Jacopo Tessarolo

Elie Benchimol

Abdelaziz Jouaiti

Wais Mir

Guido Hosseini

Clever

Modular enhancement of circularly polarized luminescence in Pd 2 A 2 B 2 heteroleptic cages

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Modular Enhancement of Circularly Polarized Luminescence in Pd2A2B2 heteroleptic cages

Jacopo Tessarolo, †* a Elie Benchimol, † a Abdelaziz Jouaiti, b Mir Wais Hosseini, b and Guido H. Clever* a Abstract: Metal-mediated assembly allows to combine an achiral emissive ligand A with different chiral ligands (such as B) in a non-statistical fashion, obtaining Pd2A2B2 heteroleptic cages showing circularly polarized luminescence (CPL). By using the 'shape complementary assembly' (SCA) strategy, the cages are exclusively obtained as cis-Pd2A2B2 stereoisomers, as confirmed by NMR, MS and DFT analysis. Their unique chiroptical properties derive from the synergy of all the building blocks. Ligand B imparts the chiral information of its aliphatic backbone, comprising two stereogenic sp [START_REF] Scherer | [END_REF] carbon centers, to the overall structure, causing CD and CPL signal induction for the chromophore on ligand A. The heteroleptic cage shows CPL with a glum value of 2.5x10 -3 , which is 3-times higher than for a progenitor based on aromatic helical building block H, thus opening a rational route towards optimizing the CPL properties of selfassembled nanostructures in a modular way.

Coordination cages have seen a considerable development since the seminal works of Saalfrank, 1 Stang, 2 Raymond 3 and Fujita, 4 and others. [5][6][7][8][9] Taking advantage of their nanoscale cavity and inherent plasticity, they are employed in a broad range of applications such as guest sensing, 7,10,11 chemical separation, 12 catalysis, 13,14 and the development of transformation networks. 15 Further, the implementation functional building blocks, paired with a careful structural design, allows to widen and tailor the capabilities of such nanoscopic assemblies. Recently, the introduction of multiple functionalities within a single architecture has moved into focus. However, the combination of different building blocks (i.e., ligands) within the same structure bears the risk of creating statistical distributions of multi-component assemblies (different stoichiometries, diastereomers) without proper morphological control, thus complicating the establishment of clear structure-function relationships. To overcome this problem, several rational strategies to restrict multi-component self-sorting, resulting in the exclusive formation of a single heteroleptic structure, have been developed. 16 Suitable approaches involve, but are not limited to, shape-complementary assembly (SCA), [17][18][19][20] coordination sphere engineering (CSE), [21][22][23] control via steric bulk in the ligand backbone, 24 guest templation, 25,26 selective ligand to ligand interactions, 27 or the use of ligands with reduced symmetry. [28][29][30][31] The number of examples in which different functions (and not just building blocks) have been incorporated into heteroleptic cages is still very small. Also, the systematic analysis of functional unit interplay and realization of emergent properties is still in its infancy.

Among a vast choice of desirable functionalities, the combination of chiral building blocks with chromophores, such as photoswitches, dyes or luminophores, within distinct cage assemblies is of interest for applications in supramolecular recognition and catalysis or, in the latter case, for achieving nanostructures with tuneable chiroptical properties. Here, a particular focus is set on circularly polarized luminescence (CPL). 32 The use of metal-mediated self-assembly comes in handy here, as it allows to avoid tedious synthetic procedures otherwise necessary to covalently couple chiral groups and chromophores. Previous examples in the area of cage chemistry have shown that chirality can be transferred from guest-to-host, [33][34][35] host-to-guest, 36 or from ligand-to-ligand, 37 with emergence of chiroptical properties such as circular dichroism (CD) and CPL, from initially achiral building blocks. In our previous work, 37 we exploited the SCA strategy to combine Pd II cations, enantiopure helicene ligands (H) and fluorenone-based emissive ligands (A), successfully achieving the first multifunctional cis-Pd2H2A2 heteroleptic cages showing CPL from the formerly achiral ligand component, with glum values up to |9.0x10 -4 | (Scheme 1a). The cages with their chiroptical response were used to probe the encapsulation of a small guest molecule, resulting in a 4-fold boost of CPL intensity as well as a pronounced shift of the emission maximum. However, our previous system left a number of open questions and room for Making of the helicene-based ligand requires several synthetic steps. Furthermore, it already shows CPL on its own (glum = |2.8x10 -2 |), 38 that -alongside its emission -is lost upon coordination to Pd II cations in order to create a 3-dimensional confined space. Also, the absorption bands of ligands H and A overlap, thus making it impossible to selectively excite the fluorenone chromophore alone, hence raising questions concerning the CPL mechanism. In this case, it was not readily conceivable whether CPL arises from homo/hetero-exciton coupling, 39 chiral energy transfer, 40,41 or simply derives from an asymmetric distortion of the emissive ligand itself or its immediate environment. To gain more insight, we herein report the modular synthesis and analysis of second example of a CPL-emitting Pd-based heteroleptic cage. Therefore, we used the same emissive achiral ligand (A) as in our previous system, while changing the chiral component from an aromatic to an aliphatic cyclohexane backbone, functionalized with amide linkers and parapyridine donor groups (B). Ligand B is inspired by chiral cyclohexyl based tectons 42 that have been used for the generation of chiral coordination networks in the crystalline phase. [43][44][45] Fig. 1 Both, ligands A and enantiomerically pure R,R-B (from now on just B) are obtained in a one-step reaction from commercially available reagents, following literature-reported procedures. [46][47][48][49] These simple building blocks are then combined with [Pd(MeCN)4](BF4)2 in acetonitrile in a 1:1:1 ratio, yielding a rather structurally complex heteroleptic cage [Pd2A2B2](BF4) 4 (namely Pd2A2B2; Scheme 1b). The assembly forms virtually quantitatively, requires no purification and its structure was confirmed by a number of analytical results, including 1 H-NMR, where we observe a typical downfield shift of protons H a H 1 of the pyridine donors of A and B, respectively (Fig. 1a). Upon assembly, each 1 H-NMR signal splits into two sets, with the enantiomerically pure B breaking the symmetry of the cage, as the oppositely arranged upper and lower halves of each ligand become non-equivalent. The cage forms as a cis-isomer with respect to the ligand arrangement around the square-planar Pd II centres, as evidenced by ROESY cross peaks between protons Hb -Hb' , Ha -H1' , Ha' -H1 and Ha -Ha' (Fig. S5). The formation of a single species was further confirmed by DOSY-NMR, with all the signals belonging to the same diffusion coefficient (D= 6.35 x 10 -10 m 2 s -1 ), corresponding to a hydrodynamic radius rH= 8.81 Å, in accordance with the formation of a Pd2L2L'2 assembly and a geometry-optimized DFT model (vide infra). The assumed stoichiometry was further supported by ESI-MS analysis, showing prominent peaks for the [Pd2A2B2] 4+ species as well as the analogue 3+ and 2+ charged assemblies with one and two associated BF4 -counter anions, respectively (Fig. 1b).

Despite several attempts, we were unsuccessful to obtain suitable crystals for X-ray diffraction analysis. To gain further structural insight we prepared a DFT-optimized model (ωb97xd/def2-SVP) of the cis-Pd2A2B2 cage (Fig. 2). The model supports the geometric complementarity of the two ligands, connected via the square-planar Pd II centers. The Pd-pyridine plane is tilted by ≈60° relatively to the Pd⋯Pd axis. The short distance between the two pyridine N atoms of B results in a distortion of oppositely arranged ligand A and a rather short Pd⋯Pd distance of 9.8Å. Interestingly, from a comparison with the previously reported cages, 37 there appears to be a correlation between the increase of the CPL intensity (as expressed in the glum value) and the observed cage compression (as read from Pd⋯Pd and pyridine N⋯N distances; see ESI). After having confirmed the assembly of the heteroleptic cage, we went on investigating the (chir)optical properties of the system. Chiral ligand B only shows rather weak absorbance below 300nm, with a broad band centred at 250nm (Fig. 3). Upon interaction with Pd II, the species forms an undefined mixture of compounds (namely PdnB2n), with an absorption spectrum resembling the one of B but decreased optical density, probably due to the formation of larger colloidal aggregates (Fig S11). On the other hand, ligand A, as well as the homoleptic cage Pd2A4, 37 shows two absorption maxima at 280 and 300 nm, a series of shoulders between 320 and 360 nm, and a broad band centred at 400 nm. These features are maintained in the absorption spectrum of Pd2A2B2, which therefore resembles the superposition of the absorption spectra of both A and B, with a predominant contribution at λ ≥ 275 nm, deriving from the fluorenone moiety. The first indication of ligand-toligand chirality transfer was obtained by CD spectroscopy, showing a strong band at 300 nm, two weaker bands at 340 and 355 nm, and a broader band in the visible range, centred around 400 nm (Fig. 3). In this spectral region, the absorption contribution derives exclusively from the formerly achiral fluorenone chromophore, thus the presence of a CD signal unambiguously confirms the chirality transfer imparted by B onto the overall assembly and thus the ground state of A (while, by definition, the entire architecture is chiral once a chiral component, here B, is included, the assembly's large size and dynamic nature does not necessarily guarantee locations remote from the stereocenters to be locked in a chiral conformation or experience an immediate chiral environment). This was further supported by studying the emission properties of the system, in particular its circularly polarized luminescence (CPL). Differently from our previously reported systems, 37 we here now have the possibility to selectively excite only the emissive ligand A, excluding any concomitant absorption of the chiral ligand. Upon excitation at λex = 335nm, the heteroleptic cage was found to clearly exhibit a broad emission centred at 490nm, ascribed to a π*-π transition localized on the fluorenone backbone, as expected for an aromatic ketone and in accordance with what we previously observed (Fig. 4). 37 Pleasingly, the heteroleptic cage Pd2A2B2 exhibits CPL in accordance with its fluorescence spectrum (Fig. 4), deriving exclusively from the formerly achiral ligand A and thus further demonstrating a ligand-to-ligand chiral induction. Interestingly, the CPL intensity is almost three times higher compared to our previously reported heteroleptic cage, with the glum value raising from |9.0x10 -4 | for Pd2A2H2 to -2.5x10 -3 for Pd2A2B2. To conclude, we herein report the second example of a Pd II -based heteroleptic cage, self-assembled from a chiral and a chromophore-base ligand, showing induced CD and CPL signals deriving exclusively from the electronic transitions of chromophore A that is achiral in its unbound form. These chiroptical properties arise from the synergistic effect of the building blocks by ligand-to-ligand chirality transfer via their coordination to the Pd II nodes. The use of the SCA strategy allows to achieve a high degree of structural and functional complexity, notably with a strongly reduced synthetic effort, compared to the previous examples. The modular character of the heteroleptic cages allowed us to replace helicene-based ligand H with cyclohexane-based ligand B. Furthermore, the absence of overlap between the absorption bands of ligands A and B allows to clearly connect the ligand-to-ligand chirality transfer to both ground (via CD) and excited (via CPL) states of the fluorenone-based ligand. Structural distortion of the chromophore by the chiral ligand may be the reason for the observed chiroptical phenomenon. Alternatively, CPL may result from a chiral co-conformation/arrangement of the close pair of luminescent backbones via an exciton coupling mechanism. While further studies are required to unravel the mechanistic details, we herein show how a modular approach can be used to improve the overall chiroptical properties of a self-assembled compound, in this case achieving a 3-fold higher CPL intensity than a preceding derivative.

Scheme 1

 1 Scheme 1 Self-assembly of Pd II -based heteroleptic cages displaying CPL via ligand-to-ligand chirality transfer. The emissive ligand A is based on a fluorenone moiety, the chiral ligands are based on a) a helicene backbone (H) or b) a cyclohexane backbone (B)

  Fig. 1 a) From top to bottom, 1 H NMR spectra (500 MHz, 298 K, CD3CN) of ligand A, ligand B, heterolytic age Pd2A2B2 and DOSY spectrum of Pd2A2B2; b) ESI-MS spectrum of Pd2A2B2 with isotopic pattern for [Pd2A2B2 +BF4] 3+ shown in the inset.

Fig. 2

 2 Fig. 2 DFT model, side view, of the heteroleptic cage Pd2A2B2. Color code: Pd grey, C beige for A light blue for B, N blue, O red, H white (when not omitted for clarity).

Fig. 3

 3 Fig.3UV-Vis absorption (top) and CD (bottom) spectra of homoleptic species Pd2A4 (dashed), PdnB2n (purple), and heteroleptic cage Pd2A2B2 (red; all in CD3CN, 0.35mM with respect to ligand concentration, 298 K).

Fig. 4

 4 Fig. 4 CPL (top) and emission (bottom) spectra of heteroleptic cage Pd2A2B2 (λex = 335 nm, CD 3 CN, 0.35 mM with respect to ligand concentration, 298 K).

Acknowledgements

This work was supported by the European Research Council (ERC Consolidator grant 683083, RAMSES) and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy EXC2033, project number 390677874 ("RESOLV") and GRK2376 ("Confinement Controlled Chemistry"), project number 331085229. The authors thank Dr. Kai Wu and Kristina Ebbert for providing ligands and Dr. Ananya Baksi for measuring ESI mass spectrometry data.

Conflicts of interest

There are no conflicts to declare.


Aurélie Lagarde

Lengo Mambu
email: lengo.mambu@unilim.fr

Phuong-Y Mai

Yves Champavier
email: yves.champavier@unilim.fr

Jean-Luc Stigliani
email: jean-luc.stigliani@lcc-toulouse.fr

Dr Mehdi A Beniddir
email: mehdi.beniddir@universite-paris-saclay.fr

Marion Millot
email: marion.millot@unilim.fr

Jean-Luc Stigliani

Dr J-L Stigliani

Chlorinated bianthrones from the cyanolichen Nephroma laevigatum

Keywords: bianthrones, dereplication, NMR calculations, lichens, Nephroma

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Introduction

Nephroma laevigatum Ach. is a lichenized Ascomycota belonging to the Nephromataceae family (Peltigerales order). It is a foliose lichen with a cyanobiont (Nostoc) as photosynthesizing partner [START_REF] Smith | The lichens of Great Britain and Ireland[END_REF]. The first phytochemical investigation of this lichen was conducted by Bentz et al., who isolated five anthraquinones (emodin (1) and chlorinated derivatives) from a Swedish specimen [START_REF] Bendz | Chlorinated Anthraquinones from Nephroma laevigatum[END_REF]. A few years later, a North American specimen was studied by Cohen et al. They described the presence of chlorinated anthraquinones [START_REF] Cohen | Anthraquinones and phenanthroperylenequinones from Nephroma laevigatum[END_REF].

Beside these hydroxyanthraquinone pigments, N. laevigatum is known for its hopane triterpenoids. Nephrin is the only triterpenoid reported and isolated from this species [START_REF] Wilkins | Nephrin: structure and occurence in Nephroma species[END_REF]. A more recent study revealed the presence of mycosporine hydroxyglutamicol from an aqueous-methanolic extract [START_REF] Roullier | Characterization and identification of mycosporines-like compounds in cyanolichens. Isolation of mycosporine hydroxyglutamicol from Nephroma laevigatum Ach[END_REF]. Mycosporine-like amino-acids were commonly associated with cyanolichen metabolism and are involved in photoprotection of the photobiont. A recent study on Nephroma laevigatum reports the endolichenic fungi growing inside this lichen thallus [START_REF] Lagarde | Antiproliferative and antibiofilm potentials of endolichenic fungi associated with the lichen Nephroma laevigatum[END_REF]. This lichen shows a rather low diversity of endolichenic fungi in comparison to other genera with a predominance of Nemania species. In an extensive research conduct on the Genus Nephroma, a French specimen was collected in a humid forest to deeply explore the anthraquinone content. Thus dichloromethane extract, particularly rich in quinoid pigments was profiled by LC-MS/MS and then purified in order to isolate anthraquinones and bianthrones. This phytochemical investigation allowed the identification of two new diastereoisomeric pairs of chlorinated bianthrones [START_REF] Roullier | Characterization and identification of mycosporines-like compounds in cyanolichens. Isolation of mycosporine hydroxyglutamicol from Nephroma laevigatum Ach[END_REF][START_REF] Lagarde | Antiproliferative and antibiofilm potentials of endolichenic fungi associated with the lichen Nephroma laevigatum[END_REF]. Due do their chemical instability, few bianthrones with a C10-C10' linkage, have been tested for their biological activity.

Chrysophanol bianthrones and emodin-physcion bianthrone have shown significant cytotoxicity activity against KB, HL-60 and A-459 cell lines [START_REF] Mai | Cytotoxicity of Rhamnosylanthraquinones and Rhamnosylanthrones from Rhamnus nepalensis[END_REF] [START_REF] Du | Cytotoxic Polyketides from a Marinederived Fungus Aspergillus glaucus[END_REF]. Anti-plasmodial activities have been described for some prenylated bianthrones [START_REF] Lenta | Anti-plasmodial and cholinesterase inhibiting activities of some constituents of Psorospermum glaberrimum[END_REF]. Finally, the ability of such compound to generate singlet oxygen upon exposure to light contributes to a photodynamic potential toward bacteria and cancer cells [START_REF] Zheng | Hypericin-based Photodynamic Therapy Induces a Tumor-Specific Immune Response and an Effective DC-based cancer Immunotherapy[END_REF].

Results and Discussion

UV-and MS-based dereplication and isolation

Extraction of the dried lichen thallus with dichloromethane by maceration at room temperature gave a brown extract enriched in quinoid pigments easily visualized on TLC.

Fractionation of the extract by silica gel chromatography yielded several fractions. These fractions were analyzed by HPLC-DAD and showed two main groups of compounds with distinct UV absorptions. The first group displays a UV spectrum with four main bands at 210-232; 271-280; 308-310 and 420-490 nm characteristic of anthraquinones [START_REF] Machatová | Study of natural anthraquinone colorants by EPR and UV/vis spectroscopy[END_REF]. The second group displays a different UV spectrum with two main bands at 278-280 and 358-360 nm strongly suggesting the presence of bianthronic compounds [START_REF] Lemli | The palmidins, a new group of dianhrones from the fresh roots of Rheum palmatum[END_REF].

In an attempt to map the chemical diversity of the dichloromethane extract, the LC-MS/MS data were processed using the feature-based molecular networking workflow [START_REF] Nothias | Feature-based molecular networking in the GNPS analysis environment[END_REF] and subsequently dereplicated against the Lichen Database (LDB) [START_REF] Olivier-Jimenez | A database of high-resolution MS/MS spectra for lichen metabolites[END_REF], hosted by GNPS [15].

The molecular networking-based dereplication process afforded only two hits (emodine and 7-O-methylgalangin). These results reveal the lack of lichen compounds references in MS/MS databases and the high potential for new compounds discovery in N. laevigatum.

The quest for tackling the issue of molecular networking annotation has fueled a number of creative and successful endeavors from the community, including our group [START_REF] Fox Ramos | Natural products targeting strategies involving molecular networking: different manners, one goal[END_REF][START_REF] Fox Ramos | CANPA: Computer-Assisted Natural Products Anticipation[END_REF][START_REF] Duperron | New Benthic Cyanobacteria from Guadeloupe Mangroves as Producers of Antimicrobials[END_REF][START_REF] Cauchie | Phenylpropane as an Alternative Dearomatizing Unit of Indoles: Discovery of Inaequalisines A and B Using Substructure-Informed Molecular Networking[END_REF]. Hence, as part of our continuous interest in the discovery of new chlorinated quinoids pigments, the molecular network was color-coded (Fig. 1 and S1 in supporting information for the whole molecular network) based on the halogenation pattern (1 x Cl, 2 x Cl) of the fragmented parent masses. This annotation revealed that there were over 50 metabolites possessing at least a single chlorine in their chemical structure. Consequently, we focused isolation efforts on molecules that exhibited the aforementioned UV absorptions in addition to their chlorination pattern. Using these UV-and MS-guided isolation approaches, we were able to isolate and characterize eight compounds: four anthraquinones (emodin, 7-chloro-emodin, 7chloro-1-O-methylemodin and 1-O-methylfragilin (1-4)) [START_REF] Bendz | Chlorinated Anthraquinones from Nephroma laevigatum[END_REF][START_REF] Cohen | Anthraquinones and phenanthroperylenequinones from Nephroma laevigatum[END_REF], two new homobianthrones (diasteroisomers 5a and 5b) and two new heterobianthrones (diasteroisomers 6a and 6b). OH OH The presence of two asymmetric carbons at C-10 and C-10ʹ easily explains the coexistence of two diastereoisomers. It is noteworthy that among the aromatic protons, the signal at δH 6.73 ppm is well defined while the other two signals at δH 6.27 and 6.23 ppm are broad singlets. This could be explained by the chemical environment of these protons. The aromatic proton at δH 6.73 ppm attached to the C-2 carbon is stabilized by the involvement of the hydroxyl group at C-1 in a hydrogen bond with the carbonyl and by the presence of the methyl group (C-3). Conversely, the protons H-4 and H-5 were influenced by the relatively unstable methine proton (C-10) and the steric hindrance and appeared as broad singlets.

CH 3 CH 3 O HO HO O R 2 R 1 OH OH 5 R 1 = R 2 = Cl 6 R 1 = H, R 2 = Cl OH OR 1 CH 3 O R 2 R 3 1 R 1 = R 2 = R 3 = H 2 R 1 = R 2 = H, R 3 = Cl 3 R 1 = CH 3 , R 2 = H, R 3 = Cl 4 R 1 = R 2 = CH 3 , R 3 =
For the stereoisomer 5b, the 1 H NMR spectrum showed slightly different chemical shifts.

Protons H-2, H-4, OH-6 and CH3-3 were shielded while protons H-5, OH-6 and OH-8 were deshielded. Due to the degradation of compound in solution during NMR acquisition, 13 C NMR data could not be acquired.

With a molecular formula of C30H21O8Cl deduced from its HR-ESI-MS at m/z 543.0867 [M-H] -, and non-overlapped 13 C NMR signals (Table 1), compounds 6a and 6b are supposed to be heterobianthrones. Considering the loss of one chlorine replaced by an additional proton at δH 6.20 (d, 1.9 Hz, H-7ʹ), these asymmetric compounds were identified as diastereoisomeric pairs of 7-chloroemodin-emodin heterodimers. The 1 H NMR spectrum of compound 6a

showed six singlets between 10.80 and 12.53 ppm, seven aromatic protons, two methine protons and two methyl groups. Among the aromatic protons, as observed for homobianthrones, three protons are well defined (H-7ʹ, H-2 and H-2ʹ) while four are broad For compound 6b, the main difference is observed in the 1 H NMR spectrum compared to 6a

with the deshielding of the aromatic protons H-4ʹ. This difference is supposed to be the consequence of a modification of the spatial configuration.

Similar chlorinated bianthrones have already been isolated from the lichens Heterodermia obscurata and Anaptychia obscurata and are called flavoobscurin A and B [START_REF] Yosioka | Three new chlorine containing bisanthronyls from a lichen, Anaptychia obscurata Vain[END_REF][START_REF] Cohen | The anthraquinones of Heterodermia obscurata[END_REF]. These new compounds, identified for the first time in the lichen N. laevigatum were named nephrolaevigatin A and nephrolaevigatin B (5a and 5b) for the homobianthrones and nephrolaevigatin C and nephrolaevigatin D (6a and 6b) for the heterobianthrones.

Relative configuration assignment

Stereochemistry of bianthrones remains difficult to establish due to the meso, racemic and axis rotation phenomena. 1 H-1 H J coupling constant magnitudes of H10-H10ʹ as well as NOESY correlations spectra are often cited in literature but are not sufficient to establish properly the relative configurations of these compounds. Even the specific optical rotation is uncertain, due to the possible impurity of meso compounds or 1:1 ratio for enantiomers (scalemic mixture). Consequently, NMR chemical shifts analysis and computational approaches are emerging as alternatives strategies to tackle this issue [START_REF] Form | Xanthone, benzophenone and bianthrone derivatives from the hypersaline lake-derived fungus Aspergillus wentii[END_REF]. In the 1 H NMR spectrum of homobianthrones nephrolaevigatin A and nephrolaevigatin B (5a and 5b), H-10 and H-10ʹ protons appear as a singlet without coupling constant due to the symmetry of the molecule. Thus, chemical shifts are the only informative data. Based on computational and experimental results obtained by Ji et al. [START_REF] Ji | A rule to distinguish diastereomeric bianthrones by 1H NMR[END_REF], the NMR data of compounds 5 and 6 provided interesting information. Comparison of 1 H NMR data of homobianthrones 5a and 5b with cis and trans emodin bianthrones, suggests that 5a is a trans isomer and 5b is a cis isomer.

Indeed, the isomer 5b possesses higher frequency 1 H NMR signals for rings A and Aʹ (H-2, CH3-3 and H-4) and lower-frequencies for rings B and Bʹ (H-5) (Fig. S2). Thus, according to optical rotation values, we concluded that 5a is a racemate and 5b is a meso form.

An inspection of 1 H NMR data of the heterobianthrones 6a and 6b, revealed slight differences in 1 H-1 H J coupling constant magnitudes of H-10 and H-10ʹ. According to Aly et al., a coupling constant of 2.0 Hz between H-10 and H-10ʹ required that these protons have a cis relationship [START_REF] Aly | NF kappa B inhibitors and antitrypanosomal metabolites from endophytic fungus Penicillium sp. isolated from Limonium tubiflorum[END_REF]. A coupling constant of 4.7 Hz is observed for compound 6a (Table 1), suggesting that 6a possesses a C-10 -C10ʹ junction in a trans configuration. In compound 6b, a coupling constant of 3.0 Hz is in favor of a cis isomer.

In order to confirm the aforementioned assignments, Gauge-Independent Atomic Orbital (GIAO) NMR 1 H and 13 C chemical shifts calculations were performed on diastereoisomers 5 and 6. The sigma C-10 -C10ʹ bond enables the two anthraquinone rings to rotate to each other; hence, heterobianthrones may take different conformations. A Conformational analysis performed around this bond showed that each structure can exhibit, by regard to the bond, two face to face stacked forms (gauche conformations) and an anti-one where ring systems are not stacked (Fig. 2 andS3). Quantum chemical geometry optimizations and vibrational frequency calculations indicated that the gauche forms are clearly more stables than the antiones. This observation has already been reported by Ji et al [START_REF] Ji | A rule to distinguish diastereomeric bianthrones by 1H NMR[END_REF].

Fig. 2. Lowest-energy gauche and anti conformers of (10R-10ʹR) heterobianthrones 6. For clarity, apolar hydrogens were omitted.

The evaluation of the Boltzmann populations of each conformer of 5 and 6 showed that the anti conformer is negligible comparing to two gauche ones (Table 2). In addition, one can notice that for the (10R, 10ʹR)-5 and 6 enantiomers, one of the two gauche conformers is more stable about 2.5 kJ.mol -1 , than the second one: the difference is due to the steric hindrance induced by the proximity of the 3ʹ-CH3 and the 7-Cl found in the stacked gauche-1 conformers (Fig. 2).

In the CP3 approach, the difference between the experimental and the ab initio calculated 13 C and 1 H NMR scaled chemical shifts is computed. The probability that experimental and theoretical data match is then calculated [START_REF] Smith | Assigning the Stereochemistry of Pairs of Diastereoisomers Using GIAO NMR Shift Calculation[END_REF].

For compounds 5 and 6, two sets of resonance signals were obtained, to which two diastereoisomers must be assigned. CP3 parameters were then determined for all possible pairs of diastereoisomers of the gauche conformers of 5 and 6. Unfortunately, we were unable to exploit the 1 H NMR chemical shifts, because they were too close for both compounds 5a and 5b. Furthermore, 13 C NMR data were not available for compound 5b.

Therefore, we give only results for the isomers of compounds 6a and 6b.

The CP3 results allowed to attribute the (10R*, 10ʹS*) relative configuration isomer for compound 6a and the (10R*, 10ʹR*) one for compound 6b (Table 3). In addition, the results are in favor of the gauche-2 conformation for 6b which is indeed the most stable conformer (Table 2). In the case of 6a, CP3 values (Table 3) are very close for the (10R, 10ʹS) gauche-1 and (10R, 10ʹS) gauche-2 conformers: 0.81 and 0.73 respectively. In fact, these two conformers exhibit a similar energy and each contributes to the Boltzmann population for about 50% (Table 2). At last, according to optical rotation value we concluded that 6b occurs as a racemate. It is important to note that the instability of bianthrones in solution have been observed during the purification process, which greatly hampered identification. Notable changes were observed i) in the physical state with color changes from pale-yellow to red-dark or greendark ii) by HPLC-DAD with the apparition of additional peaks iii) during the NMR acquisition time in solvents such as acetone or dimethylsulfoxide with a decrease in the intensity of the main compound in favor of the formation of secondary products corresponding to anthraquinone monomers (Supporting informations). Indeed, bianthrones are known to reversibly change color in solution from bright yellow to dark green when subjected to heat (thermochromism) or light (photochromism) [START_REF] Meyer | Über neue Reduktionsprodukte des Anthrachinons[END_REF][START_REF] El'tsov | Organic Photochromes[END_REF]. Similar changes were also observed when crystals of bianthrones were submitted to pressure [START_REF] Johnstone | The effect of pressure on the crystal structure of bianthrone[END_REF]. Johnstones et al., assume that the color change observed here, from yellow to red or green, results from the coexistence of two forms (folded and twisted) [START_REF] Johnstone | The effect of pressure on the crystal structure of bianthrone[END_REF]. The folded form is the more stable, but transition to the twisted form can be promoted either thermochemically or photochemically in solution. It has also been shown that the ability of the hydroxide ion to act as a one-electron reducing agent is low in aqueous media, but enhanced in aprotic solvents such as acetonitrile and dimethylsulfoxide (solvent used for the isolation and NMR analysis respectively) [START_REF] Mattar | Oxidation-reduction behavior of bianthrone and bianthronyl in basic dimethylsulfoxide solutions[END_REF]. The first step in the reduction process is a fast and reversible polar-clustering reaction. This nucleophilic addition step results in a quinone-hydroxy complex followed by a slower electron-transfer step that produces the semi-quinone form [START_REF] Mattar | Oxidation-reduction behavior of bianthrone and bianthronyl in basic dimethylsulfoxide solutions[END_REF][START_REF] Cameron | Oxidation of emodin anthrone and stereochemistry of emodin bianthrone[END_REF]. LC-MS/MS analysis of the compound after degradation (color change from pale-yellow to red dark) showed the apparition of monomer ions as well as the formation of hypericine-like compounds (reduction of the C10-C10ʹ linkage) [START_REF] Cameron | Oxidation of emodin anthrone and stereochemistry of emodin bianthrone[END_REF] (Fig. 3). Surprisingly, no degradation processes were reported in literature for flavoobscurin A and B or other related bianthrones after purification using a mixture of CH2Cl2 and MeOH or involving acetone. Anthraquinones are widely biosynthesized in nature by higher plants (Liliaceae, Polygonaceae, Rhamnaceae and Cesalpinaceae), fungi or lichens [START_REF] Bruneton | Pharmacognosie, phytochimie, plantes médicinales[END_REF]. Their biosynthesis implies the polyketide pathway [START_REF] Cohen | Biosynthetic studies on chlorinated anthraquinones in the lichen Nephroma laevigatum[END_REF]. The metabolism of halogenated compounds is restricted to fungi or lichenized fungi. In lichens, parietin is the most frequent anthraquinone biosynthesized by Xanthoria or Caloplaca species, but anthraquinones pigments are particularly prominent in the families of Nephromataceae, Physciaceae and Telochistaceae [START_REF] Bendz | Chlorinated Anthraquinones from Nephroma laevigatum[END_REF][START_REF] Cohen | The anthraquinones of Heterodermia obscurata[END_REF][START_REF] Søchting | Chemosyndromes in the lichen genus Teloschistes (Teloschistaceae, Lecanorales)[END_REF][START_REF] Giralt | New data on Sculptolumina japonica (Physciaceae)[END_REF].

Bianthrones are more scarcely ever isolated. As demonstrated in this work, it could be explained by the difficulty to access to these compounds through purification process due to their instability and rapid degradation. Beside flavoobscurin isolated from the lichen H. obscurata, two chlorinated bianthrones, were isolated from the endophytic fungus Penicillium sp. (accession number HQ112180) [START_REF] Aly | NF kappa B inhibitors and antitrypanosomal metabolites from endophytic fungus Penicillium sp. isolated from Limonium tubiflorum[END_REF] and from Aspergillus alliaceus [START_REF] Mandelare | Coculture of Two Developmental Stages of a Marine-Derived Aspergillus alliaceus Results in the Production of the Cytotoxic Bianthrone Allianthrone A[END_REF]. Emodin bianthrones were isolated from Polygonum multiflorum. Prenylated dianthrones were isolated from higher plants, such as Vismia laurentii, Psorospermum glaberrrium [START_REF] Lenta | Anti-plasmodial and cholinesterase inhibiting activities of some constituents of Psorospermum glaberrimum[END_REF][START_REF] Kemegne | Antimicrobial structure activity relationship of five anthraquinones of emodine type isolated from Vismia laurentii[END_REF] or fungus Aspergillus wentii [START_REF] Form | Xanthone, benzophenone and bianthrone derivatives from the hypersaline lake-derived fungus Aspergillus wentii[END_REF].

Conclusion

These results highlight the chemical complexity of 10-10ʹ bianthrones. These biosynthetic intermediates between anthraquinones and naphtobianthrones can be abundant in lichens.

The flexible connection between the two anthraquinones moieties gives rise to the existence of different isomers or conformers. Despite the difficulty for the chemist to isolate and properly identify bianthrones, they constitute interesting agents endowed with biological activities close to those of anthraquinones and naphtobianthrones.

Experimental Section

4.1.

General experimental procedures 1 H NMR and 13 C NMR spectra were acquired with a Bruker Avance III HD spectrometer at 500 and 125 MHz, respectively (Platform BISCEm Limoges, France). CD spectra were measured at 25°C on a JASCO J-710 spectropolarimeter. High-resolution mass spectrometry (HRMS) measurements for exact mass determination were performed on a Micromass ZabspecTOF spectrometer for chemical ionization (Platform BISCEm, Limoges, France). Analytical HPLC was done on a Waters Alliance 2690 using a reversed-phase C18

Hibar® LiChrospher® 100 column (250 x 4 mm, 10 µm, Merck) and using a photodiode-array detector (Waters 996). Semi-preparative HPLC was performed using a HPLC Waters 600 Limoges, France (HL-L1014-01). The identification was checked by lichenologists from the AFL (French Association of Lichenology).

Extraction and Isolation

A sample of cleaned and dried lichen (50 g) was extracted by CH2Cl2 (5 L) at room temperature under agitation. After concentration, a red-brown extract (2.9 g) was obtained.

The extract was chromatographed on silica gel chromatography using a gradient of C6H12/EtOAc 95:5 to EtOAc followed by a mixture of MeOH/EtOAc 50:50. Fractions were collected and analyzed by TLC and grouped following their chemical composition. Thus, 15 fractions (F1 to F15) were obtained.

The fraction F7 (116.0 mg) was purified by a reversed phase chromatography to give fraction F7c (30.0 mg). This subfraction was submitted to a silica gel MPLC eluted with C6H12/EtOAc 80:20 to obtain 10 mg of compound 1.

The fraction F11 (0,830 g) was subjected to a second purification on 40 g of Sephadex ® LH-

Feature-Based Molecular Networking

The MS 2 data files, related to the dichloromethane extract of Nephroma laevigatum were converted from the .d (Agilent) standard data-format to .mzXML format using the MSConvert software, part of the ProteoWizard package [START_REF] Chambers | A cross-platform toolkit for mass spectrometry and proteomics[END_REF]. All .mzXML were then processed using MZmine 2 v52 [START_REF] Pluskal | MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data[END_REF]. The mass detection was realized keeping the noise level at 1.2E3 at

Molecular Networking Parameters.

A molecular network was created using the online FBMN workflow (version release_20) at GNPS (http://gnps.ucsd.edu) with a parent mass tolerance of 0.02 Da and an MS/MS fragment ion tolerance of 0.02 Da. A network was then created where edges were filtered to have a cosine score above 0.65 and more than 6 matched peaks. Further edges between two nodes were kept in the network if and only if each of the nodes appeared in each other's respective top 10 most similar nodes. The spectra in the network were then searched against

Fig. 1 .

 1 Fig. 1. Molecular family containing the new targeted chlorinated bianthrones (color-coding of the halogenation pattern is as follows: red = Cl, green = 2 x Cl).

  signals (H-4, H-4ʹ, H-5 and H-5ʹ). The13 C RMN spectrum of compound 6a showed similarities with that of compound 5a and 5b except for C-6ʹ, C-7ʹ and C-8ʹ carbons. C-7ʹ was shielded by +3.4 ppm while C-6ʹ and C-8ʹ were deshielded by +5.8 ppm and +5.7 ppm, respectively. These variations of chemical shifts reflect the loss of the chlorine atom on the C-7ʹ position. The correlations observed in the HMBC spectrum for the hydroxyl protons confirm the carbon assignments. The hydroxyl proton at δH 12.60 ppm attached to the C8 carbon has a well-defined signal due to its stabilization by the ketone group at C-9 and the chlorine at C-7. This hydroxyl proton showed correlations with C-7, C-8 and C-8a.In the other moiety, the hydroxyl proton at δH 11.92 attached to the C-8ʹ carbon is less shielded due to the absence of the chlorine atom and showed correlations with C-7ʹ, C-8ʹ and C-8aʹ. The HMBC correlations of the hydroxyl proton at δH 11.52 with C-1, C-9a and C-2 justify its position on carbon C-1. The hydroxyl group at δH 10.75 ppm showed correlations with C-5ʹ, C-6ʹ and C-7ʹ whereas the hydroxyl group at δH 11.50 (OH-6) next to the chlorine is shielded and without any correlation. As in the homobianthrones (5a and 5b), the hydroxyl group at C-6 displayed a broad signal without clear correlations. Nevertheless, a small correlation is observed with C-5. The correlation of the methine proton at δH 4.50 ppm with C-4a, C-8a and C-10a allowed to confirm the chemical shift of the central quaternary carbons.

Fig. 3 .

 3 Fig. 3. Degradation products of bianthrones in presence of light and oxygen.

  MS1 and at 2E1 at MS2. The ADAP chromatogram builder was used using a minimum group size of scans of 2, a group intensity threshold of 2E3, a minimum highest intensity of 2E3 and m/z tolerance of 10 ppm[START_REF] Myers | One Step Forward for Reducing False Positive and False Negative Compound Identifications from Mass Spectrometry Metabolomics Data: New Algorithms for Constructing Extracted Ion Chromatograms and Detecting Chromatographic Peaks[END_REF]. The chromatogram deconvolution was performed using the Local Minimum Search algorithm with the following settings: chromatographic threshold = 1%, search minimum in RT range (min) = 0.1, minimum relative height = 5%, minimum absolute height = 2E3, min ratio of peak top/edge = 1.4, peak duration range (min) = 0.05 -2. MS2 scans were paired using a m/z tolerance range of 0.02 Da and RT tolerance range of 1.5 min. Isotopes were grouped using the isotopic peaks grouper algorithm with a m/z tolerance of 10 ppm and a RT tolerance of 1.3 min with the most intense peak. The adduct search module was used repeatedly to perform the annotation of the chlorination pattern[START_REF] Mcmanus | Isolation of Isotrichophycin C and Trichophycins G-I from a collection of Trichodesmium thiebautii[END_REF] using the following parameters (in this order): for Cl2, mass_difference = -1.997, Max relative adduct peak height <180%; for Cl, mass_difference = -1.997, Max relative adduct peak height <400%, RT tolerance = 1.3 min, m/z tolerance = 10 ppm. The resulted peak list was filtered to keep only rows with MS2 features. The .mgf file was exported using the dedicated "Export/Submit to GNPS/FBMN" option. The .csv file (for RT, areas and identities regarding the chlorination patterns) was generated separately. The raw data files related to the LC-MS/MS analysis were deposited on the public MassIVE repository under the accession number: MSV000086130.

Table 2 .

 2 The relative energy and the Boltzmann populations of conformers for bianthrones 5 and 6.

	Conformers	Relative Energy	Boltzmann
		kJ.mol -1	population
	(10R,10'R)-5 gauche 1	2.61	0.25
	(10R,10'R)-5 gauche 2	0.00	0.73
	(10R,10'R)-5 anti	9.23	0.02
	(10R,10'S)-5 gauche 1	0.00	0.50
	(10R,10'S)-5 gauche 2	0.01	0.49
	(10R,10'S)-5 anti	9.85	0.01
	(10R,10'R)-6 gauche 1	2.58	0.26
	(10R,10'R)-6 gauche 2	0.00	0.74
	(10R,10'R)-6 anti	14.40	0.00
	(10R,10'S)-6 gauche 1	0.18	0.48
	(10R,10'S)-6 gauche 2	0.00	0.52
	(10R,10'S)-6 anti	11.57	0.00

Table 3 .

 3 Best

			6a goes with :
		(10R-10'S)-gauche 1	(10R-10'S)-gauche 2
	6b goes with :	CP3	P	CP3	P
	(10R,10'R)-gauche 1	-0.19	2	-0.58	0
	(10R,10'R)-gauche 2	0.81	100	0.73	100

CP3 values and related probabilities for the diastereoisomers (10R,10ʹR) and (10R,10ʹS) for compounds 6a and 6b. The intersection of a row column gives the CP3 score and the corresponding probability, for a pair of diastereoisomers, that one of these matches compound 6a and the other, compound 6b.

  This species grows on bark in humid mossy communities of markedly oceanic old-growth forests and is quite sensitive to pollutants. The upper surface is grey-brown and apothecia are scabrid-areolate, ridged and frequent. Samples were identified by thalline chemical tests and stored in the herbarium at the Faculté de Pharmacie, Université de

	mL/min with 63% A / 37% B for 30 min (A = 0.1% trifluoroacetic acid -acetonitrile; B = 0.1%
	trifluoroacetic acid-water). TLC was performed on pre-coated silica gel aluminum sheets
	(Kieselgel 60 F254, 0.20 mm, Merck). The plates were visualized under UV light (254 and
	365 nm) and using anisaldehyde-H2SO4 reagent. Preparative TLC was conducted on silica
	plates Macherey-Nagel SIL G-25 UV254 (20 x 20 cm, 0.25 mm). Chromatographic
	separation was performed using C18-functionalized silica gel (LiChroprep® 15-25 µm,
	Merck). MPLC was carried out using the Büchi pump model C-605, C-615. Acetone, ethyl
	acetate, dichloromethane, toluene (all with purity ≥ 99.8 %), and orthophosphoric acid (85 %)
	were purchased from Carlo Erba. Methanol (HPLC grade, ≥ 99.8 %), chloroform (≥ 99.2 %),
	and formic acid (≥ 99.3 %) from VWR International.
	4.2.	Lichen Material
	Nephroma laevigatum samples were collected in Soudeilles (France; 45°26ʹN. 2°2ʹE) on
	October 2014.
	(Controller, Pumpand Inline Degasser AF) on a Nucleodur® C18 HTec column (250 x 21 mm,
	10µm, Macherey-Nagel). HPLC conditions consisted of isocratic elution at a flow rate of 20

  MS exclusion list criterion was set to prevent oversampling of the internal calibrant. LC-UV and MS data acquisition and processing were performed using MassHunter Workstation software (Agilent Technologies, Massy, France).

	mg). Purification of fraction F11c (60.0 mg) yields the compounds 2 (30 mg), 5a (7.4 mg), 5b
	(9.0 mg) and 6a (9.5 mg) and 6b (14.3 mg).
	(±)-Nephrolaevigatin A or 7-chloroemodine bianthrone (5a): Yellowish powder; [α] 20 D +5 (c
	0.002, (Me)2CO); 1 H and 13 C NMR (in DMSO-d6), see Table 1; Rt 24.016 min; HRESIMS
	negative m/z 577.0488 [M-H] -(calcd for C30H19O8Cl2 577.04515). The MS/MS spectrum was
	deposited in the GNPS spectral library under the identifier: CCMSLIB00005724340.
	(±)-Nephrolaevigatin B or 7-chloroemodine bianthrone (5b): Yellowish powder; [α] 20 D +9 (c
	0.002, (Me)2CO); 1 H and 13 C NMR (in DMSO-d6), see Table 1; Rt 25.667 min; HRESIMS
	negative m/z 577.0488 [M-H]-(calcd for C30H19O8Cl2 577.04515). The MS/MS spectrum was
	deposited in the GNPS spectral library under the identifier: CCMSLIB00005724341.
	(+)-Nephrolaevigatin C or (+)-(10R*, 10ʹS*) emodine-7-chloroemodine bianthrone (6a):
	Yellowish powder; [α] 20 D +66 (c 0.01, MeCN ; CCMSLIB00005724339.
	(±)-Nephrolaevigatin D or (±)-(10R*, 10ʹR*) emodine -7-chloroemodine bianthrone (6b):
	Yellowish powder; [α] 20 D 0 (c 0.002, (Me)2CO); 1 H and 13 C NMR (in DMSO-d6), see Table 1;
	Rt 18.34 min; HRESIMS negative m/z 543.0866 [M-H] -(calcd for C30H20O8Cl 543.08412). The
	MS/MS spectrum was deposited in the GNPS spectral library under the identifier:
	CCMSLIB00005724338.
	4.4.	Data dependent LC-ESI-HRMS 2 analysis
	LC-ESI-HRMS 2 analyses were achieved by coupling the LC system to a hybrid quadrupole
	time of-flight mass spectrometer Agilent 6530 (Agilent Technologies, Massy, France)
	equipped with an ESI source, operating in positive-ion mode. Source parameters were set as
	followed: capillary temperature at 320°C, source voltage at 3500 V, sheath gas flow rate at
	10 L.min -1 . The divert valve was set to waste for the first 3 min. MS scans were operated in
	full-scan mode from m/z 100 to 1700 (0.1s scan time) with a mass resolution of 11 000 at
	m/z 922. MS1 scan was followed by MS2 scans of the five most intense ions above an
	20 eluted with CHCl3/MeOH (90:10 to 0:100) to provide 11 fractions (F11a to F11k). absolute threshold of 5000 counts. Selected parent ions were fragmented at a collision
	Purification of F11a (208 mg) by preparative TLC give the compound 3 (15 mg) and 4 (26
	mg). Purification of F11b (214 mg) by semi-preparative HPLC generates the compound 2 (3

1

H and

13

C NMR (in DMSO-d6), see Table

1

; Rt 21.471 min; HRESIMS negative m/z 543.0866 [M-H] -(calcd for C30H20O8Cl 543.08412). The MS/MS spectrum was deposited in the GNPS spectral library under the identifier: energy fixed at 45 eV and an isolation window of 1.3 amu. Calibration solution, containing two internal reference masses (purine, C5H4N4, m/z 121.050873, and HP-921 [hexakis-(1H,1H,3H-tetrafluoropentoxy)phosphazene], C18H18O6N3P3F24, m/z 922.0098). A permanent MS/

Acknowledgements

This work was supported by Limousin Region (doctorale fellowship grant for A. Lagarde). This work was also financially supported by the ANR grant.LICSYFILM (ANR-17-CE35-0005). We are also grateful to A-L. Rioux, M. Arfeuillère for technical assistance and to Mrs E. Pinault for HR-MS analysis.

GNPS spectral libraries. All matches kept between network spectra and library spectra were required to have a score above 0.65 and at least 6 matched peaks. The molecular networking data were analyzed and visualized using Cytoscape (ver. 3.6.0) [START_REF] Shannon | Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks[END_REF].

4.7.

Computational details for GIAO NMR chemical shifts calculations All DFT calculations were performed using the Gaussian 09.A01 program [START_REF] Frisch | Gaussian 09[END_REF]. The calculations of the NMR spectra consisted in three successive steps. For each compound 5 and 6, isomers C-10 R/C-10ʹ R and C-10 R / C-10ʹ S were first subjected to a conformational search using the MMFF94 force-field implemented in TINKER software tools. The resulting lowest energy conformations were then subjected to further optimization at the MPW1PW91/6-31+G(d,p) level of theory. The bulk solvent effects were described with the integral equation formalism polarizable continuum Model (IEFPCM) with DMSO as solvent [START_REF] Tomasi | Quantum Mechanical Continuum Solvation Models[END_REF]. Vibrational frequencies were computed using the gauge-including atomic orbitals (GIAO) [START_REF] Barone | Structure Validation of Natural Products by Quantum-Mechanical GIAO Calculations of 13C NMR Chemical Shifts GIAO=gauge including atomic orbitals[END_REF][START_REF] Schreckenbach | Calculation of NMR Shielding Tensors Using Gauge-Including Atomic Orbitals and Modern Density Functional Theory[END_REF] method with the same level theory. The resulting shielding tensors were averaged using the Boltzmann distribution. The chemical shifts were calculated from TMS as reference standard. The systematic errors were removed by scaling according to δscaled = (δcalc -Intercept)/Slope, where Intercept and Slope, result from a linear regression calculation on a plot of δcalc against δexp [START_REF] Barone | Structure Validation of Natural Products by Quantum-Mechanical GIAO Calculations of 13C NMR Chemical Shifts GIAO=gauge including atomic orbitals[END_REF]. The CP3 probabilities were then computed as originally described by Smith and Goodman [START_REF] Smith | Assigning the Stereochemistry of Pairs of Diastereoisomers Using GIAO NMR Shift Calculation[END_REF].

Declaration of competing interest

The authors declare that there is no conflict of interest for the financial support and the redaction of the manuscript. All the authors listed have approved the above manuscript. I declare on behalf of my co-authors that this work has not been published previously elsewhere in whole or in part.

Graphical Abstract Chlorinated Bianthrones from the Cyanolichen Nephroma laevigatum

Aurélie Lagarde [a] , Lengo Mambu [a] , Phuong-Y. Mai [a] , Yves Champavier [b] , Jean-Luc Stigliani , Mehdi A. Beniddir * [d] , and Marion Millot * [a] Original chlorinated bianthrones have been isolated from the lichens Nephroma laevigatum. These compounds derived from emodin and have been highlighted by a MS/MS molecular networking-based dereplication strategy. The structures of these chemically instable molecules were elucidated on the basis of extensive spectroscopic analysis, and GIAO NMR shift calculation followed by CP3 analysis.


J-B Vaney

J Carreaud

G Delaizir

C Morin

J Monnier

E Alleno

A Piarristeguy

A Pradel

A P Gonçalves

E B Lopes

C Candolfi

A Dauscher

B Lenoir

Thermoelectric properties of the α-As 2 Te 3 crystalline phase Authors

As2Te3 exists in two allotropic configurations: α-and β-As2Te3, of which only the latter crystallizes in the same rhombohedral structure-type as Bi2Te3. While β-As2Te3 shows interesting thermoelectric properties that can be adjusted through alloying, the transport properties of the monoclinic phase α-As2Te3, more thermodynamically stable than the β-phase at room temperature, has not yet been studied thoroughly. We report here on the preparation by powder metallurgy and on the microstructural characterization of polycrystalline α-As2Te3.

Preliminary results on the electrical and thermal properties measured between 5 and 523 K are also reported.

Transport properties measurements were performed both along and perpendicular to the pressing direction indicating that the transport properties demonstrate some degree of anisotropy. Remarkably, low thermal conductivity values (below 1 W.m -1 .K -1 above 300 K) were measured suggesting that this compound may be an interesting platform to design novel thermoelectric materials with high efficiency.

Introduction

Thermoelectric materials offer an effective way to convert thermal energy into electrical energy (Seebeck effect) and, reciprocally, electrical energy into thermal energy (Peltier effect). The performance of thermoelectric devices is directly related to the materials' dimensionless thermoelectric figure of merit ZT defined by where T is the absolute temperature, α is the Seebeck coefficient (or thermopower), is the power factor, 𝜌 is the electrical resistivity and λ is the total thermal conductivity. For decades, the performance of thermoelectric (TE) materials have been limited, confining them to niche applications and markets [START_REF] Rowe | Thermoelectrics handbook: macro to nano[END_REF]. Owing to strong interdependence between the three transport properties, achieving high ZT on a broad temperature range still remains the most challenging aspect in thermoelectricity [START_REF] Goldsmid | Thermoelectric refrigeration[END_REF][START_REF] Snyder | Complex thermoelectric materials[END_REF].

Recently, the metastable β-As2Te3 phase, isostructural to the state-of-the art Bi2Te3 based materials, showed interesting performance upon substitution of Sn for As, with peak ZT around 0.6 at 423 K [START_REF] Vaney | High-Temperature Thermoelectric Properties of Sn-Doped β-As2Te3[END_REF]. As2Te3 however exists in two allotropic forms: the rhombohedral β-As2Te3, firstly described at high pressure [START_REF] Yakushev | A NEW POLYMORPHIC FORM OF ARSENIC TELLURIDE OBTAINED AT HIGH PRESSURE[END_REF] and then obtained at room pressure by by rapid quenching from the melt [START_REF] Shu | Systeme As-Te-Mise en evidence et etude structurale d'une nouvelle variete de As2Te3 metastable[END_REF][START_REF] Toscani | Polymorphism of As2Te3: structural studies and thermal behaviour of rhombohedral β-As2Te3[END_REF], and the monoclinic α-As2Te3 [START_REF] Carron | The crystal structure and powder data for arsenic telluride[END_REF], the former transforming into the latter upon heating above 410 K. α-As2Te3 has been scarcely studied from the thermoelectric point of view but may show interesting properties as early studies [START_REF] Harman | Preparation and some physical properties of Bi2Te3, Sb2Te3, and As2Te3[END_REF][START_REF] Scheidemantel | Thermoelectric power and phase transition of polycrystalline As2Te3under pressure[END_REF] and first-principles calculations hint at [START_REF] Sharma | First principles investigation of electronic, optical and transport properties of αand β-phase of arsenic telluride[END_REF]. Herein, we describe the crystalline structure of α-As2Te3 and its successful synthesis and shaping by Spark Plasma Sintering (SPS) technique. The thermoelectric properties of this binary compound are further probed between 5 and 523 K. Although the maximum ZT remains very low, our results suggest that there is still much room for further improvement upon alloying if the carrier concentration can be properly controlled.

Experimental details

The α-As2Te3 sample was prepared by direct reaction of stoichiometric amounts of pure elements (As (Goodfellow, 99.99%, shots) and Te (5N+, 99.999%, shots)) sealed under secondary vacuum (10 -5 mbar) in quartz tubes. The tubes were heated slowly up to 923 K at a rate of 10 K min -1 , dwelt at this temperature for 2 hours and finally quenched in iced water. At this step the β-phase was obtained [START_REF] Vaney | High-Temperature Thermoelectric Properties of Sn-Doped β-As2Te3[END_REF]. The ingot was subsequently

l rl a PT T ZT = = 2 r a / 2 = P
annealed at 613K for 3 days to finally obtain the pure α-As2Te3 phase. The resulting ingots were ground into micron-sized powders and consolidated by SPS (Spark Plasma Sintering) into 10 mm diameter cylindrical pellet under a pressure of 50 MPa at a temperature of 613K for 2 minutes. The obtained pellet showed a relative density close to 99% of the theoretical density.

The crystal structure was determined by powder X-ray diffraction (PXRD) at 300 K with a Bruker D8 Advance instrument using CuKα1 radiation. The chemical homogeneity of the sample was checked by scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDXS) using a Quanta FEG (FEI).

Electron Probe Micro-Analysis (EPMA) was performed with a JEOL JXA 8530F equipped with wavelengthdispersive spectrometers. Backscattered electrons were used for imaging the surface of the samples. In order to minimize matrix effects, X-ray intensities of As and Te were compared with those of a calibrated β-As2Te3 standard for quantitative analysis. The chemical compositions of the α-As2Te3 specimens were determined from analysis of a set of at least 90 different points for each sample. Bulk pieces of the densified sample were carefully polished down to 1 µm alumina powder for EPMA analysis.

The thermoelectric properties were measured between 5 and 523 K on well-shaped samples cut with a diamond wire-saw (typical dimensions of 2×3×8 mm 3 ). Owing to the anisotropic crystal structure of the present compound, the transport properties were measured on samples cut both parallel and perpendicular to the pressing direction. α and ρ data were collected in the 300 -523 K temperature range using a ZEM-3 apparatus (ULVAC-RIKO). Thermal diffusivity a was measured by a laser flash technique (Netzsch LFA 427) between 300 and 523 K. The specific heat Cp was measured by differential scanning calorimetry (DSC Netzsch Pegasus) above room temperature. The thermal conductivity was then calculated via κ = a. Cp .d where d is the density measured using the mass and the geometric dimensions of the densified pellet. The density was considered temperatureindependent in the present case. The errors for each measured properties are estimated to be about 5% so that the combined uncertainty on the ZT values is about ~20%. To measure the thermoelectric properties between 5 and 300 K, we used the thermal transport option (TTO) of a physical property measurement system (PPMS, Quantum Design). These measurements were conducted by brazing four copper bars on the samples to ensure excellent electrical and thermal contacts. Specific heat was measured on a small prism-shaped sample (mass of ~ 15 mg) from 2 to 260 K using the He 4 option of the PPMS.

Results and discussion

Structural and chemical characterizations

The study of α-As2Te3 is to be put in perspective with its allotropic counterpart β-As2Te3. The metastable β-As2Te3 (space group 𝑅3 $ 𝑚), produced by rapid quenching [START_REF] Shu | Systeme As-Te-Mise en evidence et etude structurale d'une nouvelle variete de As2Te3 metastable[END_REF] or under high pressures [START_REF] Toscani | Polymorphism of As2Te3: structural studies and thermal behaviour of rhombohedral β-As2Te3[END_REF], transforms into the α structure (space group C2/m) upon heating above 410K [START_REF] Vaney | A comprehensive study of the crystallization of Cu-As-Te glasses: microstructure and thermoelectric properties[END_REF]. The perspective views of the unit cell of both structures (the hexagonal cell of β-As2Te3 is displayed rather than the rhomboedric cell) are represented on Figure 1. It could be expected that both are very close and that the α form would appear as a distorted version of the more ordered β-structure. Projections of the atomic arrangements of the α-and β-phases along their a-axis are displayed on Figure 2. It can be clearly observed that both show layered arrangements with alternating Asplanes and Te-planes. However, upon closer examination, these projections reveal different sequences separated by van der Waals bonding with a quintet sequence Te1-As-Te2-As-Te1 for β-As2Te3 in the c-direction and a zigzag stacking for the α-As2Te3 structure [START_REF] Stergiou | Hydrothermal growth and the crystal structure of arsenic telluride, As2Te3[END_REF].

Figure 3 presents the powder X-ray diffraction (PXRD) pattern collected on the binary sample α-As2Te3. All reflections can be indexed to the C2/m space group without any additional peak that would reveal a secondary phase. Due to the anisotropy of the structure, the sample show a slight preferred orientation resulting in a very shallow renormalization of the relative intensities of the Bragg peaks. The Rietveld refinement of this pattern leads to good fits allowing determining precisely the lattice parameters, in good agreement with literature data [START_REF] Toscani | Polymorphism of As2Te3: structural studies and thermal behaviour of rhombohedral β-As2Te3[END_REF]. All refined parameters are described in Table 1. Scanning electron microscopy (SEM) and X-Ray mapping further revealed an overall homogeneous distribution of the different elements as displayed io Figure 4. EPMA gave an average composition of As1.99Te3.01 for the compound, which is close to the nominal one.

Thermoelectric properties of the binary phase α-As 2 Te 3

The temperature dependences of ρ and α measured parallel and perpendicular to the pressing direction are displayed on Figures 5-A and 5-B respectively. Both properties exhibit a slight anisotropy, clearly observed below 200 and above 150 K in the ρ(T) and in the α(T), respectively. Over the entire temperature range, the electrical resistivity in both direction displays an activated behavior with values ranging from around 1 Ω.m at 5 K to less than 600 μΩ.m at 500 K. The high-temperature region can be described by an Arrhenius law r = r0.exp[Ea/kBT] (shown by the solid line in the inset of Fig. V5-A), where the activation energy Ea = 65 meV, kB the Boltzmann's constant and r0 is a constant. This activation energy could imply an intrinsic semiconducting gap of ~130 meV. This result is however different from that of Sharma et al. [START_REF] Sharma | First principles investigation of electronic, optical and transport properties of αand β-phase of arsenic telluride[END_REF] deduced from ab-initio band structure calculations where a value of 0.4 eV was obtained. Below 17 K, r has a nearly exponential temperature dependence with much lower activation energy. The best fit to the data in this temperature region was of the form r = r0exp[T0/T] 1/4 (where r0 is a constant and T0 is the characteristic temperature of the system) indicative of Mott variable range hopping. α(T) does not evolve monotonously but increases with temperature up to 160 μV.K -1 at 250 K, followed by a two-step decrease and a transition from p-to n-type transport above 400 K in the perpendicular direction only.

This behavior is likely due to the manifestation of minority carrier effect (electrons in the present case). The fact that the p-to n-type transition is only seen in the perpendicular direction may point to some degree of anisotropy in the carrier mobility as well. Doping heavily this compound would result in pushing this transition towards higher temperatures and would likely enhance the power factor α 2 /r. Comparisons between our results and the electronic transport properties predicted by band structure calculations show important deviations [START_REF] Sharma | First principles investigation of electronic, optical and transport properties of αand β-phase of arsenic telluride[END_REF]. Among the possible reasons explaining these discrepancies, we speculate that the influence of native defects, not taken into account in the modeling, could play a major role. Actually, it is well-established that native defects such as anti-structure defects or vacancies can strongly affect the electronic transport properties in thermoelectric materials such as bismuth telluride [START_REF] Fleurial | Thermal properties of high quality single crystals of bismuth telluride-Part I: Experimental characterization[END_REF]. It is worth to note that early studies showed n-type properties for the α-As2Te3 binary compound [START_REF] Harman | Preparation and some physical properties of Bi2Te3, Sb2Te3, and As2Te3[END_REF][START_REF] Scheidemantel | Thermoelectric power and phase transition of polycrystalline As2Te3under pressure[END_REF]. According to the EPMA measurement, the excess Te in our material would corroborate a transition to p-type, likely due to Te-doping on As sites as obtained by Harman for α-As2Te3 single crystals with excess Te.

Figure 6 displays the temperature dependence of the specific heat. Extrapolation of the low temperature data is in very good agreement with the measurements above room temperature. It is seen that the specific heat deviates slightly from the calculated Dulong-Petit value of 0.234 J/g.K between 300 and 500 K. Figure 7-A presents the temperature dependence of the thermal conductivity of α-As2Te3. λ shows a marked dielectric peak at low temperatures centered at 25K, attaining the value of 6.5 W/m.K in the perpendicular direction and 5.1 W/m.K in the parallel direction, before decreasing to the very low value of 0.7 W.m -1 .K -1 at 523K. Above 300 K, the anisotropy is no longer visible to within experimental uncertainty. In this particular case where the electrical resistivity is high, the electronic contribution to thermal conductivity is negligible, so that λ reflects exclusively the lattice contribution. Noteworthy, the thermal conductivity of β-As2Te3 is even lower reaching values below 0.6 W.m -1 .K -1 at 423K [START_REF] Vaney | High-Temperature Thermoelectric Properties of Sn-Doped β-As2Te3[END_REF] with a non-negligible electronic contribution. In terms of ZT values, presented on

Conclusion

We presented results on the thermoelectric characterization of the compound α-As2Te3 between 5 and 523 K.

Owing to presumably low carrier concentration, the influence of minority carriers above 250 K strongly undermines the Seebeck coefficient, even leading to a sign change near 500K. Even though displaying an interesting thermal conductivity lower than 1 W.m -1 .K -1 above 300 K, the very low power factors (< 5.10 6 W.m - 1 .K -2 ) therefore do not allow achieving high ZT values. However, this is not to say that this phase does not deserve further attention. Appropriated substitutions to tune the carrier concentration may be beneficial in optimizing the ZT values. Between 260 and 300K, the influence of the addenda on the low temperature measurement does not allow to display reliable data. In the same fashion measurement artifacts do not allow to show reliable data between 300 and 360K.

Figure captions

Figure 7 -

 7 Figure 7-B, the large electrical resistivity and the low thermopower values result in only very low ZT values around 0.001. Further studies aiming at probing the influence of different dopants are worthwhile to determine the potential of this compound for thermoelectric applications.

Fig 1 :Fig 2 :

 12 Fig 1: Perspective view of the hexagonal crystal structure β-As2Te3 (rhombohedral of space group 𝑹𝟑 ( 𝒎, a = 4.0473 Å and c = 29.5018 Å ) (A) and α-As2Te3 (monoclinic of space group C2/m, a = 14.339, b = 4.0114, c = 9.8859, β = 95.046)(B). The As atoms are represented as small red balls and the Te atoms by large blue balls.

Fig 3 :

 3 Fig 3: Powder X-Ray diffraction pattern of α-As2Te3. The observed data are marked as open red circles. The calculated profile is represented by a solid black line while the difference between experimental and numerical patterns is shown by the solid blue line (RF = 4.024, χ 2 = 8.04). The positions of the Bragg reflections are indicated as green bars.

Fig 4 :Fig 5 :

 45 Fig 4: Scanning Electron Microscope (SEM) elemental contrast picture of the sample α-As2Te3 in Secondary electron (SE) and Back Scattering Electrons (BSE) mode, together with the corresponding element mapping of As and Te. The distribution of the elements is overall homogeneous.

Fig 6 :

 6 Fig 6: Specific heat of the compound α-As2Te3 measured between 2 and 260 K and between 360 and 523 K.

Fig 7 :

 7 Fig 7: Temperature dependence of the thermal conductivity λ (A) and the figure of merit ZT (B) of the polycrystalline α-As2Te3 sample. The measurements performed parallel and perpendicular to the pressing direction are represented by filled and open symbols respectively. The measurements of λ at low (5-300K) and high (300-523K) temperature show a slight discrepancy at 300K due to issues in correcting the radiation heat loss over 200K with the TTO option of the PPMS.

Table 1 : Parameters of the power X-Ray diffraction of the α-As2Te3 phase obtained by Rietveld refinement.

 1

	a (Å)	b (Å)	c (Å)	β (°)
	14.3392	4.0147	9.8859	95.046
	Atomic position	x	y	z
	As1	0.6135	0.0000	0.4406
	As2	0.2014	0.0000	0.1413


Laura Mannocci
email: laura.mannocci@gmail.com

Yannick Baidai

Fabien Forget

Mariana Travassos Tolotti

Laurent Dagorn

Manuela Capello

Seine Fisherieslaura Mannocci

Machine learning to detect bycatch risk: Novel application to echosounder buoys data in tuna purse seine fisheries

Keywords: Atlantic Ocean, drifting fish aggregating devices, echosounder buoys, Indian Ocean, random forests, tropical tuna purse seine fisheries

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

Introduction

The past decade has seen an unprecedented rise in data collections on aquatic ecosystems (Durden et al 2017). In the oceans, emerging sources of datasets include automatic vessel tracking systems [START_REF] Kroodsma | Tracking the global footprint of fisheries[END_REF]) and autonomous underwater vehicles [START_REF] Sahoo | Advancements in the field of autonomous underwater vehicle[END_REF]. To accelerate the processing of these massive and complex datasets often referred to as "big data", machine learning algorithms have emerged as powerful tools, with promising applications in marine sciences [START_REF] Beyan | Setting the stage for the machine intelligence era in marine science[END_REF]). Together, big data and machine learning have a huge potential for addressing conservation and management issues in the oceans.

With over half of the world's oceans subject to industrial fishing [START_REF] Kroodsma | Tracking the global footprint of fisheries[END_REF], the overexploitation of marine resources is a pervasive threat to marine biodiversity. Pursuant to the Sustainable Development Goal 14 of the United Nations, achieving sustainable use of ocean resources is a major societal challenge. Machine learning tools provide new opportunities for improving the management of fisheries by allowing the automated monitoring of catches for both target and non-target species [START_REF] Bradley | Opportunities to improve fisheries management through innovative technology and advanced data systems[END_REF][START_REF] Malde | Machine intelligence and the data-driven future of marine science[END_REF]. There is a growing need for pragmatic and illustrative cases for how these tools can be used to promote sustainable fishing practices at sea.

The global catch of tropical tuna is close to 5 million tons per year and tropical tuna purse seine fisheries (TTPSF) account for two thirds of this global catch (ISSF 2019). In these fisheries, the use of Drifting Fish Aggregating Devices (DFADs)-man-made floating objects deployed by fishers to increase their tuna catches-results in the incidental catch of other fish species, termed bycatch [START_REF] Dagorn | Is it good or bad to fish with FADs? What are the real impacts of the use of drifting FADs on pelagic marine ecosystems?[END_REF]. Though bycatch in TTPSF is relatively lower than in some other fisheries (with a reported discards rate of 3.9% in TTPSF versus 12.3% in pelagic longlines fisheries, for example) [START_REF] Roda | A third assessment of global marine fisheries discards[END_REF], the sheer magnitude of TTPSF means that the induced mortality on non-target species is not negligible. Moreover, the strong associations of some species with DFADs make them particularly vulnerable to bycatch [START_REF] Forget | Behaviour and vulnerability of target and non-target species at drifting fish aggregating devices (FADs) in the tropical tuna purse seine fishery determined by acoustic telemetry[END_REF]. Decreasing overall bycatch volumes in TTPSF is central to the application of an ecosystem approach to fisheries management [START_REF] Pikitch | Ecosystem-Based Fishery Management[END_REF]).

Between 81,000 and 121,000 DFADs are deployed every year by fishers across the globe, and this number is likely to have increased since this estimate was made [START_REF] Gershman | Estimating The Use of FADs Around the World: An updated analysis of the number of fish aggregating devices deployed in the ocean[END_REF]. Most DFADs are equipped with satellite-linked echosounder buoys that automatically provide remote information on their geolocation and fish presence. These buoys represent an unprecedented source of big data for scientists who can use this constellation across the oceans as a scientific platform for observing pelagic biodiversity [START_REF] Moreno | Fish aggregating devices (FADs) as scientific platforms[END_REF]. While echosounder buoys have been designed to provide fishers with information on tuna presence, we postulate that data from these buoys can also inform on the presence of bycatch. In this study, we explored the potential of processing echosounder buoy data with machine learning to assess bycatch risk at DFADs prior to fishing sets. Our novel approach opens the door to the development of new machine learning tools to aid fishers in reducing bycatch, thereby improving selectivity in TTPSF.

Methods

Database description

We obtained echosounder data from Marine Instruments "M3I" buoys attached to DFADs deployed by French purse seiners in the Atlantic and Indian oceans for the 2013-2018 period. Each buoy is equipped with a GPS and an echosounder operating at 50 Khz. Simplified acoustic profiles are stored every 2 h and transmitted by satellite every 12 h (by default) in the form of 50 integer acoustic scores (ranging from 0 to 7) indicating the acoustic energy recorded within 3-m depth layers over a total detection range of 150 m (Figure S1) [START_REF] Baidai | Machine learning for characterizing tropical tuna aggregations under drifting fish aggregating devices (FADs) from commercial echosounder buoys data Yannick Baidai[END_REF]). We obtained bycatch data from scientific observer programs onboard French purse seiners in the Atlantic and Indian oceans implemented under the EU Data Collection Framework (DCF) and the French OCUP program (Observateur Commun Unique et Permanent). Bycatch data were used to associate acoustic profiles with the actual bycatch biomass, based on the assumption that the entire aggregation is encircled and captured. For each DFAD fishing set, dedicated observers recorded species-specific bycatch in numbers of individuals, or in weight when the number of individuals was too high to be reliably counted. Numbers were converted to weight based on the mean recorded individual length and published length-weight relationships. Total bycatch biomass was then calculated by summing species-specific biomasses. Observers also recorded the date, time, GPS location and the buoy unique identifier associated with each set.

Acoustic data pre-processing

We pre-processed acoustic data for standardization and reduction of dimensionality as illustrated in Figure S1 (detailed in [START_REF] Baidai | Machine learning for characterizing tropical tuna aggregations under drifting fish aggregating devices (FADs) from commercial echosounder buoys data Yannick Baidai[END_REF]. We excluded the two layers corresponding to the transducer blanking zone (from 0 to 6 m depth). Acoustic scores were first aggregated temporally by averaging them over 4-h slots. Next, acoustic scores were aggregated vertically based on a cluster analysis [START_REF] Murtagh | Ward's Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward's Criterion?[END_REF], which identified 6 homogeneous groups of depth layers in each ocean [START_REF] Baidai | Machine learning for characterizing tropical tuna aggregations under drifting fish aggregating devices (FADs) from commercial echosounder buoys data Yannick Baidai[END_REF]. For each homogeneous depth group, acoustic scores recorded for each of the layers constituting the group were summed and rescaled to obtain a single score per depth group and time interval [START_REF] Baidai | Machine learning for characterizing tropical tuna aggregations under drifting fish aggregating devices (FADs) from commercial echosounder buoys data Yannick Baidai[END_REF]. This pre-processing led to daily acoustic matrices of 6 x 6 dimension providing synthetic acoustic profiles.

Machine learning

The originality of our approach lies in the ability of machine learning to detect bycatch occurrence at DFADs based on patterns on echosounder buoy outputs when bycatch species were present, with no required a priori knowledge on these patterns, nor on species-specific acoustic responses. We considered as bycatch species all non-tuna teleosts (Table S2). Because these species have swim bladders and usually form dense schools, they are highly detectable by echosounder buoys. In contrast, sharks generally occur in low numbers around DFADs (between 2 and 6 individuals on average in the Atlantic and Indian oceans, respectively), have no swim bladder and do not usually form dense schools. Hence, owing to their relatively insignificant biomass, they were less likely to be detected by the echosounders and were excluded from our analyses.

We obtained learning datasets by matching bycatch biomasses reported by observers with daily acoustic matrices in each ocean, based on buoy identifiers, and dates and times of the sets. We discarded aberrant buoy identifiers for which positions reported by observers were inconsistent with GPS positions. We used daily acoustic matrices corresponding to the day preceding the set in order to avoid potential disturbances to fish aggregations induced by the fishing operation. Because very few sets contained no bycatch (only 5.4% in the Atlantic Ocean and 6.2% in the Indian Ocean), we used a cutoff for categorizing sets into "high" and "low" bycatch, and performed a binary classification. We defined the best cutoff among values ranging from 0.1 to 1 t in each ocean as the one leading to the highest classification accuracy (see below).

In each ocean, we applied a random forest (RF) classification algorithm [START_REF] Breiman | Random Forests[END_REF] to discriminate between high and low bycatch occurrence using the R package "randomForest" [START_REF] Liaw | Classification and Regression by randomForest[END_REF]. A random forest consists of an ensemble of independent decision trees leading to a more accurate prediction than that of any individual tree [START_REF] Breiman | Random Forests[END_REF]. Candidate predictor variables were the elements of the 6 x 6 daily acoustic matrices. To deal with the imbalanced number of observations in high and low bycatch classes, we resampled the dominant size class to make its frequency closer to the rarest class [START_REF] Kuhn | Applied Predictive ModelingSpringer[END_REF]. We grew three thousand trees in each ocean. We assessed the number of predictor variables randomly sampled at each split (denoted as "mtry") through a grid-search strategy implemented with the R package "caret" [START_REF] Kuhn | caret: Classification and Regression Training[END_REF]).

We selected the best "mtry" as the value generating the lowest classification error rate. The importance of predictors was assessed using the mean decrease accuracy (i.e., the increase of prediction error after permuting each predictor, leaving all other predictors unchanged) [START_REF] Breiman | Random Forests[END_REF]).

We performed model training and evaluation through a hold-out validation (corresponding to setting a portion of the data aside to evaluate model performance) repeated 10 times. In each replica, we divided the original dataset into training and validation datasets, representing 75% and 25% of the data, respectively. We then derived the model accuracy (proportion of correct predictions) and the kappa coefficient (a reliability index) [START_REF] Cohen | Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit[END_REF]) on the validation dataset. Finally, sensitivity (true positive rate), specificity (true negative rate), and precision (positive predictive value) were derived from the confusion matrix.

Results

In both oceans, we obtained the best RF accuracy with a cutoff of 0.2 t between low and high bycatch classes (Figure S3-1 and S3-2). Learning datasets represented 838 and 2144 data points in the Atlantic and Indian Ocean, respectively (Figure 1, Table S4-1). In the Atlantic Ocean (AO), the high bycatch class corresponded to acoustic scores that were higher in intermediate depth layers (from 21 to 45 m), but slightly lower in shallow layers during the day (Figure S4-1). In the Indian Ocean (IO), differences were less clear, with a high bycatch class associated with slightly higher acoustic scores in shallow layers (from 6 to 18m) during the day.

The RF algorithm was better at discriminating high and low bycatch classes in the AO than in the IO, with respective accuracies of 0.66 and 0.58, and a kappa coefficient twice higher in the AO (Table 1).

In both oceans, the sensitivity was higher than the specificity, indicating a better ability at detecting the high bycatch class (Table 1, Figure 2).

In the IO, the most important predictors corresponded to shallow layers (6-15 m) during the day (Figure 3). Conversely, in the AO, deep layers (27-150 m) during the day, and shallow layers (9-21 m) around dawn, appeared most important.

Discussion

Fishing on DFADs accounts for more than half of the tuna landings of TTPSF [START_REF] Restrepo | A Summary of Bycatch Issues and ISSF Mitigation Initiatives To-Date in Purse Seine Fisheries, with emphasis on FADs[END_REF]), but also leads to large overall bycatch volumes [START_REF] Roda | A third assessment of global marine fisheries discards[END_REF]. We capitalized on the massive data available from fishers' buoys analyzed through machine learning to assess whether they could inform potential bycatch risks at DFADs. RF algorithms showed promise to discriminate between high and low levels of teleost bycatch, particularly in the AO, and better detected the high bycatch class.

Implemented in real time, these algorithms could help fishers to avoid fishing sets on DFADs associated with high risks of non-target species catch, thereby improving selectivity in TTPSF. Though additional research is needed to increase the algorithms' accuracy, our approach shows great potential for progressing towards an ecosystem approach to fisheries [START_REF] Pikitch | Ecosystem-Based Fishery Management[END_REF]). Indeed, our approach focuses on non-tuna teleost species impacted by fisheries and could help design spatiotemporal management measures that could lead to a reduction in overall bycatch volume, thereby complementing mitigation measures already in place for vulnerable species (e.g., [START_REF] Poisson | Mortality rate of silky sharks (Carcharhinus falciformis) caught in the tropical tuna purse seine fishery in the Indian Ocean[END_REF]. Regardless of the management strategy, knowledge on bycatch risk prior to fishing is key to support best fishing practices.

As bycatch species are generally known to occur shallower than tuna species [START_REF] Forget | Behaviour and vulnerability of target and non-target species at drifting fish aggregating devices (FADs) in the tropical tuna purse seine fishery determined by acoustic telemetry[END_REF][START_REF] Macusi | Local Ecological Knowledge (LEK) on Fish Behavior Around Anchored FADs: the Case of Tuna Purse Seine and Ringnet Fishers from Southern Philippines[END_REF], we expected acoustic scores to be higher in shallower layers in the high bycatch class. In the AO, acoustic scores in shallower layers were instead higher in the low bycatch class. We also found a pronounced geographical structure, with 65% of our low teleost bycatch class originating from coastal Angola and Gabon (Appendix S5) (an area that is nevertheless characterized by high shark bycatch [START_REF] Lopez | Using fisheries data to model the oceanic habitats of juvenile silky shark (Carcharhinus falciformis) in the tropical eastern Atlantic Ocean[END_REF]). In this region, the higher acoustic scores detected near the surface despite low teleost bycatch could be explained by an increased abundance of tuna in shallow layers usually occupied by bycatch species. RF algorithms further implemented at the regional scale had lower performances than the Atlantic-scale algorithm (Appendix S5). These results suggest that the higher performance in the AO compared to the IO could be related to the stronger geographical/environmental structure in the AO. Remarkably, these contrasted patterns between oceans and the importance of deep layers as predictor variables stress the need to reconsider the fixed 25 m depth layer previously assumed as adequate for discriminating bycatch and tuna species at DFADs [START_REF] Orue | Aggregation process of drifting fish aggregating devices (DFADs) in the Western Indian Ocean: Who arrives first, tuna or nontuna species?[END_REF].

Tables Table 1:

Figures

  Figures

Figure 1 :

 1 Figure 1: Geographical span of the learning datasets in the Atlantic (n=838 sets) and Indian oceans

Figure 2 :

 2 Figure 2: Confusion matrices standardized per row (i.e., with respect to observations) for random

Figure 3 :

 3 Figure 3: Importance of random forests predictors in the bycatch classification in both oceans

  Performances of the random forest classifications derived from a hold-out validation in each ocean. Mean and standard deviation values (in brackets) of evaluation metrics are provided.

	Evaluation Metrics	Atlantic Ocean	Indian Ocean
	Accuracy	0.66 (0.04)	0.58 (0.02)
	Kappa	0.32 (0.07)	0.16 (0.03)
	Sensitivity	0.74 (0.05)	0.63 (0.03)
	Specificity	0.59 (0.05)	0.53 (0.03)
	Precision	0.64 (0.03)	0.57 (0.02)

We would like to thank three anonymous reviewers for their feedback on an earlier version of this manuscript. This study was co-funded by the European Maritime and Fisheries Fund (EMFF) and France Filière Pêche (FFP) through the FEAMP research project "Innovations to reduce the impacts of FADs on marine ecosystems (INNOV-FAD)". The work of YB was co-funded by the ANR project BLUEMED (ANR-14-ACHN-0002). The authors are grateful to ORTHONGEL and its contracting parties (CFTO, SAPMER, SAUPIQUET) for sharing the echosounder buoys data and to Ob7 -Observatoire des Ecosystèmes Pélagiques Tropicaux Exploités for providing the data.

Competing interest statement

The authors have no competing interest to declare.

Discrepancies between bycatch detection on echosounder profiles and in the catches may negatively affect the performance of algorithms by introducing noise. For example, small schooling fish like Decapterus spp and the blue runner Caranx crysos are characterized by a strong acoustic backscatter, but are not always retained by the net. The buoy's blanking zone and its smaller acoustic cone in shallow layers also prevent the detection of bycatch species that occupy these positions in the water column during the night [START_REF] Forget | Behaviour and vulnerability of target and non-target species at drifting fish aggregating devices (FADs) in the tropical tuna purse seine fishery determined by acoustic telemetry[END_REF], leading to an overall underestimation of bycatch biomass from echosounders. Observer-derived bycatch estimates may be prone to estimation errors, especially in such large volume fisheries, but remain the most reliable data source of bycatch. In the future, observer data could be combined with complementary data sources, such as electronic monitoring, in an attempt to improve bycatch estimates [START_REF] Ruiz | Electronic monitoring trials on in the tropical tuna purse-seine fishery[END_REF]. Finally, echosounder buoys cannot be used to detect sharks despite their vulnerability to bycatch and DFAD entanglement [START_REF] Dagorn | Is it good or bad to fish with FADs? What are the real impacts of the use of drifting FADs on pelagic marine ecosystems?[END_REF][START_REF] Filmalter | Looking behind the curtain: quantifying massive shark mortality in fish aggregating devices[END_REF]. A different machine learning approach applied to video data obtained from autonomous cameras attached to DFADs could be more appropriate for detecting shark species.

Echosounder buoys initially developed as fishing tools represent an unprecedented and massive source of information for characterizing patterns in pelagic fish occurrence [START_REF] Moreno | Fish aggregating devices (FADs) as scientific platforms[END_REF]), but challenges remain for their utilization in direct fisheries management applications. Despite the large amounts of echosounder buoy data, matches with actual catches are limited (as shown by our modest learning datasets). Expanded coverage of observer programs and better reporting of buoy identifiers would help increase the size of learning datasets in the future. The potential for deriving accurate estimates of fish biomass from the current echosounder buoys is also limited, as illustrated by the poor performance of RFs for quantifying tuna biomass [START_REF] Baidai | Machine learning for characterizing tropical tuna aggregations under drifting fish aggregating devices (FADs) from commercial echosounder buoys data Yannick Baidai[END_REF]. Finally, the unique sampling frequency of the echosounder buoys does not appear as the best technological approach to differentiate species. Nevertheless, our machine learning approach is applicable to any echosounder buoy type, including multi-frequency buoys that have revealed helpful for refining species differentiation [START_REF] Moreno | Towards acoustic discrimination of tropical tuna associated with Fish Aggregating Devices[END_REF].

In conclusion, machine learning applied to massive data collected through fishers' buoys offers promise for assessing bycatch risk at DFADs and could help designing spatio-temporal measures for the reduction of bycatch in TTPSF. Implemented in real-time, such algorithms have the potential to help fishers avoid bycatch at DFADs by providing them with information prior to the fishing sets, paving the way for more sustainable fishing practices. Given the magnitude and extensive distribution of TTPSF worldwide, this novel approach could contribute to reduce the impact of fishing on pelagic marine ecosystems.