdala-prefrontal circuitry[END_REF][START_REF] Tottenham | The developing amygdala: a student of the world and a teacher of the cortex[END_REF][START_REF] Zebrowitz | Older adults' neural activation in the reward circuit is sensitive to face trustworthiness[END_REF]. More directly, previous behavioral work with the Trust Game has indicated that adolescents are less accurate in detecting trustworthiness from the face than adults (De Neys, Hopfensitz, & Bonnefon, 2015). De Neys et al. had 540 adolescents aged between 13 and 18 years decide whether or not to trust an unknown adult based on their picture in a number of Trust Game rounds. Results showed that trustworthiness detection accuracy increased with age: younger adolescents' transfer decisions differentiated less well between trust honoring and abusing Trustees than those of later adolescents and young adults. We therefore expected that if the amygdala (or any other brain region) showed sensitivity to the Trustees' trustworthiness status, the activation pattern would differ in the adolescent and adult groups.

METHOD Participants

Forty-nine (23 adults and 26 adolescents) participants took part in this study. Among the 23 scanned adults, data from one participant who exhibited a within-run maximal amplitude of translational or rotational between-volumes displacement above 2 mm or 1.5 degree, respectively, was discarded from the analysis. A second adult had to be excluded due to technical scanner problems.

Among the 26 scanned adolescents, three had to be discarded because of within-run displacements above 2mm translation or 1.5 degrees rotation, four had to be excluded due to technical scanner problems, and one had to be excluded because of a neurological abnormality. Consequently, datasets of 21 adults (mean age ± 21.4, SD ± 1.9 years, aged from 19.1 to 25.9 years, 11 females) and 18 adolescents (mean age ± 13.3, SD ± 1.3 years, aged from 11.4 to 15.8 years, 10 females) were included in the final analysis. All participants were right handed, native French speakers. An informed consent form was signed by themselves or their parents/guardians (for minors). Each participant received a 25 euro gift voucher for their participation. The study was approved by the research ethics committee (CPP Nord Ouest III; ID RCB: 2014-A00935-42) and conformed to the 1964 Declaration of Helsinki.

Material and Procedure

Behavioral task design

Trust Game. Participants were familiarized with the rules of the Trust game before the scanning session. In the scanner, each participant played a total of 60 rounds in the role of Investor, with 60 different Trustees. Note that while the words 'Investor' and 'Trustee' are used for clarity here, they were never actually used in the experiment. The Trustee was simply called 'Player B'. Each round had the same structure: Participants were endowed with a sum of 4 euros and had to decide whether to keep the endowment, or to transfer that endowment to a Trustee, whose picture appeared on the screen. In case the endowment was transferred, it was multiplied by three, and the Trustee had to decide whether to keep the whole 12 euros, to return 6 euros to the Investor, or to return 4 euros to the Investor. We refer to these strategies as the Abuser, Cooperator, and Neutral strategies, respectively. These terms were not mentioned to the participants. The participants were informed that each Trustee had already recorded his or her strategy. Participants were also informed that one round would be randomly selected after the study, and that the amount of money they made in that round would be added to the voucher they would receive at the end of the study.

Trustors' payoffs were based on a pairing with a randomly selected Trustee. Trustees did not receive any payoff in the current set of studies (they did receive their payoff in the previous study in which their picture had been taken and their strategy recorded, see [START_REF] Centorrino | Honest signaling in trust interactions: smiles rated as genuine induce trust and signal higher earnings opportunities[END_REF]. In addition, because of possible ethical objections to a performancedependent reimbursement with younger participants (e.g., De Neys et al., 2015), all Investors were paid the maximum payoff which was included in their voucher fee. Investors were not informed about their actual performance. Hence, our task design implied the use of deception in that Trustors believed that the Trustee's pay-off was contingent on the Trustor's own behavior and Trustors were not informed about their actual performance. Note also that in our variant of the Trust game the Trustee received a fixed show-up fee but no additional endowment in the game (e.g., see [START_REF] Glaeser | Measuring trust[END_REF]. Trustors were informed about this feature. This can affect the absolute level of trust (e.g., due to inequality aversion Trustors may be more likely to transfer money overall, e.g., [START_REF] Ciriolo | Inequity aversion and trustees' reciprocity in the trust game[END_REF]. However, given that our core interest lies in the accuracy of trustworthiness detection (i.e., relative contrast Abusers vs Cooperators) this design feature should not bias results [START_REF] De Neys | Split-second trustworthiness detection from faces in an economic game[END_REF].

Trustee pictures. The Trustees shown to the participants had recorded their strategy and were incentivized in the context of a previous study [START_REF] Centorrino | Honest signaling in trust interactions: smiles rated as genuine induce trust and signal higher earnings opportunities[END_REF]. In this initial study, 84 young adults played the role of Trustee and recorded a movie introducing themselves. From each of these movies, a research assistant blind to the strategies of the Trustees extracted one frame in which the Trustee had the most neutral expression. Each picture was then cropped (left and right facial boundaries, chin and top of the eyebrows) to minimize display of clothing or hairstyle, and turned to black and white (Figure 1). The trustworthiness detection study of [START_REF] Bonnefon | The modular nature of trustworthiness detection[END_REF] used a set of 60 of these pictures selected so that the proportion of abusers and cooperators would be maximally similar for male Trustees (4 abusers, 18 cooperators) and female Trustees (3 abusers, 17 cooperators). Consequently, there were a total of 7 pictures of Abusers, 35 pictures of Cooperators, and 18 pictures of Neutral players. Note that the proportion of cooperators in the 60-picture set is similar to the proportion of cooperators usually found in trust game studies and the natural environment (e.g., [START_REF] Johnson | Trust games: a meta-analysis[END_REF][START_REF] Van Lange | Generalized trust: Four lessons from genetics and culture[END_REF]. fMRI event-related design Each trial started with the presentation of the number of the round (e.g., "Round 1", 1000 ms) that was going to be played. Next, a picture of the Trustee was presented on the screen for 2000 ms.

Subsequently, participants had to indicate whether they wanted to transfer money to the Trustee by pressing one of two buttons, after which they moved on to the next round, without receiving feedback about the strategy of the Trustee. Participants were informed that they had a maximum of 3000 ms to give their response (i.e. transfer money or keep it). As soon as they answered, a fixation cross was presented in the middle of the screen for periods ranging from 2200 ms to 6400 ms. The fixation cross was followed by the next trial. Trustee pictures were presented in a jittered pseudo-randomized order for each participant. The category sequence structure was identical for each participant (e.g. Cooperator picture, Cooperator picture, Abuser picture, Neutral picture, … ) but the Trustee picture presented for each category was randomly selected among the available stimuli. Ten null events consisting of a fixation cross for a duration ranging from 2200 to 6400ms were also added to the design to optimize signal detection. The design was overall optimized using the Genetic Algorithm toolbox [START_REF] Wager | Optimization of experimental design in fMRI: a general framework using a genetic algorithm[END_REF]. Figure 1 illustrates the trial sequence. fMRI data acquisition fMRI data were acquired at Cyceron (Caen, France) using a 3T scanner (Philips Achieva, Eindhoven, The Netherlands). Scanning was done as part of a larger one hour test session in which participants were also presented with an unrelated reasoning task. For each participant, the MR data were collected using planes parallel to the anterior commissure -posterior commissure line. fMRI time series were collected using T2*-weighted FFE echo-planar imaging (EPI) sequence ( 31

Fmri data analysis

Image pre-processing and statistical analyses were performed using Matlab 2014b (Mathworks Inc., Natick, USA) and SPM12 (Wellcome Department of Imaging Neuroscience, London, UK).

Pre-processing. fMRI datasets were preprocessed to optimize the anatomical mapping of the functional results using approaches inspired by Villain et al. (2010). More precisely, individual fMRI timeseries were (1) slice time corrected, (2) realigned to correct for head movement, (3) co-registered to the respective individual T2* volume, which was already previously co-registered to the high-resolution structural imageT1-weighted volume, (4) transformed into the MNI152 T1 template space using the parameters derived from the spatial normalization of the T1-weighted image in DARTEL [START_REF] Ashburner | A fast diffeomorphic image registration Algorithm[END_REF], ( 5) resampled to 2-mm isotropic voxel size and ( 6) smoothed with a 8-mm_FWHM Gaussian

Kernel. An explicit mask was designed, based on the averaged normalized segmented T1 data, to exclude non-gray matter voxels from further fMRI analyses. fMRI modeling and statistical analyses. We analyzed the data voxel-wise using the general linear model (GLM) approach [START_REF] Friston | Spatial registration and normalization of images[END_REF]. For completeness, we modelled activation both during the critical face presentation phase in which participants saw the Trustees picture and during the subsequent transfer response phase during which they indicated their transfer decision. We defined six regressors: (1) a regressor, for each condition (i.e., the three faces types), related to the face presentation phase (i.e., the presentation of Neutral, Cooperator and Abuser faces) and (2) a regressor, for each condition (i.e., the three face types), related to the transfer phase (i.e., phase during which the participants indicated whether or not they wanted to transfer their money after the presentation of a Neutral, Cooperator and Abuser face). For each regressor we modelled the stimulus-evoked neural response as a boxcar function, with each event starting at face presentation or at transfer phase onset, and lasting 2000 ms or the time the participant took to make their transfer decision, respectively. These boxcar functions were convolved with the default canonical hemodynamic response function of SPM12.

In addition, we included one constant term and the six realignment parameters (3 translations, 3 rotations) as covariates into our model, to account for changes in signal level and influence of head motion on BOLD signal, respectively. We also applied a high-pass filter (cut off period = 128 s) to remove low-frequency drifts.

We first estimated the model at the individual level yielding two parameter estimates per condition (i.e., face presentation for Neutral, Cooperator and Abuser conditions; transfer for Neutral, Cooperator and Abuser conditions). From these values, we computed, for each participant and for both face presentation and transfer, the following statistical contrast maps: Abuser > Cooperator, Abuser > Neutral, Cooperator > Neutral. Our main interest was whether there was differential activation for Abuser and Cooperator faces. Note that some previous fMRI studies on trustworthiness evaluation pointed to a possible quadratic response pattern in the amygdala (i.e., no difference between trustworthy and untrustworthy faces per se, but increased activation for both untrustworthy and trustworthy vs neutral rated faces, e.g., [START_REF] Santos | The role of the amygdala in facial trustworthiness processing: A systematic review and meta-analyses of fMRI studies[END_REF][START_REF] Todorov | Social judgments from faces[END_REF]. The additional Neutral contrasts would allow us to track such a pattern.

At the group level, we conducted two-sample t-tests, for each contrast described above, to test for activation differences in the adult and adolescent group (Adults > Adolescents) and track the hypothesized effect of age. In addition, we also performed supplementary analyses (see results) in which we a) combined adults and adolescents in one single group and performed one-sample t-tests to test correlations between amygdala BOLD signal and age, and b) test correlations between amygdala BOLD signal and behavioral data (i.e., the difference of average transfer rate between abusers and cooperators) in both age groups separately and combined.

We determined a priori bilateral amygdala regions of interest (ROI) based on the work of [START_REF] Rule | Accuracy and consensus in judgments of trustworthiness from faces: Behavioral and neural correlates[END_REF]. The ROIs were 4mm radius spheres centered on the voxels that showed peak activation within the left and right amygdala in [START_REF] Rule | Accuracy and consensus in judgments of trustworthiness from faces: Behavioral and neural correlates[END_REF]: left amygdala [-24, 0, -12], right amygdala [27, -3, -18]. Figure 2 depicts the exact ROI location. We first performed analyses using the amygdala ROIs for which we applied both voxel-level and cluster-level thresholds at p FWE corrected < .05. For subsequent whole brain analyses, we applied a voxel-level threshold at p < .001 (uncorrected for multiple comparisons) and cluster-level threshold at p < .05 (FWE corrected).

RESULTS

Behavioral results

For each participant we calculated the average transfer rate to abusers, cooperators, and neutral Trustees. These averages were subjected to a 3 (Trustee Strategy, within-subjects; abuser, cooperator, or neutral) x 2 (Age Group, between-subjects; adolescent or adult) mixed model analysis of variance (ANOVA). Table 1 gives an overview of the results. As Table 1 indicates, behavioral performance was fairly similar across all conditions. ANOVA results confirmed that the transfer rates did not significantly differ as a function of the Trustee Strategy factor, F(2, 111) = 0.718, p = .490, η p 2 = 0.013, Age Group factor, F(1, 111) = 0.418, p = .519, η p 2 = 0.004, or their interaction, F(2, 111) = 0.160, p = .852, η p 2 = 0.003. This indicates that our participants' behavioral performance did not show the previously observed trustworthiness detection effects. This was not unexpected given that the previous behavioral studies reported small effect sizes and tested much larger samples (e.g., n = 208 in Bonnefon et al., 2013, Study 1;and n = 540 in De Neys et al., 2015). Our goal in the present study was to investigate a potentially more pronounced neural signature.

fMRI results -face presentation phase

We start by focusing on the amygdala ROI and afterwards move on to a whole-brain analysis.

For all analyses we contrasted how the activation in the adult group differed from the adolescent group (Adults > Adolescents) to track the hypothesized effect of age. For ROI analyses, voxel-level and clusterlevel thresholds were set at p < .05 (FWE corrected). For whole brain analyses, voxel-level and clusterlevel thresholds were set at p < .001, (uncorrected for multiple comparisons) and p < .05 (FWE corrected), respectively Amygdala ROI analyses. The Abuser > Cooperator contrast revealed greater activation within the left amygdala (left amygdala: [-26, 2, -14]; k = 3, t = 3.47, p < .05, FWE; see Figure 3A) for adults than for adolescents whereas no significant difference was observed in the right amygdala. Interestingly, the Abuser > Neutral contrast showed the same pattern with greater activation within the left amygdala (left amygdala: [-26, 2, -14]; k = 7, t = 3.77, p < .05, FWE; see Figure 3A) for adults than for adolescents and no significant activation difference within the right amygdala. The Cooperator > Neutral contrast did not show any significant activation differences.

Figure 3B plots the activation pattern in the left amygdala in all conditions and both age groups to further interpret the findings. As the figure indicates, adults show less deactivation when looking at trust abusers than at cooperators and neutral players resulting in a relative activation increase in the Abuser condition. With adolescents we find the opposite pattern as they show a more pronounced deactivation in the Abuser condition. Taken together, these findings indicate that there is an age related amygdala activation increase when we face Trustees who will abuse our trust.

Supplementary ROI analyses. In our main analyses, we looked at the impact of age by contrasting activation in the adult and adolescent group. Since there was some age variability within each age group, we also entered age as a continuous predictor in our analyses and tested whether it correlated with the observed left amygdala ROI activation. Results showed that this was the case: both for the Abuser > Cooperator (k = 1, t = 3.66, p < .05, FWE) and Abusers > Neutral (k = 5, t = 3.71, p < .05, FWE) contrast there was a positive correlation between age and activation of the left amygdala ROI. The scatterplot in Figure 4 illustrates the findings.

One might note that the Figure 4 scatterplot also suggests that two adolescents present very low amygdala contrast estimates which might be driving the positive age correlations. We thus redid the analyses after removing possible outliers from the data (i.e., removed data beyond + / -2 standard deviations from the mean). Results indicated that the findings were robust. Even when the two possible outliers were excluded, we still observe a positive correlation between age and activation within the left amygdala ROI for both the Abuser > Cooperator (k = 1, t = 3.36, p < .05, FWE) and the Abuser > Neutral (k = 1, t = 3.43, p < .05, FWE) contrasts.

Finally, we also explored whether the individual adolescents' and adults' left amygdala ROI activation for the critical Abuser > Cooperator contrast correlated with their behavioral performance (i.e., average transfer rate to abusers -average transfer rate to Cooperators). However, none of the correlations reached significance (Adults: r = .07, p = .75; Adolescents: r = .23, p = .37; Adults+Adolescents: r = .17, p = .29; all p FWE, see Figure 5). This again indicates that behavioral effects are subtle. The more pronounced activation of the left amygdala when faced with abusers did not result in a decreased transfer to these Trustees.

Whole-brain analysis. In addition to our amygdala ROI contrasts we also ran explorative wholebrain analyses. As with the main ROI analyses, we contrasted how the activation in the adult group differed from the adolescent group (Adults > Adolescents) in our contrasts of interest. Table 2 gives a full overview of the results. As the table indicates, in addition to the amygdala, a number of additional parietal (e.g., Angular Gyrus, Inferior Parietal Lobule, Precuneus), temporal (e.g., Inferior Temporal Gyrus), and frontal regions (e.g., Medial Frontal Gyrus) also show an age related increase when facing trust abusers. Although post-hoc and speculative, we note that many of these regions have been implicated in Theory of Mind and perspective taking tasks [START_REF] Schurz | Fractionating theory of mind: a metaanalysis of functional brain imaging studies[END_REF][START_REF] Van Overwalle | Social cognition and the brain: a meta-analysis[END_REF]. We come back to this point in the discussion section.

fMRI results -Transfer response phase

For completeness, we modelled activation both during the critical face presentation phase in which participants saw the Trustees picture and the subsequent transfer response phase during which they indicated their transfer decision. During the transfer phase neither the amygdala ROI analyses nor the whole brain analyses showed significant activation effects in any of our contrasts of interest.

DISCUSSION

In this study we explored the neural basis of facial trustworthiness detection in the Trust Game.

We had a group of adolescents and adults play a series of trust games as Investor with Trustees of which we had previously recorded the strategy. Results showed that when adult Investors were looking at the picture of a trust abusing Trustee, the left amygdala was relatively more activated than when they were looking at a trust honoring or neutral player. Younger adolescents did not show this pattern and responded with a more pronounced deactivation when facing a trust abusing Trustee. This pattern suggests that the previously observed behavioral age-related increase in Trust Game transfer accuracy and accurate trustworthiness detection among adults [START_REF] Bonnefon | The modular nature of trustworthiness detection[END_REF][START_REF] De Neys | Adolescents gradually improve at detecting trustworthiness from the facial features of unknown adults[END_REF] might be mediated by the amygdala. Thereby, the results suggest that in the specific context of the Trust Game the amygdala activation might help to accurately track the trustworthiness of our interaction partners.

Our exploratory whole-brain analyses indicated that in addition to our amygdala ROI various parietal, temporal, and frontal regions also showed age related modulation when facing trust Abusers.

One of the additionally activated regions, the angular gyrus, might be especially interesting. This region and the adjacent temporal parietal junction (TPJ) are often implicated in Theory of Mind and perspective taking tasks [START_REF] Schurz | Fractionating theory of mind: a metaanalysis of functional brain imaging studies[END_REF][START_REF] Van Overwalle | Social cognition and the brain: a meta-analysis[END_REF]. Critically, imaging studies with various economic games also point to a role of the TPJ in contemplating altruistic or selfish decision options [START_REF] Morishima | Linking brain structure and activation in temporoparietal junction to explain the neurobiology of human altruism[END_REF][START_REF] Van Den Bos | Changing brains, changing perspectives: the neurocognitive development of reciprocity[END_REF]. This TPJ activation is known to show age related differentiation [START_REF] Fett | Default distrust? An fMRI investigation of the neural development of trust and cooperation[END_REF][START_REF] Van Den Bos | Changing brains, changing perspectives: the neurocognitive development of reciprocity[END_REF]. More specifically, age related TPJ activation increases have been found to be especially prominent when dealing with negative social signals (e.g., when getting feedback about Trustees' defection, [START_REF] Fett | Default distrust? An fMRI investigation of the neural development of trust and cooperation[END_REF]. In this light, the fact that the angular gyrus/TPJ shows an age related activation increase when being faced with Abusers1 in the current study might suggest that perspective taking is specifically recruited when adults are dealing with potential trust abuse.

We want to stress that some caution is needed in interpreting the present findings. Our study is but the first in which the neural basis of accurate face based trustworthiness detection in a Trust Game is explored. Obviously, the result will need to be replicated before drawing strong conclusions [START_REF] Nosek | Scientific utopia: II. Restructuring incentives and practices to promote truth over publishability[END_REF]. But even then one should be wary of possible over-interpretation. As we noted, previous large scale behavior studies already indicated that although Investors perform slightly better than chance (e.g., 6% transfer increase to cooperators vs abusers) their decisions are far from perfect [START_REF] Bonnefon | The modular nature of trustworthiness detection[END_REF][START_REF] De Neys | Split-second trustworthiness detection from faces in an economic game[END_REF]. In the present small scale study we found that the increased amygdala response to untrustworthy Trustees did not result in an observable behavioral effect. The point is that although we believe it is important to try to identify the neural basis of a presumably noisy and coarse facial trust detection process, such a neural substrate should not be taken to imply that relying on facial trust cues (or associated brain activation) to make trust decisions is wise [START_REF] Mccabe | Seeing is believing: The effect of brain images on judgments of scientific reasoning[END_REF]. A key issue is that trust abuse in modern day societies is rare (e.g., [START_REF] Van Lange | Generalized trust: Four lessons from genetics and culture[END_REF]. For example, in our current sample, only 12% of Trustees decided to abuse trust and keep all of the transferred money. Hence, simply because the base rate of cooperation is so high, deciding to (dis)trust on the basis of an imperfect face-based signal can be counterproductive. By not transferring to those misclassified as abusers, we are missing out on the trust bonus. Consequently, a simple strategy to trust indiscriminately can be shown to result in higher payoffs than relying on imperfect trustworthiness detection cues (e.g., De Neys et al., 2017;[START_REF] Todorov | Response to Bonnefon et al.: Limited 'kernels of truth' in facial inferences[END_REF].

The present findings give rise to a number of further questions. For example, one might wonder about the discrepancy between the present results and those of [START_REF] Rule | Accuracy and consensus in judgments of trustworthiness from faces: Behavioral and neural correlates[END_REF] who found that amygdala activation did not accurately track people's cheating behavior in a mock test. As with behavioral trust studies, one possible reason for the discrepancy concerns the incentivized Trust Game task context which has been argued to create favorable conditions for trustworthiness detection [START_REF] Bonnefon | Can we detect cooperators by looking at their face?[END_REF]. Interestingly, in another task context and with a different type of evaluationperceptions of leadership -Rule and collaborators did find that face-based first impressions can be accurately reflected in amygdala activation [START_REF] Rule | Face value: Amygdala response reflects the validity of first impressions[END_REF]. [START_REF] Rule | Face value: Amygdala response reflects the validity of first impressions[END_REF] presented participants with pictures of CEOs in the fMRI scanner. Prior behavioral work [START_REF] Rule | The face of success: Inferences from chief executive officers' appearance predict company profits[END_REF] had already established that people's judgments of leadership on the basis of these pictures, corresponded to an objective measure of success: perceived leadership accurately predicted the CEOs companies' profits. Critically, [START_REF] Rule | Face value: Amygdala response reflects the validity of first impressions[END_REF] observed that this was also accurately reflected in the amygdala activation: the amygdala was more responsive when viewing faces of CEOs whose companies had higher profits. Hence, the accuracy of first impressions reflected by amygdala activation may depend on the nature of the impression and task context.

Another issue concerns the possible origin of accurate face-based trust impressions. Where does the (minimal) accuracy come from? One speculative explanation involves the role of stimulus generalization or learning mechanisms [START_REF] Feldmanhall | Stimulus generalization as a mechanism for learning to trust[END_REF][START_REF] Over | Where do spontaneous first impressions of faces come from?[END_REF]. For example, according to Over and Cook's Trait-Inference-Mapping framework, trait inferences are products of mappings between locations in 'face space' and 'trait space'. The idea is that when one repeatedly encounters individuals with particular facial features who subsequently exhibit certain behavior, a mapping forms between the corresponding face and trait representation. Once acquired, these mappings mediate spontaneous trait judgments from faces: when the face of a stranger falls close to a mapped location in face space, the associated trait will be automatically activated [START_REF] Over | Where do spontaneous first impressions of faces come from?[END_REF].

Interestingly, recent fMRI evidence also points to a role of the amygdala in the learned avoidance of untrustworthy behaving partners in the Trust Game [START_REF] Feldmanhall | Stimulus generalization as a mechanism for learning to trust[END_REF]. In their study or later [START_REF] Bulygina | Ontogeny of facial dimorphism and patterns of individual development within one human population[END_REF][START_REF] Coquerelle | Sexual dimorphism of the human mandible and its association with dental development[END_REF]. Since in Western cultures people typically interact with same-age peers [START_REF] Konner | The evolution of childhood: Relationships, emotion, mind[END_REF], adolescents in our study (which was run in Adults show less deactivation when looking at trust abusers than at cooperators and neutral players whereas adolescents show the opposite pattern. Note that this pattern is virtually identical to the response pattern in the left amygdala (see Figure 3). The error bars represent the standard error of the mean.

  Bonnefon et al. also avoided pictures of distinctively non-Caucasian Trustees to maximize homogeneity of the picture set. The same set of 60 pictures from Bonnefon et al. was also used for the present study.

  axial slices; 3.75 mm thickness; no gap; reconstruction matrix = 640 x 640 mm; field of view = 240; repetition time = 2000 ms; echo time = 35 ms; flip angle = 80°; interleaved: bottom -up). The FOV covered the top of the cortex down to at least the base of the cerebellum. The first 6 volumes were discarded from each functional run to account for spin saturation effects. A high resolution T1-weighted structural and a T2* non-EPI volumes were also acquired using 3D TFE (180 sagittal slices; resolution: 1 mm3; no gap; reconstruction matrix = 256 x 256 mm; field of view = 256; repetition time = 20 ms; echo time = 46 ms) and 2D FFE (70 axial slices; resolution: 2 mm3; no gap; reconstruction matrix = 256 x 256 mm; field of view = 256; repetition time = 20 ms; echo time = 46 ms) sequences, respectively.

FeldmanHall

  et al. had participants play repeatedly with the same Trustees. The Trustees were instructed to behave more or less trustworthily (i.e., return money more frequently). In a second stage, the participants played with a new set of Trustees whose pictures were morphed to resemble the faces of the trustworthy and untrustworthy Trustees from the initial stage. Results showed that participants were less likely to transfer money to morphed Trustees who resembled the original player they previously learned was untrustworthy. Critically, this effect was mediated by the amygdala. The more the morphed picture resembled the untrustworthy player, the more the amygdala activation increased. As FeldmanHall et al. (2018) indicate, in theory, such a learning mechanism might facilitate potentially adaptive decisions to distrust unfamiliar others on the basis of their facial features. The sketched learning account might also help to explain why adolescents did not yet show the increased amygdala activations when facing trust abusers. As De Neys et al. (2015) noted, facial features are highly unstable during adolescence: The geometry of the human face does not stabilize until age 16

Figure 1 .

 1 Figure 1. Illustration of the Trust Game trial sequence. ISI = Inter Stimulus Interval. Picture is a mock picture presented for illustrative purposes.

Figure 2 .

 2 Figure 2. Amygdala regions of interest (ROIs). Bilateral amygdala ROIs based on Rule et al. (2013). The ROIs are 4mm radius spheres centered on the following voxels: left amygdala [-24, 0, -12], right amygdala [27, -3, -18]. The left amygdala ROI is depicted in red, the right one in blue.

Figure 3 .

 3 Figure 3. A. Abusers > Cooperators and Abusers > Neutral contrasts results, in the left amygdala, for adults and adolescents. Adults show a greater amygdala activation increase when facing a trust Abuser (vs Cooperator or Neutral player) than adolescents. B. Parameter estimates in the left amygdala for all effects of interest (Neutral, Cooperators and Abusers faces for both age groups). Adults show less deactivation when looking at trust abusers than at cooperators and neutral players whereas adolescents show the opposite pattern. The error bars represent the standard error of the mean.

Figure 4 .

 4 Figure 4. Correlation between age and left amygdala activation for the Abusers > Cooperators and Abusers > Neutral contrasts. Results indicate that the amygdala activation in response to presentation of trust abusing Trustees increases with age.

Figure 5 .

 5 Figure 5. Correlation between behavioral performance (% transfer to Abuser -% transfer to Cooperator) and left amygdala activation for the Abusers > Cooperators contrast. Individuals who show a more pronounced activation of the left amygdala when faced with abusers (vs. cooperators), are not less likely to transfer money to these Trustees at the behavioral level.

Figure 6 .

 6 Figure 6. A. Abusers > Cooperators and Abusers > Neutral contrasts results, in the left angular gyrus for adults and adolescents. Adults show a greater activation increase when facing a trust Abuser (vs Cooperator or Neutral player) than adolescents. B. Parameter estimates in the left angular gyrus for all effects of interest (Neutral, Cooperators and Abusers faces for both age groups).Adults show less deactivation when looking at trust abusers than at cooperators and neutral players whereas adolescents show the opposite pattern. Note that this pattern is virtually identical to the response pattern in the left amygdala (see Figure3). The error bars represent the standard error of the mean.

Table 1 Behavioral results .

 1results Proportion (SD) of transfer to cooperators, abusers, and neutral Trustees in both age groups.

		Age
	Trustee Strategy	Adolescents	Adults
	Cooperator	52.94 (11.29)	48.27 (17.39)
	Abuser	49.05 (21.54)	48.07 (22.58)
	Neutral	46.19 (13.71)	45.56 (14.55)

Table 2 Whole-brain results (Adults > Adolescents) for the contrasts of interest

 2 . t-values refer to significant activation peaks at p < .001 (uncorrected for multiple comparisons). All reported clusters were significantly active at p < .05 (FWE). Only regions larger than 4 voxels were considered.Note. SMA: Supplementary Motor Area; ITG: Inferior Temporal Gyrus; MOG: Middle Occipital Gyrus; MFG: Middle Frontal Gyrus; IPL: Inferior Parietal Lobule; L: Left; R: Right. k represents the cluster size.

	Contrast	Region	Side X (mm)	Y (mm)	Z (mm)	k	t-value
	Abusers > Cooperators	ITG	L	-60	-6	-18	230	5.44
		MFG	L	-30	18	52	1754	5.44
		Angular gyrus	L	-46	-70	34	753	4.89
		Amygdala	L	-28	4	-20	57	4.13
	Abusers > Neutral	Frontal lobe	L	-22	-10	60	267	5.52
		(superior part)
		Thalamus	L	-14	-16	10	311	5.30
		SMA	L	-4	22	44	557	5.24
		Insula	L	-34	-2	-8	902	4.84
		MFG	L	-44	24	36	512	4.82
		IPL	L	-38	-54	56	585	4.59
		Amygdala	L	-26	2	-18	73	4.52
		Precentral gyrus	R	32	-2	50	315	4.44
		Cingulate gyrus	L	-6	2	36	246	4.30
		(middle part)
		Precuneus	L	-4	-64	44	210	4.12
	Cooperators > Neutral	No activations

See Figure6for a detailed overview of the angular gyrus/TPJ pattern of activation in all our study conditions.

Their face-trait mapping will be noisier [START_REF] Over | Where do spontaneous first impressions of faces come from?[END_REF]. As a result, their amygdala response when faced with untrustworthy adults will be less reliable.

This also points to an interesting possible extension of the present work. In the current study both adolescents and adults played the Trust Game with adult Trustees. Adolescents' might not have yet built up their representations of adult facial features in 'trait space' due to lack of experience with adults, but they may have such representations with adolescent faces due to greater contact with sameage adolescent peers. Future studies should therefore also examine adolescents' (and adults) trustworthiness detection when playing with adolescent Trustees.

Taken together, we believe that the present findings lend credence to a possible role of the amygdala in honest signaling of Trustees' trustworthiness on the basis of their facial features. Results suggest that at least in the specific context of the Trust Game, an objective increased risk of being exploited is reflected in an increased amygdala activation among adults.

OPEN DATA STATEMENT

All behavioral and imaging data can be retrieved from https://osf.io/q9em6/