Patrick Balaguer
email: patrick.balaguer@icm.unicancer.fr

Vanessa Delfosse

William Bourguet
email: william.bourguet@cbs.cnrs.fr

Angel Nadal

Juliette Legler

Vincent Laudet

Mechanisms of endocrine disruption through nuclear receptors and related pathways

Keywords: nuclear receptors, ; dioxin receptor, ; endocrine-disrupting chemicals nuclear receptors, dioxin receptor, endocrine-disrupting chemicals

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Introduction

Endocrine-disrupting chemicals (EDCs) are exogenous substances that interfere with the function of hormonal systems and produce a range of developmental, reproductive, neurological, immune or metabolic diseases in humans and wildlife [START_REF] Zoeller | A path forward in the debate over health impacts of endocrine disrupting chemicals[END_REF][START_REF] Gore | EDC-2: The Endocrine Society's Second Scientific Statement on Endocrine-Disrupting Chemicals[END_REF][START_REF] Schug | Endocrine disrupting chemicals and disease susceptibility[END_REF]. Many EDCs are man-made chemicals produced by industry and released into the environment, but some naturally occurring EDCs can also be found in plants or fungi. The group of molecules acting as EDCs is highly heterogeneous and comprises compounds that are often distantly related to endogenous ligands in terms of size or chemical structure. This group contains substances as chemically different as bisphenols, phthalates, parabens, dioxins, alkylphenols, organotins, polychlorinated biphenyls, perfluoroalkyls, or benzophenones, as well as natural compounds such as the phytoestrogens genistein, daidzein or the mycoestrogen zearalenone. Since humans and wildlife are simultaneously and chronically exposed to low doses of multiple contaminants, understanding the molecular mechanisms underlying the physiological consequences of exposure to environmentally relevant concentrations of EDCs is a major challenge [START_REF] Kundakovic | Sex-specific epigenetic disruption and behavioral changes following low-dose in utero bisphenol A exposure[END_REF]. EDCs can affect the endocrine systems of an organism in a wide variety of ways. These include mimicking natural hormones, antagonizing their action or modifying their synthesis, metabolism and transport. As of today, most of the reported harmful effects of EDCs are attributed to their interaction with nuclear or extranuclear receptors that respectively function as transcriptional regulators in the nucleus such as the members of the nuclear receptors (NRs) superfamily [START_REF] Giulivo | Human exposure to endocrine disrupting compounds: Their role in reproductive systems, metabolic syndrome and breast cancer. A review[END_REF][START_REF] Delfosse | A structural perspective on nuclear receptors as targets of environmental compounds[END_REF] and the aryl hydrocarbon receptor (AhR) [START_REF] Nebert | Aryl hydrocarbon receptor (AHR): "pioneer member" of the basichelix/loop/helix per-Arnt-sim (bHLH/PAS) family of "sensors" of foreign and endogenous signals[END_REF], or mediate rapid non-genomic responses, for instance, the membrane-associated nuclear receptors (mbNRs) [START_REF] Levin | Nuclear receptors outside the nucleus: extranuclear signalling by steroid receptors[END_REF] and the G protein-coupled receptor (GPCR) GPR30/GPER [START_REF] Prossnitz | International Union of Basic and Clinical Pharmacology. XCVII. G Protein-Coupled Estrogen Receptor and Its Pharmacologic Modulators[END_REF]. Herein, we review the main structural and molecular mechanisms used by EDCs to alter these signaling pathways and contribute to the etiology of several diseases.

Nuclear receptors are primary targets of EDCs

The 48 human NRs control a plethora of biological processes such as development, organ homeostasis, metabolism, immune function, or reproduction [START_REF] Germain | Overview of nomenclature of nuclear receptors[END_REF][START_REF] Lazar | Maturing of the nuclear receptor family[END_REF]. As a consequence, inappropriate exposure to EDCs, can cause proliferative reproductive and metabolic disorders, including hormonal cancers, infertility and obesity. Most of the studies on EDCs have originally focused on NRs involved in reproductive processes, in particular the estrogen (ER and ER) and the androgen (AR) receptors. However, mounting data reveal that most NRs are potential targets of EDCs. Among NRs, endogenous ligands have been identified for 24 family members. These receptors are ligand-dependent transcription factors that respond directly to a large variety of hormonal and metabolic substances that are hydrophobic, lipid soluble, and of small size (e.g. retinoic acid or estradiol). The other class of NRs is the group of so-called orphan receptors, for which regulatory ligands are still unknown or may not exist.

The transcriptional activity of orphan receptors is thus regulated by post-translational modifications or cell-specific expression of coregulatory proteins, and eventually by pharmacological or environmental chemicals, as for instance the estrogen related receptor γ (ERRγ) which has no endogenous ligand but is one of the main targets of bisphenol-A (BPA) [START_REF] Tohme | Estrogen-related receptor gamma is an in vivo receptor of bisphenol A[END_REF]. All NR proteins exhibit a characteristic modular structure that consists of five domains (Fig. 1) [START_REF] Weikum | The nuclear receptor superfamily: A structural perspective[END_REF]. The DNA-binding domain (DBD) is the most highly conserved domain and encodes two zinc finger modules. The ligand binding domain (LBD) is less conserved and mediates ligand binding, dimerization, and hosts a ligand-dependent transactivation function, termed AF-2 which corresponds to transcriptional coregulator interaction surfaces that are modulated by ligands. The remaining domains are the N-terminal region containing a celland promoter specific transactivation function termed AF-1, the central hinge region linking the DBD and LBD, and the C-terminal region that is not present in all receptors and whose function is poorly understood.

Genomic actions of nuclear receptors

NRs may act either as repressors or activators of gene transcription depending on their ligandbinding status that in turn determines the ability of DNA-bound receptors to recruit coregulators to target gene promoters (Fig. 2). Coactivators and corepressors are large groups of proteins with a varied range of activities and enzymatic functions that contribute to transcription regulation by NRs and many other transcription factors, including AhR.

Coactivators contribute to the enhancement of transcription by acetylating histones, a process that plays an important role in the opening of chromatin during transcription activation, whereas corepressors display the opposite activity by recruiting histone deacetylases (HDACs). Coactivator recruitment is usually ligand-dependent, whereas corepressors interact in most cases with unliganded receptors. In the absence of the cognate ligand, some NRs are located in the nucleus, bind to the DNA response elements of their target genes, and recruit corepressors, while others are located in the cytoplasm in an inactive complex with chaperones (Fig. 2). Ligand binding induces major structural alterations of the receptor LBDs leading to (i) destabilization of corepressor or chaperone interfaces, (ii) exposure of nuclear localization signals to allow nuclear translocation and DNA binding of cytoplasmic receptors, and (iii) recruitment of coactivators triggering gene transcription through chromatin remodelling and activation of the general transcription machinery.

A structural view of the interaction between nuclear receptors and EDCs

The LBD of NRs is composed of a conserved core of 12 -helices (H1 to H12) and a short two-stranded antiparallel -sheet (s1 and s2), arranged into a three-layered sandwich fold (Fig. 3A). This arrangement generates a mostly hydrophobic cavity, referred to as the ligandbinding pocket (LBP), which can accommodate the cognate ligand. In hormone-bound LBD structures, the LBP is sealed by helix H12, thus generating a hydrophobic binding groove for short LxxLL helical motifs (L stands for leucine and x for any amino acid) found within coactivators. Biochemical and cell-based assays have revealed that EDCs bind to NRs with affinities ranging from sub-nanomolar to high micromolar values and structural analyses have revealed some mechanisms by which compounds structurally and chemically unrelated to physiological ligands can bind to NRs at environmentally relevant concentrations [START_REF] Le Maire | Activation of RXR-PPAR heterodimers by organotin environmental endocrine disruptors[END_REF][START_REF] Delfosse | Structural and mechanistic insights into bisphenols action provide guidelines for risk assessment and discovery of bisphenol A substitutes[END_REF][START_REF] Riu | Peroxisome proliferator-activated receptor gamma is a PPARgamma Partial Agonist 2-Chloro-N-(3-chloro-4-((5-chlorobenzo[d]thiazol-2yl)thio)phenyl)-4-(trifluorome thyl)benzenesulfonamide (T2384) to Orthosteric and Allosteric Sites with NMR Spectroscopy[END_REF].

Representative examples are the binding of -zearalanol (α-ZA) to ER, the covalent interaction of various chemicals with the retinoid X receptor (RXR), the peroxisome proliferator-activated receptor γ (PPARγ) and the xenobiotic receptor PXR, or the cooperative binding of two chemicals to PXR and PPARγ. Even though the mycoestrogen α-ZA (Fig. 1) is not a steroidal compound, it recapitulates the key interaction networks observed between the residues of the ER LBP and the endogenous hormone 17-estradiol E 2 (Fig. 3B). As such, α-ZA appears as an E 2 mimic that binds to its target receptor at sub-nanomolar concentrations [17]. In contrast, compounds of the organotin family such as the tributyltin (TBT, Fig. 1) bind with much avidity to many NRs through a mechanism that is totally different from those used by the natural or pharmacological ligands of these receptors. Indeed, the nanomolar affinity of organotins for NRs arises from the formation of a strong covalent bond formed between the tin atom of the chemical and the sulfur atom of a cysteine residue contained in the LBP of the receptors [START_REF] Le Maire | Activation of RXR-PPAR heterodimers by organotin environmental endocrine disruptors[END_REF] (Fig. 3C). Beside tin compounds, many bioactive chemicals such as pesticides or drugs contain chemical groups that are prone to forming such covalent links with reactive cysteine residues, thereby insuring high affinity binding of the compounds. Structural studies have revealed that the insecticide fipronil and the herbicide pretilachlor bind to and activate PXR via this mechanism (our unpublished data). It is thus very likely that part of the low dose effects of a number of environmental compounds can be explained by their covalent interaction with the dozen NRs containing a cysteine residue in their LBP. Compared to binding sites located at the surface of proteins, the buried and mostly hydrophobic cavity provided by NRs probably offers an environment allowing a residence time long-enough to let the chemical reaction to occur. Finally, recent studies have shown that NR LBPs are more conformable than previously thought and can eventually accommodate several compounds simultaneously [18][19][20][21][22]. In some instances it has been shown that the compounds not only bind concomitantly to the receptor, but they do so cooperatively, i.e. the binding of one molecule promotes high affinity binding of the second, with synergistic effects on receptor function. Notably, the contraceptive 17α-ethinylestradiol (EE2, Fig. 1) and the persistent organochlorine pesticide trans-nonachlor (TNC, Fig. 1), both exhibiting low affinity and efficacy when studied separately, where shown to bind and activate the receptor PXR at much lower concentration when used in combination [20] (Fig. 3D).

Non-genomic actions of nuclear receptors

Beside their interference with the genomic pathways of NRs, EDCs have also been shown to interact with the membrane-associated fraction of these receptors (Fig. 2). Indeed, it is now well accepted that a small amount of NRs (a few percent) are positioned at the membrane (mbNRs) as previously shown for ER and , and for many other NRs such as the progesterone, the androgen, the thyroid hormone or the vitamin D receptors [START_REF] Anyetei-Anum | Thyroid hormone receptor localization in target tissues[END_REF][START_REF] Boonyaratanakornkit | Extranuclear signaling by sex steroid receptors and clinical implications in breast cancer[END_REF][START_REF] Trochoutsou | Vitamin-D in the Immune System: Genomic and Non-Genomic Actions[END_REF][START_REF] Rosenfeld | Endocrine disruption through membrane estrogen receptors and novel pathways leading to rapid toxicological and epigenetic effects[END_REF]. As for ER, the receptor is directed to the plasma membrane/caveloae via palmytoylation of an internal cysteine residue (C447) that is located in the LBD. Once localized in caveolae rafts, ligand-bound mbER is depalmytoylated and interacts with and activates various G and G/γ proteins within seconds, thereby triggering a cascade of signal transduction including cAMP production, calcium mobilization, ion channel activation, endothelial nitric oxide synthase and multiple kinases (ERK and PI3K) activation [START_REF] Levin | Extranuclear steroid receptors are essential for steroid hormone actions[END_REF]. It is interesting to note that mice expressing ER mutated in this cysteine 447 (cysteine 451 in mice) are sterile (both males and females) and present differences in E 2 vascular actions, such as abrogation of endothelial repair and eNOS phosphorylation. In contrast, other responses like endometrial proliferation are similar to will-type mice [START_REF] Arnal | Membrane and Nuclear Estrogen Receptor Alpha Actions: From Tissue Specificity to Medical Implications[END_REF]. These membrane-localized ERs are thought to mediate the rapid non genomic effects of natural (E 2 ) or environmental estrogens (BPA or alkylphenols) outside the nucleus [START_REF] Arnal | Membrane and Nuclear Estrogen Receptor Alpha Actions: From Tissue Specificity to Medical Implications[END_REF]29]. Because the membrane-associated receptors are often the same proteins as their nuclear counterparts, one can make the assumption that compounds bind to the two receptor forms with the same mechanisms and thus similar binding affinities. However, it is not excluded that the membrane environment modifies the thermodynamics of the interactions with an impact on the ligand-binding properties of the receptor. Furthermore, it has been postulated that, in contrast to the nuclear pathway requiring ER-ligand complexes of sufficient lifetime to induce a long series of molecular events including dissociation from heat shock proteins, translocation, dimerization and DNA binding, recruitment of coregulators, alteration of chromatin architecture and finally transcription initiation, the extranuclear signalling pathway involving the rapid triggering of kinase cascades could be activated by ER-ligand complexes with shorter half-life [30]. In this context, one can note that the low binding affinity constant (Kd) of compounds such as bisphenols and alkylphenols generally results from a high dissociation rate constant (Koff) so that their complexes with ER feature short lifetimes [31]. Although this hypothesis needs further investigations, it could explain that EDCs with about 10,000-fold less affinity than E 2 for ERs can activate the extranuclear-initiated signaling pathway preferentially over the nuclear pathway.

The aryl hydrocarbon receptor

AhR structure and function

The Aryl hydrocarbon Receptor (AhR), also known as the dioxin receptor, is a liganddependent transcription factor belonging to the basic helix-loop-helix (bHLH) PER-ARNT-SIM (PAS) protein family that binds to DNA following formation of a heterodimer with the AhR-nuclear translocator protein (ARNT) [32,[START_REF] Nebert | Aryl hydrocarbon receptor (AHR): "pioneer member" of the basichelix/loop/helix per-Arnt-sim (bHLH/PAS) family of "sensors" of foreign and endogenous signals[END_REF]. Although not members of the NR family, AhR and ARNT display structural and functional similarities with NRs such as a molecular organisation in four major domains including a DBD and LBD, or a transcriptional activity that is regulated by the presence of ligands and coregulators (Fig. 1). The N-terminal bHLH domain is involved in DNA recognition. The PAS domain exists as a tandem of two domains, PAS-A and PAS-B, respectively, each encompassing around 50 amino acids. The bHLH and PAS-A domains of both AhR and ARNT dimerize to form a stable DNA-bound heterodimer.

In AhR, the PAS-B domain is responsible for ligand binding. The C-terminal part of the protein also includes a transcriptional activation domain (TAD). Several multi-domain crystal structures of AhR-ARNT heterodimers have been recently reported providing insights onto the modes of DNA binding and dimerization of the complex [33,34]. These structures are characterized by sophisticated domain interplay and reveal a highly intertwined architecture that bind to DNA via the positively charged residues of the bHLH domains. None of the structures reported yet contain the PAS-B region of AhR so that the detailed mechanisms of ligand-binding and protein activation remain largely elusive. However, together with the extended interdomain interfaces, the high structural dynamics of the AhR PAS-A domain suggest an allosteric communication route to mediate ligand-induced changes in the PAS-B domain to the DNA-binding bHLH domains, the C-terminal TAD or the nuclear localization sequence (NLS). AhR binds a selection of different endogenous ligands including tryptophanderived metabolites and several dietary indoles, and is involved in many cellular processes including cell proliferation and differentiation, immune response, inflammation and circadian rhythm regulation [START_REF] Nebert | Aryl hydrocarbon receptor (AHR): "pioneer member" of the basichelix/loop/helix per-Arnt-sim (bHLH/PAS) family of "sensors" of foreign and endogenous signals[END_REF]. While AhR also functions as a sensor of exogenous chemicals and promotes metabolic clearance through the induction of metabolizing enzymes such as CYP1A1 and CYP1B1 upon activation by external compounds, it is known to mediate most of the toxic effects of a range of environmental contaminants such as polyaromatic hydrocarbons (PAHs) and dioxins. These toxic effects are numerous and include teratogenicity, immunosuppression, metabolic and endocrine disruption, skin toxicity and cancer. In the absence of ligand, AhR resides in the cytosolic compartment of the cell bound to a molecular chaperone complex containing Hsp90 and XAP2 (Fig. 2). Upon ligand binding AhR translocates from the cytosol to the cell nucleus where it forms a heterodimer with ARNT. The AhR-ARNT complex recognizes specific sequences of DNA called xenobiotic responsive element (XRE) in the promoter region of the target genes and activates transcription of these genes via the recruitment of transcriptional coactivators. The activity of the AhR-ARNT complex is negatively modulated by proteasomal degradation and the AhR repressor (AhRR) that interacts with ARNT and forms an AhRR-ARNT heterocomplex down regulating AhR signalling. In addition to its direct interaction with target gene promoters, AhR accomplishes some of its regulatory functions by modulating the activity of other transcriptions factors including ERs, AR, and many others [START_REF] Ohtake | Cross-talk of dioxin and estrogen receptor signals through the ubiquitin system[END_REF]. The liganded AhR-ARNT heterodimer modulates estrogen and androgen signaling positively by physically associating with unliganded ERs and AR and bringing transcriptional coactivators to the promoters of these receptors [START_REF] Ohtake | Modulation of oestrogen receptor signalling by association with the activated dioxin receptor[END_REF]. In contrast, in presence of estrogens and androgens, the liganded AhR-ARNT represses estrogen and androgen mediated transcription by targeting ERs and AR to the Cul4B-based ubiquitin ligase complex for proteosomal degradation [START_REF] Ohtake | Dioxin receptor is a liganddependent E3 ubiquitin ligase[END_REF]. Thus it appears that AhR acts both as a transcription factor and as an ubiquitin ligase component to mediate different signaling pathways [START_REF] Ohtake | Cross-talk of dioxin and estrogen receptor signals through the ubiquitin system[END_REF].

AhR ligands and ligand binding

Although AhR was originally discovered as a primary target of the toxic dioxin (2,3,7,8tetrachloro-dibenzo-p-dioxin, TCDD, Fig. 1), it is now recognized that AhR is able to respond to hundreds of chemically diverse endogenous, dietary and environmental compounds, a number of these compounds interacting with the receptor at (sub)nanomolar concentrations [START_REF] Denison | And Now for Something Completely Different: Diversity in Ligand-Dependent Activation of Ah Receptor Responses[END_REF]. AhR ligands include polychlorinated dibenzo-p-dioxins, dibenzofurans (Fig. 1), polychlorinated biphenyls (e.g. PCB126, Fig. 1), polycyclic aromatic hydrocarbons (PAHs) as benzo(a)pyrene (BaP) and related PAHs compounds, including 3-methylcholanthrene (3MC) and -naphtoflavone. Dietary compounds (3,3'diindoylmethane and indolo(3,2)carbazole) and endogenous metabolites, such as indirubin and 6-formyindolo(3,2)carbazole (FICZ, Fig. 1) are also known to act as AhR ligands. In addition to their high affinity, some AhR ligands such as dioxins are very resistant to metabolism, which appears to confer a greater toxicity when compared to that of compounds such as BAP or 3MC which are rapidly metabolized by CYP1A1 [START_REF] Denison | And Now for Something Completely Different: Diversity in Ligand-Dependent Activation of Ah Receptor Responses[END_REF]. In contrast, the mechanism of carcinogenicity of some PAHs includes the production of highly reactive genotoxic metabolites. While no structure of the AhR LBD has been reported yet, molecular modelling using the structures of closely related PAS domains has suggested some molecular features accounting for its ligand-binding promiscuity and specificity [START_REF] Bonati | Molecular modeling of the AhR structure and interactions can shed light on ligand-dependent activation and transformation mechanisms[END_REF]. In particular, mutational analysis, molecular modelling and molecular dynamics simulations have identified residues that control ligand preferences and the high dynamics of some structural elements rendering the AhR PAS-B domain malleable [START_REF] Pandini | Detection of the TCDD binding-fingerprint within the Ah receptor ligand binding domain by structurally driven mutagenesis and functional analysis[END_REF][START_REF] Xing | Identification of the Ah-receptor structural determinants for ligand preferences[END_REF][START_REF] Nuti | Ligand binding and functional selectivity of L-tryptophan metabolites at the mouse aryl hydrocarbon receptor (mAhR)[END_REF][START_REF] Fraccalvieri | Comparative analysis of homology models of the AH receptor ligand binding domain: verification of structure-function predictions by site-directed mutagenesis of a nonfunctional receptor[END_REF][START_REF] Pandini | Structural and functional characterization of the aryl hydrocarbon receptor ligand binding domain by homology modeling and mutational analysis[END_REF].

Interestingly, flexibility of some regions of the LBD is also a characteristic feature of the NR PXR which is another major chemical sensor known to induce the expression of detoxification proteins such as metabolizing enzymes and transporters upon activation by a broad range of chemicals [START_REF] Mackowiak | Mechanisms of xenobiotic receptor activation: Direct vs. indirect[END_REF]. PXR contains several loops clustering at the bottom of the LBD that confer a high plasticity allowing the ligand binding pocket of the receptor to adopt different shapes according to the bound ligands. Three of these flexible elements are found in a PXR-specific sequence of approximately 60 residues inserted between helices H1 and H3 that display high thermal B factors (indicating structural mobility) or are completely disordered as observed in the crystal structures. However, a striking difference between the two receptors is that AhR is recognized by a number of high affinity ligands like TCDD or FICZ (with nanomolar affinities), whereas PXR is essentially bound by compounds with affinities in the micromolar to sub-micromolar range [START_REF] Denison | And Now for Something Completely Different: Diversity in Ligand-Dependent Activation of Ah Receptor Responses[END_REF]. One potential explanation for this difference may reside in the size of the binding cavity of the two receptors. Indeed, while PXR displays the largest binding pocket among all NRs with experimentally-determined volumes ranging from 1280 to 1600 Å 3 depending on the bound compound, homology modelling of the PAS-B domain of AhR suggests a volume of the binding pocket in the range 300-400 Å 3 [START_REF] Perkins | A Structural Switch between Agonist and Antagonist Bound Conformations for a Ligand-Optimized Model of the Human Aryl Hydrocarbon Receptor Ligand Binding Domain[END_REF]. As a consequence, ligands generally occupy only a small fraction of the PXR binding pocket so that compounds appear to interact loosely with the residues lining the cavity, whereas the smaller pocket size of AhR may result in tighter contacts and a more stable ligand-bound complex. Another difference between the two proteins is that AhR is more easily antagonized than PXR. Indeed, a number of potent AhR antagonists have been discovered a while ago [START_REF] Kim | Novel compound 2-methyl-2H-pyrazole-3-carboxylic acid (2methyl-4-o-tolylazo-phenyl)-amide (CH-223191) prevents 2,3,7,8-TCDD-induced toxicity by antagonizing the aryl hydrocarbon receptor[END_REF][START_REF] Smith | Identification of a high-affinity ligand that exhibits complete aryl hydrocarbon receptor antagonism[END_REF][START_REF] Parks | In silico identification of an aryl hydrocarbon receptor antagonist with biological activity in vitro and in vivo[END_REF], whereas the first PXR antagonist has been reported only very recently [START_REF] Lin | SPA70 is a potent antagonist of human pregnane X receptor[END_REF][START_REF] Lin | Using TR-FRET to Investigate Protein-Protein Interactions: A Case Study of PXR-Coregulator Interaction[END_REF]. This observation is consistent with a smaller and more constrained binding pocket in AhR.

G protein-coupled receptor 30

The G protein-coupled receptor 30 (GPR30) also referred to as G protein-coupled estrogen receptor (GPER) was also proposed to act as a non-classical estrogen receptor localized at the plasma membrane or the endoplasmic reticulum [START_REF] Revankar | A transmembrane intracellular estrogen receptor mediates rapid cell signaling[END_REF][START_REF] Thomas | Identity of an estrogen membrane receptor coupled to a G protein in human breast cancer cells[END_REF]. Originally, GPR30 was identified as an orphan receptor belonging to the family of 7-transmembrane-spanning GPCRs. Later on, several studies reported the activation of GPR30 by natural, environmental and pharmaceutical estrogens and antiestrogens (for a review see [START_REF] Barton | Twenty years of the G protein-coupled estrogen receptor GPER: Historical and personal perspectives[END_REF]), leading to its designation as GPER. However contradictory results concerning the ability of this receptor to bind estrogens have been reported. Binding of E 2 and several xenoestrogens to GPR30 was observed by some laboratories [START_REF] Thomas | Identity of an estrogen membrane receptor coupled to a G protein in human breast cancer cells[END_REF] whereas others failed to detect any interaction [START_REF] Pedram | Nature of functional estrogen receptors at the plasma membrane[END_REF][START_REF] Otto | G protein-coupled receptor 30 localizes to the endoplasmic reticulum and is not activated by estradiol[END_REF].

Finally, the transgenic KO for GPR30 do not display phenotypes that result from estrogen depletion suggesting that GPR30 is not a direct mediator of estrogen effects but could be rather a collaborator in non-nuclear functions of the nuclear ER [START_REF] Levin | Plasma membrane estrogen receptors[END_REF][START_REF] Romano | Crosstalk between nuclear and G protein-coupled estrogen receptors[END_REF]. Several selective GPR30 agonists and antagonists have been recently identified which will probably help characterizing the role GPR30 in these toxic effects in the future [START_REF] Prossnitz | International Union of Basic and Clinical Pharmacology. XCVII. G Protein-Coupled Estrogen Receptor and Its Pharmacologic Modulators[END_REF].

Figure captions

Fig. 1 .

 1 Fig. 1. Nuclear receptors, AhR and GPR30 are the main known targets of endocrine disruptors. Structural organisation of proteins, and chemical structures of the associated EDCs mentioned in this review (EE2 = ethinylestradiol; TNC = trans-nonachlor; TBT = tributyltin; TCDD = 2,3,7,8-tetrachloro-dibenzo-p-dioxin; PCB-126 = polychlorinated biphenyl 126; FICZ = 6-formyindolo(3,2)carbazole).

Fig. 2 .

 2 Fig. 2. EDCs targeted cellular pathways. 1 The genomic pathways of nuclear receptors (NRs) and AhR, 2 the extranuclear signalling pathway of membrane-bound NRs (mbNR), and 3 the G protein-coupled receptor 30 (GPER/GPR30) pathway.

Fig. 3 .

 3 Fig. 3. Different binding modes of EDCs observed with NRs. A. Conserved 3D-structure of the ligand binding domain of nuclear receptors (here, ERα in complex with estradiol, PDB id = 3UUD). Close up view of the ligand binding pockets of B. ERα in complex with α-zearalanol (PDB id = 4MG8), C. RXR in complex with TBT (PDB id = 3E94), and D. PXR in complex with EE2 and TNC (PDB id = 4X1G).

Acknowledgements:

We would like to acknowledge the financial support from the Plan Cancer Inserm (projects SYNERPXR 2 and CONTERREC) and the ANSES, (projects EVALPE and XENOMIX).

Competing financial interests:

The authors declare no competing financial interests.


Mamiko Sasao
email: msasao@mail.doshisha.ac.jp

Roba Moussaoui

Dmitry Kogut

James Ellis

Gilles Cartry

Motoi Wada

Katsuyoshi Tsumori

Hideo Hosono

Negative hydrogen ion production from a nanoporous 12CaO・ 7Al2O3 (C12A7) electride surface

A high production rate of negative hydrogen ion was observed from a nanoporous C12A7 electride surface immersed in hydrogen/deuterium low-pressure plasmas. The target was biased at 10 -170 V negatively and the target surface was bombarded by H3 + ions from the plasma. The production rate was 1-2 orders higher than a clean molybdenum surface.

The measured H -energy spectrum indicates that the major production mechanism is desorption by sputtering. This material has potential to be used as production surface of cesium-free negative ion sources for accelerators, heating beams in nuclear fusion, and surface modification for industrial applications.

Large-scale negative ion beams of hydrogen isotopes have been intensively developed as plasma heating and current-drive tools in nuclear fusion projects 1), 2) . Medium-size negative ion beams are widely used nowadays as injectors for particle accelerators, such as those of J-PARC, CERN, SNS-Oak Ridge, China Spallation Neutron Source (CSNS), Los Alamos Neutron Science Center (LANSCE)/PFR, ISIS Spallation Neutron and Muon Facility, and so on [START_REF] Alexander | Accelerators for High Intensity Beams[END_REF] . Small-size negative ion sources are now under development for the application to accelerators in medical area [START_REF] Etoh | DEVELOPMENT OF A HIGH CURRENT NEGATIVE ION SOURCE FOR MEDICAL CYCLOTRONS[END_REF] . Negative ion sources have recently received attention due to their application in microelectronics areas, such as, proton implantation for surface modification, or smart-ion-beam cut of wafers 5), [START_REF] Ahmed | Proton implantation for effective electrical isolation of InP, InGaAs and GaAs: Role of variable doses and implant temperature[END_REF] , because the charge-up problem of positive ion injection can be avoided.

It is known that H -ions can be produced in a plasma volume [START_REF] Bacal | [END_REF] , and on a low-work-function surface covered by a half or less monolayer of alkali metals 8), [START_REF] Padama | [END_REF] . In most of large-or mediumsize ion sources, cesium vapor is introduced not only for an efficient H -surface production but also for the remarkable reduction of co-extracted electron current. However, it has many disadvantages, such as limited life time of the coverage, cesium leakage. Cesium contamination on surfaces to be treated, and surroundings is a fatal drawback for application to microelectronics. Research is currently being carried out in order to develop cesium-free negative-ion sources. Alternative materials, such as carbon materials, specially highly oriented pyrolitic graphite (HOPG) or diamond, are studied to enhance the negative ion production on a plasma grid of an ion sources 10), 11) .

In 2003 Hosono and his coworkers have found that a refractory oxide 12CaO.7Al2O3 (C12A7) can be transformed to an electride of low work function 12), 13), 14) , by exchanging of clathrated oxygen ions as the counter anion from the positively charged crystallographic cages of C12A7 leading to formations of high-density electrons in the cages. When 100% of clathrated oxygens were removed, it showed conductivity approximately 1000 siemens per centimeter at 300 K, demonstrating that the encaged electron behaves as an anion 15) . They reported that the resulting [Ca24Al28O64] 4+ (4e-) may be regarded as an "electride", and clarified the unique properties,i.e., they have a very low work function of 2.4 eV, which is comparable to that of metal potassium, but chemically and thermally stable. Figure 1 shows the schematic energy diagram of C12A7 electride. In our previous work, H -formation from a sample of C12A7 electride, was indirectly shown by exposing the sample to an atomic hydrogen (H 0 ) flux and detecting the negative current generated on it 16) . The current observed was almost similar level with that obtained from a low-work-function bi-alkali covered molybdenum surface (~2.3 eV) in the same condition. In the present work, direct measurement of H -formation was carried out by an experimental apparatus in Aix-Marseille University. It consists of an upper plasma source chamber and a lower spherical diffusion chamber. The plasma was initiated by a Huttinger PFG 1600 RF generator followed by a Huttinger matchbox. A sample, which was able to be retrieved into a separate vacuum chamber for change, was fixed on a rotatable target holder and inserted into the center of the lower diffusion chamber. The temperature of the target holder and the target itself was controllable from room temperature up to 600 C, with heating arrangement. An ECR plasma source was also equipped, and a plasma could be injected in the lower chamber towards the target. The target was biased negatively against the chamber. Fig. 2 shows the electrical potential profile between the target sample holder and the mass spectrometer. Due to the electrical potential drop, e(Vp -Vs) in front of the target sample, positive ions were accelerated and bombarded the surface. Here Vp and Vs denote the plasma potential and the bias voltage on the target sample, respectively. Most of ions were injected into the sample or near the surface, but some them were reflected on it. However due to the potential rise, only neutral particles, reflected negative ions and particles sputtered out as negative ions could escape from the surface. Negative ions were accelerated by e(Vp -Vs) and reached the sheath region in front of the grounded entrance electrodes of the mass spectrometer, and decelerated by e(Vp). Consequently, the total energy gain of negative ions was -eVs. In the present experiment, negative ions were energy analyzed by a Hiden EQP300 mass spectrometer equipped with an energy filter. 17) The aperture plate of it was placed 36 mm apart from the target surface, with the center of sample located on the axis of the spectrometer. Details on the experimental set-up and experimental conditions are given in the reference [START_REF] Wada | Proc. 3rd Int. Symp. Production and Neutralization of Negative Ions and Beams[END_REF] .

The measurement shown here were made at 2 Pa hydrogen or deuterium gas pressure fixed, from 20 to 250 W injected power for RF plasma conditions, and 1 Pa 60 W injected power for ECR conditions. In all plasmas the dominant ion species was H3 + . The target was kept at room temperature during the measurement. Plasma parameters were measured by a Langmuir probe in a separate experiment under the same condition. Typical values were ranging in Te ~ 1 eV, ne ~ 10 9 /cm 3 for the ECR operation, and Te ~ 3 eV, ne ~ 10 8 /cm 3 for the RF operation when excitation of coils for vertical magnetic field was turned off in order to avoid the interference with the spectrometer. Plasma potential, Vp, was about 8 V for both cases. Major negative ion impurities were OH -and H -. During the present experiment, the spectra of these impurities were measured occasionally and their peak values were about 3 % and 0.2 % of that of H -, respectively.

The negative ion energy distribution function (NIDEF) shown in FIG. 3a and FIG. 3b were measured by the energy-analyzed mass spectrometer from C12A7 electride (a) and a molybdenum target (b) with D2 plasmas of RF of 250 W. Imprity negative ions the vertical axis is counts per second detected by the mass spectrometer, and horizontal axis is the negative ion energy after subtraction of energy gain by the target bias voltage, so that it corresponds to the initial energy emitted from the target. Two lines shown in the figures are spectra with the target voltage of -20 V (red) and -80 V(black). The target was placed normal to the spectrometer axis, and most of particles detected were emitted almost normally. The effects of angular distribution of ions from a target, their trajectories, and collection probability by the spectrometer on the measured spectra were studied by simulations and discussed in the references 10,11 . A large peak in the low energy region less than 10 eV was seen only in the C12A7 electride spectra. It has been known that low energy negative hydrogen ions are produced through the volume production, where vibrational excited H2 (X,ν) molecules are dissociated into H -and H 0 in conjunction with electron attachment 19) . It was found that some metallic surface revealed an enhancing effect on highly vibrationally excited hydrogen molecules H2(X,ν) in gas phase experiments [START_REF] Sasao | Negative ion formation from a low-work-function nanoporous inorganic electride surface[END_REF] . However, the present potential profile shown in FIG. 2 FIG. 2 Electrical potential profile between the sample holder and the mass spectrometer EQP 300, when the target sample was biased at -20 V. Horizontal axis is not scaled.

In order to confirm that the negative ions from the C12A7 electride was produced by desorption in which implanted H/D particles were sputtered out, two measurement were carried out. In the first experiment, energy spectra of hydrogen negative ions from the C12A7 electride bombarded by hydrogen and by argon ions were compared as shown in FIG. 3 In both measurement, the target was pre-treated in the same procedure with an exposure to hydrogen ECR plasma (1 Pa H2, 60 W) at Vs= -130 V for 10 min. Then, hydrogen plasma at 1 Pa, 60 W, Vs = -60 V or argon plasma at 0.1 PA, 30 W, Vs = -60 V were switched on and negative-ion spectrum were recorded. It turned out that the dominant peak shown in the low energy region below 10 eV was those due to the sputtering of pre-implanted hydrogen particles. only by a factor 1.7 instead of 11.7. It clearly shows that hydrogenation of the material and negative-ion creation through sputtering is explaining the low-energy part of the spectrum.

In these experiment, high negative hydrogen ion (H -) production rate from a C12A7 electride target surface was observed, and there were negative ions produced through (1) the charge exchange (electron pick-up) reflection process and (2) the desorption process by sputtering [START_REF] Wada | Proc. 3rd Int. Symp. Production and Neutralization of Negative Ions and Beams[END_REF] . The latter comportment was remarkably high compared with those from molybdenum. It has been known that negative ion production ratio strongly depends on the surface work function in both processes. The high production yield of this material may due to its low work function of 2.4-2.7 eV 16) , but also due to the specific nano-structure of C12A7 electride. When this electride is exposed to hydrogen circumstance, some of the encaged electron are replaced by the hydrogen negative ions. Although the nano-crystal structure is not preserved in the as-cleaved surface, the fractured cages can be easily restored upon heating at appropriate conditions 19) .

In the present work, absolute production rate of negative hydrogen ion (H -) was not obtained. However, electric current corresponding to negative hydrogen ion current observed by the exposure to the C12A7 electride to an atomic hydrogen (H 0 ) flux was almost similar level to that obtained from a low-work-function bi-alkali covered molybdenum surface (~2.3 eV) in our previous indirect measurement [START_REF] Sasao | Negative ion formation from a low-work-function nanoporous inorganic electride surface[END_REF] . The dependence on the atomic hydrogen (H 0 ) power and other characteristics were also similar. Together with the present direct observation of the negative hydrogen ions, it is likely that this material has a potential to produce similar level of negative ions with the cesiated molybdenum surface.

This new material, C12A7 electride is air-stable, mechanically robust and machinable, and has potential to be used as production surface of cesium-free negative ion sources for accelerators, plasma heating beams in nuclear fusion, and surface modification for industrial applications.

FIG. 1 .

 1 FIG. 1. Energy diagram of C12A7 electride. Anionic electrons are accommodated in the sub nanometer-sized cages which are connected with each other. The connected cages form a new conduction band called "cage conduction band" (CCB), below the cage flame

  FIG. 2. Negative ion spectrum from a C12A7 elctride (a) and molybdenum (b) in RF plasma. The red and black lines show those obtained when the target bias was -20 V and -80 V, respectively.

FIG. 3 .FIG. 4 .

 34 FIG. 3. Comparison of normalized negative ion energy spectra measured in an ECR Ar plasma (black) under 0.1 Pa, 30 W, and in an ECR H2 plasma (red) under 1 Pa, 60 W at VS = -60 V after the sample has been treated for 10 minutes in an ECR H2 plasma (1 Pa, 60 W, VS = -130 V).

ACKNOWLEDGMENTS

The C12A7-Electride was supplied from Asahi Glass Co. LTD., and technical support by Naomichi Miyakawa, Satoru Watanabe, and Kazuhiro Ito of Asahi Glass Co. LTD and deep discussion with them are greatly acknowledged. The authors would like to T. Yokoyama for the use of C12A7-Electride. HH acknowledges a fund from JST ACCEL program and JSPS KAKENHI Grant Number JP 17H061253). JE acknowledges a support from the CDT-Fusion and the EPSRC (No. EP/L01663X/1). The experimental set-up at PIIM has been developed thanks to the financial support of the French Research Federation for Fusion Studies (FR-FCM) and of the French Research Agency (ANR) under grant 13-BS09-0017 H INDEX TRIPLED. This work was performed under the collaboration program of National Institute for Fusion Science (NIFS15KBAR011 and NIFS15KLER041).


Maria M Magiera

Puja Singh

Carsten Janke

SnapShot: Functions of Tubulin Posttranslational Modifications

Polyglycylation

E E E E E E E E E E E E E E E E Q G G E E E E E Y E G G G

SnapShot: Functions of Tubulin Posttranslational Modifications

Introduction Microtubules (MTs) are essential components of the eukaryotic cytoskeleton. Both MTs and their molecular building blocks, the α-/β-tubulin dimers, are highly conserved throughout evolution, which stands in strong contrast to the myriad of functions to which MTs can adapt. The tubulin code provides a mechanism whereby modulating MT properties allows them to adapt to specific functions in cells. The tubulin code functions by incorporating different tubulin gene products, or isotypes, into the MT lattice or by installing posttranslational modifications (PTMs) on the tubulin units. Here, we present a view of the current understanding of tubulin PTMs and their biological functions.

Tubulin Posttranslational Modifications

Tubulin can be subjected to a large number of PTMs. Most of them can take place on both α-and β-tubulin, although some are restricted to α-tubulin (e.g., detyrosination). Over the past decade, enzymes catalyzing many PTMs of tubulin have been discovered (reviewed in [START_REF] Janke | The tubulin code: molecular components, readout mechanisms, and functions[END_REF].

Tubulin detyrosination, a modification that, counterintuitively, consists of the enzymatic removal of a functional moiety-the C-terminal tyrosine of α-tubulin-is catalyzed by enzymes from the vasohibin family [START_REF] Aillaud | Vasohibins/SVBP are tubulin carboxypeptidases (TCPs) that regulate neuron differentiation[END_REF][START_REF] Nieuwenhuis | Vasohibins encode tubulin detyrosinating activity[END_REF]. The reverse reaction-re-addition of the tyrosine or re-tyrosination-is catalyzed by tubulin tyrosine ligase (TTL). After detyrosination, cytosolic carboxypeptidases (CCPs) can further remove glutamate residues to generate ∆2-and ∆3-tubulin. Acetylation of α-tubulin takes place on lysine 40, is catalyzed by aTAT1, and is removed by HDAC6 or SIRT2. Polyglutamylation and polyglycylation are catalyzed by enzymes from the tubulin tyrosine ligase-like (TTLL) enzyme family. Polyglutamylases, as well as polyglycylases, show preferences to either α-or β-tubulin, as well as catalytic specificities, to generate either short or long chains of glutamate or glycine residues, respectively. Deglutamylation is catalyzed by enzymes from the CCP family, whereas no deglycylase has been identified so far (reviewed in [START_REF] Janke | The tubulin code: molecular components, readout mechanisms, and functions[END_REF].

Mechanisms of Tubulin Posttranslational Modifications

The location of a modification site on tubulin likely determines the impact of a particular PTM on MT functions. Modifications of the conserved and highly structured tubulin core are expected to alter biophysical properties of the MTs. Indeed, acetylation of lysine 40 has been shown to render MTs more flexible and thus resistant to mechanical stress [START_REF] Portran | Tubulin acetylation protects long-lived microtubules against mechanical ageing[END_REF]. By contrast, modifications localized at the unstructured extreme C-terminal tails of tubulin (gray amino acid chains), which decorate the outer surface of MTs, are likely to differentially regulate the interactions between MTs and specific MAPs. Initial studies have proven this to be the case. Detyrosination, for example, regulates the interaction of a number of motor proteins (e.g., kinesin-1, kinesin-2, CENP-E, kinesin-13, Kif2A) and some plus-end binding (e.g., CLIP170, p150 glued ) proteins with MTs [START_REF] Peris | Tubulin tyrosination is a major factor affecting the recruitment of CAP-Gly proteins at microtubule plus ends[END_REF]. No specific mechanism has been so far proposed for ∆2-and ∆3-tubulin variants. Tubulin polyglutamylation, which adds side chains of negatively charged glutamic acid residues, has also been shown to modulate the behavior of kinesin-1 [START_REF] Sirajuddin | Regulation of microtubule motors by tubulin isotypes and post-translational modifications[END_REF] and the flagellar dynein motor [START_REF] Kubo | Tubulin polyglutamylation regulates axonemal motility by modulating activities of inner-arm dyneins[END_REF] on MTs; however, the most striking effect of this modification is the regulation of the MT-severing enzyme spastin [START_REF] Valenstein | Graded Control of Microtubule Severing by Tubulin Glutamylation[END_REF]. No molecular mechanism controlled by polyglycylation has been uncovered thus far.

Biological Roles of Tubulin Posttranslational Modifications

In the recent years, an increasing number of functional studies have strongly advanced the understanding of the biological roles of tubulin PTMs. Strikingly, it appears that modifications of tubulin are involved in almost every specialized MT function, either as essential determinants or as subtle regulators. Most of the known tubulin modifications play important roles for cilia and flagella, as they specifically modify the MT-based axoneme (reviewed in [START_REF] Wloga | Posttranslational Modifications of Tubulin and Cilia[END_REF]. In neurons, polyglutamylation is important for neuronal survival and the maintenance of synaptic transmission, while detyrosination has been demonstrated to be essential for neuronal development. More subtle functions have been found for detyrosination in the regulation of cell division, where it is important for faithful chromosome segregation in mitosis and generates asymmetry in the meiotic spindles of oocytes. Detyrosination was further implicated in mechanotransduction and load bearing during contractions of cardiomyocytes. Less is known on the physiological role of acetylation (reviewed in [START_REF] Janke | Causes and Consequences of Microtubule Acetylation[END_REF]. ATAT1-knockout mice show altered sperm morphology and motility, and some defects in neuronal migration, development, and regeneration, as well as in mechanosensation in touch neurons. Acetylation is so far the only tubulin PTM that has been demonstrated to play a role in blood platelet formation and function.

Implications for Human Health and Disease

Considering that MTs are essential for virtually every mammalian cell, deregulation of tubulin PTMs could result in a range of pathologies. Most potential disease links identified so far stem from observations in mouse models; however, rapidly developing genomic-profiling data have recently provided first direct links between tubulin-modifying enzymes and human pathologies. The emerging links to pathologies are discussed in the accompanying minireview [START_REF] Magiera | Tubulin posttranslational modifications and emerging links to human disease[END_REF].

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  Photoreceptor

1552

  Cell 173, May 31, 2018 © 2018 Elsevier Inc. DOI https://doi.org/10.1016/j.cell.2018.05.032


Ibrahim Benali

Baudouin Dafflon

Lounes Bentaha

Nejib Moalla

Emergent technologies for Inter-enterprises collaboration and business evaluation

Keywords: Industry 4.0, Collaboration, Inter-enterprise collaboration, Business evaluation, Big Data, Manufacturing, IT technologies

Conventional manufacturing systems are designed for intra-enterprise process management, and they hardly handle processes with tasks using extra-enterprise boundaries data. Besides, inter-enterprise collaboration and new IT enablers for industry 4.0 are becoming a highly topical issue to study, due to : (a) The emergence of new technologies mainly Internet of Things, big data processing and Cyber-Physical systems (b) The new customers' needs that face the SMEs.

Many constraints and issues have to be taken into account before establishing Inter-enterprises collaboration, namely: The product information, the business processes and the heterogeneous data. Moreover, the exponential growth of data coming from all the enterprises causes several challenges regarding their exploitation.

In this context, this study is interested in Big Data capabilities to help Small and Medium Enterprises to find out more lurking opportunities. We have focus on the combination between emergent IT technologies, mainly Big Data, and inter-interprises collaboration in order to provide an added value. The result of this study is a new approach, that could be adapted by SMEs, for new project evaluation within a network of enterprises.

I. INTRODUCTION

Today's manufacturing is going through the fourth industrial revolution. The term industry 4.0 has been first introduced in 2011 at the Hannover Fair in Germany, it mainly involves technological innovations applied to production processes in the field of automation, control and information technologies [START_REF] Hermann | Design principles for industrie 4.0 scenarios[END_REF]). This revolution focuses on a range of new technologies that combine the physical, digital and biological worlds [START_REF] Marr | Why Everyone Must Get Ready For The 4th Industrial Revolution? Forbes[END_REF]. These technologies are able to connect more people to the web, enhance the productivity of businesses and help to generate new assets. Also, technologies have today achieved a certain maturity which is potentially capable of changing the way to monitor, supervise and decide in the manufacturing field.

Emerging technology breakthroughs in several fields, such as: Internet of Things, artificial intelligence, robotics, Cyber-Physical Systems and big data, enable companies to adapt themselves to emergent customers needs and unplanned changes, to schedule maintenance and to predict failures [START_REF] Jazdi | Cyber physical systems in the context of Industry 4.0[END_REF]. Thus, companies step forward towards the implementation of industry 4.0.

Therefore, and in order to stay competitive, companies are moving from a traditional system to a more intelligent system in order to improve their productive capacity and their value proposition. They are moving towards exploring the opportunities and facilities afforded by the above mentioned technologies. The path of collaborating and exploit the data of a network of enterprises seems to be a valuable solution to face multi-nationals and stay in the market. Thus, enterprises are looking for a new way to make the growing industrial data as a new resource which could create new opportunities, new innovative products or new services.

According to ICD1 , the size of data is increasing immeasurably and doubling each year. It will reach about 44 zettabytes by 2020 and data set that seems large at the present time, will almost certainly seem small in the near future (MIT Technology Review 2013).

Moreover, Big data technologies need to support the volume, velocity, variety, veracity, and variability, to perform several processing and to provide scalable storages [START_REF] Anagnostopoulos | Handling big data: research challenges and future directions[END_REF]. On the other hand, from these needs, [START_REF] Sivarajah | Critical analysis of Big Data challenges and analytical methods[END_REF] group big data challenges into three main categories :

1) Data challenges: Relating to the 5 OR 6Vs (depending on the definitions of each V). 2) Process challenges: Relating to the methods and techniques of collecting, organizing and analyzing data. 3) Management challenges: Relating to the ethical aspects and access rights such as privacy and security. Companies can profit from several benefits of using big data for industry in terms of understandings customers' needs, future issues anticipation, market development, decision-making, etc. [START_REF] Yin | Big data for modern industry: challenges and trends [point of view[END_REF].

Besides, companies are looking for how to face continuous and varying changes. As a solution, synergy and collaboration between different enterprises presents an efficient way to effectively overcome these issues [START_REF] Vargas | Inter-enterprise architecture as a tool to empower decision-making in hierarchical collaborative production planning[END_REF]). However, some of collaboration processes are very complex due to : product information included in CAD files, variability of engineering and business processes, heterogeneous softwares, etc. [START_REF] Domazet | Enabling engineering collaboration in inter-enterprise design chains using collaborative agents[END_REF].

Aware of all these constraints, supporting manufacturing industries presents a major issue. Actually, it enables collaboration and data sharing in a better way in order to accelerate some tedious processes and face the new and variable customers' needs.

To provide a first solution to this problem, this paper proposes a new approach for enterprise collaboration and business evaluation. In this context, the paper is organized as follow: Section II presents a review of the techniques used for inter-enterprise collaboration and the advanced technologies used for moving towards industry 4.0. Secondly, a global view of the proposed approach is presented. In section III and IV, an application of our approach in the context of two enterprises working in different sectors (metal and plastic) is proposed.

II. RELATED WORK

This section is dedicated to give a clearer idea about the inter-enterprise collaboration backgrounds on the one hand. On the other hand, the main industry 4.0 technological enablers have been introduced. The choice of adopting this procedure of approaching the matter is due to the lack of works that deal with both technological enablers and business evaluation.

A. Inter-enterprise collaboration background

Implementing industry 4.0 will drive enterprises to set up new partnerships, with other enterprises from other sectors, in order to fit customers' requirements quickly [START_REF] Kagermann | Recommendations for implementing the strategic initiative Industrie 4[END_REF]). Thus, working within a network of businesses will be highly recommended rather than working alone in a single company.

Besides, in order to cooperate between business partners, a new system should be developed in order to connect customers, systems, suppliers and products to each other. Thereby, enterprises could work jointly and synchronously on several projects regardless of their location.

The collaboration, in a basic way, is established through emails, phone calls, chat, shared documents etc. [START_REF] Kolberg | Feature interaction in a federated communications-enabled collaboration platform[END_REF]). However, the emerging intelligent manufacturing systems within the industry 4.0 are based on real-time interaction, flexible and customized production, resource efficiency, etc. And could be reached through some emergent and new advanced technologies.

Before and after the appearance of industry 4.0, several researches have been done in order to address the topic of inter-enterprise collaboration. Also, it is worth mentioning that this topic, in most cases, have been addressed by means of ontological modeling.

For instance, [START_REF] Lin | A manufacturing system engineering ontology model on the semantic web for inter-enterprise collaboration[END_REF]) develop a manufacturing system engineering (MSE) using the Semantic Web technology in order to facilitate information exchange between several enterprises in a flexible way. In fact, they do not have to change any of their existing terminology or practices. On the other hand, they have to move all their knowledge in a specific format to the MSE. This tedious and manual method represent a big limitation of this system which bas to be automated using new advanced technologies. Furthermore, [START_REF] Lee | Design of product ontology architecture for collaborative enterprises[END_REF]) propose a product ontology architecture in order to share products' semantics with other enterprises and achieve interoperability between them.

Other solutions have been proposed aside from ontological modeling: [START_REF] Sakarya | Social alliances: Business and social enterprise collaboration for social transformation[END_REF] suggest doing social and business alliances between actors from different sectors. Enterprises can choose a collaborative strategy rather than a go-italone strategy. Thus, they need to share resources, core competencies and know-how in order to face, together, new needs. [START_REF] Kolberg | Feature interaction in a federated communications-enabled collaboration platform[END_REF] approach the need of a federated real-time collaboration platform. They present a new framework called ConnectedSpaces which consider spaces, views, information and communication resources, semantic processing and other features in order to achieve a certain level of collaboration. [START_REF] Vargas | Inter-enterprise architecture as a tool to empower decision-making in hierarchical collaborative production planning[END_REF]) develop a conceptual model based on inter-enterprise architecture which can be used by a collaborative network to handle unexpected events coming from hierarchical production planning. Their approach will help decision makers to better understand information about the complexity of the new events in order to make efficient decisions.

B. IT enablers for industry 4.0

The growing demand and the complexity of the new product are always considered as the big challenges for the enterprises. Each product follows the industrialization process through several steps before the launch on the market :

• Requirements definition • Feasibility analysis and conception • Business analysis : return on investment, budget, strategy and so on. • Creation of the quotation • Production • Quality control • etc. Each of these steps can be considered as very time consuming, especially for complex, multi-physical or large size products.

Besides, enterprises are looking for a new and innovative way to shorten or automatize some of these steps in order to enhance the responsiveness regarding customers. However, the question arises how (SMEs) Small and Medium Enterprises can exploit emergent technologies such as : big data, machine learning, cyber-physical systems, servitization, etc. in order to generate a valuable value which can impact all aspects of industrialization ?

In this context, several researches have been done using these technologies with "Big Data" as a main focus. [START_REF] Naeem | Opportunity Analysis for Enterprise Collaboration between Networks of SMEs[END_REF]) introduced a four layers framework which help enterprises to take advantage of intangible resources. Multisources data such as : Enterprise Resource Planning (ERP), Supplier Relationship Management (SRM), Product Life Cycle Management (PLM) and Customer Relationship Management (CRM) have been used. Their approach is based on a "Big Data" perspective, they could help enterprises to find out hidden opportunities and other information that could support decision-making. [START_REF] Stojanovic | Big-data-driven anomaly detection in industry (4.0): An approach and a case study[END_REF]) developed a scalable system for data-driver quality control. The system is composed of six layers and aims to detect anomalies that can appear during the manufacturing processes in a big data and real-time approach. The data are collected during the detection phase, processed (real-time and batch), analyzed using some machine learning and Complex Event Processing (CEP) implementations and finally presented to the user who can interact with it. Also, the system covers the security and integration aspects. [START_REF] Santos | A Big Data Analytics Architecture for Industry 4.0[END_REF] propose a seven layers architecture using big data technologies. The aim of their work is to deal with all existing data in a factory, from the collection to the exploitation, in order to support decision-making and help to understand the business at a more atomic level. Though, the architecture is under implementation and may need some enhancements.

In addition to big data, services are more and more adopted due to their benefits. [START_REF] Marini | Big Data As A Service For Monitoring Cyber-Physical Production Systems[END_REF]) discussed a Data as a Service approach in a Big Data perspective. Their approach aims to monitor a cyber-physical production system (CPPS). It can collect data from the machine fleet using sensors and other machine controls, clean it and prepare it for further exploitation. In fact, It's a first step towards a full-fledged architecture for CPPS.

III. COLLABORATIVE FRAMEWORK FOR BUSINESS OPPORTUNITIES EVALUATION

Data is becoming a valuable tool for the industry that can help enterprises to detect a lot of opportunities and to gather relevant recommendations. although advanced IT technologies have shown their ability to exploit and to transform these data into a useful value, recent researches revealed some challenges related to the big data 5Vs : Volume, velocity, variety, veracity and variability.

In this context, our contribution aims to use all existing industrial data in two or more enterprises from different sector in order to build a system which is able to analyze future projects from two different perspectives: technical and business.

As shown in figure 1, the idea is to take advantage of the collaborative network, gather the know-how of all enterprises, complement each other and face the new customers' needs in a win-win strategy.

The framework is based on a network of enterprises from which data will be collected, cleaned, organized and analyzed. At this step, a particular format of resulted data is needed in order to facilitate future interactions. Once the data is formated, some enrichments can be performed in order to have a more complete model. This model will receive new projects as input and provide recommendations and a project evaluation as output.

Indeed, the challenge here is not very common. Each enterprise has her own softwares : ERP, CRM, SRM, etc., her specific sensors or CPPSs and her particular industrialization phases. Multiple techniques and/or methods are needed to build a new architecture which can ensure an efficient data extraction, data processing, data analytics and overcome all problems related to latency or bandwidth.

As a first stage, we will focus on the collaboration of two manufacturing company from different sectors : metal and plastic.

IV. APPLICATION

We performed the implementation of the proposed approach in the context of two SMEs namely APR and TARDY. The first company is specialized in plastic manufacturing and deals with small to medium plastic products. The second company is specialized in metal manufacturing and deals with medium to large metal products. They both aim to integrate new technologies in order to enhance their know-how and the responsiveness regarding the customers' demands.

When they receive a request from a customer, they have to analyze its feasibility, its viability and then send a quotation to the customer. The incoming project are generally in form of e-mail or STEP file (ISO 10303 which represent Computer-aided design (CAD) 3D objects.). Thereby, the first step is to collect data from different sources :

• Existing features in the STEP.

• Data from CPPSs (production system data).

• Data from ERP, CRM, etc. (information system data). This study will focus on the translation of the various data into set of big data enablers designed for collaboration and project evaluation. In fact, several researches have addressed the problem of features extraction from a STEP file. But there is still a need to a mechanism which can transform a STEP file into a readable or neutral format.

As a result, the figure 2 depicts an application of the framework. Extracted data is subjected to real-time and batch processing in order to clean, organize and analyze data using big data technologies (such as: Hadoop, ETL, Storm, etc.) and machine learning algorithms. Some of this data will feed learning algorithms (such as: Linear Regression, SVM, Deep Learning, etc.) which lead on to a model that will be applied on future data. Several iterations could lead to several models which will be improved through several iterations. Finally, features from incoming projects will request the

Fig. 1 .

 1 Fig. 1. Conceptual layout of the proposed framework.

Data Growth, Business Opportunities, and the IT Imperatives: https://www.emc.com/leadership/digital-universe/2014iview/executivesummary.htm

VI. ACKNOWLEDGEMENT

This work is supported by a CIFRE convention (2017 / 0224) of the ANRT from the French Ministry of Higher Education and Research and "Les Etablissements TARDY".

model about feasibility, viability and recommendations based on the large accumulated volume of data as a result of old accepted/rejected projects. Recommendations will be stored in order to support the decision-making process. From a scientific point of view, the architecture arises several questions and challenges :

• How to create useful value using various data from two different sectors? • Which are the techniques and methods that could be reused or tailored to fit in this architecture ? • How to transform all the data into a enterprise assets ?

• How to use this assets to find other lurking opportunities ? From a technical point of view, several solutions are known for their ability to process versatile voluminous data such as : Hadoop and Spark. Hadoop is known for parallel and batch processing. On the other hand, Spark is known for fast and real-time big data processing. Also, it provides several libraries to structure data and perform machine learning algorithms on it. [START_REF] Anagnostopoulos | Handling big data: research challenges and future directions[END_REF]) provide the following table (figure 3) with the main Hadoop-based solutions and their characteristics : However, from comparative literature studies, the revealed issue is that there is no evidence for when any one of this solutions needs to be preferred over the others.

V. CONCLUSION Implementing industry 4.0 is a step forward towards innovation in the manufacturing field. In fact, leveraging advanced IT technologies will enhance productivity, performance and know-how of companies.

In this paper, backgrounds of the inter-enterprises collaboration and technological enablers for industry 4.0 have been presented. This includes the importance of collaboration and the benefits that data exploitation could provide. On the other hand, in the context of automated project evaluation, limited work has been carried out with the focus on big data and inter-enterprises collaboration.

The authors of this paper have proposed a new framework of inter-enterprise collaboration with the aim of performing jointly new projects and benefiting from the know-how of all the network. An application of this approach was presented but it is still under real implementation and is subjected to future enhancements.