Elena Atrián-Blasco

Elena Cerrada

Peter Faller

Mariano Laguna

Christelle Hureau
email: christelle-hureau@lcc-toulouse.fr

Role of PTA in the prevention of Cu(Amyloid-β) induced ROS formation and Amyloid-β oligomerisation in the presence of Zn

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

Introduction

Alzheimer's disease (AD) is the leading cause of dementia in the elderly affecting nearly 47 million people worldwide.1 The underlying mechanisms of this complex disorder are not clear, but there is evidence and a relatively wide agreement that the so-called amyloid cascade is a key and early event in the development of AD. This hypothesis proposes an increased extracellular accumulation of the peptide amyloid-β (Aβ) and subsequent aggregation into fibrils found in amyloid plaques, a postmortem hallmark of AD. 2 The mis-metabolism of Aβ has been suggested to be the initiating event in AD pathogenesis. Formation of Aβ aggregates would instigate further pathological events, including the formation of intracellular neurofibrillary tangles of Tau protein (the other hallmark of AD), disruption of synaptic connections and ultimately neuronal cells death and dementia.

In vitro and in vivo studies indicate that metal ions, mainly Cu, Zn and Fe ions are involved in AD. 3,4 In particular, the concentration of metal ions in the senile plaques is higher than in cerebrospinal fluid (mM versus µM).5 There is even evidence that the binding of metal ions to Aβ is required for aggregation at physiological concentrations.6 Cu and Zn ions can both bind to Aβ,7 while there is no strong evidence of Fe binding to Aβ.3,8 Cu and Zn modulate Aβ aggregation both with respect to the kinetics and mechanisms of aggregation and the morphology of the formed aggregates.9,10 Based on in vitro experiments, it has been proposed that Cu can stabilize metastable oligomeric species considered as the most toxic ones,11-13 while Zn induces the formation of weakly-structured aggregates.13-18 However, results from in vitro experiments also mainly depend on the ratio of metal ions per peptide, a parameter that is not fully known under AD conditions.7,18 Due to its redox ability, Cu ions participate in the formation of Reactive Oxygen Species (ROS) contributing to the oxidative stress implicated in AD. 19 Therefore disrupting the extracellular Aβ/Cu interaction and restoring the Cu homeostasis using synthetic ligands remains a promising therapeutic strategy.20 When Cu is regarded as the therapeutic target, Cu(II) has been preferred over Cu(I) although the extra-cellular space in brain is reductive (the ascorbate concentration in the extracellular fluid in the brain is estimated between 200 and 400 µM), 21,22 and the ability of the Amyloid Precursor Protein to reduce the Cu(II). 23 Cu dysmetabolism was also reported in other neurological diseases like prion diseases, motor neuron diseases and Parkinson's disease. 24-25 Cu is an essential metal ion26 and, in the case of neurons, this is strengthened by the fact that neurological disturbances are hallmarks of the congenital diseases of Cu metabolism, such Menkes' (accumulation of Cu) and Wilson's (lack of Cu).27 Furthermore, it was found that, when in the synaptic cleft, Cu can control the activity of neurotransmitter receptors, thus affecting excitability. These aspects reinforce the importance of the maintenance of Cu homeostasis for nervous system physiology.28 Cu(I/II) and/or Zn(II) do bind to the Aβ peptide, with the following properties (figure 1): (i) Two Cu(II)-Aβ species coexist near physiological pH with a main component (noted I) where Cu(II) is bound by the N-terminal amine, the adjacent carbonyl function and two imidazole rings from His6 and His13 or His14. In the minor component (noted II), the Asp1-Ala2 peptide bond is deprotonated and bound to the Cu(II). This induces the coordination of the adjacent carbonyl function. The last equatorial position is occupied by an imidazole ring from one of the three His residues, with no strong preference for one His residue.4,7 The most consensual value for the conditional affinity of Cu(II) to Aβ is 10 10 M -1 at pH 7.4. 29,30 (ii) Regarding Zn, the coordination is made by two His and two carboxylic acid residues, with a main contribution from His6 and Glu11 and is the predominant species around pH 7.4. 7,31 Conditional affinity is about 4 to 5 orders of magnitude weaker compared to Cu(II) at pH 7.4. 32 (iii) Cu(I) is bound by imidazole rings from two among the three His residues in a linear disposition. 3,33,34 The affinity for Cu(I) is still controversial, with values between 10 7 M -1 and 10 10 M -1 reported in the literature. 30,35,36 (iv) hetero-bimetallic species have also been observed and spectroscopically characterized. For Cu II ,Zn(Aβ), the co-presence of Zn induces a shift of Cu(II) towards the component II site, while Zn may keep two imidazole rings from the remaining His and two carboxylates. For Cu I ,Zn(Aβ), the Cu(I) site is identical as in absence of Zn (figure 1), and the Zn site may accordingly change significantly with the possibility to keep only one imidazole ring from His. 37,38 Given the different coordination geometries of Cu(II) and Cu(I) bound to the peptide, the redox properties of the Cu(Aβ) species are every complex. The electron transfer is sluggish, proceeding via a low populated highly redox-active state in equilibrium with the two Cu(I)(Aβ) and Cu(II)(Aβ) spectroscopically characterized. 39 This so-called "in-between" state is also responsible of the production of ROS. 40 Despite all the broad research undergone on the bioinorganic aspect of Alzheimer's disease in the last years, there is still no clear evidence of the in vivo metal-binding to Aβ beyond its presence in aggregates. 4,41 Nevertheless, the metal hypothesis in link to the amyloid cascade proposes that weaklybound metal ions from extracellular pools, especuially those released in the synaptic cleft, could interact with Aβ peptide. 25,42 From this interaction, a modulation of the aggregation of the peptide and a redox activity of the Cu-peptide complex have been hypothesised with different degrees of implication in the development of Alzheimer's disease.

Different strategies have been considered and studied for the treatment of AD, many of them focussed in the amyloid cascade hypothesis and its implication on the development of the disease. Given the potential impact of metal ions in AD the production of metal-coordinating ligands, and more specifically Cu-targeting molecules can be found among these strategies. 20 Two examples of these molecules are clioquinol and PBT2, ligands that made up to Phase II clinical trials but failed in this step. 43 Current attempts at regulating Cu levels in AD might not have been successful for several reasons: (i) keeping Cu(II) as the sole target and (ii) the poor selectivity between Cu and Zn of the proposed molecules given that Zn concentration within the synaptic clefts where the amyloid cascade occurs is much higher than Cu: up to 350 µM for zinc 44 and in the 10-100 µM range for copper. 45,46 With respect to Cu(I), reaching an appropriate Cu(I) over Zn(II) selectivity mainly relies on the nature of the ligand (rather than on geometrical constraints as for Cu(II)). Since Cu(I) is a softer acid than Zn(II) according to the HSAB theory, 47 softer base ligands such as S and P ligands will prefer Cu(I) over Zn(II) binding. Hence, the PTA (PTA = 1,3,5-triaza-7-phosphaadamantane) ligand previously studied for its ability to remove either Cu(I) or Cu(II) (after reduction) from Aβ and stop associated ROS formation and prevent Cu(II) modulation of Aβ aggregation, 48 should fulfil this selectivity requirement.

PTA is a cage-like water-soluble air-stable monodentate phosphine ligand with properties suitable for medicinal applications, especially the ability to solubilize transition metal complexes with anti-tumour activity. 49 Since PTA is a monodentate ligand, it can form up to 4 different species with Cu(I): [Cu(PTA)n] + (n = 1-4). Thus, depending on the concentration and Cu(I):PTA stoichiometry, the predominant species differs. 48,50,51 In the present work, we report the use of PTA in presence of Zn (and in absence for direct comparison) on Cu(I) (and Cu(II)) targeting, removal from Aβ, and consequences on ROS production and Aβ aggregation, the two key and deleterious events occurring in the amyloid cascade linked to the aetiology of AD. This is a proof-of-concept study in the sense that it addresses the possibility to keep in the presence of Zn the positive effect of PTA 48 against Cu-associated deleterious effects such as ROS production and oligomers formation. Nevertheless, other requirements the ligand should also fulfil for further therapeutic purposes such as the capacity to pass through the blood-brain barrier 52 or to have a good ADME (absorption, distribution, metabolism and excretion) / Toxicity profile 53 are not under focus.

Experimental Chemicals

A stock solution of Cu(II) at 20 mM was prepared by dissolving CuSO4•5H2O (Sigma Aldrich) in ultrapure water. Similarly, ZnSO4•H2O (from Strem Chemicals) was dissolved in ultrapure water to prepare a 20 mM stock solution of Zn(II). HEPES buffer was bought from Sigma Aldrich and dissolved in ultrapure water to a final concentration of 0.5 M, and pH was adjusted to 7.4 by addition of NaOH. A 0.5 M stock solution of Tris-d11 was prepared by dissolving the appropriate amount of the buffer powder (Sigma Aldrich) in D2O and adjusting the pH with D2SO4. A stock solution of sodium ascorbate (Sigma Aldrich) at 10 mM was daily prepared in ultrapure water. PTA was prepared as previously described in the literature. 54 A stock solution of Thioflavin T (Acros Organics) at ca. 5 mM was prepared by dissolving the powder in ultrapure water, with further titration by UV-vis spectroscopy (ε412-ε500 = 36 000 M -1 cm - 1 ). 55 From this stock solution, 250 µM aliquots were prepared and kept at -20 °C until use. All the peptides were bought from GeneCust (Dudelange, Luxembourg) with a purity grade > 98 %. Stock solutions of human Aβ16 (sequence DAEFRHDSGYEVHHQK) were prepared at ca. 5 mM by dissolving the powder in ultrapure water, and their concentration was determined by UV-vis absorption of Tyr10 considered as free tyrosine (ε276-ε296 = 1410 M -1 cm -1 ). The human Aβ40 peptide (sequence DAEFRHDSGYEVHHQKLVFFAEDVGSNKGAIIGLMVGGVV) was purified to obtain only a monomeric fraction prior its aggregation according to a previously reported protocol. 56 The peptide concentration was measured by UV-vis absorption of Tyr10 at basic pH (ε293-ε360 = 2400 M -1 cm -1 ). The shorter Aβ16 peptide has been used for the experiments studying the coordination and the ROS production as a valuable model for Cu(II) binding to the full length peptide. The longer Aβ40 peptide has been used for the experiments involving aggregation. No differences between the short and full-length hAβ peptides have been observed for their binding Cu(II) coordination, binding affinity or ROS production. 40,57 X-Ray Absorption Near Edge Structure (XANES)

Zn-K edges XANES spectra were recorded on the FAME beamline at the European Synchrotron Radiation Facility (ESRF, Grenoble, France) during an 18-shifts session in April 2017 (Experiment number 30-02-1125). The measurements were performed on mM solutions at low temperature (Hecryostat) in the fluorescence mode using a 30-element high-purity Ge detector. The energy was calibrated by the measurement of Zn foil spectra in transmission. For each sample, at least 3 XANES spectra were recorded and averaged. Samples for XANES measurements were prepared in presence of 10% of glycerol as cryoprotectant.

Nuclear Magnetic Resonance (NMR)

NMR experiments were performed on an Avance 600 Bruker NMR spectrometer. All the reactant solutions were prepared in D2O, and pH was adjusted with additions of D2SO4 or NaOD. Spectra were recorded at 298 K (for the methylene protons of PTA and its complex) or 318 K (aromatic protons of the peptide and its complexes). 318 K was chosen in order to obtain well resolved peaks of the aromatic protons of the peptide. On the other hand, temperature was decreased for the spectra of the methylene protons of PTA since at 318 K the AB system of the NCH2N protons was hindered by the signal of water.

UV-vis spectroscopy

UV-vis spectra were recorded on an Agilent 8453 UV-visible spectrometer, equipped with a Peltier temperature controller unit which maintained the solution temperature at 25 °C. For the kinetics of Cu(II) removal from the Cu II ,Zn(Aβ16) complex by PTA, the full spectra from 250 to 900 nm were recorded to study both the influence on the Tyr10 absorption band (280 nm) and the Cu(II) d-d band at 620 nm.

Ascorbate consumption

The spectra of consumption of ascorbate, which mirror the production of ROS, 37 were obtained by measuring the absorbance of ascorbate at 265 nm (ε = 14 500 M -1 cm -1 ) with a correction at 800 nm as a function of time.

Thioflavin T assay

Kinetics of aggregation by the Thioflavin T (ThT) assay were recorded using a FLUOstar OPTIMA (BMG Labtech) plate reader. The experiments were prepared in 384-wells non-binding plates (Greiner BioOne) by dissolving the appropriate quantities of each reactant, in presence of ThT at 10 µM. 0.1 µM of EDTA was added (i.e.: 0.5% of [Aβ40]) to sequestrate trace metal ions. We have control that EDTA has no effect on the aggregation of the Aβ peptide. ThT was excited at 440 nm and the emission was set at 490 nm. Three independent experiments were performed with three replicates for each condition.

Transmission Electron Microscopy (TEM)

Samples were taken after aggregation for 72 hours in the 384-well plates and collected by same conditions criteria. They were prepared for electron microscopy by using the conventional negative staining procedure. An aliquot (20 µL) of solution was absorbed on Formvar-carbon-coated grids for 2 min, blotted, and negatively stained with uranyl acetate (1%) for 1 min. Grids were examined with a TEM (Jeol JEM-1400, JEOL Inc, Pea-body, MA, USA) at 80 kV. Images were acquired by using a digital camera (Gatan Orius, Gatan Inc, Pleasanton, CA, USA) at 4000 or 25000 magnifications.

Results and discussion

Zn binding to PTA XANES (X-ray Absorption Near Edge Structure) measurements were carried out to study the possible formation of a Zn(II)-PTA complex since it is the most suitable spectroscopic technique for Zn(II) which, due to its d 10 electronic configuration, remains silent in most classical techniques. The complex [ZnCl2(PTA)2] had already been isolated by Smolenski et al. 58 as an air-stable solid product which undergoes ligand displacement in water. The formation of a Zn(II)-PTA complex is not observed in aqueous solution, as confirmed by XANES data (figure S1, a andb): the XANES spectrum of Zn(II) in buffer + 5 equivalents of PTA (b in figure S1) is virtually the same as Zn(II) in buffer (a in figure S1) at mM concentrations, thus indicating a very low affinity, at least lower than 10 3 M -1 , of PTA for Zn(II). This is the reason why PTA cannot compete with the peptide Aβ for binding Zn(II) (c in figure S1).

PTA keeps its ability to reduce and remove Cu from Aβ even in the presence of Zn(II)

The ability of PTA to reduce and remove Cu(II) from the Aβ peptide has been previously shown. 48 In this work, its ability has been tested also in the presence of Zn(II) which, as previously seen, can be found in the brain at higher concentration than copper. The very low affinity of PTA for Zn(II) leads to a good Cu-over-Zn selectivity overcoming that of Aβ as confirmed by 1 H-NMR spectroscopy (figure 2). Once PTA is added to a preformed solution of Cu II ,Zn II (Aβ), the ligand targets Cu(II) specifically to reduce it to Cu(I) and remove it from the peptide. In this process, Zn(II) remains bound to Aβ as it can be observed in figure 2,A: the aromatic protons of the peptide, and more specifically the histidine protons, recover the shift of the Zn(Aβ) complex after addition of 6 equivalents of PTA to the heteronuclear Cu II ,Zn II (Aβ). The formation of the [Cu(PTA)4] + complex is confirmed by the downfield shift of the AB system of the NCH2N protons of PTA (from 4.47 to 4.51) and the PCH2N protons (from a defined doublet at 3.90 for uncoordinated PTA to a broad singlet at 4.01 for the [Cu(PTA)4] + complex). 48,59 PTA oxide is formed as a by-product of the reduction of Cu(II) to Cu(I) 48 and it can be observed in the spectra of the reactions Cu(II) + 6 equiv. of PTA (b in figure 2B) and Cu II ,Zn II (Aβ) + 6 equiv. of PTA (c in figure 2B). The AB system of PTA oxide is centred at 4.23, while the PCH2N protons appear as a doublet at 3.95.

The low affinity of PTA for Zn(II) confers this ligand a very good Cu-over-Zn selectivity, overcoming that of Aβ. Indeed, the presence of Zn(II) does not impede PTA to reduce Cu(II) bound to the peptide and remove it to form the [Cu(PTA)4] + complex, leaving Zn(II) still coordinated to Aβ (Scheme 1).

The rate of Cu(II) to Cu(I) reduction by PTA in presence or absence of Zn(II) has also been studied by following the Cu(II)-characteristic d-d band at 620 nm (figure 3,A). This study also allows the monitoring of the time needed to reduce copper and if the addition of zinc alters the kinetic of the reduction. Data obtained were fitted to an exponential decay function characteristic of first-order reactions (equation 1). In presence of Zn(II) the reduction of Cu(II) to Cu(I) is slightly slower: k(-)Zn = 2.0 x 10 -4 s -1 vs. k(+)Zn = 1.7 x 10 -4 s -1 (figure 3,B) in line with the displacement of Cu(II) to its coordination mode II (figure 1) in the heteronuclear complex Cu II ,Zn II (Aβ), 7,37,38,60 which is expected to be more difficult to reduce. Nevertheless, this slightly slower rate does not hamper the overall reduction and removal of copper process. Indeed, after fours hours and in presence of 5 equivalents of PTA at [Cu(II)] = 90 µM (Figure 3, B), most of Cu(II) is reduced regardless the presence of zinc (Scheme 1). PTA has a higher selectivity for copper over zinc than Aβ as demonstrated by these results. Therefore, the presence of Zn(II) in solution does not prevent PTA from reducing Cu(II) to Cu(I) and subtracting it from the peptide.

The presence of Zn(II) does not impact the formation of [Cu(PTA)4] + in a ROS-forming reaction Then, the effect of PTA on ROS production by Cu(Aβ) was probed in absence and presence of Zn(II).

The redox activity of the mono-and dinuclear peptide complexes was followed by the consumption of ascorbate, which is a biologically relevant reductant. Monitoring of the ascorbate consumption at 265 nm mirrors the production of ROS because ascorbate performs the reduction of Cu(Aβ) that, in turn, reduces O2 to O2 •-, H2O2 and HO • . 19 The mixed-metal complex has indeed a slightly higher ascorbate oxidation rate than the monometallic complex Cu(Aβ) (figure 4) as already reported. 61 In this case, regardless the presence of Zn(II) and its enhancement for ROS production, 5 equiv. of PTA do effectively arrest the ROS production by Cu bound to Aβ (Figure 4 and Scheme 1).

PTA can prevent Cu-induced oligomerisation of the Aβ peptide even in the presence of Zn(II)

PTA previously showed to be effective avoiding the formation of Cu(Aβ) oligomers and restoring the formation of apo-like amyloid fibrils. 48 In this work, its ability has been also tested in presence of Zn(Aβ) and the heteronuclear complex Cu,Zn(Aβ). First, the impact of 5 and 20 equivalents of PTA on Cu(Aβ) aggregation were evaluated (Figure 5, panel A and Figure S2,panel A). Under the conditions used in the present study apo-Aβ exhibits a sigmoid-like curve in the ThT fluorescence experiment, where ThT is a dye that acquires a strong fluorescence upon interaction with β-sheets structures, thus mirroring the formation of β-sheets. 62 In the presence of up to 0.9 equiv. of Cu(II), the sigmoid-like curve is conserved but the start of the aggregation is delayed and the intensity reached at the plateau is ca. half of that observed for the apo-fibrils. This is in line with the aggregates observed by TEM (Fig. S3), since shorter fibres are formed and in less quantity. Addition of 20 equivalents of PTA leads to the recovery of the sigmoid curve and morphology of the apo-peptide fibrils. This recovery is only partial in the case of addition of 5 equivalents of PTA (Fig. S2 &S3) due to the partial oxidation of PTA to overcome the reoxidation of Cu(II) when there is not enough reductant in the medium. This is in line with what was observed and discussed in our previous work. 48 Furthermore, consistent with the low affinity of PTA for Zn(II), the addition of PTA to the Zn(Aβ40) solution does not change either the aggregation curve nor the aggregates formed: indeed, in presence of 0.9 equivalents of Zn(II), with or without PTA, an initial acceleration of the aggregation process is observed and after less than 12 hours a plateau is reached, of approximately 35% of the intensity of the apo-peptide (Fig. 5, panel B). Furthermore, the morphology of the aggregates formed in presence of Zn(II) could be described as amorphous aggregates (Fig. S3) in line with previous reports. 13,63,64 When the aggregation experiment is run in presence of 0.9 equivalents of both Cu(II) and Zn(II), a similar curve to that observed for the Zn(Aβ40) complex is obtained but with a lower final intensity (Fig. 4, panel C). The morphology of the aggregates relates as well to the Zn(II) complex (Fig. S3). In accordance to literature, 18 Zn(II) dominates the aggregation process but the presence of Cu(II) leads to lower intensity ThT signal. Addition of 20 equivalents of PTA leads to a ThT-curve and TEM images which are very similar to those of the Zn(Aβ40) complex. Therefore, the presence of Zn(II) does not preclude the removal of Cu(II) from the peptide by PTA and its addition could prevent the formation of more toxic aggregates such as Cu-induced oligomers. Contrary to what is observed after the addition of only 5 equivalents of PTA to the Cu(Aβ) complex, 5 equivalents are enough to sequestrate Cu(II) from Aβ when in presence of Zn(II) and obtain a curve similar to that of the Zn(Aβ) complex (Fig. S2). We anticipate that the formation of insoluble Zn(Aβ) aggregates facilitates the formation of the redox silent [Cu(PTA)4] + complex in solution. In brief, the presence of Zn does not preclude the removal of Cu(II) from Aβ by the PTA ligand and induces the formation of Zn-type aggregates.

Figure 1 .

 1 Figure 1. Proposed Cu(II) (upper), Cu(I) (bottom left) and Zn(II) (bottom right) coordination to Aβ at physiological pH. Values of % of Cu(II) are given from ref. 6.

Figure 2 .

 2 Figure 2. 1 H-NMR spectra at selected regions: panel A, aromatic region of a) Aβ16, b) Zn(Aβ16) complex, c) Cu II ,Zn II (Aβ16) + 6 equivalent of PTA; panel B, methylene protons of a) PTA, b) Cu(II) + 6 equivalents of PTA, c) Cu II ,Zn II (Aβ16) + 6 equivalents of PTA. Conditions: [Aβ16] = 300 µM, [Zn(II)] = [Cu(II)] = 270 µM, [PTA] = 1.8 mM, [Tris-d11] = 50 mM, pH = 7.4, T = 318 K (A) and 298 K (B).

Figure 3 .

 3 Figure 3. A) UV-Vis absorption spectra following the reduction of Cu(II) to Cu(I) by recording the Cu(II) d-d band over 5.5 h. Cu,Zn(Aβ16), dark blue line; Cu,Zn(Aβ16) + 5 equiv. PTA from 0 h (blue line) to 5.5 h (green line), measured every 120 s (0 → 2040 s) or 600 s (2040 → 20040 s). Conditions: [Cu(II)] = 90 μM, [Aβ16] = 100 μM, [Zn(II)] = 90 μM, [PTA] = 500 μM, [HEPES] = 50 mM, pH 7.4. B) kinetic of the decrease of the maximum corresponding to the d-d band of the Cu II (Aβ16) (at 630 nm, blue dots) of Cu II ,Zn(Aβ16) (at 620 nm, orange dots) complexes. Raw data of the absorbance from the UV-Vis spectra (left panel) have been averaged around the wavelength corresponding to the maximum of absorbance to eliminate noise due to the very low absorbance intensity. Data have been fitted to an exponential decay function (Cu II (Aβ16 : blue line and Cu,Zn(Aβ16) : orange line).

Figure 4 .

 4 Figure 4.UV-Vis absorption of ascorbate (followed at λmax = 265 nm) as a function of time in presence of Cu(Aβ16) (blue dots) and Cu,Zn(Aβ16) (orange dots) and after addition of 5 equivalents of PTA. Conditions: [Cu(II)] = [Zn(II)] = 10 µM, [Aβ16] = 12 µM, [PTA] = 60 µM, [ascorbate] = 100 µM, [HEPES] = 50 mM, pH 7.4, T = 25 °C.

Figure 5 .

 5 Figure 5. ThT-fluorescence spectra as a function of time of the aggregation of Aβ40 in presence of (A) Cu(II), (B) Zn(II) and (C) Cu(II) + Zn(II); and the effect of adding 20 equivalents of PTA. [Aβ40] = 20 μM, [Cu(II)] = [Zn(II)] = 18 μM, [PTA] = 400 μM, [ThT] = 10 μM, [NaCl] = 100 mM, [EDTA] = 0.1 μM, [HEPES] = 50 mM, pH 7.4, T = 37 °C. Colour code of curves: (A) a) grey, apo-Aβ; b) blue, Cu(Aβ); c) green, Cu(Aβ) + PTA; (B) d) grey, apo-Aβ; e) orange, Zn(Aβ); f) green, Zn(Aβ) + PTA; (C) g) orange, Zn(Aβ); h) purple, Cu,Zn(Aβ); i) green, Cu,Zn(Aβ) + PTA.

Acknowledgements

This research is supported by the European Research Council (StG-638712, granted to Dr. Hureau). The authors also thank Vanesa Soldan and the service of Genotoul TRI at Toulouse for their assistance in TEM and Christian Bijani for acquiring the NMR spectra. The authors acknowledge the European Synchrotron Radiation Facility for provision of beamtime (experiment 30-02-1125), and the FAME staff for their support.

Discussion and concluding remarks

As noted in the Introduction, the speciation of the [Cu(PTA)n] + complex changes depending on the Cu:PTA stoichiometry, the concentration and the other molecules present in the reaction medium. In the conditions of the experiments described in this work, both [Cu(PTA)2] + and [Cu(PTA)3] + have been proposed to be predominant in solution. 48,50,51 Quaretti et al. 51 hypothesised that, in presence of Aβ, the prevalence of the [Cu(PTA)2] + species could lead to the formation of ternary species such as [Cu(PTA)2(Aβ)], in line with the ternary complexes formed with PTA and the aromatic bidentate ligands BCA (2,2'-biquinoline-4,4'-carboxylic acid) and i-BCS (bathocuproinedisulfonic acid). Contrary to this theory, the NMR spectra shown here, together with the XANES spectra previously reported, 48 do not show the formation of a ternary Cu(I)-Aβ-(PTA)2 species. This may be due to the linear binding mode of Cu(I) by the Aβ peptide that would not easily accommodate the tetrahedral geometry of such ternary species, in contrast to what is observed with the BCS or BCA ligands. 51 To sum up, we show in this work how PTA maintains its effectiveness to remove Cu ions from the Aβ peptide even in the presence of highly-concentrated Zn(II). In fact, a Cu-over-Zn selectivity greater than that of Aβ should be one of the required characteristics for metal-targeting ligands as potential drug candidates in the treatment of AD as previously demonstrated for Cu(II). 7 The here described proofof-concept idea could be a key point to overcome the failure of metal-targeting molecules in clinical trials of AD. As presented in the introduction, a soft base atom such as P in the case of PTA, will show a greater affinity for Cu(I) than for Zn(II) satisfying the Cu-over-Zn selectivity criteria. Therefore, playing with the electronic properties of the ligand might be enough for Cu(I)-targeting ligands, while other structural parameters should be considered as well for Cu(II)-targeting ligands. This will be of importance when translating these requirements into drugs with potential clinical use due to the complexity of the biological environment.

Another interesting point is that Ceresa et al. 66 have demonstrated that the anti-cancerous [Cu(PTA)4]PF6 complex is not neurotoxic at concentrations higher than its IC50 value in human cancer cells. In addition, the complex can enter neurons without exerting any in vivo deleterious effects. 66 This could be interesting to restore a normal homeostasis of copper in the brain, another key point when developing therapeutic metal-targeting drugs aimed at restoring normal Cu homeostasis in the brain. 67,[START_REF] Mathys | Neurotoxicity of Metals[END_REF]

Conflicts of interest

There are no conflicts to declare.


Marie Bonnet

Denis Courtier-Murias

Pamela Françoise Faure

Stéphane Rodts

Sabine Caré

Paméla Faure

Sabine Care
email: sabine.care@ifsttar.fr

NMR determination of sorption isotherms in earlywood and latewood of Douglas fir. Identification of bound water components related to their local environment

Keywords: 2D NMR relaxometry, adsorption, earlywood, hemicelluloses, latewood, macrofibril

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

Introduction

Wood structure is highly heterogeneous and hierarchically organized and therefore the swelling behavior of wood in response to variations of relative humidity (RH) is also complex. The heterogeneity at the macroscopic scale is manifested in case of woods in the temperate zones as earlywood (EW) and latewood (LW), which also have distinct hygromechanical behaviors [START_REF] Care | Microstructural and multiscale characterization of wood subjected to humidity by X-ray microtomography and Magnetic Resonance Imaging[END_REF][START_REF] Almeida | Free shrinkage of wood determined at the cellular level using an environmental Scanning Electron Microscope[END_REF]. The water affinity of the cell-wall components is provided by hydrophilic molecules with hydroxyl group concentrations in this decreasing order: cellulose > hemicelluloses > lignin. However, twothirds of cellulose hydroxyls are inaccessible to water, so that hemicelluloses are the most hydrophilic molecules in wood [START_REF] Engelund | A critical discussion of the physics of wood-water interactions[END_REF]. Sorption isotherms in materials have been classified in 6 types [START_REF] Brunauer | On the theory of the Van der Waals adsorption of gases[END_REF][START_REF] Sing | Reporting physisorption data for gas/solid systems with special reference to the determination of surface area and porosity[END_REF]. They reflect sorption mechanisms, and their shape depends on physical and chemical interactions between water and solid substrate, and the number of accessible sorption sites. Many sorption isotherms exhibit hysteresis, thus adsorption and desorption isotherms can be differentiated. In this study, only adsorption is considered. The sorption isotherms of wood have a typical sigmoid shape and are commonly classified as type II. The BET theory [START_REF] Brunauer | Adsorption of gases in multimolecular layers[END_REF]) models wood sorption at low RH (< 40%), assuming that primary water is strongly bonded to hydroxyl groups, and secondary water has thermodynamic properties identical to those of liquid water. [START_REF] Dent | A multilayer theory for gas sorption. Part I: sorption of a single gas[END_REF] improved this model and proposed that the secondary water should have a binding energy higher than that of liquid water, and this approach shows a better fitting of the model at high RH. Usually, the [START_REF] Hailwood | Absorption of water by polymers. Analysis in terms of a simple model[END_REF] model is applied for wood, which considers sorption as solution phenomena with hydration and solution water components. The last isotherm models described in the literature are still a matter of debate [START_REF] Willems | A critical review of the multilayer sorption models and comparison with the sorption site occupancy (SSO) model for wood moisture sorption isotherm analysis[END_REF].

The localization of bound water requires knowledge of the supramolecular architecture of the cell-wall, which was improved in the last two decades [START_REF] Donaldson | Cellulose microfibril aggregates and their size variation with cell wall type[END_REF][START_REF] Salmén | Cell wall features with regard to mechanical performance. A review[END_REF][START_REF] Salmén | Wood morphology and properties from molecular perspectives[END_REF]. Macrofibrils are helically wound in the secondary wall. However, they are not completely straight but slightly waved, and thus build intra-macrofibril regions having a lenticular shape in the order of 10 nm [START_REF] Boyd | An anatomical explanation for visco-elastic and mechano-sorptive creep in wood, and effects of loading rate on stregth[END_REF][START_REF] Gril | Une modélisation du comportement hydro-rhéologique du bois à partir de sa microstructure[END_REF][START_REF] Salmén | Wood morphology and properties from molecular perspectives[END_REF].

These lenticular areas are filled with a matrix of lignin and xylan. Furthermore, glucomannan is present within macrofibrils and forms lamellar areas (Figure 1). Hypotheses were proposed on the location of bound water in this structure [START_REF] Gril | Une modélisation du comportement hydro-rhéologique du bois à partir de sa microstructure[END_REF][START_REF] Kulasinski | Water adsorption in wood microfibril-hemicellulose system: role of the crystalline-amorphous surface[END_REF] in order to understand the effect on its hygromechanical behavior. For instance, [START_REF] Hunt | Longitudinal shrinkage-moisture relations in softwood[END_REF] demonstrated that the longitudinal deformations and the hysteretic sorption behavior originate from two different types of bound water located in different places.

1 H NMR relaxometry at low magnetic field (LF-NMR relaxometry) is well suited to water identification and characterization in wood [START_REF] Sharp | Determination of moisture content of wood by pulsed nuclear magnetic resonance[END_REF][START_REF] Menon | An NMR determination of the physiological water distribution in wood during drying[END_REF][START_REF] Araujo | Proton magnetic resonance techniques for characterization of water in wood: application to white spruce[END_REF][START_REF] Araujo | Behaviour of solid wood and bound water as a function of moisture content: a proton magnetic resonance study[END_REF][START_REF] Labbé | Moisture content and extractive materials in Maritime Pine wood by low field 1 H NMR[END_REF][START_REF] Almeida | A NMR study of water distribution in hardwoods at several equilibrium moisture contents[END_REF][START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF][START_REF] Telkki | Moisture in softwoods: fiber saturation point, hydroxyl site content, and the amount of micropores as determined from NMR relaxation time distributions[END_REF] and in pure cellulose or other cellulosic materials [START_REF] Sasaki | A study of sorbed water on cellulose by pulsed NMR technique[END_REF][START_REF] Vittadini | 1H and 2H NMR mobility in cellulose[END_REF]. This technique can discriminate and quantify protons in water or in organic molecules regarding their local environment, i.e. affinity with molecules they are bonded to, size of the bonded molecule, and pore size. Thus LF-NMR relaxometry is the method of choice for studies of water in porous media, such as wood, concrete, clay, etc. [START_REF] Faure | An MRI-SPI and NMR relaxation study of drying-hydration coupling effect on microstructure of cement-based materials at early age[END_REF][START_REF] Faure | Proton NMR relaxation as a probe for setting cement pastes[END_REF][START_REF] Faure | Water transfers within Hemp Lime Concrete followed by NMR[END_REF]). An example of application in wood technology is the optimization of the process of thermal modification [START_REF] Javed | Magnetic resonance imaging study of water absorption in thermally modified pine wood[END_REF]. [START_REF] Sharp | Determination of moisture content of wood by pulsed nuclear magnetic resonance[END_REF] studied first wood's moisture content (MC) by 1D NMR relaxometry.

Other studies quantified bound water and free water contents by spin-spin relaxation time (T2) measurements [START_REF] Menon | An NMR determination of the physiological water distribution in wood during drying[END_REF][START_REF] Araujo | Proton magnetic resonance techniques for characterization of water in wood: application to white spruce[END_REF][START_REF] Labbé | Moisture content and extractive materials in Maritime Pine wood by low field 1 H NMR[END_REF]. Some of these studies showed that liquid water may be present below the fiber saturation point (FSP), for instance in the case of hardwood species [START_REF] Almeida | A NMR study of water distribution in hardwoods at several equilibrium moisture contents[END_REF]. PSP was also determined through NMR measurements at various temperatures below and above the melting point of water [START_REF] Telkki | Moisture in softwoods: fiber saturation point, hydroxyl site content, and the amount of micropores as determined from NMR relaxation time distributions[END_REF]). In the hygroscopic range, [START_REF] Araujo | Behaviour of solid wood and bound water as a function of moisture content: a proton magnetic resonance study[END_REF] tried to separate hydration and solution water by T2 measurements, inspired by the sorption theory of [START_REF] Hailwood | Absorption of water by polymers. Analysis in terms of a simple model[END_REF]. However, the exchange time between these two water components, which is linked to the diffusion distance of bound-water in cell-wall, turned out to be too fast to enable their distinction. [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF] carried out 2D NMR relaxometry experiments via T1-T2 correlation. Better splitting of water components permitted to detect two types of bound water in wood cell-wall, which were attributed to confined water in small clusters and to less mobile water, possibly at the origin of wood swelling. Thus the water components cannot be differentiated in 1D experiments: in T2 spectra the relaxation times of the signals are very close to each other, and in T1 spectra, the peak corresponding to less mobile water is superimposed by the solid wood peak.

It would be desirable to learn more about the two bound water components, especially to find their location within the cell-wall structure and to evaluate their influence on the hygromechanical and sorption behaviors of wood. Hence, the aims of this study are to collect more information on the sorption mechanisms of bound water in wood and to compare EW and LW sorption behaviors. The expectation is that a better hypothesis can be presented concerning the location of bound water components in wood.

Material and methods

Sample preparation: Wood blocks were collected from a 58 years old Douglas fir tree (Pseudotsuga menziesii) from the coniferous forest of Ecouves (Orne, France). After natural drying in air, the material was stored at 19.9 ±0.2°C and 54 ±6% RH. Three earlywood and latewood (EW and LW) samples (3 x 10 x 8 mm 3 , RxTxL) were cut in the growth-ring no. 14.

It is located at the juvenile-mature transition and has a width of 6.1-mm and a LW proportion of 0.4. All the samples were taken side by side, in order to minimize the variability between samples of the same type (EW or LW). The total sampling volume was thus of 6 x 24 x 20 mm 3 . Samples were cut with a diamond wire saw in the RT plane and with wood chisels for the RL and TL planes. A final polishing step was done with Silicon Carbide disks. The density of the samples was determined by weighting and volume displacement measurements with a resolution of 0.0001 g and 0.001 mm 3 , respectively. The average density at 12% MC was 0.31 g cm -3 (EW) and 0.77 g cm -3 (LW). The presence of transition wood was not taken into account.

All the samples had the same moisture history to avoid differences in this regard. Three complete adsorption/desorption cycles were imposed to the samples. They were subjected alternately for one week at 97% RH (potassium sulfate) and for one week at 2% RH (silica gel) at 20°C. The NMR adsorption experiment began at 2% RH. The studied material was never oven-dried to avoid irreversible structural damages. The mass differences between samples with 2% RH and oven-dried samples (at 103°C) were evaluated on parallel Douglas fir samples. The equilibrium moisture content (EMC) at 2% RH is about 2.5%.

EMC = m -m m × 100 (1)
where EMCx is at x% RH (%), mx the mass of the equilibrated sample (g) and m0 the mass of the oven-dried sample (g).

Experimental protocol: NMR measurements were performed at 2, 23, 44, 65, 80, and 97%

RH. Each sample was equilibrated for one week. RH was controlled with silica gel (2% RH) and saturated salt solutions (≥ 23% RH) placed in desiccators at 19.9 ±0.2°C (Table 1).

Experimental conditions were recorded with thermo-hygrometers with a precision of ±0.4°C and ±2% RH, and the equilibrium state was checked daily by weighing. The average MC difference between two mass measurements at the equilibrium was 0.1%.

NMR measurements at 20°C: NMR measurements were performed on a set of three EW and LW samples, respectively. The samples were inserted in a 18-mm diameter glass tube with the R direction oriented parallel to the tube axis (Figure 2), while the RH was controlled in each tube during the NMR experiments [START_REF] Fourmentin | Impact de la répartition et des transferts d'eau sur les propriétés des matériaux de construction à base de chaux formulées[END_REF]. To guarantee their equilibrium, samples were inserted the day before scanning. A BRUKER MINISPEC MQ20 spectrometer was applied, which was operating at 0.5 T, corresponding to a resonance frequency of 20

MHz for 1 H and enabling an analysis of samples with a maximum diameter of 18 mm and a maximum height of 10 mm. In a static magnetic field B0, magnetic moments of 1 H nuclear spins preferentially align with the B0 direction. The average of these moments is called macroscopic magnetization M and can be separated into a longitudinal component ML along the B0 direction, and a transversal component MT. At the equilibrium state, M = M0 and is oriented along the B0 direction. The excitation of the magnetization M with a radiofrequency (RF) pulse causes its disorientation and is followed by a precession-relaxation motion about B0 to come back to equilibrium. In simple samples, ML(t) and MT(t) relaxations obey first order kinetics:

M t = M -A e |M t | = A e (2) (3)
where A1 and A2 depend on the initial conditions at t=0. T1 and T2 are the spin-lattice (longitudinal) and spin-spin (transversal) relaxation times, respectively. They depend on molecular mobility of H atoms bearing molecules -in the present case water or solid wood molecules. They are also related to the strength of magnetic interactions between H spins and neighboring chemical species: the stronger the interactions, the shorter the relaxation times.

Relaxation kinetics of multicomponent systems -as humid wood material -appear as a sum of independent exponential processes. Spin-lattice and spin-spin kinetics are commonly measured with the inversion recovery (IR) [START_REF] Hahn | An accurate nuclear magnetic resonance method for measuring spin-lattice relaxation times[END_REF]) and Carr-Purcell-Meiboom-Gill (CPMG) sequences [START_REF] Carr | Effects of diffusion on free precession in nuclear magnetic resonance experiments[END_REF][START_REF] Meiboom | Modified spin-echo method for measuring nuclear relaxation times[END_REF], respectively. Inverse Laplace Transform (ILT) processing allows to some extent to resolve and quantify various components in the form of 1D spectra vs. T1 or T2 (Whittall and MaxKay 1989). Relaxation times of two components should differ by typically a factor of three for signal resolution, otherwise, the signals appear as one wide (merged) single peak [START_REF] Brown | Information available and unavailable from multiexponential relaxation data[END_REF]. Some other biases of the method have also been pointed out by [START_REF] Faure | Proton NMR relaxation as a probe for setting cement pastes[END_REF].

2D T1-T2 correlation spectra [START_REF] English | Quantitative two-dimensional time correlation relaxometry[END_REF]

S t , nTE = W !1 -2e # $ . e & ' (4)
Overall signal of a multi-component sample is regarded as the sum of such elementary contributions. 2D spectra aiming at retrieving components as a function of T1 and T2 are computed through a 2D Inverse Laplace Transform (ILT), for which a practical algorithm was proposed in recent years [START_REF] Song | T1-T2 correlation spectra obtained using a fast two-dimensional Laplace inversion[END_REF]. The volume under each peak of the 2D spectra is proportional to an amount of H atoms. The T1 and T2 values of each peak are determined by means of the coordinates of their respective maxima. 2D spectra also give unambiguous access to T1/T2 ratios. The latter is characteristic of H atoms mobility and confinement and greatly helps spectrum interpretation. Values close to 1, 2-6, and over 10 correspond to (i) unconfined water, (ii) mobile water at free or adsorbed state and (iii) bonded immobile water molecule and solid macromolecules, respectively. Ratios lower than one are physically not permitted [START_REF] Abragam | The Principles of Nuclear Magnetism[END_REF].

In this work, delay tm of the IR sequence was increased in 60 steps as a geometric series (i.e. following a regular sampling on a logarithmic scale) from 0.01 to 1000 ms. CPMG echo train comprised 200 successive echoes with an echo time TE = 60 µs, among which 50 echoes were recorded for measurement times nxTE, following approximately a geometric series from 60 µs to 12 ms. To increase the signal-to-noise ratio (S/N), the T1-T2 sequence was repeated 192 times for LW and 384 times for EW due to its lower density generating less signal.

Repetition delay TR was chosen higher than five times the highest T1 value to ensure complete equilibrium recovery between successive sequences, and was finally set to TR = 1 s to also avoid excessive RF power deposition of the CPMG part of the sequence on the sample and keep sample temperature constant.

The free induction decay (FID) sequence was also performed to validate the quantitative NMR measurements as FID detects the quasi-totality of H atoms by measuring the signal just after the emission of one single RF pulse (with a low dead time of 8 µs). The FID signal intensity is thus proportional to the number of H atoms in the studied material. The H atoms in wood supposed to be linearly evolved with the mass of water in the sample, an assumption which could be verified (Figure 4). Normalization choices in the 2D-ILT software lead to a proportional relation between peak volume of the 2D spectra and FID intensity by a constant multiplicative factor.

2D-ILT data processing:

Of particular importance in this study is the calculation of T1-T2 correlation spectra from NMR data, which was performed based on a homemade software essentially reproducing the 2D-ILT algorithm of [START_REF] Song | T1-T2 correlation spectra obtained using a fast two-dimensional Laplace inversion[END_REF]. Spectra are described as a matrix of values on a fixed, predefined grid of relaxation times and regularly spaced on a logarithmic axis (typically 100 values per axis) and spanning the desired area to be observed. They are determined by a least square fit to the data with non-negative constraint and Tikhonov regularization:

(a *,+ , = ArgMin 0 1,2 3 4 5S (5)

j i a , i T 1 j T 2 with K *,+,&, = !1 -2e # 1 $ . e & ' 2
where λ is a positive parsimony parameter, which ensures regularity of the spectrum. This is necessary because of the not perfectly conditioned nature of unconstrained least square fit.

Spectrum positivity seems to be a reasonable physical assumption in many cases, but it is actually a requirement of the algorithm itself. This point was criticized in the past because some specific samples may also exhibit negative spectral components (Rodts andBytchenkoff 2010, 2011). Despite some attempts, no fully convincing alternative for processing has been proposed up to now. To make the optimization problem (5) tractable on a standard PC, the original algorithm replaces kernel operator K by a SVD approximation (Singular Value Decomposition, made possible by the product structure of K) truncated to highest singular values so as to retain a condition number of 1000. This is a kind of data compression, which reduces by orders of magnitude the number of parameters to handle in calculations. The nonnegative truncated problem is finally solved by the BRD algorithm [START_REF] Butler | Estimating solutions of first kind integral equations with nonnegative constraints and optimal smoothing[END_REF]). This algorithm not only calculates the spectrum for a given λ value, but also automatically optimizes λ value according to the noise level on NMR data.

In this work, the algorithm had to be corrected because of some imperfections. The condition number for SVD approximation was increased to 10 6 , as it was observed that lower values are too rough and produce a significant bias on calculated spectra. Also, BRD algorithm was used only to calculate spectra at fixed λ value, because λ optimization failed to converge in some cases. The more robust and traditional S-curve approach was used instead, consisting in choosing the highest λ, which still permits fitting quality [START_REF] Whittall | Quantitative interpretation of NMR relaxation data[END_REF].

Error assessments: (i) The uncertainty due to eventual variations of MC during NMR experiments has been quantified by weighing the samples before and after each NMR experiment. (ii) The variability of sorption properties between the three samples of the same wood type was evaluated by weighting. It was verified that the sampling protocol leads to only a very small variability between the three samples. (iii) The stability of the NMR apparatus was also taken into account, as the totality of the experiment lasted several weeks. Systematic calibrations with a standard reference sample were performed and the NMR coil was additionally detuned to make its sensitivity independent on sample composition. (iv) Some bias linked to the 2D ILT data processing may appear and affect the measured values.

The stability of this data processing was analyzed by adding white noise on a model signal that is close to the experimental data, as proposed by [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF].

The error bars of the MCs have been calculated based on the above mentioned uncertainties. The average uncertainty for the whole hygroscopic range is ±0.8% MC.

Regarding T1 and T2 values, only the noise effect was taken into account. However, if known problems of 1D-ILT are extrapolated to the 2D case [START_REF] Faure | Proton NMR relaxation as a probe for setting cement pastes[END_REF], an additional bias can occur owing to the 'mathematical' interaction between neighboring peaks: T1 and T2 can easily be over-or underestimated by a factor of 1.5 without any particular physical meaning. Therefore, only stronger effects should be sought for.

Analysis of sorption isotherms:

The analysis is based on the [START_REF] Dent | A multilayer theory for gas sorption. Part I: sorption of a single gas[END_REF] theory, where the evolution of adsorbed water quantity reads as a function of RH:

y y = b x 1 -bx 1 -bx + b x (6)
where y is the MC (in g g -1 of dry material), ym the theoretical MC of the primary water when it reaches saturation (in g g -1 of dry material) and x the RH (-). The two dimensionless constants b0 and b are linked to the variation of Gibbs energy of water from the liquid state to the adsorbed state, which are ∆G0 and ∆G (in J.mol -1 ), respectively:

where R=8.314 J mol -1 K -1 is the gas constant and T is the temperature in °K. The RH for which the secondary water begins to be adsorbed (i.e. y/ym=1) is denoted xm. These physical parameters are obtained by a fit of the model to the data by the least square method.

Results and discussion

Validation of NMR measurements: Figure 4a shows the evolution of the first data point intensity of recorded signal as a function of the mass of adsorbed water determined by weighing. At 2% RH, signal mainly corresponds to H atoms of wood molecules. The ratio of FID signal LW/EW at 2% RH (2.9) is quite similar to the ratio of the dry densities (2.6). A linear dependence is found between signal increase and water adsorption with an identical slope for EW and LW.

T1-T2 correlation spectra:

In the whole hygroscopic range, five main peaks appear on T1-T2 correlation spectra for both EW and LW samples as exhibited in Figure 5 corresponding to 65% RH. The evolution of the spectra with RH is shown in Figure 6, where low signal values were removed to highlight the peaks B and C.

Peak D is identified as a signal of H atoms belonging to wood molecules as its long T1 and short T2 (with T1/T2 ≈ 2000) are the signature of relatively rigid molecules with little mobility [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF]. Moreover, its volume remains constant despite of RH variations (3.8 ±0.1 and 10.0 ±0.6 (FID units) for EW and LW respectively).

Peaks B and C are attributed to bound water. Indeed, their T1/T2 ratio is much lower than that of peak D suggesting a greater mobility. Also, the sum of peaks B and C volumes linearly increases with the mass of adsorbed water determined by weighing (Figure 4b). The position of peak B suggests that it could be an exchange peak between C and D, thus forming an exchange square of the B-kind [START_REF] Bytchenkoff | Structure of the two-dimensional relaxation spectra seen within the eigenmode perturbation theory and the two-site exchange model[END_REF]. However, off-diagonal peaks in an exchange T2-T2 spectrum were not observed in such experiments [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF].

Therefore, peaks B and C correspond to bound water located in two specific and distinct water reservoirs. Compared to peak C, peak B has a higher T1/T2 ratio indicating more restricted molecular motions: water molecules of peak B have stronger interactions with wood molecules as also demonstrated by [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF].

Finally, peaks A' and A'' are assigned to liquid water which could be present in large pores below the FSP [START_REF] Almeida | A NMR study of water distribution in hardwoods at several equilibrium moisture contents[END_REF]) as they have high T1 and T2 values and a T1/T2 ratio ranging between 1 and 5. The position of peak A'' slightly above the T1=T2 diagonal is probably a location error due to its very low intensity.

Evolution of T1 and T2 values with RH:

As observed on Figure 7, EW and LW exhibit very close T1 and T2 values evolutions with RH for both peaks B and C. Although EW and LW have not the same proportion of chemical constituents in their cell-walls [START_REF] Meier | The distribution of polysaccharides in the cell-wall of tracheids of Pine (Pinus silvestris L.)[END_REF], this result indicates that the nature of adsorption sites is quite similar in EW and LW,

i.e. they share many structural and chemical similarities at the nanometer scale.

Furthermore, as RH increases T1/T2 ratio decreases continuously for both peaks B and C (Figure 7d): it is reduced by a factor of 46 and 8 respectively, showing that both types of water gain mobility as the number of adsorbed molecules increases. A thorough analysis of independent evolution of T1 and T2 is more delicate, but the increasing trend with RH of the T2 values supports the idea of mobility increment. It is not clear, however, at this stage whether this mobility concerns water molecules themselves, or the -possibly mobilestructures bearing adsorption sites. As already pointed out by [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF], adsorption energy on sorption sites is also likely to change if additional water molecules adsorb at a same place. Moreover, a softening of the structure at high RH may appear [START_REF] Engelund | A critical discussion of the physics of wood-water interactions[END_REF].

Finally, the T1/T2 ratio does not seem to stabilize at high RH contrary to what is usually observed in rigid systems such as porous silica [START_REF] D'orazio | Enhanced self-diffusion of water in restricted geometry[END_REF][START_REF] D'orazio | Molecular diffusion and nuclear-magnetic-resonance relaxation of water in unsaturated porous silica glass[END_REF][START_REF] Porion | A NMR investigation of adsorption/desorption hysteresis in porous silica gels[END_REF]. This suggests that water molecules appearing at high RH may still enhance the mobility and interact with their environment. This result is not in accordance with the interpretation of [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF] concerning their attribution of C-water to small water clusters.

Sorption isotherms:

The sorption isotherms are calculated using the proportional coefficient α (equal to 152 ±6 g -1 ) of the linear trend observed in Figure 4, which enables to convert NMR signal quantity into MC (under the same experimental conditions). Thus, for calculation of sorption isotherms the following equation is used:

q % -q % = α w % -w % (9)
where q % and q % (a.u.) are the NMR signal quantities at the RH x% and 2% (equilibrium state) and w % and w % (g) are the masses of water in wood equilibrated at the RH x% and 2%. Because the NMR signal quantities for B-and C-water can be measured separately by 2D

NMR experiments and w % is known, Eq. 9 can be used to calculate w % at various RH values and thus to obtain individual sorption isotherms for B-and C-water. Note that this equation is also suitable to determine the MC related to the dry state by extrapolation.

The sorption isotherms of the totality of water (B+C) of EW and LW are shown in Figure 8. The two curves are quite similar confirming the literature results [START_REF] Hill | Variability in water vapour sorption isotherm in Japanese Larch (Larix kaempferi Lamb.) -earlywood and latewood influences[END_REF], and exhibit the common shape of the wood sorption isotherm (type II).

The individual sorption isotherms of B-and C-water can also be determined (Figure 9). Bwater has a sorption isotherm of type II, in the whole investigated RH range for LW and until 65% RH for EW, while C-water has a sorption isotherm of type III. Thus, the sigmoid shape of the sorption isotherm of wood emerges from the combination of two distinct sorption processes, which occur in their respective locations. Sorption isotherms are quantified according to the theory of [START_REF] Dent | A multilayer theory for gas sorption. Part I: sorption of a single gas[END_REF]: free energies of primary and secondary waters are calculated for each experimental sorption isotherm (Table 2). Note that the obtained values are of the same order of magnitude as those of the literature [START_REF] Skaar | Wood-water relations[END_REF]. First, secondary water is weakly bound compared to primary water as ∆G0 < ∆G. Moreover, ∆G > 0 so that the adsorption of secondary water is partly restricted (compared to the condensation of bulk water) by some unfavorable energetic conditions, which are not yet understood. Also, Gibbs energy values support the view that B-water has a stronger interaction strength than C-water because of ∆G0B < ∆G0C. This result is in agreement with both their T1 and T2 values and the usual interpretation that type II isotherm corresponds to adsorption with higher attractive forces between wood and water molecules than type III isotherm [START_REF] Brunauer | On the theory of the Van der Waals adsorption of gases[END_REF][START_REF] Dent | A multilayer theory for gas sorption. Part I: sorption of a single gas[END_REF]. This is supported as well by the xm value, indicating an earlier beginning of the secondary water adsorption in the B-environment than in the C-environment.

Furthermore, EW and LW exhibit almost identical sorption isotherms until 65% RH.

However, at higher RH, B-water reaches saturation in EW, whereas in LW, it is still increasing in a significant way. The inverse behavior is observed for C-water, the content of which increases less in LW than in EW at high RH. The current NMR data do not allow explaining the sorption isotherms differences between EW and LW. However, a hypothesis in accordance with the positivity of ∆G is proposed: the saturation of a sorption isotherm could be due to a limited adsorption capacity, for instance because of insufficient space or because of a limited softening of the cell-wall structure at high RH, which influences the accommodation of water molecules [START_REF] Engelund | A critical discussion of the physics of wood-water interactions[END_REF]). In the case of B-water in EW, the T2 value continues to increase with RH although no more B-water is adsorbed. This may indicate that ─ although B and C are regarded as two distinct reservoirs, which do not significantly exchange water at the time scale of an NMR experiment ─, they could nevertheless be located fairly close one to each other to enable interactions, the exact nature of which remains unclear at this stage.

Hypothesis on water molecules environments:

The hygromechanical behavior of wood could be affected by two types of water located in different areas of the wood structure [START_REF] Gril | Une modélisation du comportement hydro-rhéologique du bois à partir de sa microstructure[END_REF][START_REF] Hunt | Longitudinal shrinkage-moisture relations in softwood[END_REF]). The current NMR results show that there are two bound water components, which cannot share the same local environment, but which are close enough to develop some degree of interaction. Yet, two main areas of the wood structure, which are accessible to water, but which have different sorption environments, stand out: the lenticular and the lamellar areas (Figure 1). Their proximity within a few nanometers should be enough to enable some interactions, but avoid exchanges during the NMR experiment time, provided the case that the typical residence time of water molecules in each area is long enough. The latter hypothesis should be checked in further studies by means of specific experiments. Moreover, their structural and chemical properties are very different, so that they should have distinct NMR relaxation properties.

Lamellar areas are more arranged and hydrophilic, enabling stronger interactions with water than lenticular areas. Yet, B-water is more strongly bound to wood molecules so that it should be located in lamellar areas and C-water in lenticular areas.

Note that for a given environment, NMR relaxometry cannot identify the nature of each water molecule because of the various sorption sites in close proximity. Therefore, adsorption sites in B-and C-environment may be a mixing of sorption sites of different nature.

According to the proposed hypothesis, water molecules in lamellar areas could be adsorbed on glucomannan, at the interface with microfibrils, and in amorphous areas of microfibrils. In lenticular areas, they could be adsorbed on sorption sites of xylan, lignin, and glucomannan found at the interface with macrofibrils. This hypothesis is an alternative to that of [START_REF] Cox | A study of water exchange in wood by means of 2D NMR relaxation correlation and exchange[END_REF], who attributed B-water to adsorbed water and C-water to small water clusters, which does not contribute to moisture-induced deformations. In coherence with the NMR results and the structure of the cell-wall, both types of water should interact with wood molecules and induce deformations.

Conclusions

2D 1 H NMR relaxometry in the whole hygroscopic range affords new insights of moisture sorption in EW and LW. By means of T1-T2 correlation spectra, bound water was separated into two components, which have not the same mobility and are located in distinct environments. Their respective sorption isotherms were determined and analyzed based on the Dent theory, which revealed unequal interactions strengths with wood molecules. Both bound water components were observed in EW and LW and exhibited similar T1 and T2 values and dependence on RH, suggesting that bound water in EW and LW is situated in similar environments. However, sorption isotherms of bound water components turned out to be different between EW and LW at high RH, possibly due to a difference of sorption capacity.

Further experiments would be necessary to better understand these differences. Furthermore, experimental data and sorption isotherms analysis helped to assign the two bound water components at the macrofibril scale: the strongly bound water would be located in lamellar areas and the weakly bound water in lenticular areas. This hypothetic model gives perspectives for the understanding on the deformations induced by moisture sorption and to compare their effect on the hygromechanical behavior of EW and LW.

Tables

Table 1 Chemicals to control RH (20°C, Patm) [START_REF] Winston | Saturated solutions for the control of humidity in biological research[END_REF][START_REF] Greenspan | Humidity fixed points of binary saturated aqueous solutions[END_REF]. [START_REF] Boyd | An anatomical explanation for visco-elastic and mechano-sorptive creep in wood, and effects of loading rate on stregth[END_REF] and [START_REF] Salmén | Cell wall features with regard to mechanical performance. A review[END_REF]. For clarity, the scheme is neither to scale nor made with regular geometry. It is drawn in the cell baseline Rcell, Tcell, Lcell, with θ the microfibril angle.

  allow a better splitting of various components by classifying them according to pairs of T1 and T2 values. This technique was successful in identifying two bound water components in wood (Cox el al. 2010) and allowed a clear improvement over 1D experiments. Measurements consist of coupling IR and CPMG sequences as presented in Figure 3. Sequence is repeated for different values of tm delay, for which a signal is recorded at the top of each echo generated in series, as a function of both tm and echo index n. Signal from a sample component with identified T1 and T2 values and equilibrium magnetization -considered as the 'weight' of the component W reads:

  Primary water: ∆G = -RTln b Secondary water: ∆G = -RTln b (7)

Figure 4

 4 Figure 4 (a) FID signal and (b) integrated signal intensity of peaks B+C (T1-T2 correlation spectra) vs. mass of adsorbed water. s values correspond to the slopes of a linear trend curve.

Figure 6

 6 Figure 6 Evolution of the T1-T2 correlation spectra with RH. (a), (c), (e) EW equilibrated at 2%, 65% and 97% RH, respectively. (b), (d), (f) LW equilibrated at 2%, 65% and 97% RH, respectively.

Figure 7

 7 Figure 7 Evolution with RH of (a) T1 value of peak B (b) T1 value of peak C (c) T2 values of peaks B and C and (d) T1/T2 ratio of peaks B and C.

Figure 9

 9 Figure 9 Sorption isotherms of (a) B-water and (b) C-water of EW and LW. Continuous curves: fit to the Dent model, applied only up to 65% RH for B-water in EW and 80% RH for C-water in LW due to the saturation phenomenon. Dashed lines: non-fitted points of these data.

Table 2

 2 Parameters of sorption isotherms as fitted based on the Dent theory.

		xm	ym	∆G0	∆G
		(%)	(%)	(kJ mol -1 )	(kJ mol -1 )
	B	EW 20.50 4.23	-8.10	1.06
	water	LW 18.61 3.97	-8.25	0.76
	C	EW 44.84 2.82	-2.60	0.70
	water	LW 49.94 2.90	-2.34	0.96

Figures Figure 1 Schematic structure of macrofibrils, inspired by

Acknowledgments:

The Douglas supply by INRA Nancy (France) is acknowledged, in particular Julien Ruelle (LERFoB) for fruitful discussions. The manuscript was improved by the insightful comments of reviewers from Holzforshung.