Clémence Rose

Laure Lichon

Morgane Daurat

Sébastien Clément

Magali Gary-Bobo

Sébastien Richeter
email: sebastien.richeter@umontpellier.fr

In vitro toxicity and photodynamic properties of porphyrinoids bearing imidazolium salts and N-heterocyclic carbene gold(I) complexes

Keywords: Porphyrinoids, N-heterocyclic carbenes, Gold complexes, Photodynamic therapy

Porphyrins bearing imidazolium salts were synthesized and used as N-heterocylic carbene (NHC) precursors for the preparation of gold(I) complexes. The dark toxicity and phototoxicity of the obtained compounds were investigated in vitro on MCF-7 breast cancer cells. The obtained data showed that porphyrins equipped with imidazolium salts are non-toxic in the dark and present interesting photodynamic properties. On the contrary, corresponding NHC gold(I) complexes are not suitable photosensitizers for photodynamic therapy (PDT) applications.

Their dark toxicity strongly depends of the nature of the linker between the porphyrin core and the NHC. This work was extended to the synthesis of a pyropheophorbide a derivative with a pendant imidazolium group for PDT applications using excitation wavelengths of 450 nm, 545 nm, and importantly of 650 nm.

Introduction

In the field of cancer therapy, photodynamic therapy (PDT) represents an interesting alternative approach besides chemotherapy, radiotherapy and surgery for some types of cancer, notably skin cancer or tumors accessible to light (directly or thanks to optical fiber). [1] It relies in using a photosensitizer (PS), which is activated by light and able to generate reactive oxygen species (ROS) and singlet oxygen ( 1 O2). It implies that the PS in its singlet excited state ( 1 PS) can reach its triplet state ( 3 PS) through intersystem crossing (ISC, 1 PS  3 PS). Then, energy transfer from the 3 PS with ground state molecular oxygen in its triplet state 3 O2 lead to the generation of 1 O2.

(PDT of type 2). Alternatively, electron transfer processes involving the 3 PS lead to the formation of ROS and cytotoxic free radicals (PDT of type 1). Ultimately, these strong oxidizing agents may lead to cancer cells death through necrotic and apoptotic mechanisms. [2] The important aspect of PDT is that only cells containing PS and irradiated with visible light are susceptible to be destroyed. To date, porphyrinoids (including porphyrins, chlorins, phthalocynanines) are among the best performing PS for PDT because of their inherent chemical stability and suitable photophysical properties.[3] These tetrapyrrolic aromatic compounds strongly absorb light in the visible region and, more importantly, they are efficient PS to generate 1 O2. For example, the 1 O2 quantum yield of 5,10,15,20-mesotetraphenylporphyrin (H2TPP) in toluene is  = 68%. [4] Of course, there are some important drawbacks like their poor water solubility or their lack of selective accumulation in cancer cells, but these drawbacks may be circumvented by appropriate functionalization of the porphyrin core.

[5] Interestingly, some porphyrins were functionalized with peripheral ligands allowing the coordination of metal ions at their periphery. [START_REF] Richeter | Handbook of Porphyrin Science[END_REF] Some of the obtained complexes found relevant applications in the field of PDT. [START_REF] Longevial | [END_REF] For example, porphyrins functionalized with peripheral platinum(II) or ruthenium(II) complexes were used for dual chemo-and phototherapy. [8,9] Platinum(II) complexes have anticancer activity and also, significantly improve the photodynamic effect by promoting the generation of 1 O2 through a heavy atom effect.[8] Ruthenium(II) complexes were also reported for dual chemo-and phototherapy. [9] Moreover, some ruthenium(II) complexes proved to be efficient PS for two-photon excitation. [10] Although gold(I) complexes are promising candidates to develop new metallodrugs for cancer therapy, examples of porphyrinoids bearing peripheral gold(I) complexes for combined chemo-and phototherapy are relatively scarce. Gold(I) complexes of porphyrins functionalized with peripheral phosphine ligands were synthesized and biological studies showed that these compounds present rather low cytotoxicity. [11] However, watersoluble complexes of this type proved to be efficient PS for PDT. N-heterocyclic carbenes (NHC) are phosphine analogs and are attractive ligands to design new metallodrugs. During the last decade, we reported the synthesis of several porphyrin derivatives equipped with peripheral NHC-metal complexes, [12] including gold(I) complexes. [13,14] The photodynamic properties imidazolium salt A and gold(I) complexes B-D depicted in Chart 1 were investigated and we observed the important role played by the ligand trans to the NHC. [14] Indeed, the excellent photodynamic properties observed for the PS D functionalized with mannose are due to active targeting of cancer cells overexpressing mannose receptors at their surface. We also observed that imidazolium salt A is an efficient PS for PDT, while gold(I) complex B and C are inefficient for chemo-and phototherapy. The aim of this study is to draw more detailed conclusions about the potential of porphyrins equipped with peripheral NHC gold(I) complexes for dual chemo-and phototherapy. For this purpose, we report here the synthesis and the biological properties of porphyrins bearing imidazolium salts and NHC gold(I) complexes at their periphery.

Results and discussion

Synthesis of porphyrins meso-functionalized with imidazolium salts

Imidazolium salts are routinely used as NHC precursors. NHC could be generated upon deprotonation of an imidazolium salt with a base and trapped with a metal cation such as Ag + or Au + , for example. We first investigated compounds with imidazolium salts directly N-linked to one meso position of a porphyrin core. The first imidazolium salt, namely free-base porphyrin 3, was obtained in a three-step procedure starting from the porphyrin 1 previously described in reference [15]. The reaction of porphyrin 1 with imidazole and NaH in DMF (140 °C) afforded porphyrin 2 in 72% yield after column chromatography. [15] Then, demetalation of porphyrin 2 in acidic conditions followed by methylation of the peripheral imidazole group with CH3I afforded porphyrin 3 in an overall yield of 80% after purification (Scheme 1). The Then, we synthesized imidazolium-based porphyrin compounds with a spacer between the meso position of the porphyrin core and the imidazolium salt. For this purpose, free-base porphyrin 5 was used as starting material. The synthesis of this compound is described in reference [16]. Nucleophilic substitution on the chlorine atom of porphyrin 5 with 1methylimidazole in DMF (80 °C) afforded porphyrin 6 in 78% yield (Scheme 2). The 1 H NMR spectrum of the porphyrin 6 clearly showed the expected signal of the imidazolium proton H 2 at δ = 11.17 ppm. The signals of imidazolium protons H 4 and H 5 were also observed as apparent triplets at δ = 7.45 and 7.31 ppm. Porphyrin 7 was obtained in 90% yield by reacting free-base porphyrin 6 with Zn(OAc)2.2H2O. Scheme 2: Synthesis of the porphyrins 6 and 7.

Synthesis of gold(I) complexes

NHC-gold(I) complexes can be synthesized following different procedures. For example, complex 8 was synthesized in one step by reacting porphyrin 4-BF4 with [AuCl(tht)] (tht = tetrahydrothiophene) in the presence of tBuOK in dry THF. The mono(NHC)-gold(I) complex 8 was obtained in 80% yield after column chromatography and recrystallization (Scheme 3). The absence of signal corresponding to the imidazolium proton H 2 in the 1 H NMR spectrum of complex 8 confirmed the formation of the CNHC-Au(I) bond. Imidazolium protons H 4 and H 5 are shifted upfield by Δδ ~ 0.40 ppm as a consequence of the formation of the CNHC-Au(I) bond. The signal of the CNHC bound to Au I was observed at δ = 175.1 ppm in the 13 C{ 1 H} NMR spectrum of complex 8. This chemical shift is in good agreement with those reported in literature for [(NHC)AuCl] complexes [17]. Complex 9 was prepared in one step according to the reaction conditions reported by Richeter [13,14]. The deprotonation of the porphyrin 4-BF4 with K2CO3 in acetone in the presence of one equivalent of the complex 8 afforded the homoleptic complex 9 in 52% yield after column chromatography (Scheme 4). High-resolution ESI-TOF mass spectrometry (positive mode) featured the expected molecular mass peak at m/z = 1617.3612 Da with an isotopically resolved profile in good agreement with the calculated distribution of the monocationic species [ZnP-Au-ZnP] + (calcd m/z = 1617.3610 Da). NMR spectroscopy also confirmed the formation of the complex 9. Notably, in the 13 C{ 1 H} NMR spectrum, the signal of the CNHC bound to Au I was observed at δ = 188.8 ppm, a chemical shift in good agreement with those reported in the literature for homoleptic monocationic complexes [(NHC)Au I (NHC)] + [17]. The 1 H NMR spectra of complexes 8 and 9 are displayed in Figure 1. Interestingly, in both cases, four separated doublets were observed for the ortho and meta protons of the tolyl groups. This can be explained by the restricted rotation of the Cmeso-NNHC bond due to the presence of the sterically demanding NHC-gold(I) complexes. As a consequence, different chemical environments are experienced by the meso aryl protons. The N-Me protons signal of complex 9 at  = 2.04 ppm is significantly shielded ( = 4.23 ppm for complex 8) indicating that the N-Me group of one porphyrin sits on top of the second porphyrin ring and is exposed to its ring current. Finally, the two gold(I) complexes were characterized by diffusion-ordered spectroscopy (DOSY) 1 H NMR. As expected, the diffusion coefficient of 9 (1.15  10 -10 m 2 .s -1 ) is lower compared to 8 (1.54  10 -10 m 2 .s -1 ) because it contains two porphyrins.

Scheme 3: Synthesis of gold(I) complexes 8 and 9. Gold(I) complex 10 was prepared following a strategy that is widely used for the synthesis of NHC gold(I) complexes: the reaction of the porphyrin 7 with 1 eq. of Ag2O in dichloromethane afforded the corresponding silver(I) complex which was not isolated and used straightforward for the transmetallation reaction with [AuCl(tht)]. The corresponding gold(I) complex 10 was obtained in 41% yield after column chromatography and recrystallization (Scheme 4). The absence of signal for proton H 2 in the 1 H NMR spectrum of complex 10 and the signal of the CNHC bound to Au I observed by 13 C { 1 H} NMR spectroscopy at δ = 172.3 ppm confirmed the formation of the expected gold(I) complex. Gold(I) complex 11 containing a free-base porphyrin could not be synthesized following a similar strategy because silver(I) may be complexed by the porphyrin core. However, gold(I) complex 11 could be obtained by two different pathways. First, it is possible to remove the zinc(II) by treating the complex 10 with a TFA/CH2Cl2 mixture. These acidic conditions do not degrade the peripheral gold(I) complex as it was previously shown by us with analogous complexes. [14] Complex 11 was obtained in 70% yield after neutralization with NaHCO3 and column chromatography. It is also possible to react free-base porphyrin 6 with one equivalent of [AuCl(tht)] with tBuOK, in a THF/MeOH mixture in the dark to obtain the corresponding complex gold(I) complex 11 in 57% yield after column chromatography (Scheme 4). The formation of complex 11 was first confirmed by 1 H NMR spectroscopy and the disappearance of the signal at δ = 11.17 ppm corresponding to the imidazolium proton H 2 . In its 13 C{ 1 H} NMR spectrum, the carbene signal observed at δ = 172.5 ppm demonstrated the formation of the CNHC-Au(I) bond. Scheme 4: Synthesis of gold(I) complexes 10 and 11.

Cytotoxicity and phototoxicity studies

Biological properties of NHC-based gold(I) complexes have been extensively reported in the literature.

[18] The cytotoxicity of imidazolium salts and gold(I) complexes on MCF-7

breast cancer cells was first investigated. For this purpose, MCF-7 cancer cells were incubated for 72 hours in the dark with each compound at different concentrations varying from 0.05 to 2 µM. After 72 hours, MTT assay (3-( 4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) was performed to establish the cell viability and the results obtained are summarized in Figure 2. Free-base porphyrins 3 and 6 containing imidazolium salts are rather non-toxic up to 2 µM with less than 15% cell death irrespective of the presence or not of a linker between the porphyrin core and the NHC. In contrast, gold(I) complexes cytotoxicity strongly depends on the presence or not of a linker between the porphyrin core and the NHC. Indeed, complex 8 without linker between the porphyrin core and the NHC is not cytotoxic at 2 µM. On the contrary, complex 10 with the meso-benzylic linker between the porphyrin core and the NHC shows a significant cytotoxicity with 60% cell death at 2 µM. Therefore, the closer the NHCgold(I) complex is to the porphyrin core, the lower the observed cytotoxicity is. This is in agreement with the low cytotoxicity observed for complex B (chart 1) where NHC ligand is fused to the porphyrin core. Compound 9 is a cationic bis(NHC) gold(I) complex and it seems that the positive charge tends to increase the observed cytotoxicity since ~ 50% cell death was observed at 2 µM. Compared to complex 10, cytotoxicity of the corresponding gold(I) complex 11 including a free-base porphyrin is similar to a concentration up to 1 µM. The lower cytotoxicity observed for complex 11 at a concentration of 2 µM may be attributed to its low solubility in the cell culture medium. significant photodynamic effect whatever the irradiation wavelength. This is in agreement with our previous finding that gold(I) complexes without any specific targeting agent are not suitable PS for PDT, although their 1 O2 quantum yields may me improved through heavy atom effect. [14] On the contrary, both imidazolium salts 3 and 6 induced important cell death under laser irradiation at λ = 450 and 545 nm. The best photodynamic effect was observed for imidazolium salt 6 at 0.5 µM which induced ~ 86% cell death after 10 minutes of irradiation at λ = 545 nm. [START_REF]The values of photo-induced cell death are related to the non-irradiated cells in the same experiment to fairly describe the PDT efficiency, i.e. the cell death induced by light excitation only[END_REF] The good solubility of imidazolium salts in aqueous media and the fact that these cationic species can strongly interact with the negatively charged cancer cell membranes can explain the observed enhanced photodynamic activity compared to the corresponding gold(I) complex. Nevertheless, photodynamic activity of both imidazolium salts 3 and 6 is weaker under irradiation at λ = 650 nm since less than ~ 19-26% cell death was observed. [START_REF]The values of photo-induced cell death are related to the non-irradiated cells in the same experiment to fairly describe the PDT efficiency, i.e. the cell death induced by light excitation only[END_REF] This prompted us to investigate the functionalization of pyropheophorbide a with imidazole and imidazolium groups and their use for PDT applications.

Synthesis and photodynamic properties of pyropheophorbide a functionalized

with imidazole /imidazolium groups.

Monocationic chlorin 14 was prepared in a two-step procedure starting from pyropheophorbide a 12 as described in the literature (Scheme 5). [START_REF] Smith | [END_REF] First, the reaction of The cytotoxicity studies of chlorin derivatives 12-14 on MCF-7 breast cancer cells are summarized in Figure 5a and revealed that pyropheophorbide a 12 and imidazolium salt 14

were not cytotoxic on MCF-7 cells because they induce less than 10% cell death at a concentration of 2 µM. On the contrary, imidazole 13 exhibits significant cytotoxicity at 1 µM, with more than 30% cell death (~ 45% cell death at 2 µM). According to these results, photodynamic activity of chlorin derivatives 12-14 was evaluated with PS concentration of 0.5 µM under irradiation at λ = 450, 545 and 650 nm. The obtained data are summarized in Figure 5b. Upon irradiation at λ = 450 nm, only imidazole 13 exhibited a strong photodynamic effect by inducing 60% cell death. Imidazolium salt 14 revealed a slightly phototoxic activity with 22% cell death, whereas pyropheophorbide a 12 was not phototoxic at all (Figure 5b, left).

Upon irradiation at λ = 545 and 650 nm, all chlorin derivatives 12-14 turned out to be phototoxic (Figure 5b, middle and right). The significant phototoxicity of the three chlorins observed upon irradiation at λ = 650 nm constitutes the noteworthy result in this study, since synthetic imidazolium salts 3 and 6 induced less than ~ 19-26% cell death upon irradiation at λ = 650 nm (Figure 3). Chlorin derivatives 12, 13 and 14, induced 51%, 72% and 57% cell death, respectively, and turned out to be better photosensitizers upon irradiation with red light. [START_REF]The values of photo-induced cell death are related to the non-irradiated cells in the same experiment to fairly describe the PDT efficiency, i.e. the cell death induced by light excitation only[END_REF] Figure

Conclusion

Porphyrins bearing imidazolium salts were used as NHC precursors for the synthesis of gold(I) complexes with the aim to combine their cytotoxicity with PDT. This study shows that porphyrins conjugated with NHC-gold(I) complexes are metallodrugs possessing anticancer properties, as long as the NHC ligand is not directly bonded to the porphyrin core: a spacer is probably needed to keep away the NHC-gold(I) complex from the bulky porphyrin core.

Although heavy atom effect may be beneficial to improve 1 O2 production, these porphyrins conjugated with gold(I) complexes are not suitable PS for PDT. Additional functionalization with targeting agents is necessary to ensure active targeting of the cancer cells and simultaneously better solubility in aqueous media.

[22] By contrast, the corresponding porphyrins equipped with imidazolium salt moieties are suitable PS for PDT and this effect is attributed to the positive charges of the imidazolium cations, which are known to ensure strong interactions with negatively charged cancer cell membranes. These cationic porphyrins can induce significant cell death upon laser irradiation at 450 and 545 nm, but not at 650 nm. To improve light absorption and photodynamic effect at 650 nm, pyropheophorbide a derivatives equipped with pendant imidazole/imidazolium groups were synthesized. These hemisynthetic compounds proved to be efficient PS for PDT at 650 nm.

Experimental Section

Materials and instruments.

Reactions needing inert atmosphere were performed under argon using oven-dried glassware and Schlenk techniques. Dry THF was obtained by a PureSolve MD5 solvent purification system from Innovative Technology. Dry DMF was purchased from Sigma-Aldrich. Dry CH2Cl2 and THF were obtained by a PureSolve MD5 solvent purification system from Innovative Technology. Gold(I) complex [AuCl(tht)] (tht = tetrahydrothiophene) was prepared according to the procedure described in the literature. [23] recorded on a 25 °C on a JASCO V-650 spectrophotometer in 10 mm quartz cells (Hellma).

Molar extinction coefficients  (L.mol-1.cm-1) are expressed as log 

Synthesis and characterization of the different compounds.

Porphyrin 1. The synthesis and characterization data of the porphyrin 1 were reported in reference [15].

Porphyrin 2. Porphyrin 1 (150 mg, 0.225 mmol, 1.0 eq) and imidazole (150 mg, 2.25 mmol, 10 eq) were dissolved in dry DMF (11 mL). The solution was purged under Argon atmosphere for 10 minutes. NaH (60% in suspension in oil, 85 mg, 2.22 mmol, 10 eq.) was added and the reaction mixture was stirred at room temperature for 30 minutes. Then, the reaction mixture was stirred at 140 °C for 1 hour. After cooling at room temperature, CH2Cl2 (150 mL) was added and the organic phase was washed (distilled H2O), dried (MgSO4) and concentrated. Porphyrin 3. Porphyrin 2 (125 mg, 0.18 mmol, 1.0 eq) was dissolved in a TFA/H2SO4 4:1 (v:v) mixture and the reaction was stirred for 45 minutes at room temperature. Then, the mixture was poured into ice and water and neutralized by K2CO3(s). The organic phase was extracted with CH2Cl2, dried (MgSO4), and concentrated. The residue was purified by column chromatography (SiO2, eluent CH2Cl2). Recrystallization from CH2Cl2/n-hexane afforded the free base corresponding porphyrin in 87% yield (100 mg). Then, the obtained compound (90 mg, 0.14 mmol, 1.0 eq) was dissolved in dry THF (25 mL) and CH3I (2.2 mL, excess) was added. The reaction was stirred at 40 °C for 18 hours under argon. Recrystallization from CH2Cl2/n-hexane afforded the porphyrin 3 as a purple solid in 89% yield (98 mg). .5,140.9,137.9,137.5,134.4,139.3,134.3,134.2,132.7,131.9,130.2,128.5,128.2,128.0,127.1,123.3,123.1,121.9,108.7,36.8 (NCH3) 6, 150.1, 149.5, 146.9, 142.2, 142.2, 139.1 137.1, 134.3, 134.2, 134.1, 132.7, 133.7, 132.7, 132.3, 130.4, 128.0, 127.9, 127.6, 127.5, 126.8, 123.4, 123.0, 122.2, 108.9, 36.8 (N-CH3), 21.2 (CH3 tolyl) 150.1, 149.5, 146.9, 142.2, 142.2, 139.1 137.1, 134.3, 134.2, 134.1, 132.7, 133.7, 132.7, 132.3, 130.4, 128.0, 127.9, 127.6, 127.5, 126.8, 123.4, 123.0, 122.2, 108.9, 36.8 Porphyrin 5. The synthesis and characterization data of the porphyrin 5 were reported in reference [16].

Porphyrin 6. Porphyrin 5 (160 mg, 0.2 mmol, 1.0 eq) was dissolved in dry DMF (15 mL) and 1-methylimidazole (1.1 mL, 100 eq) was added. The solution was stirred at 80 °C for 24 hours under argon atmosphere. Alkylation completion was monitored by TLC. Once finished, the solvent was evaporated under reduced pressure. Recrystallization from CH2Cl2/n-hexane gave the porphyrin 6 in 78% yield (138 mg). 1 H NMR (400 MHz, CD2Cl2, 298 K): δ 11.17 (br s, 1H, H 2 ), 8.76 (d, 3 JH-H = 4.8 Hz, 2H, Hpyrrole), 8.67 (d, 3 JH-H = 4.8 Hz, 2H, Hpyrrole), 8.63 (br s, 4H, Hpyrrole), 8.28 (d, 3 JH-H = 8.0 Hz, 2H, Ho), 7.86 (d, 3 JH-H = 8.0 Hz, 2H, Hm), 139.8, 138.7, 138.6, 138.5, 135.8, 133.3, 128.3, 127.9, 123.9, 122.4, 121.0, 118.6, 118.6, 118.4, 22.0, 21.9, 21.7 Hz, 1H, H 4 ), 7.77 (d, 3 JH-H = 8.1 Hz, 2H, Hm), 7.30 (broad s, 6H, Hmes meta), 5.78 (s, 2H, CH2), 3.98 (s, 3H, N-CH3), 2.57 (s, 9H, CH3 mes para), 1.78, 1.77, 1.75 (3s, 18H, CH3 mes ortho) ppm.

13 C{ 1 H} NMR (150.9 MHz, DMSO-d6, 298 K): δ 149.0, 149.0, 148.9, 148.8, 143.2, 139.1, 139.0, 138.4, 138.4, 137.1, 136.9, 136.8, 134.6, 133.9, 131.5, 130.5, 130.0, 127.6, 126.2, 124.2, 122.8, 118.4, 117.7, 51.9, (-CH2), 36.0 (N-CH3), 21.6, 21.5, 21.0 (CH3 ortho, CH3 para) ppm. UVvisible (CH2Cl2): λmax (log ε) = 420 (5.63), 549 (4.22) nm. HR ESI-MS (positive mode): calcd for C58H53N6Zn + : 897.3623, found: 897.3632.

Gold(I) complex 8. Porphyrin 4-BF4 (60 mg, 0.075 mmol, 1.0 eq) and [AuCl(tht)] (26.5 mg, 0.083 mmol, 1.1 eq) were dissolved in dry THF (6.3 mL). A solution of t BuOK (9.3 mg, 0.083 mmol, 1.1 eq) in THF/MeOH (2.3 mL/ 10 drops) was added dropwise and the reaction mixture was stirred at room temperature under argon for 18 hours. After evaporation, the crude was purified by column chromatography (SiO2, eluent CH2Cl2). Recrystallization from CH2Cl2/nhexane gave the gold(I) complex 8 as a dark pink solid in 80% yield (72 mg).

1 H NMR (600 MHz, DMSO-d6, 298 K): δ 8.87 (d, 3 JH-H = 4.6 Hz, 2H, Hpyrrole), 8.80-8.76 (m, 4H, Hpyrrole), 8.71 (d, 3 JH-H = 4.6 Hz, 2H, Hpyrrole), 8.52 (d, 3 JH-H = 1.9 Hz, 1H, H 5 ), 8. 21-8.11 (m, 4H, Ho), 8.06 (d, 3 JH-H = 1.9 Hz, 1H, H 149.3,148.1,142.4,139.3,136.9,134.15,134.1,134.0,133.0,132.1,131.9,130.2,128.4,127.3,126.6,122.4,121.5,121.2,113.7,38.1 (CH3 tolyl), 21.1 (N-CH3) ppm. Gold(I) complex 9. Complex 8 (45 mg, 0.048 mmol, 1.0 eq) and porphyrin 4-BF4 (34.6 mg, 0.044 mmol, 0.90 eq) were dissolved in acetone/MeOH (18 mL/0.5 mL). Then, K2CO3 (6.7 mg, 0.048 mmol, 1.0 eq) was added and the reaction mixture was stirred at room temperature for 16 hours under argon in the dark. After evaporation, the crude was purified by column chromatography (SiO2, eluent from CH2Cl2 to CH2Cl2/MeOH 95:5 (v:v)). Recrystallization from CH2Cl2/n-hexane afforded the gold(I) complex 9 in 52% yield (40 mg).

1 H NMR (600 MHz, DMSO-d6, 298 K): δ 8.80 (s, 8H, Hpyrrole), 8.70 (d, 4H, 3 JH-H = 4.5 Hz, Hpyrrole), 8.45 (d, 3 JH-H = 1.8 Hz, 2H, H 5 ), 8.32 (d, 3 JH-H = 4.5 Hz, 4H, Hpyrrole), 8.22-8.17 (m, 4H, Ho), 8.04 and 7.98 (2dd AB system, 3 JH-H = 7.7 and 2.0 Hz, each 4H, Ha), 7.89-7.79 (m, 6H, Hm and Hp), 7.65 and 7.58 (2dd AB system, 3 JH-H = 7.7 and 2.0 Hz, each 4H, Hb), 7.34 (d, 3 JH-H = 1.8 Hz, 2H, H 4 ), 2.68 (s, 12H, CH3 tolyl), 2.04 (s, 6H, N-CH3) ppm. 13 C{ 1 H} NMR (150.9

MHz, DMSO-d6, 298 K): δ 188.8 (CNHC), 150.2,150.0,149.8,149.5,147.6,142.3,139.2,136.9,134.1,134.0,133.9,132.7,132.3,132.0,129.7,128.3,127.7,127.4,126.7,122.4,121.5,113.6,35.1 (CH3 tolyl) (10 mL). Then, Ag2O (9.9 mg, 0.043 mmol, 1.0 eq) was added and the reaction mixture was vigorously stirred at room temperature under argon protected from light. After 16 hours, [AuCl(tht)] (13.7 mg, 0.043 mmol, 1.0 eq) was added and the mixture was stirred for 18 hours under the same conditions. The solvent was evaporated under reduced pressure and the crude compound was purified by column chromatography (SiO2, eluent CH2Cl2). Recrystallization from CH2Cl2/n-hexane gave the gold(I) complex 10 as a red-purple solid in 41% yield (20 mg).

1 H NMR (400MHz, CD2Cl2, 298 K): δ 8.84 (d, 3 JH-H = 4.6 Hz, 2H, Hpyrrole), 8.73 (d, 3 JH-H = 4.6 Hz, 2H, Hpyrrole), 8.69 (d, 3 JH-H = 1.2 Hz, 4H, Hpyrrole), 8.23 (d, 3 JH-H = 8.0 Hz, 2H, Ho), 7.69 (d, 3 JH-H = 8.0 Hz, 2H, Hm), 7.29 (broad s, 6H, Hmes meta), 7.26 (d, 3 JH-H = 2.0 Hz, 1H, H 5 ), 7.13 (d, 3 JH-H = 2.0 Hz, 1H, H 4 ), 5.74 (s, 2H, CH2), 3.96 (s, 3H, N-CH3), 2.62 (s, 9H, CH3 mes para),

1.84-1.82 (2s, 18H, CH3 mes ortho) ppm. 13 C { 1 H} NMR (150.9 MHz, CD2Cl2, 298 K): δ 172.3 (CNHC), 150. 4,150.4,150.3,150.2,143.8,139.7,139.6,139.5,139.4,138.1,135.4,135.3,138.4,135.6,135.5,132.4,131.6,131.5,131.1,128.1,126.5,123.2,121.4,119.7,119.4,119.3,55.5 (CH2), 38.9 (N-CH3), 22.0, 21.9, 21.7 (CH3 mes ortho, CH3 mes para) ppm. UV-visible (CH2Cl2): λmax (log ε) = 420 (5.75), 549 (4.36) nm. MALDI-TOF + MS: calcd for C64H55Au4N12Cl4 : 1128.29, found 1128.30.

Gold(I) complex 11. Procedure A. Porphyrin 6 (40 mg, 0.043 mmol, 1.0 eq) was dissolved in dry THF (10.5 mL). Then, [AuCl(tht)] (15.4 mg, mmol, 1.1 eq) was added and the mixture was degassed with argon for 10 minutes. tBuOK (6 mg, mmol, 1.1 eq) was dissolved in MeOH (0.5 mL) and added dropwise to the reaction mixture, which was stirred at room temperature for 18 hours under argon in the dark. Then, the solvent was evaporated under reduced pressure and the residue was purified by column chromatography (SiO2, eluent CH2Cl2). Recrystallization from CH2Cl2/n-hexane afforded the gold(I) complex 11 as a purple solid in 57% yield (28 mg).

Procedure B. Porphyrin 10 (30 mg, 0.027 mmol) was dissolved in acetone (12 mL) under argon.

Then, a CH2Cl2/TFA 4:1 mixture (6 mL) was slowly added and the reaction mixture was stirred for 30 mn. After neutralization with NaHCO3, the solvent was evaporated and the residue purified by column chromatography (SiO2, eluent CH2Cl2). Recrystallization from CH2Cl2/nhexane afforded the gold(I) complex 11 as a purple solid in 70% yield (20 mg). 1 H NMR (400 MHz, CD2Cl2, 298 K): δ 8.77 (d, 3 JH-H = 4.8 Hz, 2H, Hpyrrole), 8.67 (d, 3 JH-H = 4.8 Hz, 2H, Hpyrrole), 8.63 (s, 4H, Hpyrrole), 8.22 (d, 3 JH-H = 8.0 Hz, 2H, Ho), 7.69 (d, 3 JH-H = 8.0 Hz, 2H, Hm), 7.29 (s, 6H, Hmes meta), 7.24 (d, 3 JH-H = 1.9 Hz, 1H, H 5 ), 7.12 (d, 1H, 3 JH-H = 1.9 Hz, H 139.9,138.9,138.8,138.6,138.4,135.6,135.5,128.3,126.7,123.2,121.4,118.8,118.6,118.4,55.5 (CH2), 39.0 (N-CH3), 21.9 (2s, CH3 were reported in reference [START_REF] Smith | [END_REF].

Chlorin 13. Pyropheophorbide a 12 (62 mg, 0.12 mmol, 1.0 eq), 1-(3-aminopropyl)imidazole (18.6 µL, 0.16 mmol ,1.4 eq) and 4-DMAP (18.4 mg, 0.15 mmol, 1.3 eq) were dissolved in dry CH2Cl2 (4.0 mL). DCC (31.1 mg, 0.15 mmol, 1.3 eq) was portionwise added at 0 °C under argon atmosphere. The reaction mixture was stirred at room temperature for 3 hours in the dark.

The reaction was monitored by TLC. Once finished, H2O (4.0 mL) was added and the mixture was stirred for 15 minutes. Then, organic phase was extracted with CH2Cl2, washed (distilled H2O), dried (MgSO4) and concentrated. The residue was dissolved in a minimum amount of CH2Cl2 and put in fridge overnight. The crude was then filtered, washed with cold CH2Cl2, and the filtrate was concentrated (the operation was reiterated twice). Recrystallization from CH2Cl2/n-hexane afforded the chlorin 13 as a dark green solid in 46% yield (34 mg). 174.4, 173.1, 161.8, 155.6, 151.1, 149.4, 145.6, 142.1, 138.1, 137.3, 136.7 (2s), 136.1, 132.8, 130.8, 129.6, 128.6, 123.5, 122.9, 122.7, 104.4, 97.1, 94.5, 52.5, 50.5, 49.6, 48.8, 47.7, 37.0, 35.7, 34.4, 33.6, 31.0, 29.9, 26.2, 25.6, 23.5, 19.9, 17.7, 12.5, 12.2, 11.5 Cytotoxicity study in the dark. MCF-7 cells were seeded into 96-well plates at 5000 cells per well in 200 µL culture medium and allowed to grow for 24 h. Increasing concentrations (from 0 to 2 µM) of compounds were incubated in culture medium of MCF-7 cells during 72 h. Then, a MTT assay was performed to evaluate the toxicity. Briefly, cells were incubated for 4 h with 0.5 mg.mL -1 of MTT (3-( 4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide;

Promega) in media. The MTT/media solution was then removed, and the precipitated crystals were dissolved in EtOH/DMSO (1:1). The solution absorbance was read with a microplate reader at 540 nm.

PDT experiments. For 450 nm and 545 nm in vitro phototoxicity, 1000 cells by well were plated in a 384-well plates, in 50 µL of culture medium. Twelve hours after seeding, compounds were added on cells at a concentration of 0.5 µM for 24 h. After this incubation, cells were submitted (or not) to laser irradiation for 10 min with the Leica DM IRB at 450 nm (4.6 J.cm - 2 ) or 545 nm (19.5 J.cm -2 ). The laser beam was focused by a microscope objective lens (magnification x4). Two days after irradiation, an MTT assay was performed to measure the cell viability. For 650 nm in vitro phototoxicity, 5000 cells by well were plated in a 96-well plates, in 100 µL of culture medium. Twelve hours after seeding, compounds were added on cells at a concentration of 0.5 µM for 24 h. Then, cells were submitted (or not) to laser irradiation with a red laser at 650 nm for 10 min (18.75 J.cm -2 ). Two days after irradiation, an MTT assay was performed to evaluate the cell viability.

  Chart 1. Left: Structures of compounds A-D. Right: Cytotoxic (no laser) and photodynamic effect (laser) of imidazolium salt A and gold(I) complexes B-D. The cells were incubated or not (control experiment in black) with 10 µm of PS for 4 hours and then, submitted or not to laser irradiation (= 405 nm, 18.75 J cm -2 , 10 minutes). Cells were allowed to grow for 2 days and cell viability was quantified with MTT assay. Data are mean values standard deviation from three independent experiments. *No living cells detected.[14]

  Scheme 1: Synthesis of porphyrins 3, 4-I and 4-BF4.

Figure 1

 1 Figure 1: 1 H NMR spectra (400 MHz, DMSO-d6, 298 K) of gold(I) complexes 8 (a) and 9 (b).

Figure 2 :

 2 Figure 2: Cytotoxicity of imidazolium salts 3 and 6, and their corresponding gold(I) complexes 8-11 on MCF-7 cancer cells. The cells were incubated without (control) or with 0.05, 0.1, 0.5, 1 or 2 µM of the different compounds for 72 hours. Cell viability was quantified with MTT assay. Data are mean values standard deviation from three independent experiments.

Figure 3 :

 3 Figure 3: Photodynamic effect of imidazolium salts 3 and 6, and their corresponding gold(I) complexes 8-11 on MCF-7 cancer cells. The cells were incubated with 0.5 µM of each compound for 24 hours and then submitted to laser irradiation at λ = 450, 545 or 650 nm for 10 minutes. Cells are allowed to grow for 48 hours and cell viability was quantified with MTT assay.

  Scheme 5: Synthesis of the monocationic chlorin 14.

Figure 4 .

 4 Figure 4. 1 H 2D DOSY NMR spectrum (600 MHz, CD2Cl2, 298 K) of the chlorin 14.

  Figure 5. a) Cytotoxic effect of chlorin derivatives 12-14 on MCF-7 cancer cells. The cells were incubated without (control) or with different concentrations of compounds 12-14 for 72 hours. Cell viability was quantified with MTT assay. Data are mean values standard deviation from three independent experiments. b) Photodynamic effect of the chlorin derivatives 12-14under irradiation at λ = 450 nm (left), 545 nm (middle) and 650 nm (right). MCF-7 cancer cells were incubated with 0.5 µM of each chlorin for 24 hours and then submitted to laser irradiation for 10 minutes. Cells were allowed to grow for 48 hours and the living MCF-7 cells were quantified with MTT assay.

  1 H DOSY NMR (600 MHz, CD2Cl2, 298 K): 1.54  10 -10 m 2 .s -1 . UV-visible (CH2Cl2): λmax (log ε) = 420 (5.75), 548 (4.38) nm. HR ESI-MS (positive mode): calcd for C44H32AuClN6Zn: 946.1911, found: 946.1923.

13 C{ 1 H} NMR (150.9 MHz, CD2Cl2, 298 K):

	4 ), 5.73
	(s, 2H, CH2), 3.95 (s, 3H, N-CH3), 2.61 (s, 9H, CH3 mes para), 1.86-1.84 (2s, 18H, CH3 mes ortho), -
	2.62 (s, 2H, NH) ppm.

δ 172.5 (CNHC), 143.0,

-visible (CH2Cl2):

  mes ortho), 21.7 (CH3 mes para) ppm. UV

	λmax (log ε) = 418 (5.65), 514 (4.28), 548 (3.80), 590 (3.75), 647 (3.55) nm. MALDI-TOF +
	MS: calcd for C64H55Au4N12Cl4: 1066.38, found 1066.40.

Pyropheophorbide a 12. The synthesis and characterization data of pyropheophorbide a 12

  Chlorin 13 (30 mg, 0.047 mmol, 1.0 eq) was dissolved in dry THF (6.0 mL) and CH3I (290 µL, 4.7 mmol, 100 eq) was added. The solution was stirred at 40 °C for 2 days under argon atmosphere and protected from light. The reaction was monitored by TLC. After evaporation of the solvent, recrystallization from CH2Cl2/n-hexane afforded the monocationic chlorin 14 as a black solid in 52% yield(19 mg). 9.50, 9.37, 8.72 (each s, each 1H, 5, 10 and 20-H), 9.26 (br s, 1H, Hd), 8.04 (dd, 3 JH-H = 17.9, 11.5 Hz, 1H, 3 1 ), 7.04, 6.98 (each br s, each 1H, He and Hf ),6.31 and 6.18 (2d AB system, 2 JH-H = 19.8 Hz, each 1H, 3 2 ), 5.32 and 5.07 (2 d AB system, 2 JH-H = 19.2 Hz, each 1H, 13 2 ),4.70-4.64 and 4.33-4.28 (each m, each 1H, 17 and 18), 3.79 (s, 3H, Hg), 3.62 and 3.23 (each s, each 3H), 3.00-2.91 (m, 2H, Ha), 2.71-2.56 and 2.43-2.32 (each m, each 3H, 17 1 , 17 2 and Hb), 1.81(d, 3 JH-H = 7.4 Hz, 1H, 18 1 ), 1.69 (t, 3 JH-H = 7.6 Hz, 4H, 8 2 ), -1.75 (s, 2H,

	1 H NMR (400 MHz, CD2Cl2, 298 K): δ 9.44, 9.41, 8.64 (each s, each 1H, 5, 10 and 20-H), 8.04 (dd, 3 JH-34-6.16 (m, 2H, 3 2 ), 5.24 and 5.06 (2d AB system, 2 JH-H = 19.8 Hz, each 1H, 13 2 ), 4.58-4.51, 4.39-4.36 (each m, each 1H, 17 and 18), 3.75-3.69 (m, 2H, 8 1 ), 3.59-3.49 (m, 2H, Hc), 3.65, 3.43, 3.26 (each s, each 3H, 2 1 , 7 1 and 12 1 ), 2.89-2.72, 2.66-2.42, 2.25-2.17 and 1.95-1.80 (each m, each 2H, 17 1 , 17 2 , Ha and Hb), 1.81 (d, 3 JH-H = 7.3 Hz, 3H, 18 1 ), 1.67 (t, 3 JH-H = 7.6 Hz, 4H, 8 2 ), -1.79 (s, 2H, NH) ppm. UV-visible (CH2Cl2): λmax (log ε) = 412 (4.57), 508 (3.88), 538 (3.82), 609 (3.75), 667 (4.13) nm. MALDI-TOF + MS: calcd for C39H43N7O2 642.35, found 642.30. Chlorin 14. NH) ppm. 13 C{ 1 H} NMR (150.9 MHz, (CD2Cl2/CD3OD 9:1 (v:v), 298 K): δ 197.1 (C=O),

H = 17.8, 11.6 Hz, 1H, 3 1 ), 7.18 (br dd, 1H, Hd), 6.81 (br dd, 3 JH-H = 1.3 Hz and 4 JH-H = 1.3 Hz, 1H, Hf), 6.62 (br dd, 3 JH-H = 1.3 Hz and 4 JH-H = 1.3 Hz, 1H, He), 6.1 H NMR (400 MHz, (CD2Cl2/CD3OD 9:1 (v:v), 298 K): δ

  ppm. UV-visible (CH2Cl2): λmax (log ε) = 413(4.67), 509 (3.75), 540 (3.67), 610 (3.61), 668 (4.28) nm. HR ESI-Human breast cancer cells (MCF-7) were purchased from ATCC (American Type Culture Collection, Manassas, VA). Cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM-F12) supplemented with 10% fetal bovine serum and 1% penicillinstreptomycin. Cells were allowed to grow in humidified atmosphere at 37 °C under 5% CO2.

MS (positive mode): calcd for C40H46N7O2 + 656.3708 found 656.3694. HR ESI-MS (negative mode): calcd for I  : 126.9050 found: 126.9046.

4.3. Biological studies.

Cell culture.

Acknowledgement

The authors are grateful to the University of Montpellier, the CNRS and the French Ministry of Research for financial support. SR is also grateful for financial support from the Région Languedoc-Roussillon (Research Grant "Chercheur(se)s d'Avenir -2015-005984) and the FEDER Program (Fonds Européen de Développement Régional).

Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/xxxxxxx


Fabrice Damon
email: damon.fabrice@gmail.com

Zhihan Li

Yin Yan

Wu Li

Kun Guo

Paul C Quinn

Olivier Pascalis

David Meary

David Méary

Yin Li

Wu Yan

Li

Preference for attractive faces

Keywords: humans, rhesus macaques, faces, attractiveness, eye-tracking, mate choice

published or not. The documents may come

Despite the long held view that "beauty is in the eye of the beholder," judgments of facial attractiveness are largely shared both within and between cultures [START_REF] Cunningham | Their ideas of beauty are, on the whole, the same as ours": Consistency and variability in the cross-cultural perception of female physical attractiveness[END_REF][START_REF] Jones | Criteria of facial attractiveness in five populations[END_REF][START_REF] Langlois | Maxims or myths of beauty? A meta-analytic and theoretical review[END_REF][START_REF] Little | Facial attractiveness: Evolutionary based research[END_REF][START_REF] Perrett | Effects of sexual dimorphism on facial attractiveness[END_REF][START_REF] Perrett | Facial shape and judgements of female attractiveness[END_REF][START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF][START_REF] Rhodes | Attractiveness of facial averageness and symmetry in nonwestern cultures: In search of biologically based standards of beauty[END_REF]. While acknowledging interobserver variation [START_REF] Hönekopp | Once more: Is beauty in the eye of the beholder? Relative contributions of private and shared taste to judgments of facial attractiveness[END_REF], multiple reports indicate that there can be a common sensibility of what is attractive across cultures and point to a biological account of the preference for attractive faces [START_REF] Hahn | Neural and behavioral responses to attractiveness in adult and infant faces[END_REF][START_REF] Little | Facial attractiveness: Evolutionary based research[END_REF][START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF].

Facial attractiveness is influenced by a variety of factors (for a review and a meta-analysis, see [START_REF] Little | Facial attractiveness: Evolutionary based research[END_REF][START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF], eluding explanation by a single principle. Due to this multifactor determination, physical measurements of attractiveness are not straightforward as are, for example, height or weight measures. The easiest and most common way to evaluate beauty in a face is to ask human observers to rate a face for its attractiveness. These explicit judgments of attractiveness are a good predictor of implicit behaviors linked to preferences, such as longer looking times, either in adults [START_REF] Hayden | Economic principles motivating social attention in humans[END_REF][START_REF] Leder | When attractiveness demands longer looks: The effects of situation and gender[END_REF][START_REF] Shimojo | Gaze bias both reflects and influences preference[END_REF], or in infants from 2-to 3-day-olds to 15-montholds (Damon, Méary, et al., 2017;[START_REF] Damon | A review of attractiveness preferences in infancy: From faces to objects[END_REF][START_REF] Langlois | Facial diversity and infant preferences for attractive faces[END_REF][START_REF] Langlois | Infant preferences for attractive faces: Rudiments of a stereotype[END_REF][START_REF] Samuels | Facial aesthetics: Babies prefer attractiveness to symmetry[END_REF][START_REF] Samuels | Aesthetic perception of faces during infancy[END_REF][START_REF] Slater | The role of facial orientation in newborn infants' preference for attractive faces[END_REF][START_REF] Slater | Newborn infants prefer attractive faces[END_REF][START_REF] Van Duuren | Early aesthetic choices: Infant preferences for attractive premature infant faces[END_REF]. The overlap between ratings made by adults and visual preferences in adults and infants suggests that some of the features upon which adult raters rely to make their judgments are correlated with the features that drive visual attention toward implicit preferences. Contrary to adults, young infants are unlikely to be influenced by cultural standards of beauty. Thus, such results might also indicate that there are some biologically based principles of attractiveness [START_REF] Damon | A review of attractiveness preferences in infancy: From faces to objects[END_REF][START_REF] Quinn | Preference for attractive faces in human infants extends beyond conspecifics[END_REF][START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF].

Two evolutionary frameworks have been proposed to explain what makes faces attractive and why humans show preferences for attractive faces. On the one hand, preference for attractive faces can be seen as an adaptation to solve the problem of mate choice because attractiveness and its components may serve as indicators of mate quality, such as health, parasitic resistance, or fertility [START_REF] Fink | Evolutionary psychology of facial attractiveness[END_REF][START_REF] Little | Facial attractiveness: Evolutionary based research[END_REF][START_REF] Thornhill | Human facial beauty: Averageness, symmetry, and parasite resistance[END_REF], 1994;[START_REF] Thornhill | Developmental stability, disease and medicine[END_REF][START_REF] Zebrowitz | Sensitivity to "bad genes" and the anomalous face overgeneralization effect: Cue validity, cue utilization, and accuracy in judging intelligence and health[END_REF]. Potential mate quality indicators include, but are not limited to, prototypicality (i.e., the proximity of a face to the average of a population, in terms of mathematical trait values), sexual dimorphism (i.e., feminine traits in female faces and masculine traits in male faces), and bilateral symmetry (i.e., the similarity between left and right halves of the face). For example, averageness is linked with greater genetic diversity, which may result in greater parasitic resistance, whereas deviations from average could signal chromosomal disorders [START_REF] Thornhill | Developmental stability, disease and medicine[END_REF]. Similarly, facial symmetry can be an indicator of stability in development and resistance to environmental perturbations [START_REF] Little | Facial attractiveness: Evolutionary based research[END_REF][START_REF] Thornhill | Human fluctuating asymmetry and sexual behavior[END_REF][START_REF] Thornhill | Developmental stability, disease and medicine[END_REF].

On the other hand, preference for attractive faces could be an emergent property of our object recognition systems [START_REF] Damon | A review of attractiveness preferences in infancy: From faces to objects[END_REF][START_REF] Halberstadt | The generality and ultimate origins of the attractiveness of prototypes[END_REF][START_REF] Halberstadt | The attractiveness of nonface averages: Implications for an evolutionary explanation of the attractiveness of average faces[END_REF], 2003;[START_REF] Quinn | Preference for attractive faces in human infants extends beyond conspecifics[END_REF][START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF][START_REF] Wallis | Toward a unified model of face and object recognition in the human visual system[END_REF]. Generalization effects in biological systems of object recognition have been shown to induce biases toward prototypical or symmetrical stimuli as a response after category learning [START_REF] Enquist | Symmetry, beauty and evolution[END_REF][START_REF] Enquist | Generalization and the evolution of symmetry preferences[END_REF][START_REF] Ghirlanda | Chickens prefer beautiful humans[END_REF][START_REF] Jansson | Experimental evidence of receiver bias for symmetry[END_REF][START_REF] Wallis | Toward a unified model of face and object recognition in the human visual system[END_REF][START_REF] Wallis | The prototype effect revisited: Evidence for an abstract feature model of face recognition[END_REF]. Even preferences for extreme sexual dimorphism can be attributed to sensory biases without a link to individual fitness [START_REF] Garcia | Evidence that sensory traps can evolve into honest signals[END_REF][START_REF] Guilford | Receiver psychology and the evolution of animal signals[END_REF][START_REF] Ryan | Sexual selection, receiver biases, and the evolution of sex differences[END_REF].

However, these frameworks are not mutually exclusive. Both mechanisms may act independently to shape attractiveness preference (Waitt & Little, 2006), or one could derive from the other. For example, initial sensory biases could evolve as signals of mate quality [START_REF] Garcia | Evidence that sensory traps can evolve into honest signals[END_REF][START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF], or mechanisms derived from mate choice could operate on top of perceptual biases to make humans particularly attentive to facial attractiveness in conspecifics [START_REF] Little | Evidence against perceptual bias views for symmetry preferences in human faces[END_REF]. These possibilities seem, at first glance, to conflict with reports showing that components of attractiveness such as symmetry or prototypicality can influence preferences for a variety of stimuli, including those both relevant and not relevant to mate choice in humans [START_REF] Halberstadt | The attractiveness of nonface averages: Implications for an evolutionary explanation of the attractiveness of average faces[END_REF], 2003;[START_REF] Reber | Processing fluency and aesthetic pleasure: Is beauty in the perceiver's processing experience?[END_REF]) and monkeys [START_REF] Anderson | Are monkeys aesthetists? Rensch (1957) revisited[END_REF]Damon, Méary, et al., 2017;Waitt & Little, 2006, but see Tomeo, Ungerleider, & Liu, 2017). However, the influence of these components has been shown to be modulated by the category of stimuli presented. Symmetry is most pleasant when it corresponds to human faces rather than to the faces of other species or nonface objects [START_REF] Little | Domain specificity in human symmetry preferences: Symmetry is most pleasant when looking at human faces[END_REF]. Similarly, the magnitude of the influence of prototypicality on attractiveness judgments for exemplars of various nonhuman animal categories is related to their perceived or actual phylogenetic similarity to humans [START_REF] Halberstadt | The generality and ultimate origins of the attractiveness of prototypes[END_REF]. From an evolutionary perspective, it would indeed make sense that humans are more sensitive to attractive traits in human faces compared with other-species faces.

Both the mate choice and the sensory bias frameworks place the mechanisms responsible for the preferences for attractive faces in the evolution of the human lineage [START_REF] Little | Facial attractiveness: Evolutionary based research[END_REF][START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF], leaving open the possibility that nonhuman primates might also share such mechanisms, for example, preference for symmetry or regularity in monkeys [START_REF] Anderson | Are monkeys aesthetists? Rensch (1957) revisited[END_REF]Waitt & Little, 2006), and therefore show a form of sensitivity to attractive faces. Furthermore, if human ratings of attractiveness are the product of mechanisms shared among primates, they might also predict visual face preferences in monkeys. Although the issue of how much a monkey evaluates a face as attractive is a question difficult to address (if even possible), implicit face preferences can be inferred from looking-time measures [START_REF] Méary | Seeing two faces together: Preference formation in humans and rhesus macaques[END_REF].

The aim of the current study was to determine whether explicit ratings of attractiveness by human judges would predict implicit visual preferences in other humans and also in rhesus macaques and, if they do, whether such preferences would extend beyond conspecific faces. The sensory bias account of preference formation implies that human ratings of attractiveness should predict the visual preferences of human observers, irrespective of the species corresponding to the stimulus faces. Human ratings of attractiveness of human and monkey faces could also predict the visual preferences of macaque observers if the macaques share similar perceptual biases due to the common lineage between humans and macaques. By contrast, a mate choice account suggests that humans should present a preference for attractive human faces but not attractive monkey faces. Furthermore, if human ratings of attractiveness only reflect human mate choice, macaques should not present a preference for attractive human or attractive monkey faces. A last possibility is to envision that both mechanisms can play a role in preference formation but that their contributions are modulated by the species of the faces.

To test these hypotheses, human judges were asked to rate the attractiveness of human and rhesus macaque faces. The faces were then paired in accord with the attractiveness ratings (i.e., attractive faces were paired with unattractive faces) and shown to human and rhesus macaque participants while their eye-movements were recorded.

Method Participants

Humans. A total of 26 students from the University of Grenoble Alpes (23-32 years, 13 women) participated in the experiment. Participants had no specific history of being familiar with rhesus monkey faces, although they all had seen monkey This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

faces in TV documentaries or in books. Participation was rewarded with credit in an experimental psychology course. The investigation was conducted at the University of Grenoble Alpes, approved by the local ethics committee "Comité d'éthique des centre d'investigation clinique de l'inter-région Rhône-Alpes-Auvergne", Institutional Review Board, and informed consent was obtained.

Monkeys. Five male adult rhesus macaques (Macaca mulatta, 5-9 kg, 5-9 years) participated in the experiment. All the monkeys were born in captivity and housed indoors. They grew up in groups and were exposed to their conspecifics as well as masked and unmasked caretakers on a daily basis in Beijing, China. The monkeys had very limited experience with Caucasian faces, although they could have occasionally seen Caucasian visitors. The monkeys also had limited experience with viewing photographs of Caucasian and Asian human and monkey faces (Ͻ1 week for each tested monkey) and were unfamiliar with the rhesus macaque and human faces used as stimuli. All of the monkeys were midranked individuals in the hierarchy of the colony. All the monkeys that participated in the current study had previous experience with eye-tracking experiments. They were familiar with the setting and the eye-tracking apparatus. Ethical approval was granted by the Institutional Animal Care and Use Committee of Beijing Normal University, with all procedures in compliance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals.

Stimuli

We used 16 Caucasian faces (eight female) and 16 rhesus (16 female) macaque faces to make up the set of face pairs used in the experiments. A total of 12 rhesus macaque faces came from a rhesus cohort in the Laboratory of Comparative Ethology, and four faces came from the PrimFace database (http://visiome.neuroinf .jp/primface). All the faces were frontal views with open eyes and neutral (mouth closed) expression (see Figure 1 for an illustration of the faces used in the experiment). Macaques were presented with opposite sex faces only. Presenting the face of an unfamiliar own-sex conspecific could signal the presence of an out-group individual (i.e., potential rival), thus creating a situation of increased vigilance resulting in longer looking time [START_REF] Pfefferle | Monkeys spontaneously discriminate their unfamiliar paternal kin under natural conditions using facial cues[END_REF][START_REF] Schell | Adult but not juvenile Barbary macaques spontaneously recognize group members from pictures[END_REF]. In a visual-preference paradigm, this gaze behavior would be confounded with any face preference due to attractiveness. Because it is difficult to unequivocally establish the biological significance of specific response biases from looking-time procedures, we sought to avoid this potential confound. Unfamiliar opposite sex faces of conspecifics (portraying possible mates) do not trigger vigilance behavior and are better suited to our purpose. Studies examining the influence of various facial features on face preference in macaque monkeys have typically used opposite sex faces [START_REF] Dubuc | Is male rhesus macaque red color ornamentation attractive to females?[END_REF][START_REF] Hughes | Extraneous color affects female macaques' gaze preference for photographs of male conspecifics[END_REF][START_REF] Waitt | Evidence from rhesus macaques suggests that male coloration plays a role in female primate mate choice[END_REF]Waitt & Little, 2006).

Attractiveness ratings. The 16 rhesus macaque faces were previously individually rated for attractiveness by a group of 15 students from the University of Grenoble Alpes and by six primatologists from the University of Strasbourg. There was a strong correlation between the mean rating of the students (nonexperts with macaques) and the mean rating of the primatologists (experts with macaques), r( 14) ϭ 0.86, and interrater reliability was good (Cronbach's ␣ ϭ .76), so all ratings were averaged together. The 16 human faces were rated by another group of 19 students. The faces were normalized for luminance in the L ء a ء b color space before attractiveness evaluation. Attractiveness could range from 1 (low attractiveness) to 7 (high attractiveness). Attractiveness ratings of the monkey and human faces were normalized within their respective categories using Z scores.

Visual preference task. Each attractive face was randomly paired with an unattractive face within species according to the attractiveness ratings. We prepared eight pairs of human faces (four pairs of male faces and four pairs of female faces) and eight pairs of rhesus faces (eight pairs of female faces), each showing faces with high and low attractiveness ratings. The faces were pasted side by side on a 30-cd/m 2 gray background. We constructed a second set of 16 face pairs by counterbalancing the left-right positioning of the high and low attractiveness faces. Within an experimental session, the participants viewed each of the 16 face pairs twice, thus yielding a total of 32 stimulus pairs presented in a random order to each participant. This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

Procedure

During the visual preference task, eye positions of monkey and human participants were measured by an EyeLink 1000 (SR Research Ltd., Ontario, Canada). For technical reasons, sampling frequency and viewing distance were 500 Hz and 100 cm for monkeys and 250 Hz and 60 cm for humans. A standard 5-point calibration procedure was conducted before the beginning of each experimental session. Both groups of participants viewed the display binocularly. Stimuli were displayed on a gamma-corrected color monitor (Iiyama Vision Master Pro 514, 40 ϫ 30 cm, Iiyama, North America) with a resolution of 1024 ϫ 768 pixels and frame rate of 100 Hz. Given the screen distance and the face size, the stimuli on screen subtended visual angles of 12°and 20°vertically for the monkey and human participants, respectively.

Monkey participants. The detailed experimental setup has been described in [START_REF] Mcfarland | Social interactions through the eyes of macaques and humans[END_REF]. The monkeys were seated in a primate chair with their head restrained. A trial was started with a fixation point (FP) displayed on the center of the monitor. If the monkeys maintained fixation for 1 s, the FP disappeared, and one of the image pairs was presented for 5 s. During the free-viewing presentation, the monkeys passively viewed the images. The intertrial interval was 1 s, during which the monkeys received a juice reward without any specific task requirement related to the stimuli. We conducted three testing sessions for each monkey participant, separated by 2 to 3 days.

Human participants. Humans were also seated, and head movements were limited with a chin rest. A trial was started with an FP displayed on the center of the monitor. The experimenter triggered the image presentation manually after ensuring that the participant fixated on the FP. A drift correction was performed every five trials to realign gaze and correct for small involuntary head movement. Each stimulus pair was presented for 5 s, and the instructions emphasized free viewing of the images. A single testing session included the 32 stimulus pairs presented in a random order.

Results

Data Processing and Statistical Analysis

All calculations for the identification of fixations were performed in degrees of visual angle. The parsing of the eye data into saccades and fixations was done according to the method developed by [START_REF] Engbert | Microsaccades uncover the orientation of covert attention[END_REF] for microsaccades. Parameters were adjusted for saccade detection. In our analyses, the minimum duration for the fixations was set to 80 ms. The fixations within each trial were then classified according to their locations (on the low or high attractiveness face, or elsewhere on the screen). Only trials where participants gazed at both faces, for at least one fixation and with the initial gaze on the FP, were included in the data set. In the group of human participants, these criteria excluded one and nine trials out of 416 trials (i.e., 0.2 and 2.16% of the trials) for the human and monkey face types, respectively. For the monkey participants, the number of valid trials for each monkey is given in Table 2. The number of trials was 48 per face type (3 ϫ 16). The number of valid trials was small for monkey I (N ϭ 10 and N ϭ 12 for the human and monkey faces, respectively), with 79 and 75% of invalid trials. For the other four rhesus macaques, the rejection rate ranged from 2% to 18%.

The number of fixations and the total looking time on each face were calculated for each participant. The goal of the main analysis was to test whether the attractiveness level influenced looking time and whether this effect depended on face type (human or monkey). This was completed separately for the human and rhesus macaque groups using a linear model of the form

Y ij ϭ ϩ ␣F ij ϩ ␤X ij ϩ ␥F ij X ij ϩ E ij
, where Y ij represented the group's looking duration at a face j (one of the 16 faces used for each species) of face type i (own or other-species), and X ij represented the Z value of attractiveness for this face. Face type (human or rhesus macaque) was recoded as face species (own or other depending on the participant group) and was treated as a factor, with F ij ϭ 0 for other-species faces and F ij ϭ 1 for own-species faces. The Z score of attractiveness was treated as a numeric variable. According to the linear model, is an intercept term that approximates the average looking time at other-species faces (due to the transformation of attractiveness ratings into Z scores). The slope ␤ is a coefficient capturing the effect of attractiveness in other-species faces. The ␣ and ␥ terms represent the modification of the intercept and slope, respectively, when looking at own-species faces (i.e., when F ij ϭ 1). We used partial p 2 measures to estimate effect sizes. Stimulus presentation and data processing were done with Matlab using the Psychtoolbox [START_REF] Brainard | The psychophysics toolbox[END_REF], and the EyeLink Toolbox (Cornelissen, Peters, & Palmer, 2002) for data acquisition. Statistical analyses were done with R (R Development Core Team, 2008).

Linear Model of Attractiveness Effects

Human participants. When applied to the mean spontaneous looking time in the human group, the linear model accounted for 49% of the variation in mean looking duration at the face photographs, multiple R 2 ϭ 0.49, F(3, 28) ϭ 8.88, p Ͻ .001. Table 1 reports the values for the model's parameter , ␤, ␣, and ␥. Figure 1 (top) can be used to illustrate the model's output. The intercept coefficient and the slope coefficient ␤ were used to fit the looking duration for other-species faces. Because we used Z scores for the attractiveness ratings, the intercept gives the mean looking time to other-species faces. The nonsignificant t value for the slope ␤ indicates that mean Residual standard error: .253 on 28 degrees of freedom Note. Bold face ϭ p Ͻ .05. This document is copyrighted by the American Psychological Association or one of its allied publishers.

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looking duration for other-species faces was not linearly related to attractiveness level. The mean looking time to own-species faces was fitted using the intercept coefficient ( ϩ ␣) and the slope (␤ ϩ ␥). The change in mean looking time due to face type, captured by the coefficient ␣, was not significant. This outcome suggests that, overall, both face types (own-and other-species faces) were looked at for the same average duration. However, the change in slope, captured by the coefficient ␥ (␥ ϭ 0.165 s) was significant. This result indicates that attractiveness influenced the mean looking time to ownspecies faces. According to Table 1, the slope for the own-species faces was 0.194 (␤ ϩ ␥), meaning that change of one unit in Z score was associated with an increase of 0.194 s in looking time. Thus, attractiveness ratings correlated with the spontaneous looking duration of human participants toward the faces of their conspecifics; however, this effect was not significant when the human participants looked at monkey faces.

Rhesus macaque participants. When applied to the mean spontaneous looking time in the group of rhesus macaque participants, the linear model accounted for 32% of the variation in mean looking duration at the face photographs, multiple R 2 ϭ 0.32, F(3, 28) ϭ 4.34, p ϭ .012. The slope coefficient ␤ was nonsignificant, indicating that the mean looking time to other-species faces (i.e., the human faces in this case) was unrelated to the attractiveness ratings (Table 1). As for the human participants, the coefficient ␣, representing the change in mean looking time between own-and other-species faces was not significant, suggesting that both face types (own-and other-species faces) were looked at for the same average duration. More importantly, the ␥ coefficient was positive and significant, indicating an effect of attractiveness for own-species faces. Overall, then, as was the case for the human participants, attractiveness rating predicted the spontaneous looking duration of the rhesus macaque participants, but only for the faces of their conspecifics.

Results From Individual Monkeys

Table 2 provides the mean differences in number of fixations on human and monkey faces of high and low attractiveness for each rhesus macaque participant. When the monkeys were looking at pairs of human faces, neither the number of fixations nor the looking times increased significantly for faces of high attractiveness. For conspecific monkey faces of high versus low attractiveness, however, we found a significant increase in both fixation number and looking time toward faces high in attractiveness in three out of five monkeys. Monkey I had only a small number of valid trials but was nevertheless included in the study. Removing this monkey's data strengthened the ownspecies effect found in the previous analysis of monkey performance.

Additional Analyses

Effect of gender. An attractiveness preference influenced by mate choice mechanisms would imply that the effect of attractiveness is stronger for male participants looking at attractive female faces (compared with attractive male faces). Conversely, female participants should present a stronger effect of attractiveness for male than female faces.

To examine this possibility, we tested the influence of "Face Gender," "Subject Gender," and "Attractiveness Rating" on the human looking times toward attractive faces. Results showed interactions between Attractiveness Rating and Subject Gender, and between Attractiveness Rating and Face Gender-Rating ϫ Subject Gender, F(1, 832) ϭ 23.989, p Ͻ .001; Rating ϫ Face Gender, F(1, 832) ϭ 18.565, p Ͻ .001, see Table S2, in online supplemental material. Overall, these interactions indicated that (a) the effect of attractiveness was stronger in our male participants looking at female faces, which is consistent with the mate choice hypothesis, and that (b) the effect of attractiveness was also stronger on female face stimuli than on male face stimuli. Although this latter result may reflect an artifact of our stimuli, it may also indicate that female participants attended to attractive female faces. Such behavior has been previously interpreted either as engagement of "social comparison" (e.g., check out the competition) or a higher tendency toward bisexual [792,1956] Note. LT ϭ looking time; CI ϭ confidence interval. Bold face ϭ p Ͻ .05. This document is copyrighted by the American Psychological Association or one of its allied publishers.

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orientation in female participants [START_REF] Hall | Differential gaze behavior towards sexually preferred and non-preferred human figures[END_REF][START_REF] Little | Domain specificity in human symmetry preferences: Symmetry is most pleasant when looking at human faces[END_REF].

We also examined the effect of Subject Gender on the human looking times toward monkey faces. This analysis showed no effect of Subject Gender, F(1, 828) ϭ 0.913, p ϭ .340, which is not surprising given that there was no effect of the attractiveness ratings on the human looking times toward monkey faces.

Our monkey participants were all males, and they were presented with female monkey faces, and with male and female human faces. We therefore examined the effect of Face Gender only for human faces. Results showed no effect of Face Gender or Rating, nor of any interaction (all ps Ͻ .11, see Table S3, in online supplemental material), indicating that there was no significant difference in monkey looking times on male versus female human faces.

Pearson correlation between looking times across species of observers. To examine the potential correlation between looking time across species of observers, we computed the Pearson's linear correlation coefficients between human and monkey looking times toward human faces, monkey faces, or both (Figure 1). Overall, we found no significant correlation for (a) looking times of humans and monkeys on human faces: r( 14) ϭ 0.17, p ϭ .510, 95% CI [Ϫ0.49, 0.71], or (b) looking times of humans and monkeys on both human and monkey faces: r(30) ϭ 0.29, p ϭ .110, 95% CI [Ϫ0.18,0.65]. Only the correlation between human and monkey looking times on monkey faces approached significance, r(14) ϭ 0.44, p ϭ .084, 95% CI [Ϫ0.23, 0.83]. These results are consistent with our pattern of findings showing that the attractiveness effect is species-specific (e.g., human and monkey looking times toward human faces were not correlated because only human participants looked longer at human faces rated as attractive). Notably, the correlation between human and monkey looking times on monkey faces is close to significance (although it is below the threshold of ␣ ϭ .05 using a one-tailed t test). Because monkey faces were rated by human judges for attractiveness, it follows that human looking times would show a trend toward a preference for the monkey faces rated as attractive. The effect size is however much smaller for monkey faces (R 2 ϭ 0.11) compared with human faces (R 2 ϭ 0.66), supporting our conclusion that the influence of attractiveness on looking times is stronger for own-species faces than for other-species faces. Further analyses, including (a) representation of the time course of visual attention toward high and low attractiveness faces; (b) the spatial distribution of fixations over the human and monkey faces; (c) scatter plots of human and monkey looking times toward human faces, monkey faces, or both; and (d) analysis of variance tables describing overall effects of each factor (main effect and interaction) for all the models tested, are provided in the supplemental files.

Discussion

In the present study, we sought to examine whether explicit evaluations of facial attractiveness by human judges would predict implicit visual preferences of adult humans and rhesus macaques. The findings revealed species-specific visual preferences for faces with high attractiveness ratings, because human participants looked longer at attractive human faces but not attractive monkey faces, whereas macaque participants looked longer at attractive macaque faces but not attractive human faces. Strikingly, human judgments of facial attractiveness of monkey faces predicted the visual preferences of macaque monkeys, suggesting at least a partial overlap between the features used by the human raters and those driving visual attention in macaques.

The current outcomes can be discussed in the context of the larger debate about the origin of preferences for attractive faces. Do attractiveness preferences reflect an adaptation for mate choice, or do they come about as a consequence of sensory processing biases [START_REF] Halberstadt | The generality and ultimate origins of the attractiveness of prototypes[END_REF][START_REF] Halberstadt | The attractiveness of nonface averages: Implications for an evolutionary explanation of the attractiveness of average faces[END_REF], 2003;[START_REF] Rhodes | The evolutionary psychology of facial beauty[END_REF]? Our view is that the findings can be taken as evidence that both explanations are needed to account for attractiveness judgments and should not be considered as mutually exclusive alternatives. Although preferences stemming from adaptation for mate choice are likely to be species-specific [START_REF] Halberstadt | The generality and ultimate origins of the attractiveness of prototypes[END_REF][START_REF] Little | Domain specificity in human symmetry preferences: Symmetry is most pleasant when looking at human faces[END_REF], preferences arising out of general perceptual mechanisms could be shared among phylogenetically close species, such as humans and macaques, and have led to similar preferences: for symmetry in humans, capuchin monkeys, and squirrel monkeys [START_REF] Anderson | Are monkeys aesthetists? Rensch (1957) revisited[END_REF][START_REF] Little | Domain specificity in human symmetry preferences: Symmetry is most pleasant when looking at human faces[END_REF], for curved contours in humans and chimpanzees [START_REF] Munar | Common visual preference for curved contours in humans and great apes[END_REF], and for prototypicality in human and macaque infants (Damon, Méary, et al., 2017).

The human looking time preference for attractive human faces replicates previous findings [START_REF] Hayden | Economic principles motivating social attention in humans[END_REF][START_REF] Leder | When attractiveness demands longer looks: The effects of situation and gender[END_REF][START_REF] Shimojo | Gaze bias both reflects and influences preference[END_REF] and suggests that the features used by the independent group of observers to explicitly rate human faces were at least partly correlated with the features driving implicit visual attention in our group of human participants. Contrary to what was expected under a strict sensory bias account of preference formation, the attractiveness effect was not found for nonhuman primate faces. Human ratings of attractiveness predicted implicit preferences in humans only for own-species faces. This result is consistent with findings showing that some components of attractiveness such as symmetry [START_REF] Little | Domain specificity in human symmetry preferences: Symmetry is most pleasant when looking at human faces[END_REF] or prototypicality [START_REF] Halberstadt | The generality and ultimate origins of the attractiveness of prototypes[END_REF]) have a greater influence on attractiveness judgments applied to human faces compared with other-species faces. When human observers rate the attractiveness of monkey faces, they may rely more on features linked to general perceptual mechanisms rather than features linked to adaptation to mate choice, which are irrelevant in this instance. In contrast, when human observers rate the attractiveness of human faces, influences of both basic perceptual mechanisms and features reflecting sexual selection pressures might contribute to responding. Features linked to human mate choice are likely to be irrelevant for macaques and, consequently, did not drive their visual attention for attractive human faces as they did for human participants. Yet, human judgments of facial attractiveness of monkey faces predicted the visual preferences of macaques. This outcome suggests that some of the features used by humans to rate the faces overlap with those driving visual attention in macaques. Features linked to general perceptual mechanisms are plausible candidates, as they may be shared between human and nonhuman primates. Moreover, it has been shown that both humans and monkeys find symmetry attractive in faces [START_REF] Little | Symmetry is related to sexual dimorphism in faces: Data across culture and species[END_REF]Waitt & Little, 2006). Similarly, both human and macaque infants show visual preferences for face prototypicality (Damon, Méary, et al., 2017). Interestingly, the influence of symmetry or prototypicality on attractiveness preference appears to be stronger for frequently experienced faces (Damon, Méary, et al., 2017;[START_REF] Halberstadt | The generality and ultimate origins of the attractiveness of prototypes[END_REF][START_REF] Little | Domain specificity in human symmetry preferences: Symmetry is most pleasant when looking at human faces[END_REF], which This document is copyrighted by the American Psychological Association or one of its allied publishers.

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usually correspond to conspecific faces in ecological conditions. Along with the current findings, these results are consistent with a species-specific effect of face attractiveness. However, it can be argued that the interaction between species and attractiveness could be due to a rating bias rather than a sensory bias in the participants. We believe that far from being mutually exclusive, both phenomena are linked. It may be because different mechanisms were at work when rating conspecific and heterospecific faces that the ratings of macaque faces were able to predict looking time in macaque participants, while ratings of human faces did not. We argue that the ratings of human faces may be perturbed by mate-quality influence, whereas ratings of macaque faces were solely influenced by more general sensory processes. Therefore, in a way, the species and attractiveness interaction may have reflected a rating bias, but the bias in turn reflected the influence of different mechanisms, that is, mate choice adaptation mechanisms, general sensory bias, and categorization of a face as a conspecific.

Despite the correlation between human ratings of attractiveness and monkey looking times, we acknowledge that it is difficult to unequivocally establish that visual preferences truly reflect stimulus attractiveness. However, there is considerable evidence that this can be considered a reasonable conclusion based on the data and has been interpreted as such in previous studies with human adults and infants, and nonhuman primates [START_REF] Langlois | Infant preferences for attractive faces: Rudiments of a stereotype[END_REF][START_REF] Leder | When attractiveness demands longer looks: The effects of situation and gender[END_REF][START_REF] Quinn | Preference for attractive faces in human infants extends beyond conspecifics[END_REF][START_REF] Shimojo | Gaze bias both reflects and influences preference[END_REF]Waitt & Little, 2006). Visual preference paradigms typically bear such an uncertainty in interpretation because the preference is implicit and based on an inference. We do not suggest that there is a total overlap between the features that drive monkey looking times and those used by human raters. A more circumspect explanation would be to consider that there is a partial overlap of the features driving human ratings and gaze behavior in monkeys. [START_REF] Humphrey | Interest' and 'Pleasure': Two determinants of a monkey's visual preferences[END_REF] suggested that two independent factors influence visual preferences in human and nonhuman primates, interest (stemming from stimulus information properties), and pleasure (stemming from attractiveness of the stimulus which induces pleasurable feelings). Of the two, interest is proposed to supersede pleasure in driving gaze behavior, with monkeys attending preferentially to stimuli with high information content despite their unpleasant properties. It is worth noting, however, that interest and pleasure are not mutually exclusive, and a stimulus can be both informative and attractive. In the current design, the use of opposite-sex faces of conspecifics reduced the probability of monkey faces triggering a vigilance response [START_REF] Pfefferle | Monkeys spontaneously discriminate their unfamiliar paternal kin under natural conditions using facial cues[END_REF][START_REF] Schell | Adult but not juvenile Barbary macaques spontaneously recognize group members from pictures[END_REF] or aversion mechanisms [START_REF] Mendelson | Face scanning and responsiveness to social cues in infant rhesus monkeys[END_REF][START_REF] Taubert | Face pareidolia in the rhesus monkey[END_REF]. The downside of this methodological choice is that the monkeys were only tested with female monkey faces, and thus our conclusions about monkey performance only apply for opposite sex faces. Similarly, because our monkey sample was exclusively composed of male macaques, our results might not generalize to female monkeys. Sex differences in the influence of facial features on visual preferences for faces are not uncommon (e.g., skin color, [START_REF] Dubuc | Is male rhesus macaque red color ornamentation attractive to females?[END_REF][START_REF] Waitt | Selective attention toward female secondary sexual color in male rhesus macaques[END_REF], or symmetry, Waitt & Little, 2006). Hence, future studies could resolve this issue by examining attractiveness preferences in female macaque monkeys.

The findings also showed an unexpected dissociation between explicit judgments (i.e., attractiveness ratings by humans for humans and macaques) and attentional biases (i.e., preference by humans only for human faces and not for macaque faces). Although facial attractiveness ratings can be collected from adult human observers for almost any class of faces, not just for human faces, the implicit behavior that may be induced by a face rated as attractive (i.e., visual preference) could be tied to the evolutionary relevance of such a face, regardless of the origin of the preference (i.e., mate choice, sensory bias, or both mechanisms). The dissociation may indicate that implicit visual preferences are influenced by another cognitive process: categorization of a face as a conspecific. If so, triggering attractiveness-based visual preferences might necessitate prior categorization of a face as own-species. Human adults [START_REF] Méary | Seeing two faces together: Preference formation in humans and rhesus macaques[END_REF] and infants (Di Giorgio, [START_REF] Di Giorgio | The face perception system becomes species-specific at 3 months: An eyetracking study[END_REF][START_REF] Heron-Delaney | Infants' knowledge of their own species[END_REF] preferentially allocate visual attention toward own-species faces over other-species faces, and similar findings have been reported in nonhuman primates [START_REF] Fujita | Species recognition by five macaque monkeys[END_REF][START_REF] Sugita | Face perception in monkeys reared with no exposure to faces[END_REF], but see Méary et al., 2014). Moreover, other face processing tasks also reflect an attentional advantage for own-species faces, such as detection (e.g., in humans, [START_REF] Crouzet | Fast saccades toward faces: Face detection in just 100 ms[END_REF] and visual search (e.g., in humans, [START_REF] Simpson | Visual search efficiency is greater for human faces compared to animal faces[END_REF]in macaques, Simpson et al., 2017).

Furthermore, both human and nonhuman adults have a faceprocessing system that becomes species-specific during early development, leading to poorer discrimination and recognition abilities in human infants for other-species faces as measured in looking-time tasks relying on familiarity or novelty preference [START_REF] Pascalis | Face recognition in primates: A cross-species study[END_REF][START_REF] Pascalis | Is face processing species-specific during the first year of life?[END_REF]. Human and nonhuman face processing systems become attuned to frequently experienced categories (e.g., human faces for humans, monkey faces for macaques) in relation to their perceptual experience with faces [START_REF] Pascalis | Plasticity of face processing in infancy[END_REF][START_REF] Sugita | Face perception in monkeys reared with no exposure to faces[END_REF]. Of interest here is that this specialization in the recognition system might also alter the attractiveness system, weakening the effect of attractiveness for other-species faces. Thus, when human observers are asked to rate the attractiveness of monkey faces, they might not be able to recruit the "expert" face processing strategy that is used for human face processing (which may be human-specific) and hence rely more on general object processing strategies (which could be shared among primates). Note that such an interpretation leads to the prediction that infants tested before the perceptual narrowing window (i.e., 3-to 6-month-old infants, [START_REF] Maurer | Perceptual narrowing during infancy: A comparison of language and faces[END_REF] might show a preference for attractive other-species faces, whereas older infants (e.g., 9-to 12-month-old infants) should perform like the adult participants from the present study and display no such visual preference. Evidence consistent with this prediction includes the finding that 3-to 4-month-old human infants look longer at attractive over unattractive domestic and wild cat faces [START_REF] Quinn | Preference for attractive faces in human infants extends beyond conspecifics[END_REF]; however, older infants have thus far not been tested for their preference for attractive versus unattractive other-species faces.

In conclusion, we have reported behavioral evidence of a species-specific effect of facial attractiveness in adult humans and macaques. For both species, attractive own-species faces (as rated by human observers), but not attractive other-species faces, were preferred. These findings suggest that (a) human ratings of attractiveness correlate with features driving visual attention in mon-This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

keys, and (b) that implicit preferences for faces, even rated as attractive, are tied to their evolutionary relevance. To further evaluate the influence of face-processing specialization on face preferences, future investigations should examine the developmental trajectory of attractiveness preferences for own-or other-species faces, before and after the perceptual narrowing window.

Figure 1 .

 1 Figure 1. Mean looking time to faces with different attractiveness levels for the human (top) and rhesus macaque (bottom) groups. The effect of attractiveness is found only for own-species faces. The bottom plot also shows the photographs of the three rhesus macaque faces that were the least and most looked at by their conspecifics. See the online article for the color version of this figure.

Table 1

 1 Coefficients From the Linear Model and Corresponding p Values (Coefficients are Time Values in Seconds)

	Parameter Estimate SE t value p value p 2	95% confidence interval
			Human group
		1.959 .037 52.87 <.001	.990	[1.88, 2.03]
	␤	0.030 .038	0.77	.446	.021	[Ϫ0.05, 0.11]
	␣	Ϫ 0.025 .052 Ϫ0.48	.638	.008	[Ϫ0.13, 0.08]
	␥	0.165 .054	3.04 < .01	.249	[0.05, 0.28]
	Residual standard error: .148 on 28 degrees of freedom
		Rhesus macaque group
		1.043 .063 16.51 <.001	.907	[0.91, 1.17]
	␤	0.013 .065	0.194 .847	.001	[Ϫ0.12, 0.15]
	␣	0.139 .089	1.553 .132	.079	[Ϫ0.04, 0.32]
	␥	0.199 .092	2.162 .039	.143	[0.01, 0.39]

Table 2

 2 Mean Differences in the Number of Fixations (N Fix) and Looking Time (in Milliseconds) Between Faces of High and Low Attractiveness for Each Rhesus Macaque Participant and Stimulus Type (Human vs. Rhesus Macaque Faces)

			Mean differences
		N valid	in number of				Mean differences
	Monkey participant	trials	fixations	t	p	[95% CI]	in LT	t	p	[95% CI]
					Human faces
	D	42	0	0	.50	[Ϫ1.26, 1.26]	Ϫ34	Ϫ.21	.58	[Ϫ370, 302]
	C	3 9	Ϫ1.23	Ϫ1.22	.89	[Ϫ3.26, 0.80]	Ϫ298	Ϫ1.22	.88	[Ϫ794, 198]
	G	4 0	Ϫ.55	Ϫ1.69	.95	[Ϫ1.21, 0.11]	Ϫ133	Ϫ1.53	.93	[Ϫ309, 43]
	I	10	.7	.94	.18	[Ϫ.98, 2.38]	291	.84	.21	[Ϫ489, 1071]
	J	47	1	1.15	.13	[Ϫ.76, 2.76]	344	1.06	.15	[Ϫ311, 999]
					Rhesus macaque faces
	D	46	.68	1.46	.07	[Ϫ.24, 1.60]	149	1.06	.14	[Ϫ133, 431]
	C	44	1.41	2.21	.02	[0.13, 2.69]	435	2.51	<.01	[86, 784]
	G	43	1.56	2.75	<.01	[0.42, 2.70]	361	2.63	<.01	[85, 637]
	I	1 2	Ϫ.67	Ϫ1.17	.86	[Ϫ1.92, 0.58]	Ϫ296	Ϫ1.31	.89	[Ϫ790, 198]
	J	45	3.91	3.90	<.01	[1.89, 5.93]	1374	4.75	<.01

We thank Annika Paukner for sharing pictures of rhesus macaque faces, and Mike Burt for sharing pictures of human faces. This research was supported by the Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning, and the National Natural Science Foundation of China (Grant 91432102).

R code and raw data are available at: https://mfr.osf.io/render?urlϭ https%3A%2F%2Fosf.io%2Ftq8bg%2Fdownload.